188 Articles
Dr. Krishna Anand, Prashant Singh, Prof. Raj Kumar, Sanjeev Kumar
The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the field of Chemistry marks the beginning of a transformative era. Traditionally, chemical research relied heavily on manual “trial and error” methods and extensive laboratory experimentation, which were both time-consuming and resource-intensive. Today, Al innovations are digitizing the chemical landscape, providing high-speed, accurate, and cost-effective solutions for complex scientific challenges. This abstract explores the core technological advancements of Al in chemistry and their far-reaching impacts on research and industry. Technological Innovations-One of the most significant breakthroughs is in Predictive Molecular Modeling. Impact on Research and Industry-The impact of Al is most visible in Drug Discovery and Material Science. Core Technologies: Keywords: Artificial Intelligence (Al), Machine Learning (ML), Deep Learning, Networks, Big Data Analytics, Algorithm Transparency. Chemical Innovations: Automated Synthesis, De Novo Molecular Design, Retrosynthetic Analysis, Drug Discovery, Material Informatics, In Silica Modeling, QSAR (Quantitative Structure-Activity Relationship). Analytical Techniques: N H-NMR Spectroscopy, Infrared (IR) Spectroscopy, Mass Spectrometry, Structure Elucidation, Automated Spectral Interpretation. Risk & Security: Dual-Use Research of Concern (DURC), Chemical Biosecurity, Data Bias, Algorithmic Accountability, Toxicological Prediction, Hazardous Substance Design. Sustainability & Future Trends: Green Chemistry, Sustainable Manufacturing, High-performance Computing (HPC), Self Driving Laboratories, NVIDIA TITAN GPLJ computing.
Aman, Sorab Hassan, Supervisior Krishna Anand
Artificial Intelligence has become a genuine game-changer in chemistry and related fields like medicine, engineering, and physics. In this paper, we explore how AI is helping researchers develop new drugs at a much lower cost, predict how well a compound will dissolve, find the best conditions for chemical reactions, and even suggest practical ways to synthesize complex molecules. One standout example comes from MIT, where scientists used a machine learning system to discover a powerful new antibiotic. This shows how AI can move beyond theory into real-world breakthroughs. Our analysis reveals that AI can generate up to ten times more antibody sequence clusters compared to traditional lab-only methods. That is a massive leap in efficiency. On top of that, modern algorithms and supercomputers now allow us to model systems with hundreds of interacting ions and electrons – something that was practically impossible just a few years ago. These are not just incremental improvements; they represent a fundamental shift in how chemical research is done. Of course, challenges remain. Data is often scarce, and many AI models are still hard to interpret. But the direction is clear. AI is not replacing chemists; it is giving them a powerful new tool. This paper provides a clear overview of where AI stands today in chemistry, what has already been achieved, and what needs to happen next. Our goal is to help both chemists and AI specialists work together more effectively to create faster, cheaper, and more innovative solutions for the chemical industry.
Isaac Adom Boachie
This study examines the dynamic relationship between financial development and financial inclusion in Ghana using time-series causality and cointegration techniques. Drawing on annual data spanning 2005–2023, the study employs the Autoregressive Distributed Lag (ARDL) bounds testing approach, Error Correction Models (ECM), Vector Error Correction Models (VECM), impulse response functions, forecast error variance decomposition, non-linear threshold models, panel estimations, time-varying parameter models, and structural equation modeling to capture both linear and non-linear dynamics. The ARDL bounds test confirms the existence of a stable long-run equilibrium relationship between financial development and financial inclusion. Empirical results reveal bidirectional causality, with financial development exerting a stronger and more persistent influence on financial inclusion, particularly in the post-digital finance era. Short-run dynamics indicate significant adjustment toward long-run equilibrium, while impulse response and variance decomposition analyses show that shocks to financial development increasingly explain variations in financial inclusion over time. Non-linear and time-varying estimates further demonstrate that the impact of financial development on inclusion intensifies beyond critical financial depth thresholds and strengthens over successive periods. Structural equation modeling highlights the mediating roles of financial infrastructure and regulatory quality in reinforcing this nexus. The findings underscore the complementary and mutually reinforcing nature of financial development and financial inclusion in Ghana. Policy implications emphasize the need for integrated financial sector reforms that deepen financial markets while expanding inclusive access through digital innovation, institutional strengthening, and regulatory efficiency to support sustainable and inclusive economic growth.
Dr. Manisha Boricha, M.D. (Hom.), PhD
Homeopathy operates on ultra dilute principles, yet clinical effects are observed. This review explores possible physiological and molecular mechanisms. Methods: Narrative review integrating physiology, molecular biology, and biophysics evidence to analyze mechanisms underlying homeopathic potencies. Results: Findings suggest low-dose homeopathic remedies can trigger hermetic adaptive responses, modulate gene expression, and interact with cellular signaling. Nanostructures and electromagnetic coherence in potentized solutions may facilitate information transfer. Conclusion: Homeopathic potencies may act as informational regulators influencing systemic adaptive responses. Future research using multi-omics and biophysical methods is recommended.
Khushnaseeb, Krishna Anad, Mubayyana Parveen, Raj Kumar
Artificial Intelligence (AI) has emerged as a transformative tool in enzyme catalysis, revolutionizing the way researchers design, predict, and optimize enzymatic reactions. Enzymes play a crucial role in biological systems and industrial processes due to their specificity, efficiency, and eco-friendly nature. However, traditional methods of enzyme discovery and engineering are often time-consuming, labor-intensive, and expensive. The integration of AI technologies, including machine learning, deep learning, and data-driven modeling, has accelerated advancements in enzyme catalysis by enabling rapid prediction, design, and optimization of enzyme performance. AI-driven approaches facilitate enzyme discovery by analyzing vast biological datasets such as protein sequences, structural information, and functional annotations. Machine learning algorithms can identify patterns and relationships between enzyme structure and function, allowing researchers to predict catalytic activity, substrate specificity, and stability. These predictive models significantly reduce experimental efforts by narrowing down potential enzyme candidates for laboratory validation. Additionally, AI tools like protein structure prediction and molecular docking simulations enhance understanding of enzyme-substrate interactions, further improving catalytic efficiency. It also plays a key role in reaction optimization and process development. Machine learning algorithms can analyze experimental data to determine optimal conditions such as temperature, pH, solvent composition, and substrate concentration. This data-driven optimization enhances catalytic performance while minimizing waste and energy consumption. Furthermore, AI-enabled automation and robotics have enabled high-throughput experimentation, allowing rapid screening of enzyme variants and reaction conditions. Recent advancements in deep learning and computational biology have further expanded AI applications in enzyme catalysis. Tools such as generative models and neural networks enable the design of entirely new enzymes with desired catalytic functions. These innovations open new possibilities for synthetic biology and green chemistry by creating sustainable and efficient biocatalysts. AI-driven enzyme design also contributes to solving global challenges, including climate change, plastic degradation, and renewable energy production. This paper reviews AI-driven approaches like CNNs, GNNs, and transformers for protein structure prediction, catalytic activity estimation, and pathway optimization. We discuss datasets, model architectures, and case studies in pharma, biofuel, and green chemistry. Challenges like data scarcity and model interpretability are also addressed.
Abdul Ahmed Koroma, Michael Kingsley Afful, Victor S. Kamara
Preliminary geotechnical characterization for large-scale infrastructure projects is often hindered by the high cost and logistical constraints of intrusive borehole drilling. This study proposes a robust, non-invasive methodology to estimate the allowable bearing capacity (qa) using Vertical Electrical Sounding (VES) resistivity (ƥ).
Changli Li, Khalil Benbrahim, Yi Shi
Phase-sensitive optical time-domain reflectometry (Φ-OTDR) is a well-established technique for the distributed measurement of dynamic strain along the optical fiber. However, the metrological reliability of event identification is inherently degraded by coherent fading noise, laser phase fluctuations, and environmental interference, which corrupt the acquired backscattering signals and limit the measurement accuracy of the sensing system. This paper presents a novel signal processing architecture that enhances the information extraction capability within the Φ-OTDR measurement chain. By integrating multi-scale residual convolutional feature extraction with dual channel-spatial attention mechanisms and an improved Kolmogorov-Arnold Network (KAN) classifier employing learnable radial basis function splines, our approach robustly suppresses measurement noise to improve the fidelity of extracted event signatures. The hybrid architecture addresses the limitations of conventional threshold-based detection methods that suffer from poor estimation accuracy under low signal-to-noise ratio conditions. Experimental evaluation on the BJTU dataset demonstrates a significant improvement in measurement precision, achieving 99.87% classification accuracy with 6.2 ms end-to-end inference latency and 161 samples/s throughput—representing a 2.4× speedup over Φ-GLMAE and eliminating the 2.5 ms STFT preprocessing overhead of STFT-AECNN, while maintaining real-time suitability for embedded deployment. Ablation studies quantitatively validate the contribution of each component to noise robustness and measurement reliability, demonstrating that dual attention mechanisms provide the largest single accuracy gain (0.46%), while the KAN classifier and RBF splines collectively enable 79% error reduction versus CNN baselines. This work offers an effective solution for high-fidelity distributed acoustic measurement in challenging operational environments.
Ajaz Siddiqui, Badruddin, Hammad Hassan, Juber Akhtar, Md Hasheem Khan, Mohammad Irfan Khan, Sagufta Farheen, Shami Ahmad, Warisha Iman Ansari
Melasma is a chronic hyperpigmentation disorder characterized by symmetrical brown to greyish patches on sun-exposed areas of the skin, particularly affecting women with darker skin types. Although not harmful, it significantly impacts aesthetic appearance and psychological well-being. The condition arises due to increased melanogenesis triggered by ultraviolet (UV) radiation, hormonal influences, genetic predisposition, and oxidative stress. Conventional treatments such as hydroquinone, retinoids, and corticosteroids are commonly used but are often associated with adverse effects, limiting their long-term application. The present study focuses on the formulation and evaluation of a herbal cream as a safer and effective alternative for melasma management. The cream was developed using natural ingredients including aloe vera, rose water, licorice extract, almond oil, shea butter, vitamin E, and emulsifying wax. These ingredients possess antioxidant, anti-inflammatory, moisturizing, and tyrosinase-inhibiting properties, which collectively help in reducing melanin production, protecting against UV-induced damage, and improving overall skin health. The formulation was prepared using the oil-in-water (O/W) emulsion method and evaluated for various physicochemical parameters such as pH, spreadability, washability, texture, homogeneity, and irritancy. The results indicated that the cream had a smooth texture, good spreadability, excellent washability, and a skinfriendly pH of 5.60. No irritation or phase separation was observed, confirming its stability and safety. In conclusion, the developed herbal cream demonstrated promising characteristics and can be considered a safe, effective, and economical alternative for the management of melasma with minimal side effects and improved patient compliance.
Chinyere Ebirika, Mike Johnson Ugbogbo, Oluwaseyi Oluwatola Omonijo, Oluwatobi Akanbi Johnson
Agricultural financing institutions in Nigeria are still structurally fragmented despite growing efforts to promote digital inclusion initiatives. Majority of the existing Agri-Fintech interventions concentrate on digital payments, mobile access or isolated credit analytics; however, they rarely offer an integrated architecture that connects data capture, decision-making automation, secure execution and continuous monitoring. In order to addresses that gap, this study proposed a Design Science-grounded ICT-based automation framework that restructures agricultural financial service delivery as an end-to-end system. Drawing on recent literature, the framework translates documented problem clusters into a five-layer architecture that includes stakeholder data formalization, interoperable ICT integration, embedded decision intelligence, secure transaction execution and adaptive feedback mechanisms. Each layer directly addresses a literature-identified systemic weakness, with explicit traceability between theoretical gaps and architectural components. An illustrative system execution scenario is used to demonstrate operational feasibility and end-to-end process flow. Evaluation results indicate that the framework improves integration, reduces decision time, enhances transaction traceability and supports inclusion in low-connectivity environments. The system reduces information asymmetry and limits fund diversion through controlled execution mechanisms. The framework offers a context-aware blueprint suitable for low-connectivity and high-risk agricultural environments, emphasizing execution integrity, transparency and institutional accountability. Despite being conceptual, the model establishes a systematic framework for prototyping, empirical validation and extendable policy implementation in developing countries.
Dr. Avani Doshi, Hinal Patel
A robust, sensitive, and reproducible reverse-phase high-performance liquid chromatography (RP-HPLC) method was developed and validated using a Quality by Design (QbD) approach for the simultaneous estimation of dapagliflozin propanediol monohydrate and sacubitril–valsartan sodium complex in a synthetic mixture. Critical method parameters were systematically optimized through experimental design to ensure optimal separation, peak symmetry, and resolution. The chromatographic separation was achieved using a suitable C18 column with an optimized mobile phase composition under isocratic conditions. The method demonstrated excellent linearity, precision, accuracy, and specificity within the tested concentration ranges. Validation was performed in accordance with regulatory guidelines, confirming the reliability of the method for routine analysis. The QbD framework enabled a thorough understanding of method variability and robustness, ensuring consistent performance. This developed method can be effectively applied for quality control and simultaneous quantification of these drugs in combined pharmaceutical formulations.
Ajoku Kingsley Kelechi, Amobi Ikeolisa Victor, Onuoha Chidiadi Uchechi, Oparauwah Nnaemeka Macdonald
Many business organizations are quickly leveraging on powerful state-of-the-art Artificial Intelligence (AI) technologies and algorithms to learn from growing amounts of customer data in order to arrive at better business decisions that has the potential to improve services to customers, and by extension, their business operations. This paper x-rays how AI technologies are being utilized to enhance business decision-making processes and strategies. The global streaming giant Netflix was purposively selected for this analysis due to its global recognition as a pioneer in AI-driven personalization, content optimization, and data-driven strategic decision-making. The company provides publicly documented evidence of its AI research and deployment, making it a suitable and information-rich case for examining the relationship between AI technologies and business strategy. This review paper identified some specific AI technologies strategically adopted by Netflix which are providing enhancements in some business areas such as personalized user experiences, recommendation systems, optimized content delivery, streaming quality and optimization, etc. Some of these AI technologies include machine learning, computer vision, natural language processing, and predictive analytics. This paper equally emphasizes the growing ethical concerns in the utilization of AI technologies, especially in modern business operations and decision-making strategies. Some of the challenges reviewed with respect to Netflix AI-based operations include consideration for data privacy, algorithmic bias, and possible job displacement. The submission of this article demonstrate that the integration of AI has significantly improved Netflix’s business decision making, positioning it as a leader in the use of AI for business optimization.
Ambe Sangbong, Fonbeyin Henry Abanda, Laurantine Awah, Ngome Ngome
Indoor acoustic performance is increasingly recognized as a key component of sustainable interior design, influencing occupant’s comfort, perception, and productivity. Effective acoustic analysis requires the inte-gration of geometric data, such as spatial layout, with non-geometric data, including material sound absorption properties. While early-stage analysis is essential to avoid costly retrofits, current practices rely heavily on standalone tools like ODEON Room Acoustics Software, which often limit integration with the broader design workflow. Building Information Modelling (BIM) provides a holistic platform where acoustics can be em-bedded alongside architectural, structural, and sustainability considerations. This study addresses the gap between acoustic and sustainable interior design by developing a custom Revit plugin using the Autodesk Revit API in C#. The plugin calculates reverberation time (RT60) through Sabine’s and Eyring’s formulas, extracting geometric and material data from Revit and an external material database. Results are reintegrated into the BIM model as new attributes, enabling visualization within Revit, export as .csv files, and frequen-cy-based data highlighting. Findings show that embedding acoustic analysis within BIM enhances efficiency, supports informed material selection, and enables performance-based decision-making in sustainable interior design. By integrating sound quality with sustainability goals, this approach contributes to healthier, more comfortable, and environmentally responsible interior environments.
Mayank Jain, Nitin Goyal, Pankaj, Piyush Kumar Singh, Uttkarsh Sharma
Lung cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due to delayed diagnosis and limited availability of early screening services. Early identification of warning symptoms and modifiable risk factors can substantially improve clinical outcomes and timely intervention. This study presents a questionnaire-based intelligent system for preliminary lung cancer risk assessment and clinical recommendation. The proposed mobile application collects user information related to demographic characteristics, smoking history, environmental exposure, lifestyle habits, medical history, and common respiratory symptoms such as persistent cough, chest pain, wheezing, and shortness of breath. A weighted rule-based scoring model is applied to evaluate cumulative risk and classify users into Low, Moderate, or High Risk categories. Based on the identified risk level, the system generates personalized health guidance and consultation recommendations. In addition, an integrated AI chatbot provides instant responses to common health-related queries and promotes user awareness regarding lung cancer symptoms and prevention. The proposed framework offers a non-invasive, low-cost, user-friendly, and accessible solution for early-stage risk screening, particularly in rural and resource-constrained regions.
Dr. C.G. Vishnu Kumar, Dr. D. Ashalatha
Background: Neuromarketing has emerged as a field that applies neuroscience tools to understand consumer decision-making. However, the concept of neuromodulation – the targeted alteration of neural activity through external stimuli – represents a distinct and potentially more powerful paradigm for influencing consumer behavior at a neurophysiological level. Objective: To systematically map the existing literature on neuromodulation techniques applied to consumer buying behavior, identify the range of neuromodulatory interventions studied, critically appraise the evidence quality, and establish a research agenda for this emerging field. Methods: A scoping review was conducted following the Arksey and O'Malley framework and PRISMA-ScR guidelines. A systematic search was performed across PubMed, Scopus, Google Scholar, and Web of Science from inception to March 2026. The Mixed Methods Appraisal Tool (MMAT) was used for quality assessment of included studies. Results: Of 98 records identified, 21 studies met inclusion criteria. Quality assessment revealed that 62% of studies were of moderate to high quality, with case series and proof-of-concept studies dominating the evidence base. The evidence mapped across three primary neuromodulatory approaches: 1) Caloric Vestibular Stimulation (CVS) demonstrating reduced purchase probability via insular cortex modulation; 2) Transcranial Magnetic Stimulation (TMS) affecting valuation and preference formation in prefrontal regions; 3) Transcranial Direct Current Stimulation (tDCS) with emerging evidence for consumer choice modulation. Critical gap: The majority of studies focus on measurement (neuromarketing) rather than modulation (neuromodulation), with only CVS studies directly testing causal neuromodulatory effects on buying decisions. Conclusion: Neuromodulation of consumer behavior is an emerging but underdeveloped field. Caloric vestibular stimulation provides proof-of-concept that non-invasive brain stimulation can causally affect purchase decisions. Future research should prioritize replication studies, exploration of tDCS applications, and development of ethical frameworks.
Dr. Ashlatha, Dr. C.G. Vishnu Kumar
Background: Consumer decision-making is increasingly understood through neuroscientific frameworks, yet the specific roles of the prefrontal cortex (PFC) and corpus callosum (CC) in processing dynamic visual color stimuli remain unclear. Understanding these mechanisms has significant implications for product design, particularly in emerging categories such as health-oriented foods. Objective: To systematically map the existing literature on prefrontal and interhemispheric contributions to value-based consumer decision-making, with particular focus on how dynamic and attractive color stimuli influence neural valuation processes. Methods: A scoping review was conducted following the Arksey and O'Malley framework and PRISMA-ScR guidelines. A systematic search was performed across PubMed, Scopus, and Web of Science from inception to March 2026. Results: The evidence maps across three domains: (1) The ventromedial prefrontal cortex (vmPFC) serves as a central hub for integrating multi-attribute value signals into a "common currency" for decision-making ; (2) The lateral prefrontal cortex (lPFC) mediates goal-directed attention to relevant stimulus attributes ; (3) Color stimuli influence purchase intention through pathways involving trust, perceived safety, and emotional preference, with distinct neural correlates in frontal and visual processing regions . Critical gap: Direct evidence for corpus callosum involvement in interhemispheric color-value integration remains sparse, with most inferences drawn from connectivity studies rather than direct interventional research . Conclusion: The PFC, particularly vmPFC, plays a well-established role in value-based consumer choice. Color influences purchase decisions through both automatic attention capture and higher-order cognitive evaluation. There is a scope in future research to directly investigate corpus callosum contributions towards cross-hemispheric integration of color and value signals
Christina P. Atal, Francis Arlando L. Atienza, Jesus G. Calma Jr., Joy N. Sadol, Rejan L. Tadeo, Rhonnel S. Paculanan
This study presented the development of a Smart Collaborative Learning Platform that integrated Natural Language Processing (NLP), deep learning models, and recommendation algorithms to automate content generation and enhance learning experiences. The system was designed to process uploaded learning materials and transform them into structured outputs such as summaries, quizzes, and flashcards. It utilized NLP techniques to analyze and understand semantic content, enabling accurate interpretation of user inputs and educational materials. Deep learning models were employed to generate meaningful summaries and insights that supported efficient studying. Additionally, a recommendation engine personalized learning by suggesting relevant topics based on user behavior and performance. The platform also incorporated collaborative features that allowed users to interact, share knowledge, and engage in real-time learning activities. The system was evaluated using ISO 25010 software quality standards, focusing on functionality, usability, reliability, and performance. Results indicated that the platform achieved high user satisfaction and demonstrated strong system performance. Findings showed that the system improved learning efficiency, reduced study time, and enhanced knowledge retention. Furthermore, the integration of AI technologies enabled adaptive and personalized learning experiences. The study highlighted the effectiveness of combining automation and collaboration in modern education. Overall, the proposed platform provided an innovative and scalable solution for improving digital learning environments.
Dr. Tanushree Nayak, Swasti Bisai
Love, in its most profound and intricate essence, serves as both a muse and a mirror to the human condition. The poetic oeuvre of Pradip Kumar Patra is a testament to this emotional force, skillfully portraying its many dimensions whether be it the ecstatic heights of romantic devotion, the despair of unrequited affection, or the contemplative nuances of spiritual love. This study embarks upon an exploration of the conceptualization of love within a select group of Patra’s poems, focusing on the ways in which the poet weaves the fabric of affection, longing, and intimacy into a tapestry of poignant imagery and thought-provoking metaphors. Patra’s poems unfold like vivid snapshots, each one a lens through which the various facets of love are magnified. Love in Patra’s works is not merely an emotion but an evolving journey, intricately intertwined with the landscapes of time, identity, and the metaphysical. At the heart of this study is an investigation into how Patra’s lyrical voice captures the multidimensionality of love, transcending the simplistic definitions often associated with the term. In Patra’s poems, love is not merely a feeling confined to the limits of human interaction, but an expansive force that reverberates through the rhythms of nature, history, and the cosmos. His poems are not merely expressions of affection but are a testament to how love can become a prism through which one perceives the entire spectrum of life’s beauty and sorrow. Moreover, Patra’s poems delve deeply into the intersection of love and spirituality, suggesting that love, in its purest form, can transcend the physical realm and become a connection to the divine. In his verses, love is often depicted in its quieter, more contemplative moments: the fleeting glance, the soft touch, the unspoken word. Through this exploration, it becomes evident that love in Pradip Kumar Patra’s poetry is not simply a thematic element but a lens through which we can examine the larger questions of existence, connection, and purpose. Thus, this study highlights the profound impact of love in Patra’s poetry, illustrating how it serves as both a personal and universal force that fosters transformation, connection, and self-discovery and challenges the traditional paradigms of it.
Balasubbaiah Lukku, Gopichand Agnihotram, Raja Sekhar Reddy
Indoor navigation remains a critical challenge for existing GPS based systems, particularly within large campuses, warehouses, retail complexes, and industrial facilities. This study introduces a fully integrated navigation framework that seamlessly unifies outdoor GPS based routing with indoor digital-twin navigation using point cloud data. The proposed system, developed in Unity, supports real time localization, augmented reality (AR) based guidance, and hotspot driven pathfinding in complex indoor environments. Outdoor navigation is powered by GPS and Mapbox APIs for route computation, while indoor navigation employs Matterport generated digital twins combined with point cloud based spatial mapping to achieve high precision localization and mapping. The system autonomously detects transition boundaries between outdoor and indoor zones, dynamically switching navigation modes to maintain continuity.
Dr Shivani Gupta (PT)
Background: Patient adherence to physiotherapy rehabilitation protocols remains a critical challenge globally, with rates as low as 40–65% reported in neurological and musculoskeletal populations. Artificial intelligence (AI) and wearable technology offer promising solutions for objective monitoring and improving exercise adherence beyond the clinic. Objectives: To review the current evidence on AI and wearable technology applications for monitoring and improving patient compliance with physiotherapy rehabilitation programmes. Methods: A narrative review methodology was employed consistent with PRISMA 2020 reporting guidelines and structured using the PICO framework. Five electronic databases were searched (PubMed, Scopus, Cochrane Library, PEDro, and Web of Science) for studies published between January 2018 and April 2026 using search terms related to artificial intelligence, machine learning, wearable technology, and physiotherapy adherence. Studies involving any adult demographic and any physiotherapy environment were incorporated. Results: Six core AI mechanisms were identified across the thirteen included studies: real-time monitoring, personalised feedback, gamification, predictive non-adherence detection, automated reminders and adaptive exercise progression. Six of the thirteen included studies addressed predictive non-adherence detection and adaptive exercise progression which were the most widely supported mechanisms. In contrast, five studies supported real-time monitoring, gamification, and automated reminders. Wearable smart watches and IMU-based systems provided strong and consistent evidence for objective real-time exercise recognition in both clinical and home settings. AI-driven virtual assistants and gamification platforms demonstrated the greatest potential to improve patient engagement and motivation in home-based rehabilitation. Evidence for gamification and adaptive progression was primarily derived from review-level and observational studies rather than from primary, randomised experimental research, leading to a need for robust clinical trials in these areas. Conclusion: AI and wearable technology offer a transformative but underused opportunity for monitoring adherence to physiotherapy. Robust clinical trials, particularly in neurological rehabilitation, are urgently needed. Physiotherapists and researchers must engage with these technologies to ensure evidence-based, equitable, and patient-centred implementation.
Abiodun Olukayode Olotuah, Ejiro Eruese, Reuben Peters OMALE
This study covers the use of renewable energy technologies in study buildings, practices of energy efficiency, building materials that promote environmental sustainability, as well as the application of energy conservation methods in construction and operation of buildings. It is aimed at ascertaining and adopting energy efficient buildings to have better efficient and sustainable buildings in Nigeria. A qualitative analysis approach was employed by the researchers, while data was obtained through keen observations and case study analysis on three sustainable buildings within the FUTA campus. The three case study buildings are the A.T.E.D building, the C.R.E.T building, and the block of shops building for S.E.E.T School, all within the FUTA campus, and these buildings were selected because of the sustainable design strategies that were adopted and implemented in the construction. Findings show that there are existing and functional buildings with energy efficient features in FUTA, and these features can be replicated in future designs and constructions in the country, if the challenges in this area can be taken care of. The study recommends that government should provide more energy efficient building codes to support environmental sustainability. Also, the environmental professionals should see sustaining the environment as a priority and hence push for practices that will ensure a safer and more sustainable environment.
Adekunle Ogunnaike, Ayodeji Toluhi .F, Azuka Divine-Favour. O, Eribake Ayomikun, Gbemudu Ikechukwu .E, Lawal Rodiat .I, Oyebanjo Sesan
Building envelope systems determine energy efficiency, environmental impact, and occupant comfort in modern buildings. This systematic review of 101 Scopus-indexed sources (2020–2025) evaluates advanced envelope technologies for tropical climates, with emphasis on developing regions. Buildings consume 30–40% of global energy, with tropical regions exceeding 50% for cooling. This review evaluates performance advantages, implementation challenges, and current trends for advanced envelope technologies including phase change materials (PCM), adaptive facades, smart glazing, building-integrated photovoltaics (BIPV), and IoT-enabled systems. Results indicate that climate-responsive envelope design, interdisciplinary collaboration, and policy support are essential for sustainable buildings. Tropical office buildings achieve 14.2–31.5% energy savings through PCM and adaptive dynamic facades with IoT monitoring. Developing regions face barriers including high initial costs, limited technical expertise, and inadequate regulatory frameworks.
I. G. Saidu, K. A. Dabai, M. B. Abdullahi, Y. Abdullahi
This study presents the design and implementation of a low-cost indoor air quality monitoring and alert system capable of detecting particulate matter (〖PM〗_1.0,〖PM〗_2,5,〖PM〗_10).The system integrates real-time sensing, data acquisition, and an alert mechanism using LED indicators and a buzzer. Experimental results demonstrated strong dynamic responsiveness between particulate matter concentrations, exposure duration, and pollutant density, validating the sensor’s sensitivity and measurement stability under controlled indoor conditions. The prototype effectively detected rapid changes in air quality, issued timely alerts under unhealthy conditions, and returned toward baseline values after exposure. These findings highlight its reliability, affordability, and suitability for indoor applications, particularly in resource-limited environments.
Achammagari Niharika, Aishwarya N, Anujith KM, Dr. Suma
The educational landscape is undergoing a profound structural shift driven by the rapid maturation of Artificial Intelligence (AI) technologies. Rather than simply digitizing existing practices, AI systems—ranging from intelligent tutoring networks to predictive analytics—are fundamentally altering pedagogical delivery and classroom dynamics. This study investigates the concrete effects of these technologies on cognitive engagement, instructor workloads, and the broader learning environment. Diverging from purely theoretical reviews, this paper adopts a mixed-methods approach: it synthesizes secondary literature from 2018 to 2024 and incorporates primary empirical data collected via a structured survey of 67 educational stakeholders. Our integrated analysis reveals that AI-driven personalization drastically improves comprehension rates by adapting to individual learning paces, while simultaneously alleviating severe administrative bottlenecks for educators. However, the data also expose critical hurdles, notably persistent anxieties regarding data privacy, infrastructural deficits, and a reliance on continuous internet connectivity. Ultimately, we argue that realizing the full potential of educational AI requires a deliberate "human-in-the-loop" framework. Technology must act as an empathetic amplifier for human mentors, guided by strict ethical oversight and comprehensive professional development, rather than operating as an autonomous substitute.
Caleb Lateef Umoru, Emmanuel Eturpa Salami, Precious Bamiyo Metiboba, Tajudeen Isah, Vincent Onuwabhagbe Ogbeide
The increasing digitalization of critical infrastructure by developing countries has opened new security problems that existing conventional methods have failed to address. Particularly with advanced threats rapidly evolving. This paper aims to develop a system that monitors both active and passive threats using Artificial Intelligence integrated with lightweight deep learning for optimization to watch for threats in places where resources are limited. We used an hybrid model that combines Autoencoder and LSTM. The model performed excellently in learning threats. We used 20 epochs in training the system and observed a stable convergence when training the epochs and when it was tested, which means it performed good in terms of it generalization capacity. The reconstruction error distributions result showed a significant separation between benign and anomalous events (p < 0.01). Our tests showed that the proposed threat model framework was very good at detecting threats with accuracy of 96% and a confidence range of 94.95% to 97.05%. We did a a two-sample t-test comparing reconstruction errors between normal and attack traffic that produced a statistically significant separation (t ≈ 18.7, p < 0.001) with threat detection score of 95%. This showed the model performed well at telling the difference between attack traffic. All these results together show that our model is reliable and can work well in places where resources are limited. The outcome is a system that can watch for threats and adapt to situations, within countries that are resource constrained.
Dr. Thanakit Ouanhlee
Purpose: This study investigated the relationship between AI integration in compensation systems and the quality of human capital accounting disclosure (HCAD) among manufacturing organizations in Thailand's Eastern Economic Corridor (EEC), and developed and validated an integrated framework that links AI-driven compensation analytics to human capital disclosure practices. Design/Methodology/Approach: A cross-sectional, exploratory sequential explanatory mixed-methods design was employed, combining quantitative survey data from 400 manufacturing organizations across Chonburi, Rayong, and Chachoengsao with qualitative thematic analysis of three open-ended questions embedded in the same survey instrument. Quantitative analysis used correlation analysis, Cronbach's alpha reliability testing, and subgroup moderation testing through Fisher's z-test. Qualitative analysis followed Braun and Clarke's (2021) six-phase thematic method, with quantitative and qualitative findings integrated through a joint display (Fetters et al., 2013). Confirmatory factor analysis, bootstrapped mediation testing, and inferential moderated regression are committed to the next research phase. Findings: AI integration in compensation systems demonstrated moderate-to-high levels (M = 4.73), while human capital disclosure quality remained persistently low (M = 2.98), producing a data-to-disclosure gap of 1.75 points. The direct relationship between AI integration and HCAD quality was not supported (H1: r = −0.075, p = .132), nor was mediation by integration protocols (H2) or moderation by organizational size (H4). Pay transparency was confirmed as a significant positive moderator (H3: z = 2.25, p = .024), demonstrating that organizational transparency culture — rather than technological capability alone — conditions disclosure outcomes. Qualitative themes (organizational readiness, governance, ethical legitimacy) provided convergent evidence from an independent methodological lens. A tiered AI–Human Capital Accounting Disclosure (AI-HCAD) implementation framework was developed and validated across organizational segments. Barrier–enabler analysis revealed that technical constraints (M = 3.67) and weak external support structures (M = 2.45) sustain the gap between AI capability and disclosure practice. Practical Implications: Manufacturing organizations must invest simultaneously in AI infrastructure and in an internal transparency culture to translate data capabilities into stakeholder-accessible disclosures. Policymakers and industry bodies should strengthen external enablers through regulatory guidance and technical assistance frameworks. Originality/Value: This study provides the first empirically grounded framework that integrates AI-driven compensation systems with human capital accounting disclosure in emerging-economy manufacturing. The findings reframe AI integration as a necessary but not sufficient condition for disclosure quality — institutional readiness, embodied in pay transparency, is the enabling mechanism that translates technological capability into stakeholder-accessible reporting. By demonstrating that institutional readiness, not technological capacity, conditions disclosure outcomes, the study advances theory across AI transparency, human capital accounting, and organizational disclosure behavior.
Keerthanaa Vijayanand
Rapid urbanization across Indian cities has placed severe strain on existing wastewater management infrastructure, driving widespread contamination of surface and groundwater bodies. Conventional monitoring approaches depend on periodic laboratory analyses that fail to capture the dynamic spatiotemporal variability inherent in complex urban wastewater systems. This study proposes an integrated framework combining Internet of Things (IoT)-based real-time sensor networks with Machine Learning (ML) predictive models and AI-guided bioremediation protocols for comprehensive urban wastewater quality management. A multi-parameter sensor array measuring pH, dissolved oxygen, biochemical oxygen demand (BOD), chemical oxygen demand (COD), turbidity, nitrate, phosphate, heavy metal concentration, and temperature at sub-hourly intervals was deployed across seven nodes in a peri-urban Chennai catchment. A hybrid deep learning architecture (HydraSenze-AI v2.0) combining Long Short-Term Memory (LSTM) networks with Random Forest classifiers achieved a cross-validated contamination event prediction accuracy of 91.3% F1-score at 24-hour horizons. Prediction outputs dynamically scheduled bioremediation interventions using optimized consortia of Bacillus subtilis, Pseudomonas putida, and Rhodotorula mucilaginosa tailored to detected pollutant profiles. Pilot deployment in a peri-urban Chennai catchment demonstrated a 67% reduction in BOD load, 58% reduction in heavy metal concentration, a 33-percentage-point improvement in CPCB Class-C compliance, and a 34% freshwater substitution potential. These results demonstrate significant promise for scalable, cost-effective, AI-enabled urban water sustainability aligned with India's National Water Mission and SDG-6 targets.
Chandu C. B., Devayani J., Saptha Sanil, Sreejitha S. G., Sreelekshmi Y.
This paper investigates the optimization of Spectral and Energy Efficient Orthogonal Frequency Division Multiplexing (SEE-OFDM) for Visible Light Communication (VLC) systems, with a primary focus on mitigating the high Peak-to-Average Power Ratio (PAPR) and its adverse effects. Although SEE-OFDM enhances power efficiency by transmitting only positive signal components, it remains highly susceptible to LED nonlinearity, which introduces clipping distortion and degrades system performance. To address this challenge, a hybrid signal processing framework incorporating transform-based precoding, nonlinear companding, and time-domain noise cancellation is proposed. The combined approach effectively reduces PAPR and improves Bit Error Rate (BER) performance under nonlinear conditions. Simulation results demonstrate that the proposed methods significantly enhance signal integrity and transmission reliability while maintaining energy efficiency. This work provides a practical and robust solution for enabling high-speed, reliable VLC systems in the presence of hardware nonlinearity.
Dr. Anshul Rajawat, Dr. Maria Janet
This study empirically examines the challenges faced by Human Resource (HR) managers in contemporary organizations. A quantitative research design was adopted, and primary data was collected through a structured questionnaire from HR professionals across various industries. The study identifies key challenges such as talent acquisition, employee engagement, technological adaptation, and compliance management. Statistical analysis reveals that employee retention and engagement are the most critical concerns affecting organizational performance. The findings provide practical and theoretical insights by linking observed challenges with Strategic Human Resource Management frameworks. However, the study is limited by sample size and geographic concentration. Future research may expand the sample and incorporate qualitative methods for deeper insights.
Anazia Eluemunor Kizito, Maduabuchukwu Christopher, Nwokolo Geofrey Augustine
This study presents an Intelligent Role-Based Access Control model enhanced with Risk-Based Multi-Factor Authentication (R-MFA) to overcome the limitations of traditional Role-Based Access Control (RBAC) and standard role-based access control with Multi-Factor Authentication (MFA) approaches. The model combines structured authorization with adaptive, context-aware authentication to achieve a better balance between security and system performance. Its effectiveness was assessed by comparing it with traditional role-based access control and role-based access control integrated with multi-factor authentication using key performance metrics such as authentication time, access success rate, false acceptance rate (FAR), system throughput, and security strength index. The findings reveal that traditional role-based access control offers the fastest authentication time (1.2 seconds) and highest throughput (120 requests per second), but suffers from weaker security, with a 6.5% FAR and a security strength index of 68.0%. The introduction of standard multi-factor authentication improves security, increasing the success rate to 96.2% and reducing FAR to 3.1%, although it leads to higher authentication time (3.8 seconds) and lower throughput (95 requests per second). In contrast, the Intelligent role-based access control model enhanced with risk-based multi-factor authentication achieves a more balanced outcome, delivering a 97.8% success rate, a low FAR of 1.2%, moderate authentication time of 2.4 seconds, throughput of 110 requests per second, and the highest security strength index of 94.2%. Overall, the results highlight the model’s ability to enhance security without significantly compromising system efficiency.
Friday Nguvayasvika Mudondo Kubiku, Mary Gaviyao, Munyaradzi Kennedy Mutimbu, Nyasha Sakadzo
This study investigated the efficacy of Warburgia salutaris (pepper-bark) leaf extracts as an organic fungicide for controlling foliar fungal diseases in tomato crops (Solanum lycopersicum cv. ‘Jemar’). The experiment was conducted at Mutare Polytechnic, Zimbabwe, in 2024, using a Randomised Complete Block Design (RCBD) with five treatments and five replications. Treatments comprised three extract concentrations (5%, 10%, and 15%), a commercial fungicide (Bravo® 500 SC), and an untreated control. Results showed significant differences among treatments (p ≤ 0.001) for all measured variables. The 10% and 15% concentrations achieved mean disease severity ratings of 1.5 ± 0.2 and 1.2 ± 0.1 respectively, representing Alternaria solani disease reductions of 66.7% and 73.3% relative to the untreated control (4.5 ± 0.5), and were statistically comparable to Bravo (1.8 ± 0.2). The 15% concentration produced the highest fruit yield (3.3 ± 0.2 kg/plant) and fruit count (13.1 ± 1.2 fruits/plant), exceeding Bravo in both A. solani disease control (122%) and yield performance (118%). A strong negative correlation was observed between disease severity and fruit weight (r = −0.89, p ≤ 0.001). These findings demonstrate preliminary evidence that W. salutaris leaf extract, particularly at 10–15% concentrations, is an effective and practical organic fungicide option for smallholder tomato farmers, comparable to or exceeding the performance of a conventional synthetic fungicide under field conditions.
C. N. Onyechi, Chinedum Amaechi, Onyemelukwe Nnaemeka
In March 2026, a threat actor designated "Byte To Breach" exploited CVE-2025-55182 (CVSS 10.0)—a pre-authentication remote code execution vulnerability in React Server Components—on an unpatched, internet-facing pilot server belonging to Sterling Bank Plc, a Tier-2 Nigerian commercial bank. The initial compromise triggered a cascading breach that ultimately exposed 3 terabytes of data from Remita, Nigeria's primary government payment platform, including 657,242 KYC documents and Hardware Security Module (HSM) key files for 46 financial institutions. This paper presents a technical autopsy of the cascading breach, analyzing: (i) how a single CVE enabled lateral movement across interconnected financial infrastructure; (ii) the four-stage exploit chain of React2Shell and its evasion of existing defenses; and (iii) why "trust corridors" between financial institutions amplify rather than contain breaches. Drawing on open-source intelligence analysis of actor-published artefacts, network telescope measurements of React2Shell exploitation, and the threat actor's own Q&A with researchers, we reconstruct the complete attack chain using the MITRE ATT&CK framework. Our analysis demonstrates that the breach was not a sophisticated targeted operation but an opportunistic exploitation of elementary security failures: an unpatched vulnerability, hardcoded credentials in source code, and implicit trust relationships between connected institutions. We conclude with technical recommendations for zero-trust inter-bank architectures, secrets management, and detection rules for CVE-2025-55182 exploitation patterns.
Apurva Kanyalkar
The research focuses on reassessing the global fashion goods industry across its value chain using digital literacy and digital transformation. It encompasses design, material sourcing to manufacturing, logistics, and retail. Illustrating five major categories of digital technologies—connectivity tools, transaction processing platforms, analytical and data visualization tools, security systems, and artificial intelligence. The study explores how digital capabilities enhance responsiveness, traceability, operational excellence, and customer experience. With a structured analysis of value chain functions, the study highlights utilization of digital tools in addressing persistent industry challenges like volatile demand, long lead times, sustainability compliance, counterfeiting and logistics complexity. The paper further examines use of digital tools in planning processes including forecasting, inventory optimization, production scheduling, and logistics execution. Emerging future readiness themes such as AI driven design, intelligent retailing, cybersecurity, resilience against geopolitical and climate disruptions are discussed to summarize the next stage of digital evolution. The study concludes that digital literacy is a technical competency along with a strategic capability that will define competitiveness, adaptability, and sustainable growth in the fashion goods industry.
Dr. Suma S., Eldhose James, M. S. Bhavath Krishna, Muhammed Sanad V. K.
The digital world is expanding fast, but so are the cracks in its armor. Traditional security tools are failing to keep up with the sheer volume of modern cyber threats. This paper takes a hard look at how Artificial Intelligence (AI) is stepping in to fix this mess. We're shifting from a reactive defense strategy to one that predicts attacks before they land. We explore how AI is being used to detect intrusions, classify malware, and stop phishing, while also being honest about the risks, like attackers using AI against us and the problem of opaque algorithms we can't explain. The bottom line? AI isn't a magic fix, but it’s the only way we stand a chance against the speed of modern cybercrime.
Chanchal Kashyap, Dr Krishna Anand, Prof. Raj Kumar, Rishabh Kumar
Rare diseases affect a significant portion of the global population despite their individual rarity, yet therapeutic development remains limited due to economic and scientific constraints. Artificial intelligence (AI) has emerged as a transformative approach in pharmaceutical research, enabling the analysis of large-scale biological datasets and accelerating the identification of potential drug candidates. This study explores the role of machine learning and deep learning techniques in rare disease drug discovery. AI-driven models facilitate drug-target interaction prediction, molecular optimization, and drug repurposing, significantly reducing time and cost. The paper also discusses methodological frameworks, applications, challenges, and future directions of AI integration in pharmaceutical research. The findings indicate that AI has the potential to revolutionize rare disease treatment by improving efficiency, accuracy, and accessibility.
Krishna Anand, Rajkumar, Vaishnavi Sharma
The Suzuki–Miyaura cross-coupling reaction is among the most widely employed carbon–carbon bond-forming reactions in synthetic organic chemistry. Despite its broad utility, conventional protocols rely on hazardous solvents such as toluene and dichloromethane, stoichiometric inorganic bases, and energy-intensive heating all of which conflict with the Twelve Principles of Green Chemistry articulated by Anastas and Warner (1998). This research paper investigates how Artificial Intelligence (AI) and Machine Learning (ML) can be systematically applied to render this reaction sustainable, efficient, and scalable. A four-stage AI-Green Chemistry Optimisation (AI-GCO) Framework is proposed, integrating Molecular Transformer networks for retrosynthetic planning, COSMO-RS with Random Forest classification for green solvent screening, Life Cycle Assessment (LCA)-coupled multi-objective route ranking, and hybrid ML-Computational Fluid Dynamics (CFD) scale-up simulation. The framework is validated on the model reaction of 4-bromoanisole with phenylboronic acid to yield 4-methoxybiphenyl. Key outcomes include a predicted yield of 89.4 ± 2.1%, E-factor of 6.2 ± 0.8 kg waste/kg product (reduced from 32.1 in the toluene baseline), Global Warming Potential (GWP) of 4.1 ± 0.6 kg CO2-eq/kg product, and Process Mass Intensity (PMI) of 18.4 ± 1.2 representing a 43% improvement over the conventional protocol. The industrial sitagliptin biocatalytic case study further demonstrates an 86% reduction in E-factor (50.3 ± 6.1 to 7.1 ± 1.2, p < 0.001) alongside a 104% yield gain. A meta-analysis of 72 peer-reviewed studies (2018–2025) provides statistical grounding for task-specific model selection, revealing that Transformer networks, Bayesian Optimisation, and Random Forest classifiers each excel within distinct sub-problems of the green chemistry workflow. Taken together, these findings underscore the transformative potential of AI as a practical enabling tool for green synthesis, offering chemists a rigorous, data-driven alternative to exhaustive experimental screening in both academic research and industrial manufacturing contexts. All computational findings are reported as mean ± standard deviation from five independent runs, with statistical significance confirmed at α = 0.05. Important disclaimer: all yield, E-factor, PMI, and GWP values reported in this study are computational predictions derived from machine learning models and literature data, not experimental measurements. Future experimental validation at laboratory and pilot scale is explicitly recommended to confirm these predicted outcomes.
Joseph Musona
The cement industry remains essential for infrastructure development yet generates significant air pollution with consequent health and livelihood risks for surrounding communities. Despite global decarbonisation commitments and corporate mitigation pledges, evidence from developing countries suggests persistent implementation gaps. The research gap this study addresses lies in the limited empirical examination of whether documented corporate mitigation measures translate into measurable community-level livelihood protection, particularly for informal sector workers in African cement-producing areas. This study examines the effectiveness of air pollution mitigation measures at the Lafarge Zambia cement plant in Chilanga District, focusing on impacts on vegetable vendors in adjacent Freedom Compound. A convergent mixed methods design employed a quantitative survey of 87 vegetable vendors, four focus group discussions with community members, key informant interviews with three Zambia Environmental Management Agency officials and four community leaders, and systematic analysis of institutional reports and corporate documents. Dust exposure was measured through vendor-reported frequency of visible dust deposition on produce, with cross-validation against documented complaint records and institutional inspection reports. Economic impact was operationalised as reported weekly income loss, frequency of customer rejection, price discounting necessitated by dust, and disposal of unsalable produce. Despite documented commitments including electrostatic precipitators, baghouse filters, and water spraying systems, 81.6 per cent of vendors reported daily dust deposition on produce. Economic impacts included reduced sales reported by 67.8 per cent of respondents, discounted prices for affected produce, and product spoilage requiring disposal. Regulatory oversight was perceived as ineffective, with 70.1 per cent of vendors expressing low trust in ZEMA and 80.4 per cent expressing low trust in Lafarge. These findings indicate that community-perceived dust exposure persists at levels causing measurable economic harm, despite corporate claims of mitigation functionality. The study concludes that gaps between documented mitigation commitments and observed environmental outcomes arise not from absence of technology but from implementation and enforcement deficits. Positioning these findings within the global cement sector's decarbonisation trajectory and Africa's evolving regulatory landscape, the study argues that sustainable solutions require strengthened implementation, expanded monitoring, genuine community participation, and enhanced regulatory enforcement to protect vulnerable livelihoods and advance environmental justice.
Adeleke O.A, Ademu Ali, Adewoyin J.E, Amos Ibrahim S, Ashiru S.K, Benson A. G, Ehijamuse J.O, Idris I.A, Micheal A.I, Oche J.O
Rapid urbanization in many developing cities has placed increasing pressure on emergency response infrastructure, particularly fire service systems, where spatial accessibility is crucial for minimizing response time and mitigating fire-related risks. This study evaluated the spatial adequacy of fire station coverage in Ibadan North Local Government Area (LGA) of, Nigeria. It identifies optimal locations for additional facilities using Geographic Information System (GIS)-based spatial analysis. High-resolution satellite imagery, road network data, and population statistics were integrated within an ArcGIS environment to conduct service area modelling, route optimization, origin–destination cost matrix analysis, and location–allocation modelling. The road network was digitized and classified according to the road hierarchy and travel speed to simulate realistic emergency vehicle movements. The results indicate that only seven operational fire stations serve the wider Ibadan metropolis, with only one located within the study area. Relative to the recommended benchmark of one station per 50,000 residents, the current configuration is inadequate for populations exceeding 300,000. Accessibility modelling shows that incidents within approximately 1.4 km of a station can be reached within 2.1 min under ideal conditions and 2.8 min under constrained scenarios; however, service-area analysis using 4-minutes, 5-minutes, and 8-minutes thresholds reveals fragmented coverage, leaving several densely populated areas beyond acceptable response limits. Location–allocation modelling identified optimal sites for additional stations, and simulated deployment significantly improved spatial equity and response coverage. These findings demonstrate the critical role of GIS-driven spatial optimization in strengthening emergency planning and highlight the urgent need for strategic expansion of fire service to enhance urban resilience in rapidly growing cities.
Assoc. Prof. Hannington Twinomuhwezi, Dr. Basake Julius Aochere, Mr Masereka Joackim, Mr. Ndyabarema Robert, Mr. Nkuutu David Nelson
Urban wetlands are increasingly exposed to microplastic contamination driven by rapid urbanisation, inadequate waste management and expanding wastewater discharges. This study presents a comprehensive assessment of microplastics in the Lubigi Wetland (Kampala, Uganda). Water and sediment samples were collected from nine sites spanning upstream, midstream and downstream zones and from four vertical strata (surface, middle, bottom water and 0–10 cm sediment). Samples were processed by density separation (saturated NaCl), peroxide digestion and vacuum filtration; particles were morphologically classified by stereomicroscopy and polymer types confirmed by Fourier Transform Infrared Spectroscopy (FTIR). A total of 1,118 microplastic particles were recorded: microbeads dominated (58.7%), followed by pellets (15.9%) and fragments (11.4%). Transparent particles comprised 42.8% of the assemblage and 61% of particles were < 0.001), with midstream sediment layers (notably Namungona and Nabweru) identified as depositional hotspots. FTIR confirmed polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), polyvinyl chloride (PVC) and Nylon6, with PET and PP more frequent in water and PE, PS and PVC more common in sediments. The dominance of microbeads and the polymer signature implicate urban and domestic sources (personal care products, packaging, wastewater and textile effluents) and reflect transport and depositional processes governed by hydrodynamics and wetland geomorphology. These findings align with regional and global observations that freshwater and wetland systems are important sinks and conduits for microplastics and underscore the need for targeted waste management, wastewater controls and routine monitoring to protect wetland ecosystem services and public health.
Aina Oluwagbenga Oluwole, Bamise Paul Adedayo, Ojo Akintunde Akinsehinde, Oloruntimilehin Oyindamola Esther, Owolabi Babajide Augustine
Pain is a major and distressing symptom among orthopedic patients, often hindering recovery, psychological wellbeing, and quality of life. Although global progress has been made in pain management, inadequate awareness and negative perceptions of pain relief options persist, especially in low- and middle-income countries. In Nigeria, particularly Ekiti State, limited studies have explored patients’ knowledge and perceptions regarding pain and available management strategies. This study assessed the awareness and perception of pain and pain-management options among orthopedic patients in selected tertiary hospitals in Ekiti State and examined the factors influencing their utilization, including commonly used non-pharmacological methods. A descriptive cross-sectional design was employed among patients receiving care in the orthopedic units of Federal Teaching Hospital, Ido Ekiti and Ekiti State University Teaching Hospital. Using a total enumeration and convenience sampling approach, 53 eligible patients aged 18 years and above were recruited. Data were collected using a validated structured questionnaire and analyzed with SPSS version 27, using descriptive and inferential statistics at a 0.05 significance level. Findings revealed generally low awareness, with 58.5% demonstrating poor knowledge of pain-management options. Perception was largely negative (62%), with misconceptions linking analgesics to addiction, weakness, and adverse effects. Key influencing factors included inadequate health-worker education, fear of addiction, high cost or unavailability of medications, and cultural beliefs. Prayer, distraction, and positioning were common non-pharmacologic methods, while evidence-based techniques were underused. Both null hypothesis were accepted meaning there is no significant relationship between the level of education(p=0.5412), as well as duration of admission and awareness and perception of pain management. The study concludes that orthopedic patients exhibit poor awareness and negative perceptions toward pain-management options.
Mohamed Ichou, Saad Ichou
Using panel data for six partner economies participating in China’s Belt and Road Initiative from 2010 to 2023, this study examines whether formal participation increases bilateral trade with China. We estimate gravity-style two-way fixed effects models and a Poisson pseudo-maximum likelihood specification for exports, imports, and net exports. The results show no consistent average trade effect from participation. Instead, gains depend on partner economic size, infrastructure capacity, and broader macroeconomic conditions. These findings caution against assuming automatic trade expansion and highlight the importance of complementary domestic policies to realize meaningful and sustainable benefits.
Bhushan Anand Ladgaonkar, Dr. Roshni Padate
Deep learning classifiers exhibit susceptibility towards iterative adversarial perturbations, often under high-fidelity attacks experiencing total categorical collapse. To address this, we introduce the Asymmetric Latent Purifier (ALP), a novel structural defence mechanism inspired by the stochastic information bottlenecks of the 2026 Unified Latents (UL) generative framework, Unlike Traditional deterministic autoencoders, ALP incorporates an adaptive, non-differentiable Gaussian noise layer within a 64-channel latent manifold to disrupt adversarial gradient flows. Empirically validated on CIFAR-10 dataset using an Apple M4 8-core GPU architecture. While the unprotected baseline experiences a total categorical collapse ( 0.00% accuracy) under a 7-step iterative PGD attack, our 20-sample adaptive ensemble approach achieves a robust accuracy of 32.06% (SD=1.94%)( averaged over 5 trials ) while ensuring a high-fidelity reconstruction of 25.68 dB. Operating a total system latency of 13.86ms, offers a promising path towards real-time flexibility for complex RGB varieties. Furthermore, with a single-sample inference latency of 1.25 ms, ALP represents a 100x to 1000x speedup over iterative diffusion-based purifiers, enabling real-time adversarial immunity in safety-critical systems.
Ade Dwinta, Eko Nursanty, Firda Herlina, Hilma Erliana, J.C. Heldiansyah, Julianti Marbun, Naimatul Aufa, Rais D. Hi Yusuf, Soraya Rosna Samta
This community service paper presents a field-based engagement program conducted with the Minang Saiyo Community in Kuala Lumpur, a group of Indonesian Minang migrant families whose livelihoods are closely tied to restaurant entrepreneurship. The program addressed the relationship between domestic living conditions, restaurant-based work patterns, and family health in migrant working households. Many participants lived in environments where residence, business support, storage, rest, and childcare overlapped, creating challenges related to ventilation, sanitation, spatial comfort, safety, and healthy daily routines. The program was carried out by experts in architecture and building engineering through field observation, participatory discussion, environmental health education, and technical guidance on simple spatial improvements. The intervention focused on practical aspects of healthy living environments, including natural ventilation, lighting, sanitation, circulation safety, waste handling, moisture control, and clearer separation between clean and service areas. Recommendations were designed to be low-cost, gradual, and feasible within rented or spatially constrained settings. The activity found that participants responded positively to practical and context-sensitive guidance that connected health, family well-being, and spatial arrangement. The program also showed that architecture-based community service can contribute meaningfully to strengthening healthy living practices among migrant entrepreneur families. More broadly, the study highlights the importance of spatial literacy as part of community empowerment in urban migrant settings.
Dr. Basake Julius, Ndyabarema Robert, Nkuutu David Nelson
Environmental and Social Audits (ESAs) are institutionalised post‑implementation accountability mechanisms intended to ensure that infrastructure projects meet environmental sustainability and social equity standards. This document‑based study evaluates ESA effectiveness for electricity transmission infrastructure in the Greater Kampala Metropolitan Area (GKMA), Uganda, using a qualitative‑dominant mixed documentary approach. A purposive sample of 24 ESA and related follow‑up documents (2015–2025) was systematically coded and analysed using deductive and inductive thematic techniques; compliance indicators were extracted for descriptive quantitative comparison. Findings reveal a persistent compliance–outcome paradox: audit records routinely document procedural adherence but provide limited, verifiable evidence of ecological recovery or social redress. Structural constraints identified include epistemic erasure, institutional fragility and weak stakeholder participation. Audit frameworks show ecological blind spots notably under‑monitoring of habitat fragmentation and avian mortality and recurring social grievances over land acquisition, compensation delays and perceived electromagnetic field (EMF) risks. Descriptive indicator comparisons and a diagnostic OLS model indicate a weak association between reported compliance and documented sustainability outcomes (compliance coefficient = 0.12, Std. Error = 0.09, t = 1.33, p = 0.18, R^2 = 0.08). The study concludes that ESAs in GKMA currently function more as symbolic governance instruments than as transformative sustainability tools. It recommends reorienting audit systems towards participatory, adaptive and knowledge‑inclusive frameworks that institutionalise long‑term ecological monitoring, embed community‑based auditing and establish binding enforcement mechanisms to ensure audit findings translate into measurable outcomes.
Kafeer Ahamed Mohideen
This paper provides a critical review of the literature exploring the relationship between Enterprise Resource Planning (ERP) systems and the financial performance of Small and Medium-sized Enterprises (SMEs). While substantial research exists on ERP in large enterprises, the SME context is distinct and fraught with unique challenges. The review synthesizes findings into three dominant narratives: the "Productivity Paradox," the "Integrated Value Proposition," and the "Contextual Mediation" perspective. A critical analysis reveals significant methodological limitations, including a reliance on perceptual data, short-term financial metrics, and a lack of consensus on the definition of "financial performance." Furthermore, the literature often under-theorizes the complex mediating role of organizational and external factors. The paper concludes by identifying critical research gaps and proposing a framework for future studies to move beyond simplistic cause-and-effect models towards a more nuanced understanding of how, when, and why ERP systems influence the financial health of SMEs.
Grace Ann Lagare, James Paglinawan
This qualitative study explores the lived experiences of seasoned teachers with over 10 years of service at Holy Cross College of Calinan Inc., a private Catholic-Riverian institution in Davao City, Philippines. The purpose was to understand the factors sustaining their long-term commitment amid the public-private salary gap and systemic challenges in private education. Guided by a phenomenological narrative inquiry, the research addressed four key questions: reasons for staying, challenges faced, benefits gained, and advice for novice teachers. Data were collected through Google Forms with open-ended questions and semi-structured interviews from 5–10 purposively sampled participants, analyzed via thematic analysis and interpreted through Herzberg’s Two-Factor Theory. Key themes emerged: interpersonal connectivity and institutional belongingness as primary motivators, with colleagues described as “family” fostering affective commitment; intrinsic fulfillment from student growth, professional mastery, and alignment with the school’s Catholic-Riverian values; and benefits such as spiritual maturity, curriculum familiarity, and resilience. In contrast, hygiene factors—financial constraints, heavy workloads, accreditation pressures, and student behavior—were identified as sources of dissatisfaction, reflecting systemic challenges in private schooling. Despite these hurdles, teachers remained because motivators outweighed hygiene deficiencies, transforming teaching into a vocation rather than a mere occupation. The study concludes that teacher retention in private Catholic schools is sustained less by material incentives and more by relationships, values, and shared identity that anchor educators in their institutions. While these findings provide valuable insights for cultivating supportive cultures, reducing administrative burdens, and enhancing faith-based support, they are context-specific to one institution and a small participant pool. Future research should expand to diverse private school contexts to test whether similar motivator–hygiene dynamics hold true across sectarian and non-sectarian institutions.
Mohamed Ichou, Wang Mengmeng
AI chatbots have become central to e-commerce customer service globally, yet the trust mechanisms driving their adoption in emerging markets remain poorly understood. Existing research, grounded largely in the Technology Acceptance Model, emphasizes perceived usefulness and personalization as primary adoption drivers — constructs whose predictive validity in low AI-exposure, high uncertainty-avoidance markets cannot be taken for granted. This study proposes and tests a credibility-first framework among Moroccan e-commerce users, arguing that in high uncertainty-avoidance cultures, credibility — defined as the perceived honesty, reliability, and transparency of the chatbot — will be the primary feature activating consumer trust, while perceived usefulness, interactivity, and personalization are expected to have weak or non-significant effects. Survey data from 150 respondents were analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) via the lavaan package in R, with mediation tested through 5,000 bootstrap resamples. Model fit was excellent (CFI = 0.978, RMSEA = 0.076). Results confirm that credibility is the primary significant predictor of trust (β = 0.486, p < .001), while usefulness, interactivity, and personalization are non-significant. Trust strongly predicts satisfaction (β = 0.532, p < .001), and full mediation is confirmed exclusively for the credibility–trust–satisfaction pathway (indirect β = 0.259, p < .001). These findings establish the credibility highway as the primary verified route to consumer satisfaction in this market, with direct implications for chatbot design priorities, personalization strategy, and AI governance policy in comparable emerging markets.
Ajay. T, Dhesigan. K. S, Karmugilan. K. V, Logith. A, Meera. S
Voting with Fingerprint Technology and the Internet of Things (IoT) will encourage greater confidence in voting due to added security and efficiency during elections. Technology has evolved and traditional voting systems suffer from various issues including impersonation, duplicate voters, and human error when counting or recording the vote. The Fingerprint-Based Voting System using IoT will use fingerprint technology to authenticate votes in order to ensure that only registered voters will be able to vote. Once the voter is verified by the system, that voter can cast his/her vote via push buttons and the system will record the vote at that time. Since data transmissions occur in real-time from IoT Devices to a cloud services provider, the vote can be monitored from anywhere and results will be processed more quickly than under current voting standards. The Fingerprint Based Voting will help avoid multiple voting by changing the status of the voter after they vote. Most importantly, the Fingerprint Voting System will minimize human business and improve voting accuracy, transparency, and reliability for today's digital voting methodologies.
Lorel Marie G. Igot
This study sought to determine the level of alignment between the MATATAG Curriculum and Pre-service teachers from the Bachelor of Technical-Vocational Teacher Education (BTVTEd) program at Cebu Technological University-Main Campus, as basis for a curriculum enhancement plan. The study used a quantitative descriptive method, which involved the use of a survey questionnaire distributed to fifty pre-service teachers. The data were analyzed using descriptive statistics, such as mean and standard deviation, and inferential statistics to identify differences in the perceptions based on selected profile variables. The results revealed that the MATATAG Curriculum is perceived as highly effective in highlighting the key competencies, including the technical skills, occupational safety, entrepreneurship, sustainability, and experiential learning. Likewise, the BTVTEd program was perceived as effective in developing technical skills and pedagogical skills for pre-service teacher. It also revealed a strong alignment between the curriculum requirements and the competencies developed in the BTVTEd program. Respondents indicate a high need for continuous improvement in curriculum design, faculty professional development, institutional collaboration, and the provision of instructional resources. Moreover, no significant differences in perceptions were found when grouped according to age, gender, or program enrolled. This research concludes that the MATATAG supports the development of learner’s competencies and the BTVTEd program sufficiently equips pre- service teachers for curriculum-aligned instruction. It is recommended for institutions to continue and maintain a regular review of their curriculum, enhance mentoring and practical training for pre-service teachers, and enhance communication and collaboration among stakeholders to ensure program effectiveness and relevance.
Chikwado Precious Nwaiwu, Yirakpoa Patience Nwambo
The growing interest in natural and sustainable skincare products requires innovative strategies. This trend is driven by increasing consumer demand for products that are environmentally sustainable and skin-friendly. This study examines the characteristics of sugarcane bagasse-based activated carbon (SBAC) to evaluate its potential use in skincare formulations. Sugarcane bagasse was carbonised at 700°C and subsequently chemically activated with 30% (w/w) phosphoric acid (H3PO4) to enhance its adsorptive properties. The activated carbon was analysed for its physicochemical properties, including carbon content, moisture content, ash content, sulphur content, pH value, adsorption capacity, and removal efficiency. The results revealed a carbon content of 97.07%, moisture at 1.77%, ash content at 2.93%, sulphur content at 0.25%, a neutral pH of 7.04, an adsorption capacity of 148.80 mg/g, and a removal efficiency of 98.35% for methylene blue. The characteristics suggest potential benefits in skincare products, including enhanced impurity removal, reduced skin irritation, and improved skin clarity. The neutral pH of 7.04 and the low sulphur content of 0.25% indicate that this formulation is suitable for use on sensitive skin. The SBAC demonstrated significant adsorption capacity (148.80 mg/g) and removal efficiency (98.35%) for methylene blue, highlighting its potential for detoxification and purification of the skin. The findings suggest that SBAC serves as a viable natural ingredient for skincare formulations, offering a sustainable and effective alternative for skincare applications.
Harrison E. OkulA, Tajudeen O. Ajayi, Tope S. Ayodele
Climate change and rapid urbanisation are intensifying housing deficits and environmental pressures in Nigeria, necessitating a transition toward climate-smart housing systems. However, there is a lack of empirically validated architect-centred integration frameworks linking design, materials, and digital technologies. This study addresses this gap by adopting a PRISMA-based systematic review methodology, analysing 57 peer-reviewed journal articles (2016–2026) selected from an initial pool of 493 records, following PRISMA guidelines and supported by international policy reports. The study synthesises evidence across three core domains: passive design strategies, low-carbon materials, and digital technologies. Findings show that passive strategies reduce operational energy demand by 30–50%, low-carbon materials decrease embodied emissions by 30–40%, and digital technologies enhance construction efficiency and reduce waste by 15–25%. Inferential analysis using a Chi-square test (χ² = 0.94, p > 0.05) indicates no statistically significant difference in thematic prominence, confirming that these strategies are complementary rather than hierarchically dominant. The results further reveal strong correlations between passive design and thermal comfort, low-carbon materials and emission reduction, and digital technologies and lifecycle optimisation. Despite these benefits, adoption remains constrained by institutional inefficiencies, financial limitations, and gaps in technical capacity. The study establishes the architect as a system integrator within socio-technical housing systems, capable of aligning environmental performance, material innovation, and technological application. It concludes that architect-led, interdisciplinary, and policy-supported approaches are essential for scaling climate-smart housing and achieving sustainable urban transformation.
Elly Gamukana, Gloria B Muhoza, Justina Ogabon, Ramadhan Malinga
Cancer case management requires coordinated collaboration among multidisciplinary teams to ensure effective treatment, continuity of care, and improved patient outcomes. However, fragmented information sharing remains a persistent challenge across healthcare systems. This systematic review examines existing collaborative processes, frameworks, and systems used in cancer case management, with the aim of identifying their strengths, weaknesses, and research gaps. Guided by Arksey and O’Malley’s scoping review methodology, a comprehensive search was conducted across five databases: PubMed, Google Scholar, PLOS, ScienceDirect, and IEEE Xplore, covering studies published between 2015 and 2025. A total of 287 records were identified, of which 23 peer-reviewed studies met the inclusion criteria and were analysed. The findings reveal that while current approaches support care coordination, symptom monitoring, and patient engagement, they are largely constrained by the lack of real-time information exchange, limited stakeholder inclusion, over-reliance on manual communication channels, and inadequate integration across care teams. Furthermore, many existing digital systems emphasize data storage, security, and privacy but fall short in facilitating dynamic, multistakeholder collaboration and seamless workflow integration. These limitations highlight a critical gap between technological capabilities and the practical requirements of multidisciplinary cancer care. This review underscores the need for integrated, real-time, and stakeholder-inclusive frameworks to enhance information sharing and improve the overall effectiveness of cancer case management.
Joan P. Bacarisas, DM, MAN, RN, Mariel Gay B. Guerra, RN
Existing literature often focuses on communication outcomes without fully comparing communication behaviors across generational groups, creating a gap that this study aimed to address. This study utilized a quantitative-descriptive comparative research design to determine the levels of communication patterns, communication styles, and communication skills among intergenerational nurses and to assess whether significant differences existed according to generation. The study was conducted among 205 nurses in a tertiary government hospital using adopted and validated questionnaires. Descriptive statistics, including frequency, percentage, mean, and standard deviation, were used to describe respondents and communication variables, while Analysis of Variance (ANOVA) was employed to test differences among groups. Findings revealed that nurses demonstrated very high levels of communication patterns and communication skills, with assertive communication identified as the dominant style. Furthermore, no significant differences were found in communication patterns, communication skills, and communication styles across generational groups, indicating that nurses generally followed shared communication practices regardless of age category. The study concluded that communication among intergenerational nurses is shaped more by professional standards and workplace culture than by generational differences. Based on the findings, an Intergenerational Communication Enhancement Plan was proposed to sustain effective communication and strengthen collaboration among nurses.
Dr. Temitope Babatimehin
This study analysed 2016 WAEC and NECO Senior School Certificate Physics Examination Items using Item Response Theory. The study determined the difficulty levels of 2016 WAEC and NECO Physics objective tests. It also investigated the discriminating power of items on WAEC and NECO Physics objective tests and finally ascertained the difference in guessing parameter of WAEC and NECO 2016 physics objective test items. These were done with a view to providing information on the comparability of the psychometrics qualities (discrimination and difficulty) of the examination items. Descriptive survey research design was adopted for the study. The population of the study consisted all public Senior Secondary school Physics student in Osun state. A sample size of 1020, SS3 Physics Students was selected using multi-stage sampling technique. From each of the three Senatorial Districts in Osun State, two Local Government Areas (LGAs) were selected using simple random sampling technique. Three schools were selected from each Local Government Area using simple random sampling technique, making a total of 18 schools. The research instruments for the study were WAEC and NECO Physics objective tests. These instruments were the adopted versions of 2016 WAEC and NECO Physics objective tests. These instruments were administered on the SS3 Physics Students who enrolled for 2019 WAEC. The data were analysed using chi square, mean and standard deviation. The results showed that the average difficulty levels of NECO and WAEC Physics objective items were 2.11 and 1.25 respectively. Also, the results showed that the average discrimination levels of NECO and WAEC Physics tests items were 3.43 and 2.37 respectively. The results equally showed that the average vulnerability to guessing of 2016 NECO and WAEC Physics test items were 0.13 and 0.16 respectively. The study concluded that the item parameters of WAEC and NECO Physics objective tests were statistically comparable.
Chandrakant S. Karigar, Sunil. S. More, Vidya A. S
Cellulases are pivotal enzymes in the bioconversion of lignocellulosic biomass, finding applications across waste management, biofuel production, and industrial processes. Among microbial sources, fungi and bacteria represent two dominant and distinct producers of cellulases, each with unique enzyme systems, biochemical properties, and operational advantages. This review presents a comparative analysis of fungal and bacterial cellulases, focusing on their structural differences, catalytic efficiency, environmental stability, and industrial relevance. The synergistic use of both microbial types is also explored as an emerging strategy to enhance cellulose degradation. This synthesis aims to guide future research and practical applications by evaluating the strengths, limitations, and evolving potential of fungal and bacterial cellulases in sustainable waste valorisation and bioeconomic systems.
Sumaila Mohammed Ibrahim
A triangular socio-economic contributory shackle to Ghana’s fiscal management practices is observed. Notably, a National, Institutional and Community level socio-economic shackles are systemic in the democratic governance structures and found to have very profound negative effect on Annual Tax Revenues and GDP Growth. Total Public Debt was found to have both long-run positive (0.10%) and negative (0.12%) effect on GDP using Variable Selection and Stepwise Least squares (VARSEL) model. Proposed radical solutions to the contributory shackles could free significant fiscal space for phenomenal economic investments that are more likely to make Ghana exit its structural developmental gaps over a decade. The essay concludes by postulating an optimal total debt level of 30% of GDP; a reorganization of the national parliament, employment of technology in revenue collection, critical investments in effective transport network, agriculture, education and reliable national internet connectivity.
Mohamed Omar, Stephen Ngala Muthoka
The study aims to review and expand general understanding on the relationship between corporate governance, external environment and firm performance. The study is motivated by the current debate on strategic role of external environment in corporate governance on organizational performance relationship. Using narrative review as its guiding approach to draw themes and insights, the study examines empirical and theoretical literature that looked at the influence of the external environment on the relationship between corporate governance and organizational performance. The study is anchored on three theories; the agency theory (Jensen and Meckling (1976), resource dependance theory (Pfeffer, & Salancik, 1978) and Resource based view (Birger Wernerfelt, 1984; Barney 1991). The agency theory, explains the relationship between the two key players of an organization, the principal, who is the owner, and the agent, who is the manager. The resource dependency theory suggests that the external environment holds resources which are needed by the organization to survive and that since an organization does not operate in a vacuum but in an environment, for it to succeed it must align its operations with the environment. In this paper focus is placed on external environment as one of the strategic resources which play a key role in the relationship between corporate governance and organizational performance. In conclusion, this paper postulates that external environment influences the relationships between corporate governance and organizational performance
Mohamed Omar, Stephen Ngala Muthoka
The study aims to review and expand general understanding on the relationship between corporate governance, external environment and firm performance. The study is motivated by the current debate on strategic role of external environment in corporate governance on organizational performance relationship. Using narrative review as its guiding approach to draw themes and insights, the study examines empirical and theoretical literature that looked at the influence of the external environment on the relationship between corporate governance and organizational performance. The study is anchored on three theories; the agency theory (Jensen and Meckling (1976), resource dependance theory (Pfeffer, & Salancik, 1978) and Resource based view (Birger Wernerfelt, 1984; Barney 1991). The agency theory, explains the relationship between the two key players of an organization, the principal, who is the owner, and the agent, who is the manager. The resource dependency theory suggests that the external environment holds resources which are needed by the organization to survive and that since an organization does not operate in a vacuum but in an environment, for it to succeed it must align its operations with the environment. In this paper focus is placed on external environment as one of the strategic resources which play a key role in the relationship between corporate governance and organizational performance. In conclusion, this paper postulates that external environment influences the relationships between corporate governance and organizational performance.
Mugarura N. Edward, Nkuutu David Nelson, Nyapidi Brenda Emilly, Prof. Asimmwe Specioza Magunda
This paper examined how cultural creativity among the Basoga and Baganda functions as a communal technology that sustains social cohesion and family unity. The study adopts a synthetic, interdisciplinary approach, drawing on documented heritage, ethnographic descriptions, and policy literature to analyse how ritual performance, oral literature and material craft are institutionalised through clans, royal and elder custodianship, rites of passage and apprenticeship. Using thematic synthesis of heritage files, ethnomusicological accounts and craft studies, the analysis shows that practices such as Bigwala gourd trumpet performance, barkcloth manufacture and court dances operate as collective mechanisms for moral education, conflict mediation and intergenerational transmission. The findings indicate that these creative forms transmit values, form identity, socialise youth, and create occasions for communal participation that bind families and clans into durable networks of mutual obligation. Contemporary pressures urbanisation, migration, commodification and the erosion of apprenticeship pathways threaten continuity, yet adaptive responses including creative industries, factualisation and digital documentation offer pathways for renewal. The paper concludes that safeguarding cultural creativity requires participatory, ethically grounded policies and community led programmes that support apprenticeship, custodianship, family engagement and community controlled digital preservation to protect the mediating processes through which creativity produces cohesion and family unity.
Dr. V. K. Veerakumar, Mr. Elaiyabharathi K
The retail sector's rapid evolution has spurred Quick Commerce (Q-Commerce), which delivers essentials in 10–30 minutes. While thriving in metros, Q-Commerce remains underexplored in semi-urban areas. This study investigates customer perception and satisfaction with Q-Commerce services in Erode District, Tamil Nadu, focusing on Swiggy Instamart and Blinkit. A descriptive research design employed primary data from 150 respondents via a structured questionnaire. Analyses included percentage analysis, mean scores, standard deviation, ANOVA, chi-square tests, correlation, regression, and Henry Garrett ranking. Results reveal that delivery speed, service reliability, app usability, and product freshness strongly shape perception and satisfaction. The regression model shows robust explanatory power (R^2>0.70; details in full paper). These insights offer strategies to enhance service quality and retention in semi-urban markets.
Dr. Suma S., Jovita Philix, Saniyah Mariam, Vainavi Swaminathan
The rapid digital transformation of the aviation industry has significantly improved operational efficiency, communication, navigation, and passenger services. However, this increasing dependence on interconnected digital systems has also expanded the sector's exposure to cybersecurity threats. Modern aviation relies on aircraft avionics, satellite-based navigation, air traffic management systems, airport information infrastructure, and airline databases, all of which may become targets for cyberattacks. This paper presents a narrative review of major cybersecurity challenges affecting contemporary civil aviation systems. The study is based on secondary sources including academic literature, regulatory documents, industry reports, and selected incident cases. The review identifies key threats such as GPS spoofing, ADS-B manipulation, malware, ransomware, data breaches, denial-of-service attacks, and insider threats, and examines critical vulnerabilities linked to legacy systems, weak authentication mechanisms, growing system interconnectivity, and fragmented cyber governance. In addition, the paper examines the main technical and organizational responses discussed in the literature, including intrusion detection systems, continuous monitoring, encryption, zero-trust principles, employee training, and international information-sharing frameworks. The findings suggest that aviation cybersecurity must be approached not only as an information technology issue but also as a broader safety, operational, and regulatory concern requiring coordinated action among airlines, airports, manufacturers, regulators, and cybersecurity experts.
Graciel Monica P. Tormis, Rhey Daffodiel G. Tormis
Working students are plunged to poor conditions. I explored the working conditions of working students as outcomes of their strain. Using descriptive qualitative research design, I interviewed 10 study participants selected through purposive sampling. Through thematic analysis, I ascertained that the most difficult challenge of working students is balancing time between work and school, which leads to chronic time pressure, physical exhaustion, and compromised academic performance. Educational leaders may consider flexible academic arrangements, such as adjusted deadlines, hybrid learning options, and accessible mental health services; while employers may implement student-friendly policies like flexible schedules and reduced workloads during peak academic periods. Future directions may include the use of multiple linear regression to examine time-related factors in balancing school and work predict the level of strain arising from competing work–school demands.
Emily C. Navarro, RN, Joan P. Bacarisas, DM, MAN, RN
Nurse managers influence the nursing work environment through their decision-making approaches and delegation practices, which can affect staff morale and workplace functioning. Limited local evidence exists examining how these leadership behaviors relate to staff morale among nurses in Department of Health (DOH)-retained hospitals. This quantitative study utilized a descriptive–correlational research design to determine nurse managers’ decision-making styles and delegation practices and to examine their relationship with staff morale among nurses in a DOH-retained hospital. Data were collected from 205 staff nurses using standardized questionnaires measuring decision-making styles, delegation practices, and staff morale. Descriptive statistics were used to determine levels of the variables, while inferential statistics, including chi-square and Pearson r, were applied to test the relationships among them. Results indicated that nurse managers were predominantly perceived to demonstrate rational decision-making styles and very high delegation practices across all dimensions. Staff morale among nurses was also found to be very high, particularly in terms of job satisfaction, team climate, and organizational communication. Further analysis showed significant relationships between decision-making styles and staff morale, as well as between delegation practices and staff morale, suggesting that leadership behaviors influence nurses’ workplace experiences and perceptions. The study concludes that effective decision-making and delegation practices contribute to sustaining positive staff morale. Based on these findings, a Leadership-Based Staff Morale Enhancement Plan was proposed to strengthen managerial practices and support a healthy nursing work environment.
Brindha C., Malavika J., Pooja K.M.E., Sowmia Narayani V.
Spices play a vital role in food products by enhancing the flavor, aroma, and nutritional value. The overall quality of the spices relies on a proper roasting and grinding process. By using methods, we can’t achieve the best quality of spice powders because these processes may lead to the damage of volatile compounds, excessive moisture removal, and uneven roasting of spices. To avoid such problems, we have designed a portable spice roaster cum grinder in a compact size for the usage of households and small-scale industries .Our system integrates roasting and grinding using Arduino-based control mechanism to ensure controlled time and temperature during the processing time. Experimental trails were done for the coriander and cumin seeds. For coriander (initial weight: 25 g), the efficiency increased gradually from 1.6% to 6.4% with increasing roasting time. The optimum condition was selected at Trial 7, where the final weight was 23.5 g with an efficiency of 6%. At this stage, uniform light brown color, strong aroma, and absence of burning were observed, indicating effective roasting.For cumin (initial weight: 25 g), the efficiency ranged from 2.0% to 6.8%. The optimum condition was achieved at Trial 6, with a final weight of 23.4 g and an efficiency of 6.4%. Cumin showed slightly higher efficiency due to its smaller size and higher surface area, allowing faster heat transfer and moisture removal.Grinding efficiency reached 100% at 25 seconds for coriander and 20 seconds for cumin, producing fine powder of uniform particle size. The developed system demonstrated improved efficiency, consistency, reduced processing time, and better retention of flavor and aroma.
Adriene A, Dharani D, Karnika M U, Sharmeela R.
One of the essential operations in the poultry supply chain, egg sorting ensures uniform grading and quality before packaging. The limitations of manual sorting, such as slow speed, inconsistent accuracy, and higher breakage rates, remain a major challenge for small and medium-scale farms. Automated systems used in large industries provide high precision but are often expensive, bulky, and inaccessible to smaller producers. Integrating load cell–based weighing, microcontroller processing, and conveyor-driven movement enables accurate, continuous, and non-destructive sorting suitable for low-cost applications. By combining mechanical components, sensor-based detection, and automated diverter mechanisms, the proposed system enhances productivity, reduces labour dependence, and provides a compact, scalable solution for efficient egg grading. This summarises the operating principles, operational benefits, and potential applications of a multiple-egg sorting system, while highlighting opportunities for future improvements and technological integration. With IoT integration, the system can wirelessly transmit sorting data to cloud servers, where it is processed and displayed on mobile devices. This supports real-time monitoring, data logging, analytics, and traceability for smarter poultry farm management.
Bhumika C. Desai, Dipayan Tarafder, Hema V. Badgujar, Richa I. Champaneria, Yahya Moolla
Migraine is a chronic neurological disorder associated with significant disability and reduced quality of life. Limitations and adverse effects of conventional pharmacotherapy have increased interest in complementary and integrative approaches. Herbal medicines, grounded in traditional systems, offer multi-target therapeutic potential with improved tolerability. A randomised controlled clinical study was conducted involving 60 migraine patients without aura. Participants were allocated to a Herbal Medicine group (HM, n=30) receiving Panchakarma (virechana) followed by a standardized polyherbal formulation for 90 days, and a Control group (CT, n=30) receiving standard symptomatic treatment with NSAIDs. Outcomes were assessed using the Cerebral Headache Questionnaire (CHQQ), Visual Analogue Scale (VAS), Migraine Disability Assessment Scale (MIDAS), Perceived Stress Scale (PSS), heart rate variability (HRV), and surface electromyography (sEMG) of the frontalis muscle. Phytochemical standardisation and antioxidant studies were also performed. Statistical analysis was conducted using repeated-measures ANOVA with Bonferroni post-hoc testing.
Joshua Ayobami Adigun, Rofiat Ajoke Ismail
The aim of this study is to examine the relationship between Foreign Direct Investment (FDI) and some macroeconomic indicators such as; Gross Domestic Product (GDP), inflation and exchange rate fluctuations in Nigeria. The data used were extracted from the website of the Central Bank of Nigeria (CBN) and World Bank spanning from 1990 to 2023 to capture long-term economic trends. The study employed a Bayesian regression approach within a hierarchical framework to analyze the impact of these macroeconomic variables on FDI inflows. The results indicate that GDP has a positive and significant effect on FDI, suggesting that economic growth enhances the attractiveness of Nigeria to foreign investors. In contrast, inflation exhibits a negative relationship with FDI, reflecting the adverse effect of macroeconomic instability on investment decisions. Exchange rate fluctuations also show a negative, though relatively weaker, influence on FDI inflows. Model diagnostics confirm that the estimates are stable and reliable, with satisfactory convergence and predictive performance. Overall, the findings highlight the importance of maintaining macroeconomic stability and promoting sustained economic growth to attract foreign investment. The study recommends that policymaker’s priorities growth enhancing policies, inflation control, and exchange rate stability to improve Nigeria’s investment climate. Furthermore, the adoption of Bayesian techniques is encouraged for future econometric analysis due to their ability to incorporate uncertainty and provide robust parameter estimates
Deborah A. Abong'o, Joyce G.N. Kithure, Precious M. Mumo
Maize is a staple food consumed by the Kenyan population; however, heavy metal contamination in maize seeds poses significant health risks. This study determined the levels of lead (Pb2+), cadmium (Cd2+), zinc (Zn2+), copper (Cu2+), and manganese (Mn2+), in three maize seed varieties harvested from Masii Ward, Mwala Sub-County, Machakos County, Kenya. Fresh and dry SC Duma 43 and SC Sungura 301 hybrid with Indigenous Kamba (Kinyaanya) maize seeds, were collected from selected farms in Mbaani, Kathama, and Muthei sub-location in Masii Ward and transported to the Department of Chemistry, University of Nairobi, for analysis. The dried and ground maize seeds were digested using an optimized acid mixture of HNO₃, HClO₄, and H₂O₂ in a ratio of 2.5:0.75:0.5 v/v at 105°C for 2.5 hours. The heavy metals were analysed using Atomic Absorption Spectroscopy (AAS). The results showed that zinc levels ranged from 0.343 ± 0.0505 mg/g to 0.389 ± 0.0007mg/g, cadmium from 0.562 ± 0.217 mg/g to 1.998 ± 0.110 mg/g, copper from 0.700 ± 0.0380 mg/g to 0.756 ± 0.101 mg/g, manganese from 0.270 ± 0.0586 mg/g to 2.745 ± 0.851 mg/g, and lead from 8.247 ± 0.798 mg/g to 10.449 ± 0. 398 mg/g. Despite falling below World Health Organization / Food and Agriculture Organization (WHO/FAO), and Kenya Bureau of Standards (KEBS) limits , the detected levels of zinc, copper, and manganese requires monitoring regarding long-term bioaccumulation. Cadmium and lead levels exceeded permissible limits (0.1 and 0.5 mg/g, respectively), with lead concentration particularly high across all three varieties. The analysis revealed that maize seeds pose severe health risks and are unfit for human consumption. This study highlights the urgent need for regular monitoring of heavy metals contamination in food crops and for the implementation on remediation strategies to safeguard public health in Machakos County and similar agricultural regions in Kenya.
Dr .A. Lovelin Jerald, Shri Nidhi M, Sreelakshmi Anil, Visalini T
Groundnut (Arachis hypogaea L.) is a common oilseed crop. The way it is processed after harvesting greatly affects product quality and economic value. Decortication is the process of separating kernels from shells. Traditionally, this is done using manual or semi-mechanized methods. These methods require a lot of labour, take up considerable time, and often lead to higher losses. This study reviews the existing methods for decorticating groundnuts and points out their shortcomings in efficiency, kernel damage, and scalability. Based on these findings, we suggest a new design for a groundnut decorticator. This design includes a cylindrical shelling mechanism that aims to improve the effectiveness of shelling while keeping the kernels intact. The new design prioritizes simplicity, cost-effectiveness, and is suitable for small- and medium-scale operations. This work lays the groundwork for further development and testing of better decortication systems to improve post-harvest processing.
Chaudhary Raj Ashok, Riya Khare
This paper presents the design and implementation of an IoT-based accident detection and alert system using Raspberry Pi 3B+. The system integrates a vibration sensor, GPS module, and Telegram-based communication to enable real-time accident notification. To address limitations of single-sensor systems, the proposed framework incorporates threshold-based validation and discusses the integration of multi-sensor fusion for improved reliability. Experimental evaluation is conducted to analyze system performance in terms of detection accuracy, response time, and false alarm rate. Results demonstrate that the system can generate alerts within an average latency of 3–5 seconds. The proposed system provides a low-cost and scalable solution for real-time accident monitoring, with future scope for machine learning-based prediction and cloud integration.
Anene Somadina Chijioke, Eyinade Adegoke, Muoemenam Christian Chukwuemeka
A lot of parents and guardians in Nigeria have a hard time paying for their children's college education. This study suggests creating a Children Education Investment Plan (CEIP) as a strategic way to get ready financially for future educational needs. The proposed system allows parents to make regular payments weekly, monthly, or yearly into a university-managed account through the bursary unit. This encourages parents to save money in a structured way for higher education. A review of the existing literature reveals that, although financial institutions provide education-related savings plans, there is currently no evidence of a university-based education investment system of this kind. This gap shows how new and useful the proposed model could be. The system was built as a web-based application using HTML, CSS, PHP, and MySQL database technologies. This made sure that it was easy to use, accessible, and able to handle data well. The study stresses the importance of proactive financial planning for ensuring the educational futures of children and suggests that Nigerian universities should use institution-based education investment plans.
Mrs. K. Pooja, P. L. A. Prasanna Priyah, Sarah Jenesis S., Spandhana
The present study aimed to develop and evaluate a functional nutribar enriched with date seed powder and psyllium husk, focusing on enhancing dietary fiber content and promoting overall health benefits. Functional snack products have gained increasing attention due to their role in preventing lifestyle- related disorders such as obesity, diabetes, and cardiovascular diseases. In this context, the utilization of agro-industrial by-products like date seeds offers a sustainable and nutritionally valuable approach to product development. Date seed powder is recognized as a rich source of insoluble dietary fiber and phenolic compounds, contributing to antioxidant activity and improved gut health. Psyllium husk, derived from Plantago ovata, is a well-established soluble fiber known for its gel-forming ability and its role in regulating blood glucose levels, cholesterol reduction, and digestive health improvement (Sanlier & Ozler, 2026; Halász et al., 2024). The incorporation of psyllium into food systems has also been reported to enhance functional properties and act as a natural binding agent in fiber-enriched food products. The nutribar formulation consisted of foxtail millet, chia seeds, flax seeds, pumpkin seeds, cashews, and almonds, providing a balanced composition of macronutrients, essential fatty acids, and micronutrients. Peanut butter and date syrup were used as natural binders to improve cohesiveness and palatability without the addition of refined sugars. Response Surface Methodology (RSM) was employed to optimize ingredient proportions and to study their effect on physicochemical and sensory characteristics. Texture Profile Analysis (TPA) was conducted to evaluate hardness, cohesiveness, and chewiness of the developed nutribar. Previous studies have indicated that incorporation of high-fiber ingredients significantly influences texture due to the disruption of matrix structure and water-binding properties (Sucharitha et al., 2022). The developed nutribar showed improved nutritional quality, particularly in dietary fiber content, compared to conventional snack bars. The findings suggest that date seed powder and psyllium husk can be effectively utilized in functional food development to produce value-added, health-promoting snack products. Further shelf-life studies are required to evaluate product stability under storage conditions.
Dr. Basake Julius Alochere, Nabimanya Norman, Otieno Kenneth Okelloa
This article examines how digital governance shapes the efficiency of public service delivery in local governments in developing countries, with particular attention to selected local governments in Uganda. The article is anchored in Digital Era Governance, which treats digital reform not simply as the automation of existing procedures but as the reintegration of fragmented processes, the redesign of services around citizens’ needs, and the digitization of administrative routines. A convergent mixed-methods design was used. Quantitative data were generated through structured questionnaires administered to 120 respondents drawn from local government officials, ICT personnel, and service users, while qualitative evidence was obtained through key informant interviews and document review. Quantitative data were analyzed using descriptive statistics, and qualitative data were interpreted through thematic analysis and then integrated with survey findings. The results show that electronic document management systems, online tax payment platforms, digital land records, and online service portals are increasingly used in local governments and are associated with shorter service processing time, greater transparency, and improved citizen satisfaction. However, the findings also reveal that the benefits of digital governance are uneven because financial constraints, weak ICT infrastructure, poor internet connectivity, and limited digital skills continue to restrict implementation. The article argues that digital governance improves service delivery most effectively when technological adoption is supported by organizational capacity, process redesign, and inclusive citizen access. Its main contribution is to move beyond descriptive accounts of e-government by offering a clearer theoretical framing of digital governance, a more critical review of competing perspectives, and a methodologically stronger account of how local government evidence can be generated and interpreted in developing-country settings.
Agnaldo de Assunção Cardoso Fernando, Maria Pedro António Isabel Dias, Monizi Mawunu, Zassala Garcia
This study aimed to document the fruits and leafy vegetables sold in the markets of Soyo City, Angola. The data were collected from May to November 2025. Data collection was carried out through a semi-structured questionnaire, followed by direct field observations. In total, 81 fruit and leafy vegetable vendors were surveyed, of which 62.96% were men and only 37.04% were women. The main occupation of the respondents is trade (66.67%). The ethnobotanical inventory identified a total of 36 species of fruits and leafy vegetables, distributed across 33 genera and 18 botanical families. The most represented families are Malvaceae, Cucurbitaceae, and Solanaceae (4 species), and Arecaceae, Brassicaceae (3 species). Fruits are more abundant (62.96%) than leaves (37.04%). Most of the leafy fruits and vegetables (93.83%) documented in this study are cultivated, with only 6.17% being native. It is recommended that scientific research on this topic be conducted throughout the entire Angolan territory in order to better document all the different leafy fruits and vegetables produced nationally and to establish economic policies that allow their export, thus contributing to the country's economic diversification. Finally, it is also recommended to carry out economic studies to assess the quantities produced and harvested annually.
Al-Harath Ateik, Ramah Safwan Daoudi
The digital transformation of consumer markets has made e-marketing a pivotal driver of customer satisfaction in the competitive food and beverage sector. This study investigates the impact of e-marketing strategies on customer satisfaction at Al-Baik Restaurant, one of Saudi Arabia's most iconic fast-food chains. Employing a descriptive-analytical design, data were collected from 154 Al-Baik customers via a structured questionnaire covering key e-marketing dimensions: social media marketing, website usability, online ordering, digital advertising, online reviews, loyalty programs, and campaign effectiveness. The instrument demonstrated acceptable internal reliability (Cronbach's α = .757). Statistical analyses — including ANOVA, Pearson correlation, multiple regression, and one-sample t-tests — were conducted using SPSS. Results confirm significant positive relationships between all three core e-marketing dimensions and overall marketing strategy performance: online loyalty programs (r = .291), online reviews (r = .241), and campaign effectiveness all emerged as significant predictors. Regression analysis reveals that campaign effectiveness (β = .171, p = .035) is the strongest statistically significant predictor of customer satisfaction. The model explains approximately 11.5% of variance in satisfaction (R² = .115, Adjusted R² = .097), with a strong overall correlation (R = .839). Findings support the strategic importance of integrated digital marketing for restaurants operating in digitally mature Gulf markets.
Agom Emmanuel Agom, Felix Edoiseh Ehidiamhen, Grace Chukwu Chinyere, Iteshi Onyekachi
The increasing cost of healthcare services globally has placed a significant financial burden on households, particularly in low- and middle-income countries where health insurance coverage remains inadequate. Out-of-pocket expenditure (OOPE) has emerged as a critical issue, as patients and their families often bear the direct costs of medical treatments, medications, and associated non-medical expenses. Unlike systems where healthcare is funded through taxation or insurance, OOPE exposes individuals to financial distress, with many facing catastrophic health expenditures that push them into poverty. In Nigeria, healthcare financing is predominantly structured on a "cash-and-carry" basis, where patients must pay directly for services at the point of care. This system disproportionately affects low-income populations, who may forgo necessary treatments due to financial constraints. Despite government efforts to introduce health insurance schemes, such as the National Health Insurance Scheme (NHIS), coverage remains limited, leaving a substantial portion of the population reliant on OOPE. In an effort to address the lack of financial risk protection, the Federal Government of Nigeria launched the National Health Insurance Scheme (NHIS) in 2005 with the goals of ensuring that households are protected from the financial burden of out-of-pocket health payments and that access to quality healthcare services is made possible. The majority of low- and middle-income countries (LMICs), including Nigeria, are grappling with the issue of poverty. Financial protection ensures that households do not face financial hardship and become impoverished as a result of seeking healthcare. The National Health Insurance Scheme (NHIS) was introduced to provide social health insurance (SHI) to Nigerians and ensure Universal Health Coverage (UHC). (WHO; 2010). However, according to the National Insurance Scheme (2019), federal government employees are the only ones required to participate in the NHIS programs, which fall under the categories of Formal Sector, Informal Sector, and Vulnerable Sector. In contrast, state government employees are not legally aentitled to be beneficiaries
Abd Rashid Li, Azman Mohamed, Mohd Kamal Nik Hasan, Zaridah Mohd Zaki
Thermal processing plays a critical role in modulating the phytochemical composition and biological activity of plant extracts. This study investigated the effects of extraction temperature (40–100 °C) and duration (15–180 min) on total phenolic content (TPC), total flavonoid content (TFC), antioxidant capacity, and pancreatic lipase inhibitory activity of Hibiscus sabdariffa water extract. TPC was maximized at 40 °C for 30 min (48 mg GAE/g), whereas TFC peaked at 60 °C for 30 min (650 mg CE/g). DPPH radical scavenging activity remained relatively stable across extraction conditions (75–90%), with optimal activity observed at 80 °C for 120 min. In contrast, ferric reducing antioxidant power (FRAP) increased with temperature, reaching a maximum at 100 °C for 120 min (2100 µM Fe²⁺/g). Notably, pancreatic lipase inhibition was highest at 100 °C for 30 min (92%), approaching the activity of the reference inhibitor orlistat. Antioxidant activity did not directly correlate with total phenolic or flavonoid content, indicating that qualitative changes in phytochemical composition contribute significantly to bioactivity. These findings demonstrate that extraction parameters should be optimized based on the targeted functional endpoint, with high-temperature short-time conditions favoring enzyme inhibition, while moderate conditions preserve antioxidant-associated phytochemicals. This study provides a bioactivity-driven framework for optimizing aqueous extraction of H. sabdariffa for functional food and nutraceutical applications.
Aubrey Jane Dagdag, Cindy Nicole Obar, Janessa Joy Arnado, Jocel Amper, Justine Lozano, Renalyn Coralde
This study examined the effectiveness of cursive writing instruction in enhancing the fine motor skills of Grade 3 pupils in face-to-face classes at Doña Rosario Elementary School. Using a mixed-method experimental design, two groups were compared: a control group that continued with regular handwriting practice and an experimental group that received structured cursive writing instruction. Pre-test and post-test tasks assessed sentence writing, paragraph writing, and narrative writing. Results revealed that the experimental group achieved significantly greater improvements (gains of +5.80 to +6.25) compared to the control group (+1.55 to +1.90). A t-test indicated a statistically significant difference between groups (p < 0.001), confirming that cursive writing positively enhances writing fluency, hand coordination, and stroke control. Qualitative feedback from teachers supported these findings, highlighting increased confidence and smoother writing performance among pupils exposed to cursive instruction. The study concludes that cursive writing is an effective tool for improving fine motor development and writing proficiency in Grade 3 learners.
Adam A. Wali, Adamu A., Machina M. A., Machina M.M., Muhd Talba
Enacted in 2007 upon World Bank recommendation, Nigeria’s Federal Public Procurement Act established a mandatory framework to ensure transparency, competition, and value for money in public procurement. Adhering to this mandate, Yobe State enacted its Public Procurement Law in 2016, covering the state government and its 17 local government areas. This study examines the effectiveness of the law on state and local government construction projects, utilizing questionnaires from 320 participants selected through a purposive, maximum variation sampling technique. Seven construction success factors identified in the law were analyzed based on field data, which showed high internal consistency (Cronbach’s α = 0.865). The analysis yielded an overall weighted mean score of 2.25 on a 4-point Likert scale, indicating overwhelming dissatisfaction with the law’s effectiveness on state and local government construction projects in Yobe state. Regarding the seven factors, the study revealed that construction delivery suffers from high bureaucratic inefficiency and lack of transparency (71.43% dissatisfaction), irregular issuance of certificate of no objection (79.07% dissatisfaction), and poor regulatory compliance (73.95% dissatisfaction). This exists despite moderate satisfaction (66.28%) in the payment of mobilization fees and some level of satisfaction (57.98%) in final project delivery. Conversely, contractors were found wanting in the presentation of bid security (83.72% dissatisfaction) and performance guarantee (79.07% dissatisfaction). The study concludes that the law is largely ineffective on state and local government construction projects in Yobe State. Consequently, it recommends strengthening regulatory oversight, digitizing procurement processes for enhanced transparency, and training procurement officers on mandatory legal compliance.
Derick Oduro, Ebenezer Jeremiah Durosimi Belford, Nana Opoku Agyeman
Soil moisture stress is a major constraint to cocoa production in West Africa, particularly under changing climatic conditions. This study evaluated the response of the seedlings of three cocoa varieties and selected genotypes to soil moisture stress under greenhouse conditions. The experiment was arranged in a Completely Randomized Design (CRD) involving seven cocoa genetic materials (three varieties and four selected genotypes) subjected to four soil moisture stress treatments, each replicated four times. Pots were randomly arranged on greenhouse benches to minimize environmental variation. Cocoa seedlings were exposed to controlled soil moisture levels representing drought stress conditions. Morphological and physiological parameters, including plant height, leaf area, stem thickness, leaf and soil relative water content, chlorophyll content (NDVI), and root anatomical characteristics, were assessed. Soil moisture stress significantly affected seedling growth and physiological performance (p < 0.05). Seedlings exposed to reduced moisture levels exhibited decreases in plant height, leaf area, and chlorophyll content compared to well-watered plants. However, certain genotypes maintained relatively higher NDVI values and improved root development under moisture stress, suggesting enhanced drought tolerance. Genotypes PA150 and Forastero showed superior drought tolerance, while PA7 and C42 were highly susceptible. Based on percent reduction from control, Forastero (23% reduction from 20.5 to 15.8 leaves) was more tolerant than Criollo (28% reduction from 21.8 to 15.8 leaves), despite similar absolute leaf counts under severe stress. These findings highlight the importance of identifying drought-tolerant cocoa varieties or genotypes for breeding programs to improve climate resilience in cocoa production systems in Ghana and across West Africa.
Adolphe Andriamanga Ratiarison, Andriamasinoro Rahajaniaina
Early detection of breast cancer significantly reduces the number of deaths caused by this disease. In Africa where the number of new cases and deaths is constantly increasing. For Madagascar, very little information is available regarding the number of people affected by this disease. Advances in the application of artificial intelligence in medicine are improving the techniques for detecting this disease. Unfortunately, most of these techniques are cumbersome, complex, and very expensive. In this work, we propose a lightweight, hybrid approach to clustering breast cancer images. Our approach combines deep learning, ArcFace and unsupervised clustering. The architecture relies on the MobileNetV3Small convolutional network as a feature extractor. At the output of the backbone, a projection head is added to transform the feature maps into a compact embedding vector. The goal is to project the data into a low-dimensional (64-dimensional) latent space, where the discriminating properties between classes are strengthened. The use of ArcFace ameliorate intra-class compactness and inter-class separability, enhancing the quality of the learned representations. Two phases of training were adopted: firstly, only the projection layers and the ArcFace layer are trained, with the backbone remaining frozen to stabilize the learning process. Then, partial fine-tuning is performed by unfreezing the final layers of the convolutional neural network. Principal Component Analysis algorithm is used to facilitate the structuring of the embedding in a lower-dimensional space while preserving most of the discriminating information. A comparative study was conducted to evaluate the clustering capabilities of K-Means and HDBSCAN. The overall metrics results show that K-Means provides the best results for all metrics used. Despite the lightweight of our model (3,6 GFLOPs), it achieved a performance comparable to other state-of-the-art approach.
Anegbe S. Abel, Folasire M. Ayorinde, Oladeji A. Adebayo, Sarimiye O. Foluke
Background Oncology residency training is associated with high emotional and professional demands, predisposing trainees to burnout. In low- and middle-income countries such as Nigeria, systemic challenges may further increase this risk. This study assessed emotional burnout and job satisfaction among oncology residents in Nigeria and identified associated factors. Methods A multicentre cross-sectional study was conducted among oncology residents across seven accredited tertiary institutions in Nigeria. Data were collected using a structured self-administered questionnaire incorporating the Maslach Burnout Inventory and the Job Satisfaction Survey. Descriptive statistics, correlation analysis, and regression models were used to evaluate associations between burnout, job satisfaction, and sociodemographic variables. Results A total of 57 residents participated (mean age 33.7 ± 4.9 years; male: female = 2.2:1). Emotional exhaustion was high (3.50 ± 0.82), while depersonalization and personal accomplishment were moderate. Overall job satisfaction was moderate (3.12 ± 0.84), with high satisfaction in supervisor support and co-worker relationships but lower satisfaction with work environment. Emotional exhaustion showed a strong negative correlation with job satisfaction (r = –0.61, p < 0.001). Early-year residents had significantly higher burnout (p = 0.022). Female gender predicted lower job satisfaction (p = 0.046). Low job satisfaction, poor work environment, and long working hours were significant predictors of burnout. Conclusion Oncology residents in Nigeria experience substantial emotional burnout, particularly in early training years. While interpersonal support is strong, systemic factors such as workload and work environment drive burnout. Targeted institutional interventions are needed to improve resident well-being and sustain the oncology workforce.
Edelbert G. Israel
Security professionals serve as the first line of defense against evolving threats, yet little is known about how current training programs shape their professional experiences and aspirations. This study explored the lived experiences of ten private security professionals in the Philippines through a descriptive-phenomenological approach. Semi-structured interviews were analyzed using Colaizzi’s method, revealing that training is perceived as practical, relevant, and empowering. Participants reported enhanced confidence, professional competence, and interpersonal skills, and expressed aspirations for continuous learning, technological competency, and leadership development. Findings highlight the importance of aligning training programs with real-world demands and supporting professional growth.
Collins Antwi, Eric Tieku Agyemang, Happy Boamah Gyasi, Roselyn Agyemang
The energy and financial sectors have been incorporated into the quest to solve climate change, with increasing recognition of the direct impacts that financial institutions' lending and investment practices have on environmental sustainability. This study applies Quantile Autoregressive Distribution Lags (QARDL) Model to examine the dynamic impact of energy efficiency budgeting on carbon dioxide emissions, controlling carbon footprint of banks’ portfolios in United Kingdom. First, an in-depth descriptive statistics analysis of data for various variables are conducted. The study then uses Quantile Augmented Dickey-Fuller to test for stationarity, then proceeds to perform Quantile Cointegration test and closely followed by Quantile Autoregressive Distributed Lags (QARDL) estimation to examine the impact of energy efficiency budgeting and carbon footprint of banks’ portfolios on carbon dioxide emissions. The empirical results validate the findings of stationarity for each variable. There is evidence of first-order differential integration I (1) among variables. There is a cointegration link between the three variables and that they have a more prolonged and stabled relationship. The results showed that energy efficiency budgeting has a reducing effect on carbon dioxide emissions. Its effectiveness varies across different emission quantiles, there is the need for a flexible budgeting approach. Policymakers should develop mechanisms to adjust budget allocations based on current emission levels, potentially increasing budget during periods when the impact is likely to be strongest. However, carbon footprint of banks portfolios promote rise in carbon dioxide reduction. The central bank of UK should implement mandatory carbon screening tools for bank portfolios. These mechanisms would help banks understand and manage their immediate carbon impact. Banks should be required to develop comprehensive carbon accounting systems that track both direct and indirect emissions from their investments
Hamisu Mukhtar, Jabir Isah Karofi, Muhammad Nuraddeen Ado
Machine learning (ML) has become a cornerstone of modern anomaly detection, yet existing reviews predominantly emphasize pre-2021 studies and focus narrowly on network intrusion detection. Building upon these limitations, this paper presents an integrative review of machine learning models for anomaly detection published between 2020 and 2025, emphasizing hybridization, explainability, and cross-domain applicability. Using Bou Nassif et al. (2021) and Yang et al. (2022) as baseline systematic reviews, we extend their scope through the inclusion of recent developments such as adaptive density-based clustering (K-DBSCAN, GWOKM), optimized support-vector models (EMSVM), explainable Isolation Forest derivatives (DIFFI, RIFIFI), and active-learning frameworks (ALIF). The study systematically maps algorithms, performance metrics, and application domains ranging from cybersecurity and industrial systems to geochemical and renewable-energy contexts. Results reveal an emerging shift toward interpretable, data-centric, and federated approaches capable of handling concept drift and limited labeling. We identify persistent challenges in cross-domain generalization, dataset imbalance, and evaluation standardization. A conceptual taxonomy linking model family, evaluation criteria, and domain context is proposed to guide future research. This review thus bridges earlier surveys with the current generation of intelligent, interpretable, and adaptive ML systems, providing a comprehensive foundation for advancing anomaly detection research beyond traditional network-centric paradigms.
Akampurira Paul, Atuhe Aarone Mike, Dr, Wilison Tumuhimbise, Dr. Richard Ntwari
The rapid shift to WFH practices in higher education has increased cyber security risks influenced by user behavior, usability challenges, and contextual constraints. Although several cyber security frameworks have been proposed to address these risks, many lack empirical validation in real academic environments. This study evaluated a behavior-centered cyber security framework designed for university WFH contexts using expert review to assess its feasibility, relevance, and contextual suitability. A mixed-methods expert-based evaluation was conducted, combining structured quantitative ratings with qualitative feedback from cyber security and higher education ICT professionals. Quantitative data were analysed using descriptive statistics and non-parametric tests, while qualitative responses were examined using thematic analysis. The results showed that experts rated the framework as highly relevant and deployable for academic WFH environments, particularly in terms of risky behavior identification and contextual adaptability. Lower ratings were associated with implementation effort, reflecting practical organisational considerations rather than conceptual weaknesses. The study provides empirical evidence supporting the feasibility and applicability of behavior-centered cyber security frameworks in remote academic work environments and demonstrates the value of expert-based mixed-methods evaluation for validating socio-technical security frameworks prior to deployment.
Elizabeth Sandu George, Faraja Idd Athuman, Herieth Benedict Manyikila, Protaz Nyambuye Ladisalus, Richard J Mbaula, Stanslaus Peter Kashinje
This study investigates the efficacy of remedial physics classes in enhancing academic performance among secondary school students in Luguruni area, Ubungo District, Tanzania by using the mixed method. Against a backdrop of systemic educational challenges including overcrowded classrooms, resource limitations, and persistent underperformance in national science examinations, remedial interventions emerge as critical supports for struggling learners. Remedial physics classes are crucial for supporting students struggling with foundational concepts, yet student perspectives on these interventions are often overlooked. This study explored the lived experiences and the impact of remedial physics classes on students attending remedial physics programs for secondary schools in Luguruni area. Guided by Constructivist Learning Theory of Piaget, Cognitive Load Theory by Sweller, and Zone of Proximal Development by Vygotsky, the research employed an embedded pragmatic design. Data were collected through questionnaires from 177 students across five secondary schools and semi-structured interviews with physics teachers. Key findings reveal that over 94% of remedial participants (143/152 students) demonstrated measurable improvement in physics comprehension and problem-solving abilities, attributed to targeted instructional strategies such as small-group collaboration, individualized feedback, and hands-on experimentation or activities. Crucially, a 44% performance gap was identified between students of comparable baseline ability who attended remedial classes and non-participants, underscoring the intervention’s significant impact. Thematic analysis highlighted student motivation, teacher student ratio, session frequency, and peer-supported learning as primary mediators of success. The study concludes that remedial program practices have a strong positive impact on the academic performance of learners in Physics in Luguruni area, Ubungo District and shows big performance gap between students who attended remedial classes and students who did not. The study recommends that Schools should implement structured remedial programs tailored to the specific needs of students and increase the frequency of remedial sessions. In addition there should be smaller teacher-student ratios in remedial classes.
Dr. P. Sekar, Reshma Venugopalan
This research paper will deal with examining the problems and threats faced by fish market vendors in Ernakulam district, Kerala. The main aim of the study is to find out the key financial, operational, and environmental challenges of fish vendors, discuss the main problems of operations like price fluctuation and seasonal changes, and measure the degree of satisfaction with the income, working conditions, and market facilities. The primary data on which the study will be based is the survey of 75 respondents who will be given a structured questionnaire. The data were analysed using different statistical methods which included percentage analysis, weighted average ranking, correlation analysis as well as factor analysis. The findings of factor analysis indicated that three key dimensions of the challenges, i.e. financial risks, operational problems, and environmental factors, can be responsible of the substantial portion of the total variance. Diverging all these, financial risks became the most decisive aspect upon the vendors. It was found that the most important issues that affect the operation of the vendors are price variations, seasonal factors, and buying pressure in bulk. It is also found that income levels, working conditions and market facility availability have a significant effect on vendor satisfaction. Depending on the results, the research recommends that the livelihood and general satisfaction of fish market vendors should be improved through financial assistance, better infrastructure, and proper policy interventions. All in all, the research is an important contribution to understanding the challenges of fish vendors and can be a viable solution to their better economic conditions and terms of work.
Alfred A. Abiodun, Awopeju K. Abidemi, Bright F. Ajibade
Using the Exponentiated approach and three-parameter Weibull distribution as baseline function, a newly generalized distribution was formed called the Exponentiated Generalized Modified Weibull distribution. One of the properties of a proper probability density function was used to ascertain that the resulting function is a proper probability density function. Statistical properties of the newly generated distribution were studied and graphs of probability density and cumulative density functions of the distribution were plotted using varying parameter values. Monte Carlo simulation approach was used for the test of homogeneity of the distribution and it was observed that the parameters in the distribution approach the true value as sample size increases. The distribution was compared with some of the existing distributions in its category and it was observed that the distribution outperformed the existing distributions using secondary data. Therefore, it was concluded that Exponentiated Generalized Modified Weibull distribution can be adopted in modeling events involving distributions of its category
Feyisetan Leo-Olagbaye, Gbenga Agunbiade, Henry Odeyinka
As demand for sustainable development grows globally, role of Quantity Surveyors in integrating sustainability into construction processes has become vital. This study therefore investigates the Factors Influencing Quantity Surveyors' Involvement in the Delivery of Sustainable Housing Projects in Nigeria. The study comprises a sample of 48 Quantity Surveyors who had participated in sustainable housing projects. They were selected using the Respondent Driven Sampling technique. Data gotten from the questionnaires were analyzed using amongst others, mean score test, analysis of variance and factor analysis. The study reveals that Quantity Surveyors' involvement in sustainable housing projects in Lagos is driven by a complex interplay of factors. Continuous professional development, technological advancements, and market demands emerge here as key drivers. Quantity surveyors are willing participants in this new era of technological advancement, this finding cements the importance of ongoing learning and skill enhancement in adapting to the evolving demands of sustainable construction. The originality lies in its exploration of the factors influencing the involvement of Quantity Surveyors in the delivery of sustainable housing projects, offering novel perspectives on how these factors can pave the way for transformative improvements in construction sector. The study provides empirical insights into factors that can aid Quantity Surveyors involvement in the delivery of sustainable housing projects in the construction industry and beyond.
Annie R. Capin
This study investigated the factors associated with the choice of Bachelor of Industrial Technology (BIT) major in Food Technology among students enrolled in BIT-FT. Utilizing a descriptive-correlational research design, data were collected from 86 respondents across three-year levels through a validated Likert-scale survey. The research examined three primary dimensions: Personal/Interpersonal, Institutional, and Socio-Economic factors. Statistical analysis using One-Way ANOVA revealed that there are no significant differences in the factors affecting career choice when respondents are categorized by age (p=0.165), sex (p=0.682), or Senior High School track (p=0.314). This indicates a unified motivational profile within the BIT Food Technology cohort, suggesting that the program attracts a specific demographic driven by consistent industrial interests regardless of their diverse academic or demographic backgrounds. Furthermore, Pearson Product-Moment Correlation analysis demonstrated a very strong positive relationship between Personal Factors and the final choice of major (r=0.91), followed closely by Institutional Factors (r=0.88). These results highlight that while students are primarily driven by internal passion and self-efficacy, the quality of university laboratories and the perceived industrial relevance of the curriculum serve as critical validation points for their commitment. Socio-Economic Factors also showed a strong correlation (r=0.82), reflecting the students' rational alignment with the "recession-proof" demand of the ASEAN food manufacturing sector. The study concludes that internal interest, supported by high-quality institutional facilities and clear marketability, remains the cornerstone of student recruitment and retention in industrial technology programs. It is recommended that the institution continues to prioritize laboratory upgrades to sustain this high level of student validation.
Dr. Dimple Patel, Dr. Harshal Patel, Dr. Kruti Desai, Dr. Shamji Kalsariya
Prolonged standing is a routine occupational demand for traffic police, placing them at high risk for foot and ankle musculoskeletal disorders due to cumulative mechanical stress and altered plantar pressure distribution. Despite the resulting pain and functional decline, this issue remains underexplored in the Indian healthcare context. Early identification of these impairments is critical to preserving occupational capacity and preventing chronic long-term disability.
Rodolfo Scottie A. Cordero
Forecasting stock market indices like the Philippine Stock Exchange Index (PSEi) is crucial for investors, economists, and policymakers in understanding market behavior and making strategic decisions. This study aimed to examine the historical trend of the PSEi from 2004 to 2023 and determine which among various time series models best predicts its value in 2025. Specifically, the study evaluated polynomial regressions, logarithmic, power series, moving averages, exponential smoothing, and autoregressive models to identify the most suitable forecasting approach. A quantitative research design was employed using secondary data collected from Yahoo Finance and Investing.com. Monthly PSEi closing prices were compiled, averaged annually, and analyzed using Microsoft Excel and the Data Analysis Toolpak, which enabled trendline generation, smoothing applications, and lag-based regression modeling. The results showed that the PSEi experienced an overall upward but volatile movement over two decades, with notable dips during global crises. Among the models tested, the quintic polynomial regression achieved the highest explanatory power, but its predicted value of 15,872.78 suggests potential overfitting. Moving average models effectively smoothed short-term fluctuations but tended to underpredict future growth, while autoregressive models captured significant temporal dependencies, with higher-order lags revealing delayed market responses. The study concludes that while polynomial and curve-fitting models can capture nonlinear behavior, they should be used cautiously due to overfitting risks. It is recommended that future forecasting efforts explore hybrid models that combine polynomial trends, autoregressive structures, and smoothing techniques for improved accuracy.
Venson B. Sarita
Coconut agriculture is a key economic driver in Davao Oriental, contributing significantly to livelihoods and local industries. The province is among the top coconut-producing areas in the Philippines, yet farmers struggle with low yields, aging trees, and limited access to modern processing facilities. To enhance productivity and market competitiveness, investments in processing infrastructure, sustainable farming techniques, and value-adding innovations are crucial. Agrotourism, precision agriculture, and indigenous knowledge integration can boost profitability and resilience. Government policies play a vital role in sustaining the sector through financial aid, training, and technology adoption. Programs such as the Philippine Coconut Authority’s (PCA) replanting initiatives, mechanization support, and market linkages help modernize operations. Strengthening farmer cooperatives improves supply chains and international trade compliance. However, challenges persist due to bureaucratic delays and inadequate farmer awareness. Strengthened policy implementation, public-private collaboration, and transparent governance are essential to ensure a sustainable and competitive coconut industry.
Dr. James L. Paglinawan, Lorie mae G. Realda
This descriptive qualitative study explores the lived experiences of learning loss in reading and literacy among fifteen Grade 10 Alternative and Relevant Learning or ARAL students at Bukidnon National School of Home Industries, a public secondary school in Bukidnon, Philippines. The study was conducted during the transition from pandemic-era modular and online learning to face-to-face instruction in the new normal. Using purposive sampling, data were collected through a semi-structured Google Forms questionnaire and analyzed using the six-phase thematic analysis developed by Braun and Clarke (2006). Four salient themes emerged. Instructional isolation and technical skill decline were the most prominent, affecting vocabulary, fluency, and pronunciation due to the lack of real-time teacher feedback. Cognitive erosion and reduced reading stamina were also observed, as modular learning encouraged surface-level processing and weakened higher-order reading skills. Technology functioned as both a distraction and a support, diverting attention while also providing tools that aided literacy development. Finally, learners demonstrated resilience through multimodal and collaborative recovery strategies such as peer reading, viewing subtitled media, and parental support. The findings highlight that literacy is a social and cognitive process vulnerable to isolation. Recovery efforts should prioritize face-to-face instructional support, sustained engagement in extended reading, balanced use of digital tools, and peer-assisted learning programs aligned with the Department of Education ARAL framework.
Bahar Sidick Youssouf, Boné Jean Djamou, Djumyom Wafo Guy Valerie, Julius Kajoh Boyah, Valerie Njitat Tsama, Zachée Ambang
This article presents the results of a survey conducted at the University Hospital Center (CHU) of the Renaissance in N’Djamena on the health perception and environmental risks related to biomedical waste management. A total of 100 respondents were interviewed, including healthcare personnel and the general public. The randomly selected sample is predominantly young, with 74% men and 26% women, with 47% age groups ranging from 18–30 years and 53% over 31 years. The distribution shows an over-representation of healthcare workers (38%) and a critical under-representation of cleaning staff (7%), who are nevertheless the most exposed. Most respondents are newly integrated, with a length of service less than one year (38%) to between one and five years (29%). The results reveal that most personnel are aware of the risks associated with poor waste management: 22% reported being exposed to accidents (needle sticks, splashes), and 46% believe that the waste has a significant environmental impact. The study also highlights a lack of information, the absence of visible procedures, and insufficient protective equipment. However, this study recommends strengthening training, establishing an effective waste management system, and promoting a health and environmental safety culture adapted to the realities of this university hospital Center.
Ezeamaechi, Ejiofor Chibuzor, Kalu, O. Obasi, Ubuoh Emmanuel Attah
Heavy metal contamination of fish is a serious public health concern worldwide and Nigeria is not an exception to this. In this study, eight commonly consumed fish species namely; African Cat Fish (Clarias gariepinus), Croacker Fish (Micropogonias undulatus), Sardine Fish (Sardinella maderensis), NileTilapia (Oreochromis niloticus), Tilapia (Tilapia zillii), Bony Tongue Fish (Heterotis niloticus), Cat Fish (Chrysichthys nigrodigitatus) and Elephant Fish (Campylomomyrus rhychophorus) were analyzed for Arsenic (As), Cadmium (Cd), Lead (Pb), Copper (Cu), Chromium (Cr), Zinc (Zn) and Mercury (Hg) using Atomic Absorption Spectrophotometer. The fish samples were collected from fisher men at the beaches. The Estimated Daily Intake, Target Hazard Quotient, Health risk index, Hazard Index, and Carcinogenic/Cancer Risk (CR) were assessed for adults and children. Heavy metal analysis showed that Pb, Cr, Zn and Cd were observed in all the fish species, Cu in some of the fish species while Hg and As were not observed in any of the fish species. Cd and Pb exceeded the maximum permissible limit. The estimated daily intake (EDI) values for the metals were lower than the recommended dietary allowance for adults for both seasons while Pb exceeded the recommended dietary allowance for children at Tourist beach and Ibeno beach during the wet season, Tourist, Ibeno, Okpoama and Asaba beaches during the dry season. The Target Hazard Quotient (THQ) were <1 for all the fish species in adults and children for both season indicating no apparent health risk from these heavy metals over a life time of exposure. Health Risk Index (HRI) was <1 in all the fish species in all the adults indicating no apparent health risk from these heavy metals over a life time of exposure while HRI was <1 in children from all the beach waters except Cr in Tourist and Agenobode beaches during the wet and dry season respectively. Hazard Index for all the fish species from beach waters were <1 for both adults and children for both season showing that the non-carcinogenic adverse effect is negligible. The carcinogenic risk for both adults and children, showed all estimated values for Cr, Cd, As and Pb for some of the fish species to be above the tolerable limit. This indicates that excessive consumption over a long time period might cause carcinogenic effect as the Cancer Risk (CR) values were higher than the acceptable guideline value (10−4–10−6) (E−6 and E−4). This indicates that consumption of fish from these beach waters should be of concern to the public that patronize barbecue sellers at the beaches. This calls for periodic monitoring of heavy metals in fish species sold at the beaches as well as sensitization of the beach tourists on the need to check what they consume.
Dr. Ashish Jawarkar, Dr. Avani Dangar Pathology, Dr. Jaini Pinkeshkumar Doshi, Dr. Kumarsinh J Solanki, Dr. Mirat Donga, Dr. Nidhi Ajay Choudhary
● Bone consists of cartilage, osteoid, fibrous tissue and bone marrow elements. (1) ● Each tissue can give rise to benign or malignant tumours. (1) ● A spectrum of pathological bone lesions can present in any form from inflammatory to neoplastic conditions. (2) ● Bone tumours are classified on the basis of cell type and recognized products of proliferating cells. (1) ● Bone tumours may be primary which originate in the bone or secondary. (1)
Dr. Chibesa Felix
This study critically examines human rights gaps within Zambia’s correctional legal and policy framework, with particular focus on the Zambia Correctional Service Act No. 37 of 2021. The study is grounded in a qualitative doctrinal research approach, relying on systematic document analysis of national legislation and international human rights instruments, including the International Covenant on Civil and Political Rights (ICCPR) and the United Nations Standard Minimum Rules for the Treatment of Prisoners (the Nelson Mandela Rules). The general objective was to assess the extent to which Zambia’s correctional legal framework aligns with international human rights standards and effectively protects the rights of persons deprived of liberty. Specifically, the study examined alignment with international standards, analysed key human rights provisions, identified legal and policy gaps, assessed governance and accountability mechanisms, and evaluated the protection of specific human rights within correctional settings. The findings reveal that the Act reflects a progressive shift toward a rights-based and rehabilitative correctional system, incorporating principles such as dignity, humane treatment, and reintegration. However, the alignment with international standards remains partial. The study identifies significant gaps, including lack of explicit human rights guarantees, absence of detailed and enforceable standards for detention conditions, weak accountability and oversight mechanisms, and limited protection for vulnerable groups. The study concludes that while the Act establishes a strong normative framework, it lacks the legal specificity and institutional mechanisms necessary for effective human rights protection. It recommends the introduction of explicit rights-based provisions, strengthening of oversight systems, and development of enforceable standards to enhance compliance with international human rights obligations.
prof Nilesh Modi, Ritaben Meghajibhai Marawada
As cybercriminals adopt advanced AI to launch "PhishBots"—automated tools that create highly realistic and personalized scam emails—traditional "black-box" security measures are failing to maintain user trust (Kumarage et al., 2025; Roy et al., 2023; Uddin & Sarker, 2024). This paper introduces a transparent, hybrid framework that combines the deep-learning power of RoBERTa-base with the SHAP interpretability engine. Our model achieves a peak accuracy of 99.43% on the PhreshPhish benchmark (Dalton et al., 2025; Meléndez et al., 2024). By optimizing input sequences to 128 tokens, we achieve sub-100ms inference times, making it suitable for real-time enterprise deployment (Ferrag et al., 2023; Shirazi et al., 2022). This approach provides a "Digital Highlighter" for security analysts, transforming automated alerts into verifiable forensic evidence (Al‐Fayoumi et al., 2024; Lim et al., 2025).
Kanika Prajapati, Krishna Anand, Raj Kumar
Hydrogen is emerging as a promising clean energy carrier due to its high energy content and zero carbon emissions during utilization. This paper presents a comprehensive review of hydrogen production technologies, storage systems, and handling challenges. Various hydrogen production methods, including thermochemical, electrochemical, and biological processes, are critically analyzed in terms of efficiency, cost, and environmental impact. The study also examines storage techniques such as compressed gas, liquid hydrogen, and solid-state storage, along with associated safety and material challenges. Furthermore, key issues related to hydrogen handling, including high flammability, leakage risks, and infrastructure limitations, are discussed. The paper highlights recent technological advancements and explores future prospects for improving hydrogen utilization. The findings suggest that although hydrogen has significant potential for supporting a low-carbon energy transition, challenges related to cost, storage efficiency, and large-scale infrastructure development must be addressed for its widespread adoption.
Dr. Rinkal N. Nakawala MD
The stool exam is a crucial diagnostic tool for identifying intestinal parasites. It is a non-invasive procedure that involves analyzing a stool sample to detect the presence of parasites, their eggs, or larvae. This test is particularly important for diagnosing infections caused by organisms such as Giardia, Entamoeba histolytica, and various types of worms. Common gastrointestinal infections are reported as food poisoning or stomach infections. The stool exam is also vital for early detection, which can prevent complications like dehydration and severe nutrient deficiencies. It plays a significant role in public health, allowing healthcare provides to tract outbreaks and implement preventive measures. The test’s accuracy and reliability have been enhanced by advances in laboratory techniques, including stool microscopy and molecular testing.
Gaurav Kumar, Mohammad Saif, Nasar Equbal, Rajbala, Rashid Khan
Geneva mechanisms are widely used in robotic and automated systems to produce controlled intermittent motion. However, their dynamic behaviour—especially changes in acceleration and velocity—can significantly affect mechanical wear, vibration, and system accuracy. This study presents a comparative analysis of Geneva mechanisms with different slot counts (N = 4, 6, and 8) to understand how slot number influences motion smoothness and dynamic performance. Using MATLAB-based simulations, angular displacement, velocity, and acceleration profiles were generated while maintaining constant geometric and input parameters. Results indicate that increasing the number of slots reduces peak angular acceleration and velocity fluctuation, improving overall motion continuity. This study presents a comparative kinematic analysis of Geneva mechanisms with slot counts N = 4, 6, and 8 using MATLAB simulation. A smoothness index is proposed to quantitatively compare motion continuity and dynamic response. This contributes design-oriented insights for robotics and CNC tool changers. The present work is simulation-based and provides a foundation for future experimental validation.
Teresita H. Borres, Vergel C. Molina
Collaborative Strategic Reading (CSR) is an approach which uses a mix of whole class instruction and small cooperative peer learning groups. It begins with teacher modeling, role playing, and teacher think-aloud and then, followed by the formation of heterogeneous cooperative learning groups in which students employ four comprehension strategies: Preview, Click and Clunk, Get the Gist, and Wrap Up. This study investigated the effects of Collaborative Strategic Reading on students’ comprehension and motivation. Specifically, it sought determine the reading comprehension level of the students in the CSR and non-CSR groups in the pre-test and post-test; identify the attitude level of the students in the CSR and non-CSR groups in the pre-test and post-test; find out if there is significant difference in the reading comprehension level of the students in the CSR and non-CSR groups; assess if there is significant difference in the attitude level of the students in the CSR and non-CSR groups. The study used a descriptive evaluative design method. It utilized a random sampling among 87 Grade 12 participants. The reading comprehension levels of students were identified through a teacher-made comprehension test which was interpreted using Phil-IRI Silent Reading Program. Students’ attitude was determined through a questionnaire which was adapted from Candilasa (2019) and Brooks (1996), who have developed the Students’ Attitudes Toward Reading and the Short Form Reading Attitude Survey, respectively. Results showed that the CSR group outscored the non-CSR group on their reading comprehension. Also, students in both groups shows positive attitude towards reading, however, the CSR group has higher attitude level compared to non-CSR group. Moreover, there was a significant difference in the reading comprehension of students exposed to CSR and non-CSR groups. On the other hand, the reading attitude of students exposed to CSR and non-CSR groups was statistically significant. Indeed, CSR was effective in improving the reading comprehension of students as well as enhancing their reading attitude.
Azagbaesuweli, Monday Joseph, Jegede, Joy Anwuli, Nomuoja, Omonigho Francisca, Okoye, Boniface Stephen Adim
The issue of waste generation and management in any living environment is very critical since almost every activity of man leads to waste production including the metabolism of the human body system. Solid waste applies to non-liquid wastes generated by households and those of similar character from shops, offices, commercial units and health facilities. This paper addresses the problems associated with the management of these wastes and the measures adopted by stakeholders in ensuring proper management for an enhanced environmental quality. Three methods of waste disposal were adopted in the study area – waste drums, open dumbing and burning. The Pair-wise correlation was employed to analyse the relationship between the waste generation/disposal methods and the management mechanisms by the Kogi State Waste Management and Sanitation Board and other stakeholders as well as their knowledge and performance level to ensure safe environmental quality and health for the people. The result revealed that the major factors that drive waste problems in Idah include poverty, high population and urbanization growth rate as well as funding and infrastructural deficiencies. Amongst the recommendations made from this study is that the government of Kogi State should carry out a review of the waste management Act in order to enhance the proper management of solid waste and ensure a safe environment for a healthy living in Idah.
Anyakoha, Chukwunonye N., Belinda U. Anyakoha
This study investigates the influence of corporate social responsibility (CSR) initiatives on consumer purchase decisions in Nigeria's fast-moving consumer goods (FMCG) sector, a highly competitive market characterized by frequent, low-involvement purchases and intense rivalry. While traditional factors like price, quality, and availability dominate decision-making, growing consumer awareness in emerging economies has elevated CSR—encompassing social, environmental, and ethical dimensions—as a strategic differentiator that shapes brand trust, credibility, and loyalty. Drawing on stakeholder theory, signalling theory, and the theory of planned behaviour, the research addresses a key gap in context-specific empirical evidence from Nigeria, where socio-economic challenges amplify expectations for corporate societal contributions. A quantitative cross-sectional survey of 397 urban FMCG consumers revealed that CSR initiatives exert significant positive effects on purchase decisions (R² = 0.52), with social CSR showing the strongest impact (β = 0.32), followed by ethical (β = 0.28) and environmental (β = 0.21) dimensions. Consumer perception of CSR partially mediates these relationships, confirming that perceived authenticity, trust, and relevance translate CSR actions into behavioural outcomes rather than direct effects alone. These findings highlight the salience of community-oriented initiatives in developing contexts while underscoring the need for transparent communication to counter scepticism. The study advances understanding of multidimensional CSR in low-involvement markets and offers practical guidance for FMCG firms seeking competitive advantage through responsible practices aligned with local consumer values.
Dr. Wing Cheung TANG., 3Ir K. M. CHAN, Ir Dr Assoc Professor Samuel Kwok Piu LIP, Ir K. M. CHAN
The design, renovation, and retrofitting of hotels, restaurants, and hospitals are very difficult because they must deal with a lot of different things at once, including architectural aesthetics, building services engineering, structural integrity, and compliance with many different rules. This paper combines knowledge from different fields with rules that are specific to Hong Kong to make a single guide for professionals who work with these types of facilities. The paper looks at the steps involved in sequential renovation, such as demolition, service coordination, ceiling installation sequencing, and finishing works, while also talking about the different operational needs of each type of facility. The focus is on strategies for optimising space in food and beverage design, the integration of mechanical, electrical, and plumbing services in hotel developments (including swimming pool systems, guest room layouts, and gymnasium ventilation), and the unique ventilation and pressure management needs of healthcare facilities, especially in terms of preventing and controlling infections. The paper critically examines a recent incident concerning a malfunctioning operating theatre lamp in Hong Kong to demonstrate the repercussions of inadequate design integration and craftsmanship. This paper provides practitioners with a comprehensive framework for achieving quality outcomes in these facility types by systematically reviewing licensing requirements, construction sequencing, and discipline-specific design considerations. Recognised are the constraints pertaining to quantitative design parameters and comprehensive regulatory oversight, accompanied by suggestions for additional research.
Akpan, Nsima A., Aliyu Sarah O., Anukam, Basil N., Anumaka, Collins C., Etukudo, Nsikan J., Ndife, Chidiebere T., Okafor, Brian O., Okonkwo, Princewill C., Okpanachi, Clifford B., Okpoji, Awajiiroijana U., Onuchukwu, Ejikeme E., Otuuh, Azubuike G.
This study presents an integrated seismic and petrophysical evaluation of structurally controlled hydrocarbon prospects in the Eastern Niger Delta Basin, Nigeria. A high-resolution 3D post-stack time-migrated seismic dataset covering approximately 125 km² was analysed alongside well log data from three exploration wells to delineate structural traps and assess reservoir characteristics. Three key reservoir horizons (H1–H3), occurring between 1850 ms and 2600 ms two-way travel time (approximately 2450–3150 m depth), were identified within fault-assisted closures associated with NE–SW trending growth faults and rollover anticlines. Seismic attribute analysis, including RMS amplitude, instantaneous frequency, acoustic impedance, and sweetness, reveals pronounced amplitude anomalies and low-frequency shadows consistent with hydrocarbon-related effects. Petrophysical evaluation indicates excellent reservoir quality, with porosity ranging from 22.8% to 26.1%, permeability between 1320 mD and 1600 mD, and hydrocarbon saturation averaging approximately 71%. Volumetric estimation yields a Stock Tank Oil Initially in Place (STOIIP) of about 185 million barrels, suggesting significant commercial potential. However, uncertainties related to seismic resolution, lithological effects on amplitude response, and assumptions in petrophysical modelling introduce moderate risk, reflected in a geological chance of success of 0.45. The results demonstrate that integrating seismic structural interpretation, attribute analysis, and quantitative petrophysical evaluation provides a robust framework for reducing exploration uncertainty and enhancing hydrocarbon prospect assessment in structurally complex deltaic systems.
Benita Yawah Kpankpala, Dekontee D. Nyah, Randall Yeaney, Reagan S.B Falaba
Raw cow milk from informal dairy systems in developing countries, including Liberia, is frequently contaminated with enteric bacteria, posing significant public health risks due to widespread consumption without pasteurization. This study investigated microbial safety of raw cow milk produced at Carysburg Slaughter House, Montserrado County, Liberia. Hence, isolating, identifying, and characterizing enteric bacteria from raw cow milk and determine their antibiotic susceptibility profiles. Four raw milk samples were collected aseptically from individual cows at Carysburg Slaughter House in 2025. Samples were cultured on MacConkey agar, HiCrome agar, and nutrient agar. Presumptive enteric isolates were identified using Gram staining, standard biochemical tests (Kligler Iron Agar, citrate, motility indole-ornithine, urea), and colony characteristics. Antibiotic susceptibility testing was performed using the Kirby-Bauer disk diffusion method against gentamicin (10 µg), ciprofloxacin (5 µg), amoxicillin (30 µg), ceftriaxone (30 µg), and chloramphenicol (30 µg), with results interpreted according to CLSI guidelines. Results: Two of the four milk samples (50%) yielded enteric bacteria. The isolates were identified as Citrobacter freundii and Salmonella enterica serovar Typhi. Both isolates were resistant to amoxicillin (100%) but fully susceptible to gentamicin, ciprofloxacin, ceftriaxone, and chloramphenicol. No multidrug resistance was observed. Raw milk from Carysburg Slaughter House is contaminated with potentially pathogenic enteric bacteria, including the alarming presence of Salmonella Typhi, indicating severe hygienic deficiencies and human fecal contamination. Immediate interventions—improved milking hygiene, routine milk testing, and promotion of pasteurization—are urgently needed to prevent foodborne outbreaks in this community.
Joan P. Bacarisas, DM, MAN, RN, Prescela Mariz C. Cedro, RN
This study utilized a quantitative descriptive–correlational research design to assess the level of just culture and nursing work performance, and to determine whether the dimensions of just culture predict nursing performance in a pediatric unit of a government hospital. A total of 67 nurses participated in the study using validated questionnaires measuring just culture and nursing work performance in terms of frequency and quality. Descriptive statistics, including mean and standard deviation, were used to determine levels of just culture and performance, while multiple regression analysis was used to examine predictive relationships. Findings revealed that nurses perceived a high level of just culture across organizational trust, openness of communication, quality of event reporting, accountability, and continuous learning, while fear of reporting was moderate. Nursing work performance was high in terms of both frequency and quality. However, regression analysis showed that the dimensions of just culture did not significantly predict nursing performance. This indicates that nurses maintained consistent and quality performance regardless of variations in perceived just culture. The findings suggest that just culture supports a safe and fair work environment, while nursing performance is primarily sustained by professional competence, clinical standards, and organizational systems. A Just Culture and Nursing Performance Enhancement Plan is proposed to strengthen patient safety culture and sustain high-quality nursing care.
Deepthi Rani S. S., Dr. Renu Aggarwal
Knowledge graphs (KGs), which represent entities and their relationships in a structured semantic network, have been widely applied in the study of various diseases such as thyroid disorders, cardiovascular diseases, and neurological conditions. However, current diagnostic approaches often face challenges including incomplete data integration, limited scalability, and reduced diagnostic accuracy. These limitations highlight the need for advanced methodologies capable of addressing the complex nature of COVID-19 diagnosis.The proposed research introduces a framework that integrates knowledge graphs with deep learning techniques for improved COVID-19 analysis. Initially, COVID-19 related datasets will be collected from publicly available repositories such as Kaggle, including information on viral characteristics, transmission patterns, clinical symptoms, and public health data. From these datasets, relevant entities and relationships will be extracted to construct a COVID-19-specific knowledge graph. The constructed KG will then be transformed into low-dimensional vector representations using embedding techniques, enabling semantic representation within a vector space.Based on this knowledge representation, a novel deep learning model will be developed to predict COVID-19 cases using relevant input features. The model will utilize virus-related word vectors and knowledge entity vectors derived from the knowledge graph. Through supervised learning, the model will be trained to classify samples based on COVID-19 related symptoms and associated features. The effectiveness of the proposed diagnostic model will be evaluated using standard performance metrics.By integrating knowledge graph construction with deep learning models, the proposed study aims to improve understanding of COVID-19 pathogenesis and support evidence-based decision making in pandemic management. This approach has the potential to provide an efficient and accurate diagnostic tool for the early detection and management of COVID-19 cases.
Silayi Tashrifa Otenyo, Wilson Muna PhD
Access to accurate information on abortion laws and policies plays a critical role in shaping women’s reproductive health decisions. In Kenya, uncertainty and misconceptions regarding the legal provisions governing abortion continue to influence women’s choices, often resulting in unsafe abortion practices. This study sought to examine the effect of knowledge of abortion laws and policies on abortion choices among women in Bungoma County. The study was guided by the Health Belief Model, which emphasizes the influence of perceived knowledge and awareness on individual health-related decisions. A descriptive research design was adopted, targeting 78 young women aged 18–24 years, 10 Kenya Registered Nurses, and 10 gynecologists. Data from the women were collected using structured questionnaires administered through snowball sampling, while key informant interviews were conducted with nurses and gynecologists. Quantitative data were analyzed using the Statistical Package for Social Sciences, while qualitative data were analyzed thematically using Nvivo. The findings revealed that knowledge of abortion laws and policies had a strong positive influence on abortion choices among young women, with those possessing accurate legal awareness more likely to seek safe and medically supervised abortion services. Limited knowledge and prevailing misinformation, however, contributed to continued reliance on unsafe abortion methods driven by fear of legal repercussions, stigma, and social pressure. The study concludes that enhancing women’s knowledge of abortion laws is essential in promoting informed, safe, and health-conscious reproductive choices. It recommends that health facilities, county reproductive health programs, and community actors intensify targeted awareness campaigns, youth-friendly counseling, and policy dissemination to reduce unsafe abortion practices and improve reproductive health outcomes.
D.V. Jothika, Devarajan Natarajan, M. Kesavapriya, Muthu Kanagarasan, Sivaprakasam Varshini
Agro-industrial waste serves as a viable substitute material for the manufacturing of biofuels. The objective of current research was to production of bioethanol using agricultural by-products and waste materials under laboratory scale. Pretreatment was conducted on rice straw and banana fruit peels, and the cellulose degrading bacterium was isolated and identified as Bacillus sp. The hydrolyzed sample underwent fermentation using adapted yeast (Saccharomyces cerevisiae) in a controlled laboratory environment. The fermented sample analyzed by potassium dichromate method, and spectroscopic investigations to quantify bioethanol. The results of the study demonstrated that banana peel, rice straw and their combinations yielded bioethanol i.e. banana peel - 4.6 mg/mL, rice straw - 5 mg/mL, and a combination of banana peel and rice straw - 5.04 mg/mL. This yield is lower than industrial-scale production, indicating that the study is at a preliminary laboratory scale and requires further optimization. The outcome of study suggests that the combinations of banana peel and rice straw substrate yielded the maximum quantity of bioethanol compared to other substrates.
Dr. Praveen K. R., Sumaja Sasidharan
The digital revolution has fundamentally altered how we communicate, giving rise to what can be termed ‘neo-communication’—a mode of interaction shaped by technological platforms, artificial intelligence, and multimodal expression. This paper explores how natural language technologies, including machine translation, speech recognition, natural language processing, and social media linguistics, are reshaping human communication across cultural, educational, and economic domains. Through an examination of contemporary digital communication practices, we analyze both the transformative potential and critical challenges of these technologies. Our findings reveal that while language technologies democratize access to information and enable cross-linguistic communication, they also raise concerns about linguistic homogenization, data privacy, and the preservation of cultural nuances. This study synthesizes current interdisciplinary research to offer a structured analytical framework that evaluates language technologies across cultural, educational, and economic dimensions, contributing to ongoing discussions about the future of human communication in an increasingly digitalized world and emphasizing the need for balanced approaches that harness technological benefits while safeguarding linguistic diversity and cultural authenticity.
Joan P. Bacarisas, Maria Geraldine P. Macaldo
This study aimed to determine the relationship between leader support for innovation and innovation competence among nurses in a government hospital. Using a quantitative descriptive–correlational design, the study assessed the level of leader support for innovation and innovation competence and examined their relationship with selected nurse profile characteristics. Data were collected through standardized questionnaires administered to nurses across various clinical units. Descriptive statistics were used to determine variable levels, while chi-square test, Cramer’s V, and Pearson correlation were applied to determine relationships among variables. Findings revealed that nurses perceived leader support for innovation at a very high level, while innovation competence was rated high. Significant relationships were identified between most profile variables and both leader support and innovation competence, except unit or department assignment. A strong positive relationship was also found between leader support and innovation competence. The study concludes that supportive leadership plays a crucial role in strengthening nurses’ innovation competence. A Leader Support for Innovation and Innovation Competence Enhancement Plan is proposed to sustain innovation-focused leadership practice.
Maulika Patel, Vaghani Hemangi
This research paper proposes an effective, secure, and immutable digital will system through the use of blockchain technology, aiming to replace traditional paper-based methods that are vulnerable to fraud and theft. The system utilizes the Polygon network to ensure the immutability and transparency of the Testator’s will through the use of cryptographic hashing. The system also includes a verification process with multiple tiers, including the Lawyer and the Admin, as well as an analytical dashboard for monitoring the system in real time. The innovation in the system lies in the integrationof the "Dead Man's Switch" principle, which will notify the stakeholders in case there is no activity from the testator for some period of time. To guarantee maximum security, is mandatory for the Beneficiary to get verified through Aadhaar-based biometric authentication, that is, Face Scan, prior to transferring the property in the form of NFTs.
Abanda F.H, Florian M.Z, Nyibanda N.G
In Sub-Saharan Africa, and particularly Cameroon, the demand for socially inclusive and environmentally responsible architecture is growing due to rapid urbanisation, climate pressures, and the needs of vulnerable communities. Orphanages, as critical social infrastructure, are frequently delivered through cost-driven approaches that neglect sustainability and long-term performance. While Building Information Modelling (BIM) has globally advanced design precision, cost optimisation, and environmental performance analysis, its application in Africa especially for projects using eco-friendly materials such as compressed earth blocks (CEBs) remains limited. This study employs BIM, through Autodesk Revit, to design sustainable, child-centred orphanages in Cameroon using locally sourced materials. Two functionally equivalent prototypes, one with sandcrete blocks and another with CEBs, were developed and evaluated through comparative cost estimation, embodied carbon and energy analysis, and operational performance assessment, in line with life-cycle assessment (LCA) standards and thermal comfort benchmarks. Results show that CEBs delivered lower construction costs, reduced embodied impacts, and improved thermal comfort compared to sandcrete. BIM-enabled workflows enhanced quantity take-offs, integrated early LCA, and supported evidence-based material selection. This research provides one of the first regionally validated datasets on sandcrete and CEB performance in Cameroon, while proposing a replicable digital design framework for humanitarian architecture in resource-constrained Sub-Saharan contexts.
James L. Paglinawan, Kathleen Erikah Dahe
The transition from arithmetic to algebra often triggers “symbol shock” among Filipino learners, where variables are perceived as abstract symbols disconnected from reality. This phenomenological study explored the lived experiences of 15 Grade 7 students at Sumilao National High School as they engaged with algebraic expressions and simple equations through MATATAG lesson exemplars implemented in the fourth quarter of school year 2025-2026. Data were collected via semi-structured interviews, “3-box” reflection activities involving relatable scenarios like cupcake sharing and budgeting, represented through bar models and colored strips, and researcher’s notes. Thematic analysis revealed five emergent themes: (1) visual representations effectively bridged abstract algebraic concepts to concrete real-life scenarios ;(2) students initially encountered challenges in constructing bar models, specifically in labeling unknown quantities and representing operations like subtraction; (3) conceptual breakthroughs occurred through collaborative visualization, where variables were reconceptualized as “missing pieces” within equal-length bar configurations; (4) participants’ perceptions shifted from viewing algebra as an abstract requirement to a practical tool for daily utility; and (5) exemplar strengths included the combination of group collaboration, concrete manipulatives, and guided teacher feedback. Findings revealed that visual scaffolding and social negotiation are essential for reducing cognitive load during algebraic transitions. These findings indicate that MATATAG-based visual and contextualized instruction effectively supports the transition from arithmetic to algebra by reducing abstraction, promoting collaboration, and grounding learning in meaningful experiences. However, the results also highlight the need for deliberate scaffolding to address initial difficulties in translating word problems into visual representations, ensuring smoother cognitive transitions for learners.
V. Geetha
Cancer treatment outcomes vary widely among patients due to tumour heterogeneity, genetic diversity, and environmental factors. Predicting drug response accurately is a central challenge in precision oncology. Machine learning (ML) has emerged as a powerful tool to integrate multi-omics data and clinical information to forecast therapeutic responses. This paper provides a comprehensive and in-depth analysis of machine learning approaches used in predicting cancer drug response. It discusses data sources, preprocessing strategies, feature engineering, algorithmic models, validation techniques, and real-world applications. The study also highlights challenges such as data imbalance, interpretability, and reproducibility, and explores emerging directions including explainable AI, federated learning, and digital twin models. The integration of ML into oncology is expected to revolutionize personalized medicine, improve treatment efficacy, and reduce adverse effects.
Akanchha Rani, Bhawna Anand, Dr. Avinash Kumar, Shashank Pandey
The growing reliance on internet-based technologies, cloud infrastructures, and interconnected digital systems has resulted in a significant rise in the incidents of cyber crimes and sophistication of the attack. Many modern cyber threats such as distributed denial-of-service (DDoS) attacks, dissemination of malware, and unauthorized access, as well as the large-scale data breaches, take place through network communication channels. These activities create a large volumes of network traffic that can be used as important digital evidence during cybercrime investigations. Network traffic forensics concentrates on analyzing such traffic to gain understanding of the attack behavior and help reconstruct security incidents so as to support the analysis of investigative nature. However, traditional forensic methods based on manual inspection or predefined rules are often not able to handle the volume and complexity of traffic generated on modern high speed networks.
David Kuparadze, Dimitri Pataridze, Nino Khundadze, Violeta Kirakosyan
The Middle Corridor is increasingly gaining strategic importance, as north of it, the war between Russia and Ukraine has created a stalemate, while to the south, there is significant instability due to periodic armed conflicts related to Iran. Georgia, with access to the Black Sea, is one of the key countries in the Middle Corridor. According to World Bank forecasts, transit traffic through Georgia will increase by 52% in the coming years. This article examines the impact of increasing freight traffic on the geo-ecological state of the territories adjacent to the international highways E60 and E70, which are part of the Middle Transport Corridor. A study of soil samples and maize grown on them was carried out. The concentrations of heavy metals and toxic chemical elements were determined. Based on the results obtained, calculations were made of the Contamination Factor (CF) of soil and corn and the Translocation Factors (TF) of polluting elements from the root layers to cereal grains.
Muzammil Umar, Yahaya Haruna
The crude oil sector plays a vital role in Nigeria's economy, accounting for the majority of government revenue and foreign exchange earnings. However, the inherent volatility in crude oil prices, driven by global factors and market shocks, poses significant challenges to economic stability and fiscal planning. This study aims to model Nigeria's crude oil price dynamics by incorporating selected error innovations to enhance the accuracy of volatility modeling and forecasting. Using a dataset spanning 1960 to 2024, econometric models such as GARCH, EGARCH, and TGARCH were employed to analyze the impact of error innovations on oil price volatility. The research evaluates the performance of these models in capturing stylized facts, such as volatility clustering and asymmetries, while considering different error distributions. Findings highlight the critical role of error innovations in explaining price fluctuations and demonstrate the superior forecasting accuracy of models that incorporate these shocks. The study provides both theoretical and practical contributions, advancing econometric methodologies for volatility modeling and offering insights for policymakers, investors, and industry stakeholders. Accurate forecasts can aid in mitigating economic risks, improving fiscal policy formulation, and guiding investment decisions in Nigeria's oil sector. Despite limitations related to model assumptions, data quality, and structural changes in the oil market, the research underscores the importance of error innovations in understanding and managing crude oil price volatility.
James L. Paglinawan, Ranz Raymund S. Rio
This study explored the experiences of graduates of the Bachelor of Secondary Education major in Mathematics regarding mathematics courses taught by non-education instructors. Specifically, it examined their reasons for pursuing the program, the challenges they encountered, the ways they coped with those challenges, and their recommendations for future students and higher education institutions. The study used a qualitative design and analyzed semi-structured interview data through thematic analysis. Thirteen graduates of Central Mindanao University were selected through purposive sampling. Interview transcripts were coded, grouped into categories, and refined into interpretive themes. The findings showed that the participants pursued the program mainly because of their interest in mathematics, desire to deepen their content knowledge, improve their teaching skills, and attain professional growth. The findings also indicated that non-education instructors were often perceived as mathematically competent but pedagogically limited, which made lessons fast-paced, highly technical, and less accessible. In response, the participants relied on self-study, peer support, and external learning resources, suggesting that pedagogical gaps shifted much of the work of understanding from the instructor to the student. The participants recommended stronger student initiative and institutional support for pedagogical training, especially for non-education instructors assigned to major mathematics courses. The study therefore underscores the need to align content expertise with pedagogical competence in mathematics teacher education.
Dr. James L. Paglinawan, Evelyn R. Camus
Public-school educators in the Philippines, under the Department of Education (DepEd), increasingly pursue part-time teaching in private schools to supplement income, enhance professional skills, gain diverse pedagogical exposure, and mentor pre-service teachers. This interpretive phenomenological study focuses on 15 purposively selected DepEd educators from Valencia City, Bukidnon, who balance full-time public-school responsibilities with part-time roles at Valencia Colleges (Bukidnon), Inc., while managing heavy ancillary workloads and contextual challenges such as weather disruptions. The study addresses a local knowledge gap concerning their lived experiences of time conflicts, exhaustion, policy adaptation, and resource constraints, despite existing Philippine and international literature on teacher workload and moonlighting. Using semi-structured interviews and thematic analysis, the study explores educators’ motivations, struggles, coping strategies, and advice. Findings indicate multifaceted drivers, persistent time-management pressures, and the use of proactive planning and flexible modalities to sustain dual roles. The results underscore the need for policy measures such as workload caps, flexible scheduling guidelines, and targeted training to support teacher retention, promote work–life balance, and enhance educational equity.
James L. Paglinawan, PhD, Ralph Lyndon F. Quilla
Gaming online now fits naturally into how many workers spend their free time, especially in the Philippines, where fast-growing esports meet the realities of mixed office-and-home jobs. Instead of interviews, researchers used open questions sent through Google Forms during March 2026, gathering detailed answers from 15 working adults who play games regularly. Participants were between 25 and 45 years old, came from fields like tech support, customer service abroad, and teaching, selected carefully using private Facebook gaming communities reached by message. What people said around 2,000 lines of personal reflections was studied closely following a clear six-step method created by Braun and Clarke back in 2006. Patterns emerged around why they played, how often, what drew them in, along with effects on energy, mood, and daily life balance. From start to finish, the process focused on real experiences without adding assumptions or generalizations about gamers everywhere. Most people talked about escaping stress gaming helped them unwind when pressure built up at work. Mobile Legends was not just a pastime, it became a way to clear their heads after long hours. Instead of small talk around the water cooler, they leaned on group chats inside games. Those moments filled gaps left by working alone from home. Yet some noticed sharp focus during play often led to exhaustion later. Late nights bled into mornings, making balance hard to keep. Notifications pulled attention back even after logging off. This mix showed how games could support well-being or interfere with routine. Light involvement linked to better mood, according to local findings. Heavy use carried downsides like patterns seen elsewhere when tech blurs personal limits. Research across regions backs this tension between recovery and disruption in modern jobs. Among the country’s 43 million players and a fast-growing industry (YCP Solidiance, 2020; Statista, 2025), this work fills key holes in how professionals are studied through personal stories. Instead of fixating on young people and dependency myths, it reveals deeper real-life insights. Tools allowing users to manage their own habits emerge here, alongside office strategies for healthier tech use. Long-term studies also gain importance balancing gains against risks as Southeast Asia moves further into digital life.
Aathirai Malar M A, Akshaya P, Dr A Reni, Swathi C S
The current study aimed to develop and evaluate a fruit leather made from red banana (Musa acuminata var. Red Dacca) and mango (Mangifera indica) as a fruit product with added value. Fruit leather is a dehydrated snack made from fruit. It offers a longer shelf life while keeping important nutrients and flavors. In this study, ripe red banana and mango pulps were mixed in various proportions with liquid glucose to improve sweetness, texture, and stability. We used Response Surface Methodology (RSM) to optimize the recipe and examine how the variables affected product quality. We analyzed the produced fruit leather for physicochemical properties such as moisture content, ash, protein, fat, carbohydrates, titratable acidity, total sugars and energy value. Texture Profile Analysis was performed to evaluate qualities like hardness, cohesiveness, springiness, gumminess, and chewiness. We also assessed functional properties, including antioxidant activity and total phenolic content. Shelf-life studies were conducted over one month under regular storage conditions. Microbial analysis included total plate count, yeast and mold count and coliform count to check product safety. The results showed that the optimized recipe had desirable physicochemical properties and acceptable texture. The microbial load stayed within safe limits during storage. The product also demonstrated good antioxidant potential. Overall, the study shows that using Musa acuminata var. Red Dacca and Mangifera indica can successfully create a nutritious fruit-based snack. This research highlights the potential of this product as a functional food with added value in the fruit processing industry.
Dr. Namrata Srivastava, Dr. Nayab Ishrat
Background: Congenital nasolacrimal duct obstruction (CNLDO) is a common ocular disorder in infants characterized by persistent epiphora and mucopurulent discharge caused by blockage of the nasolacrimal duct. Although many cases resolve spontaneously within the first year of life, conservative management is usually recommended as the initial treatment. Lacrimal sac hydrostatic pressure application (HPA), a physician-performed pressure technique, has been proposed as an effective office-based intervention to relieve obstruction and accelerate symptom resolution. Aim: To evaluate the efficacy and safety of lacrimal sac hydrostatic pressure application as a conservative treatment for infants with congenital nasolacrimal duct obstruction. Methods: This retrospective cohort study included 179 infants (261 eyes) diagnosed with CNLDO who underwent HPA performed by a pediatric ophthalmologist. The procedure involved applying controlled downward pressure over the lacrimal sac to generate hydrostatic force within the nasolacrimal duct. Treatment success was defined as complete resolution of epiphora and/or mucopurulent discharge within 48 hours after the procedure. Patients were followed with a mean follow-up duration of 11.6 ± 13 months, and statistical analyses including logistic regression were used to determine predictors of success. Results: Complete resolution after the first HPA occurred in 102 eyes (39.1%). Infants aged ≤6 months had significantly higher success compared with older infants (43.7% vs 30.9%, p = 0.04). Younger age was a significant predictor of success. A second HPA resulted in additional resolution in 12 eyes (26.1%) without major complications. Conclusion: Lacrimal sac hydrostatic pressure application is a safe, practical, and effective conservative treatment for CNLDO, particularly in infants younger than six months, and may reduce the need for surgical intervention.
Cheska V. Tulinan, James L. Paglinawan
Degree–career alignment is increasingly emphasized in the Philippine basic education system; however, many language education teachers pursue advanced degrees that do not fully match their current classroom roles. Within a policy environment that promotes merit and competency based career progression and rewards advanced qualifications, alongside persistent specialization mismatch noted by EDCOM II, such misalignment raises questions about motivation, professional strain, and identity. This qualitative study explored the lived experiences of language education teachers who are working in Language Education while pursuing or holding graduate degrees in management and leadership. Using a phenomenological approach, data were gathered through a semi structured Google Form from 15 language education teachers at Malaybalay City National Science High School to examine their reasons for pursuing non aligned degrees, the challenges they encounter, the coping mechanisms they employ, and the advice they offer others. Thematic analysis revealed four major themes. The most frequently reported was Functional and Relational Friction (93.30%), followed by Personal Evolution and Strategic Career Versatility (86.70%), Transformative Adaptation and Knowledge Synthesis (80.00%), and Strategic Narrative Building and Proactive Alignment (66.70%). Teachers viewed their misaligned degrees as long term investments in professional growth, flexibility, and credibility, yet they experienced theory–practice gaps, role ambiguity, and identity strain. At the same time, they actively translated leadership concepts into their work, bridged skill gaps through self directed learning and mentoring, and crafted narratives that frame their combined expertise as a professional edge. Overall, degree–career misalignment emerged as a multifaceted condition shaped by policy reforms, institutional expectations, and teachers’ own strategies, generating both friction and opportunities for expanded professional identity and practice.
Chukwuemeke Ufeli Ovili, Emeka Agabor, Osahon James Ediae, Thaddeus Origho
This study examines passive design strategies in traditional Nigerian architecture as expressions of indigenous environmental knowledge in hot-humid climates. While contemporary architectural practice in many tropical regions often prioritizes technology-driven sustainability solutions, it tends to overlook the spatial, cultural, and climatic intelligence embedded in vernacular building traditions. Using a qualitative research approach, the study draws on architectural interpretation, field observation, and critical spatial analysis to investigate selected traditional Nigerian building typologies. It focuses on key design elements such as spatial organisation (the arrangement of spaces), building form (overall shape and massing), envelope permeability (the degree to which walls and openings allow airflow), shading hierarchies (layered systems of sun control), and semi-open transitional spaces (e.g., courtyards and verandas) that help regulate indoor climate. The findings show that traditional Nigerian architecture operates through an integrated environmental logic, where passive design strategies are closely linked to social organisation and everyday spatial practices. The study argues that their decline in contemporary architecture is not due to technical limitations, but rather to a neglect of indigenous knowledge systems. By repositioning vernacular architecture as a source of climate-responsive design intelligence-rather than merely a stylistic reference-this paper contributes to architectural theory and calls for a renewed qualitative engagement with indigenous knowledge in sustainable design discourse.
Abdel Naser Abdel Galil Mohamed Mousa, Mohamed Hamed Mohamed Said, Rabie Ibrahim Mohamed Hassan, Shaaban Abdel hameed Refae Mohamad
Contemporary Islamic societies are societies with multiple religions, races, ideas and sects. It is very difficult to unite them all on one religion or sect, or even to bring them closer together, but coexistence is possible among them in light of mutual rights and duties within one nation. This research aims to correct misconceptions about the relationship between Muslims and others, and to present a practical model of coexistence through looks at the Noble Sunnah and the biography of the Prophet, may God bless him and grant him peace. The problem of this research lies in the misconceptions about the relationship between Muslims and others, internally and externally, and the importance of this research is highlighted in correcting these concepts about the relationship between Muslims and others internally and externally, and highlighting the meaning of peaceful coexistence between Muslims and others through looking at the Noble Sunnah The practical application of the Noble Sunnah, represented by his fragrant biography, and in this research I relied on the inductive approach in tracing the texts of the Sunnah and the events of the biography in which the manifestations of peaceful coexistence, its foundations and controls are manifested, then the analytical approach in analyzing and discussing research issues, then the deductive-deductive approach to know the correct approach to the relationship of Muslims with others, and among the most important results that I reached through this research is that the origin of human relations is that they are based on acquaintance, not denial And on cooperation, not conflict, and on peace, not war, and that Islam accepts others and cooperates with them within the framework of common denominators and the general interests of society, and that the Islamic state that the Prophet, may God bless him and grant him peace, established in Medina was based on peaceful coexistence and cooperation between all sects of society.
Ellah Mae Sheane B. Eusebio, Joan P. Bacarisas
This mixed-methods research utilized a convergent parallel design to assess e-Health readiness and explore perceptions related to digital health implementation among 198 healthcare workers and 12 qualitative participants in a municipality in Leyte during the second quarter of 2025. Quantitative results showed high overall e-Health readiness, with core readiness, technological readiness, learning readiness, societal readiness, and policy readiness all rated as high. Relationship testing revealed that age, sex, current position, years in service, type of facility, internet access, and training had no significant correlation with e-Health readiness, which indicated that digital preparedness was broadly consistent regardless of demographic differences. Qualitative findings provided depth and context, particularly regarding the perceived strengths of core, learning, societal, and policy readiness. Upon integration, the results for all dimensions converged; however, in technological readiness, the findings diverged. While the quantitative data suggested high scores, qualitative narratives highlighted persistent structural barriers such as limited ICT equipment, unstable internet connectivity in barangays, and a lack of dedicated IT support. Overall, the study revealed strong motivational readiness alongside persistent structural challenges. Based on these findings, the e-Health Readiness Enhancement and Adoption Plan was developed to address infrastructure, training, and policy support needs.
Aftab Alam, Ajay Singh Thakur, Anushree Gautam, Deepak Koshti, Ramdarshan Parashar, Vaibhav Rajoriya, Yogesh Sharma
The present study aimed to evaluate the anti-inflammatory effects and wound healing potential of Momordica charantia fruit extracts. Plant material was subjected to maceration and Soxhlet extraction, and the resulting extracts were analyzed for physicochemical parameters including water- and alcohol‑soluble extractive values, as well as acid and water‑soluble ash content. Quantitative phytochemical analysis confirmed the presence of active constituents, with the methanolic extract showing a total phenolic content of 72.22 mg GAE/g and a total flavonoid content of 72.23 mg GAE/g. Pharmacological evaluation was performed using two animal models: carrageenan‑induced paw edema in rats for anti-inflammatory activity, and the incision wound model for wound healing potential. The ethyl acetate extract at 20 mg/kg body weight demonstrated maximum inhibition of inflammation (76.92%), which was comparable to the standard drug indomethacin (10 mg, 82.69%). In wound healing studies, the methanolic extract exhibited superior tensile strength (512.62 ± 1.23 g) compared to EMC (489.60 ± 0.58 g), EAMC (338.63 ± 1.66 g), and the standard formulation. Overall, the findings indicate that Momordica charantia possesses significant anti-inflammatory activity and enhanced wound healing properties, with the methanolic extract showing particularly promising results for potential therapeutic and commercial applications.
Archie S.H Toomey, Beatrice Newland, Benita Yawah Kpankpala, Dekontee D. Nyah, John D. Manwor, Randall Yeaney
Nauclea latifolia Sm, a useful medicinal plant belonging to the Rubiaceae family, is found in the humid tropical rainforest and West and Central Africa. This study aims to investigate the phytochemical constituents and antibacterial efficacy of Nauclea latifolia (African Peach/Bon Bon leaf) ethanol leaf extracts against two clinically significant bacterial pathogens: Salmonella typhi and Escherichia coli. Fresh leaves of N. latifolia were collected around the Fendall Campus, University of Liberia, dried and ponded into fine powder, 50g of the powder was macerated in 250mL of ethanol, resulting in a percent yield of 5.4%. After the Qualitative phytochemical screening of the phytoconstituents documented the presence of key bioactive compounds, including saponins, steroids, anthraquinones, flavonoids, alkaloids, tannins, and resins phytochemicals known for their therapeutic and antimicrobial properties. Antibacterial activity was assessed using the agar disk diffusion method, with ciprofloxacin as the standard control. The ethanolic extracts exhibited concentration dependent inhibitory effects on both S. typhi and E. coli, producing inhibition zones ranging from 16 mm to 22 mm, while ciprofloxacin demonstrated higher inhibition zones of 35 mm and 26 mm, respectively. Although the extract showed moderate antibacterial activity compared to the standard antibiotic, it remained effective and nonresistant within Clinical and Laboratory Standards Institute (CLSI) interpretation thresholds. These findings support the traditional medicinal use of N. latifolia and highlight its potential as a complementary agent in managing bacterial infections, especially in settings confronted with rising antimicrobial resistance. Further research is recommended to isolate active constituents, determine minimum inhibitory concentrations, and evaluate potential synergistic interactions with conventional antibiotics.
Dr. Roopa Vishwanath Sangvikar, Radhika Bhalchandra Deshpande
Medicinal plants are an important source of natural bioactive compounds with significant therapeutic potential. Aegle marmelos is a well-known medicinal plant widely used in traditional systems of medicine for the treatment of various ailments, including diabetes and oxidative stress-related disorders. The present study was undertaken to evaluate the phytochemical constituents and biological activities of Aegle marmelos leaf extract. Preliminary phytochemical screening was carried out using standard qualitative methods, which revealed the presence of important secondary metabolites such as flavonoids, glycosides and steroids. The total phenolic and total flavonoid contents of the extract were also determined, indicating the presence of polyphenolic compounds. The antioxidant activity of the extract was evaluated using the DPPH free radical scavenging assay, while the antidiabetic potential was assessed through the α-amylase inhibition assay. The results demonstrated that the extract exhibits notable antioxidant and antidiabetic activities. Further analysis using HPTLC confirmed the presence of flavonoid compounds, while LC–MS profiling revealed a diverse range of phytoconstituents, indicating the chemical complexity of the extract. Overall, the findings suggest that Aegle marmelos leaves are a promising source of bioactive compounds with potential therapeutic applications, supporting their traditional medicinal use.
Dimple T. Soria, Emercelyn May Latumbo, Janine A. Donaire, Maedel Joy V. Escote
Phytochemicals are compounds found in plants that help the plants survive and defend themselves against threats. In medicinal plants, these compounds are responsible for the plant’s effectiveness in treating different illnesses. Most of these medicinal plants lack phytochemical studies, and some studies only target a specific part of the plant. This study aims to identify the specific phytochemical compounds that are present in the selected medicinal plants used by the B'laan tribe. This study used a descriptive research design to describe and interpret the selected medicinal plants: Gmelina (Gmelina arborea), Balbas-pusa (Orthosiphon aristatus), and Agik-agik (Acmella oleracea). Plant samples were collected at Barangay Assumption, Koronadal, South Cotabato, Philippines, sealed in a zip-lock bag, and directly delivered to the WVN Research Laboratory located at Davao City, Philippines. Two tests, qualitative test and quantitative test, showed that flavonoids, tannins, phlobotannins, steroids, and glycosides were present in all three samples. At the same time, alkaloids were only present in Gmelina, and saponins were absent in all three. These compounds are significant for the anti-inflammatory, antiviral, antimicrobial, analgesic, antipyretic, and antioxidant properties of plants, Quantitative test results on Gmelina shows a strong concentration on flavonoids and tannins with 16.52 mg/g and 15.21 mg/g respectively, phlobotannins 7.56 mg/g and small concentration of glycosides, alkaloids, and steroids containing 3.25 mg/g, 3.52 mg/g, and 1.42 mg/g respectively. Flavonoids and tannins contain 14.22 mg/g and 10.24 mg/g, respectively, on Balbas-pusa. Plobotannins, glycosides, and steroids with 5.26 mg/g, 2.12 mg/g, and 1.23 mg/g, respectively. Lastly, Agik-agik contains 12.65 mg/g and 11.28 mg/g of flavonoids and tannins. Plobotannins, glycosides, and steroids contain 4.23 mg/g, 2.45 mg/g, and 1.32 mg/g, respectively. These results show the medicinal plants used by the tribe and the specific illnesses they treat. They will be helpful in future pharmacological studies of these plants to develop medicines.
Dr. Suma S., Sadeel Shamim Wani, Sarthak Singh, Utkarsh Loyalka
The widespread adoption of e-learning platform has transformed modern education by enabling continuous monitoring of students engagement, learning behavior, and academic performance. Learning management system [LMS]. Such as moodle, Coursera and Edx collect large volume of behavioral data including login, activity, resource interaction, assignment, submission and discussion. Forum Participation. These datasets provide valuable insights that can be analyzed using machine learning algorithms to predict student academic outcomes and identify learners at risk of academic failure. However, raw LMS interaction data is often noisy, inconsistent and difficult to interrupt, which limits the Reliability of predictive models Feature Engineering plays a critical role in transforming raw behavioral logs into meaningful indicators such as study consistency, time on tasks, participation intensity, and learning persistence Students using real world data. Let's demonstrate that Engineered features. Significantly improved predicting, accuracy and interpretability of machine learning Model. This research analyzes how feature engineering enhances academic performance predicting models while maintaining transparency. Fairness and ethical AI adoption in education. The study synthesizes binding from recent research to propose a conceptual framework that supports Interpretable predictive analytics aligned with responsible AI principles in educational environment.
Aayush Pawar, Anhad Singh, Rahul, Sakshi
To receive proper help and effective educational planning, one must predict the academic results of the pupils. In this work, the machine learning approach is applied to research the key factors that influence academic performance of students, 17 features that include demographic data, behavioral (raising hands, visiting resources, watching announcements, and participating in discussions) and parental involvement (survey participation and school satisfaction) data, and attendance records of 480 students were analyzed. The students were categorized as three groups namely: High (H), Medium (M), and Low (L), according to their performance. Random Forest was selected as the best classification model after testing various other classifier models and the optimized model gave the best classification accuracy of 79.17% In order to resolve the uneven performance distribution, this model was set with the estimators numbered 600, depth to its maximum of 20 and the weights of the classes were equal. The following behaviors were identified to be significant contributors, student engagement behavior, parental satisfaction, educational stage, and absence patterns. The research proves that machine learning can be successfully used to predict academic achievement and help teachers to recognize at-risk students and intervene in their areas of need. The presented piece of work provides a handy reference to developing the performance prediction systems of students and fits in the growing body of research in the area of the educational data mining.
Dr. James L. Paglinawan, Floreda Cahuan Dumandan
This study aimed to examine the relationship among professional development opportunities, organizational commitment, and workload demands of private school teachers in Bukidnon during the School Year 2025–2026. Specifically, it sought to determine the levels of professional development opportunities, organizational commitment, and workload demands, as well as to identify their significant relationships and predictive influences. Employing a descriptive-correlational quantitative research design, data were gathered from 300 private school teachers using adopted standardized survey questionnaires. The collected data were analyzed through descriptive statistics, Pearson product-moment correlation, and multiple regression analyses. Findings revealed that teachers perceived a high level of professional development opportunities across instructional, scientific, personal, and organizational domains, indicating favorable access to professional growth activities. In terms of organizational commitment, teachers demonstrated moderate levels of affective, continuance, and normative commitment, suggesting a reasonable sense of attachment and responsibility toward their institutions, albeit influenced by existing conditions. Meanwhile, teachers reported high workload demands in terms of time, quantitative, and qualitative aspects, signifying that although workloads are manageable, they remain consistently challenging. Correlation analysis showed a significant positive relationship between workload demands and both professional development opportunities and organizational commitment. This implies that increased engagement in professional growth and stronger organizational attachment are associated with heightened perceptions of workload demands. Furthermore, regression analysis revealed that normative commitment, affective commitment, and selected dimensions of professional development—particularly instructional, organizational, and personal development—significantly predict workload demands. These findings suggest that as teachers become more professionally involved and organizationally committed, their responsibilities and perceived workload likewise increase.
James L. Paglinawan, Jonel L. Caparoso
This study examined the relationships among psychological resilience, decision-making capability, and resource mobilization practices in relation to the adaptive leadership competence of school leaders. Using a descriptive-correlational research design, data were gathered from 233 school leaders in selected public schools in Bukidnon through a validated and reliable survey questionnaire. Descriptive statistics, Pearson correlation, and stepwise multiple regression were used for data analysis. Findings revealed that school leaders demonstrated high to very high levels of psychological resilience, decision-making capability, resource mobilization practices, and adaptive leadership competence. Psychological resilience was strongest in spirituality, competence, and adaptability. Decision-making capability was high, particularly in data literacy and data usage purpose, while resource mobilization practices were very high, especially in resource acquisition, utilization, innovation, and sustainability. Adaptive leadership competence was also high, with strengths in collaboration, inclusivity, and perspective-taking. Correlation results showed that all variables were significantly related to adaptive leadership competence, with resource mobilization practices showing the strongest relationship, followed by decision-making capability and psychological resilience. Regression analysis identified resource acquisition and utilization, innovation and sustainability, resource planning and needs assessment, adaptability and support, and data usage culture as significant predictors of adaptive leadership competence. Notably, resource acquisition and utilization emerged as the strongest predictor, while psychological competence showed a negative relationship. Moreover, adaptive leadership competence is best explained by strong resource management, data-informed decision-making, and flexible leadership behaviors. The findings underscore the importance of strengthening organizational systems and strategic leadership capacities to enhance adaptive leadership in schools.
Dr. James L. Paglinawan, Rienheart Gaborno
Punctual submission of academic outputs is widely viewed as an indicator of responsibility, time management, and self regulation; however, many Senior High School learners struggle to meet deadlines due to distractions, competing responsibilities, and fluctuating motivation. Previous studies have established that effective time management is associated with improved academic performance and reduced stress, positioning punctuality as a critical self regulatory behavior (Macan, Shahani, Dipboye, & Phillips, 1990; Zimmerman, 2002). This qualitative study explored the lived experiences of 20 Senior High School students from Dangcagan National High School to understand the reasons behind timely and delayed submissions and the strategies students use to cope with challenges to punctuality. Using a phenomenological approach, semi structured interviews were conducted to investigate students’ reasons for punctual submission, struggles encountered, coping mechanisms, and the advice they offer peers. Thematic analysis revealed nine major themes. The most frequently reported motivations were responsibility and discipline (85%) and stress avoidance or preventing cramming (85%), followed by respect for teachers, time, and deadlines (75%), and time management and organization (65%). These results support previous findings indicating that procrastination often driven by task aversiveness and low self efficacy negatively affects timely task initiation and academic performance (Steel, 2007). Instructional factors were also found to influence punctuality. Prior research suggests that clear deadline policies and late point schemes can highlight early warning signs of non persistence, while earlier submissions are often associated with higher academic performance (Santelli et al., 2020; Jones & Blankenship, 2021). Overall, punctuality emerged as a multifaceted behavior shaped by self regulation, emotional management, social expectations, and instructional design. The findings suggest that implementing scaffolded deadlines, anti procrastination coaching, and transparent yet supportive submission policies may help students manage workloads, reduce stress, and improve academic outcomes.
Dr. Manjusha Nikale
Ayurvedic medicines have a lot of potential because of their comprehensive approach to illness care. Yet there is a need for sufficient standardization before they can be used in modern medicine. Nevertheless, there is a lack of work efforts directed towards the concurrent assessment of biomarkers in polyherbal formulation using HPTLC fingerprinting. Quality Control (QC) in herbal medicine is essential to ensure the safety, efficacy and consistency of products, protecting consumers from harmful adulterants and inconsistent active compound levels. It also involves testing for botanical authenticity, heavy metals, pesticides and concentration of plant parts in the drug. The drug to be administered should adhere to WHO standards to validate medicinal potential and ensure reliable therapeutics. It is relatively easy to trace the percentage of a drug in the modern medicines. In the case of herbal medicines most of the products over counter are polyherbal. To detect the percentage of a specific herb, or part of the herb like leaf stem etc., some phytochemical marker has to be developed. This marker may not be an active component of that herb. In the present study, a marker was developed from Ricinus communis leaf extract by HPTLC, after scanning at 310nm, at RF 0.68, by calculating the AUC of markers from leaf extract and the polyherbal formulation. The concentration of Ricinus communis in the formulation was calculated.
Akarsha Malik, Dinkar Malik, Krishna Anand, Navdeep Arora, Raj Kumar
Semiconductors are fundamental materials in modern science and technology, forming the backbone of electronic, optoelectronic, and energy devices. From a chemical perspective, their properties arise from electronic band structure, atomic bonding, and controlled impurity doping. This paper focuses on the structural, chemical, and electrical properties of semiconductors, along with recent advancements in materials such as two-dimensional (2D) systems and wide bandgap semiconductors. Experimental analysis of semiconductor behaviour through current–voltage (I–V) characteristics has been carried out to understand charge transport mechanisms. The study highlights the limitations of silicon-based technology at nanoscale dimensions and explores emerging materials like graphene, MoS₂, GaN, and SiC. These materials exhibit superior electrical, optical and thermal properties, making them promising for high-speed, low-power, and energy-efficient applications.
Dr. Muhammad Yabagi, Dr. Suleiman Salami, Prof. M.S. Tijjani, Rukayya Tijjani Ibrahim
Following the recent Covid 19 pandemic, a lot of countries especially developing countries like Nigeria have been struggling to increase their revenue base to stabilize their economies. Taxation is one of the alternatives used by the Nigerian government among other alternatives such as borrowing which has been criticized by stakeholders. However, tax noncompliance has been a threat to the revenue generation efforts which necessitates government to put in necessary measures to curb the tax noncompliance menace including constantly rolling out tax reforms such as the Nigeria Tax act 2025. Scholars have agreed that solutions to tax noncompliance should be a continuous process and also contextualized because different factors have been globally recognized as factors that lead to tax noncompliance including firm attributes. Therefore, this study intends to review existing literature on the relationship between firm attributes with a focus on firm’s size, financial leverage, capital intensity, corporate reputation and intangible intensity among others and tax noncompliance to identify research gaps and frontiers for further research with a view to finding lasting solutions to tax noncompliance, the findings could be used to arrive at solutions that will boost revenue generation and improve per-capita GDP. The basic problem which this paper seeks to answer is what is the relationship between firm attributes and tax non-compliance? What are the Gaps identified from the analysis? What areas of study could be explored to bridge Gap identified? The research effort utilizes a literature survey and analysis of content to arrive at an inference. Therefore, this study intends to review existing literature on the relationship between (firm’s size, financial leverage, capital intensity, corporate reputation and intangible intensity) tax noncompliance to identify research gaps and frontiers for further research with a view to finding lasting solutions to tax noncompliance, which would boost revenue generation and improve per-capita GDP. The basic problem which this paper seeks to answer is what is the relationship between firm attributes and tax non-compliance? What are the Gaps identified from the analysis? What areas of study could be explored to bridge Gap identified? The findings indicate that there exists a relationship between firm attributes and tax noncompliance, however mixed findings were found in some studies. The study recommends further research in firm attributes and tax noncompliance with a view to understanding the reaction to specific attributes to tax noncompliance to inform accurate decision making on tax noncompliance issues.
Dr. James L. Paglinawan, Loren S. Rule
This qualitative study investigates the lived experiences and underlying reluctance of Senior High School students toward the Filipino subject within the contemporary multilingual educational landscape of the Philippines. Utilizing a reflexive thematic analysis framework, the research explores the multifaceted barriers to learner engagement among fifteen (15) students at Bukidnon National High School. The findings reveal a complex interplay of four critical thematic domains: pedagogical and teacher-centered obstacles, linguistic competence and vocabulary deficiencies, self-regulated learning through strategic interventions, and the role of affective commitment. Notably, 80% of participants identified instructional issues such as passive "reporting" methods and unclear explanations as primary demotivators. In comparison, 93.3% cited a significant "vocabulary gap" and English language dominance as barriers to comprehension. Despite these challenges, the study highlights strong learner agency, with all respondents employing self-regulated strategies, including media immersion and peer collaboration, to navigate academic hurdles. Building upon these findings, the study proposes a Contextualized Filipino Curriculum that integrates contemporary media, digital literacy, and "Taglish" as a bridge to academic Filipino, making content more relatable and accessible. Additionally, it recommends implementing Teacher Sensitivity and Competency Workshops to address the high rate of dissatisfaction with instructional quality. Future research should include a Parental Perception Survey to better understand the influence of home environments on language hesitance. Finally, the introduction of a "Filipino for Professionals" module could help students view Filipino as a valuable career asset. These recommendations provide a context-responsive foundation for curriculum developers and school administrators to bridge the gap between student interest and Filipino language acquisition.
Ishaka Saini, Krishna Anand, Raj Kumar
The integration of Artificial Intelligence (AI) into green chemistry has emerged as a transformative approach for developing sustainable and environmentally benign chemical processes. AI techniques such as machine learning, data analytics, and predictive modeling enable researchers to design eco-friendly synthesis pathways, optimize reaction conditions, reduce waste generation, and minimize energy consumption. By analyzing large chemical datasets, AI can identify greener solvents, catalysts, and reaction mechanisms that enhance efficiency while lowering environmental impact. Furthermore, AI-driven tools accelerate the discovery of sustainable materials and improve lifecycle assessment, supporting the principles of green chemistry. The application of AI also facilitates real-time monitoring and intelligent process control in industrial chemistry, leading to safer and more resource-efficient production systems. Despite challenges such as data availability, model transparency, and computational limitations, the synergy between AI and green chemistry holds significant potential for advancing sustainable innovation.
Dr. Basake Julius Alochere, Nabimanya Norman, Otieno Kenneth Okelloa
Despite continued reforms in Uganda’s public service compensation framework, limited empirical evidence exists on how specific reward components shape employee performance in local government agencies. This study examined the relationship between rewards and employee performance at Kampala Capital City Authority (KCCA), with attention to compensation, performance recognition, career development opportunities, and fringe benefits. Guided by Herzberg’s Two Factor Theory and Maslow’s Hierarchy of Needs, the study adopted a mixed methods descriptive survey design. A sample of 85 employees was drawn from a population of 108 using Yamane’s formula at a 5% level of precision, with stratified and purposive sampling used to ensure representation across departments. Data were collected through structured questionnaires and interviews. Rewards were measured through compensation, recognition, career development, and fringe benefits, while employee performance was assessed using indicators such as service quality, task completion, teamwork, dependability, and creativity. Descriptive statistics, correlation analysis, and multiple linear regression were used to analyse the data. The findings showed that all reward dimensions were positively associated with employee performance. Fringe benefits emerged as the strongest predictor, followed by career development opportunities, compensation, and performance recognition. The model was statistically significant, although the findings should be interpreted with caution because the study was limited to one agency and a relatively small sample. The study concludes that both monetary and non monetary rewards matter, but a balanced reward system that strengthens employee welfare, growth, and recognition is more likely to improve performance in public institutions. Policy makers and managers in government agencies should therefore design integrated reward frameworks that combine fair compensation with career support, recognition, and benefits in order to improve motivation, retention, and service delivery.
Gitika Saini, Krishna Anand, Muskan Khan, Raj Kumar
Artificial Intelligence (AI) is transforming the chemical industry by enhancing efficiency, safety, and sustainability. This paper explores the role of AI in industrial chemical applications, including process optimization, predictive maintenance, drug discovery, and green chemistry. By integrating machine learning algorithms with chemical processes, industries can reduce costs, improve product quality, and minimize environmental impact. The study proposes a conceptual AI-driven framework for real-time monitoring and optimization of chemical processes. Furthermore, it highlights current challenges such as data limitations, high implementation costs, and lack of skilled workforce. The paper concludes with future directions emphasizing the importance of AI in achieving sustainable industrial growth.
Gulista, Km. Ekta, Krishna Anand, Rajkumar
Chemistry plays a vital role in understanding medicinal plants and their healing properties. It provides the scientific basis for identifying, isolating, and analyzing the active chemical compounds present in plants. These compounds, such as alkaloids, glycosides, flavonoids, tannins, and essential oils, are responsible for the therapeutic effects observed in traditional and modern medicine. Through chemical analysis, scientists can determine the composition and concentration of these bioactive substances, which is essential for their effective use in healthcare. The rules and principles of chemistry, including solubility, pH, and chemical reactivity, play an important role in the extraction and purification of medicinal compounds. Organic chemistry helps in understanding the structure, bonding, and functional groups of plant-based molecules, which determine their biological activity and effectiveness. Chemistry also explains how these compounds interact with the human body. This knowledge is important for ensuring proper dosage, minimizing side effects, and improving the safety of herbal medicines. In addition, modern analytical techniques such as chromatography and spectroscopy are used to study plant constituents and ensure the quality of herbal products. Thus, chemistry forms the foundation for the study and safe use of medicinal plants. It also helps in standardizing herbal formulations for consistent results. Chemistry supports the discovery of new drugs from natural plant sources. It improves the effectiveness of traditional medicines through scientific validation. Therefore, chemistry remains essential in the advancement of medicinal plant research.
Annu, Krishna Anand, Rajkumar, Tanu Pundir
This study investigates the role of chemistry in renewable energy technologies through experimental evaluation of solar cell materials and battery systems. Perovskite and organic semiconductor films were synthesized and characterized using spectroscopic and structural techniques such as UV–Vis and X-ray diffraction to assess their optical and structural properties. Solar cell prototypes were fabricated and tested under standard illumination conditions to determine power conversion efficiency and stability. In parallel, electrochemical performance of battery materials, including lithium-ion and sodium-ion systems, was analyzed using cyclic voltammetry and charge–discharge cycling. The results indicate that perovskite-based solar cells exhibit higher initial efficiency but reduced stability under environmental conditions, whereas silicon-based systems demonstrate superior durability. Battery analysis revealed that lithium-ion systems provide higher energy density, while sodium-ion batteries offer improved sustainability and cost advantages. The study highlights the influence of material composition and chemical processes on performance parameters such as efficiency, capacity, and cycle life. Furthermore, the experimental findings emphasize the need for improved material stability and environmentally benign alternatives. This work provides valuable insights into optimizing renewable energy technologies through chemical innovation and experimental validation.
Joan P. Bacarisas, Jun Carl Lewis E. Hernandez
This quantitative study used a descriptive-correlational design to examine roster flexibility, work absence behavior, and their association with selected profile variables among 234 nurses in a government hospital during the first quarter of 2026. Standardized questionnaires were utilized, and data were analyzed using frequency, percentage, mean, standard deviation, chi-square test, and Pearson r correlation. Results indicated generally high roster flexibility and responsible absence behavior among nurses, with significant relationships identified between selected variables. Roster flexibility was also found to be significantly correlated with work absence behavior. These findings underscore the importance of effective roster management in supporting workforce stability. A roster optimization and absence management enhancement plan is proposed to improve scheduling practices and promote nurse well-being.
Alok Kumar, Dr. Nisha Chandel
The present study examined the self-concept of visually impaired students in relation to the use of smart assistive devices. A descriptive comparative research design was employed to compare self-concept between smart assistive device users and non-users. The sample consisted of 67 visually impaired students aged 12–16 years selected from inclusive schools and special institutions, including 32 users and 35 non-users of smart assistive devices. Data were collected using the Self Concept Questionnaire developed by Saraswat. The mean, standard deviation, and an independent-samples t-test were used for statistical analysis. The findings revealed that visually impaired students who used smart assistive devices scored significantly higher than non-users across all dimensions of self-concept, including physical, social, temperamental, educational, moral, and intellectual. The null hypothesis was rejected as significant differences were found between the two groups. The study concludes that the use of smart assistive devices positively influences the self-concept of visually impaired students. The findings highlight the importance of integrating smart assistive technologies in educational settings to promote holistic development and psychosocial well-being among visually impaired learners.
Hope Herbert Nkhoma, Mavuto Tembo, Thokozani Bvumbwe
Background: Non-communicable diseases (NCDs) are the leading cause of morbidity and mortality worldwide, with disproportionate effects in low- and middle-income countries. In Malawi, fragile health systems face challenges in managing NCDs, yet psychological determinants such as self-efficacy remain underexplored. Self-efficacy, defined as confidence in one’s ability to execute health behaviors, has been shown to predict adherence, quality of life, and engagement in Western contexts, but evidence from Sub-Saharan Africa is limited. Methods: A mixed-methods design was employed at Kamuzu Central Hospital, combining quantitative surveys (n = 150) with qualitative interviews (n = 30). Self-efficacy was measured using the General Self-Efficacy Scale; medication adherence using the Morisky Medication Adherence Scale (MMAS-8); quality of life using the WHOQOL-BREF; and treatment engagement using a structured questionnaire. Regression analyses tested predictive relationships, controlling for demographic covariates, while thematic analysis explored lived experiences of adherence and engagement. Results: Self-efficacy significantly predicted medication adherence (β = .42, p < .01), quality of life (β = .38, p < .01), and treatment engagement (β = .45, p < .01). R² values indicated substantial variance explained (.38 for adherence, .32 for QoL, .41 for engagement). Qualitative findings reinforced these results, showing that patients with higher self-efficacy employed proactive coping strategies and relied on social support networks, while those with lower self-efficacy reported ambivalence and poor treatment participation. Conclusion: Self-efficacy is a robust predictor of both clinical and psychosocial outcomes in NCD management in Malawi. Integrating self-efficacy training into routine care, enhancing peer support programs, and designing gender-sensitive interventions can improve patient outcomes in resource-limited settings. These findings highlight empowerment as a central mechanism for transforming health systems and advancing culturally responsive chronic disease care in Sub-Saharan Africa.
Afsar, Krishna Anand, Raj Kumar, Shivam Sharma
Semiconductor devices play a crucial role in modern energy systems by enabling efficient energy conversion and storage. With increasing global energy demand and environmental concerns, semiconductor-based technologies such as solar cells, batteries, fuel cells, and supercapacitors are becoming essential. This research paper presents a detailed overview of semiconductor principles, energy band theory, and electrochemical processes that govern energy storage and conversion. It also discusses recent advancements in nanotechnology and integrated systems, highlighting the future potential of semiconductor devices in sustainable energy solutions It highlights the indispensable role of energy storage in modern society, particularly in facilitating the transition towards renewable energy sources. Additionally, it explores cutting-edge developments in energy storage technologies and ongoing research initiatives aimed at addressing global energy challenges and promoting sustainability within the energy sector
Deva Suriya S., Devasridharan K.M., Hari S., Mrs. K. Jayanthi, Naren Ariya S.
Accurate identification of hazardous gases remains a critical challenge in environmental monitoring due to the limitations of single-sensor and threshold-based systems. This work presents an intelligent gas identification approach based on sensor fingerprinting and embedded artificial intelligence. A multi-sensor array comprising MQ-series sensors is used to capture distinct response patterns generated by different gases. These patterns are preprocessed and analyzed using a lightweight TinyML model deployed on an ESP32 microcontroller for on-device classification. The system enables real-time detection, local visualization, and wireless transmission of gas data for remote monitoring. An integrated alert mechanism enhances safety by providing immediate warnings when abnormal conditions are detected. The proposed solution offers a compact, low-cost, and scalable framework suitable for smart environments, industrial safety, and IoT-based monitoring applications.
Billy James K. Plaza, RN, Joan P. Bacarisas, DM, MAN, RN
This study aimed to examine the impact of shift pattern transitions on the health and well-being of nurses and to explore their experiences during this transition. This study utilized a mixed-method research design using the convergent parallel approach. The quantitative component employed a descriptive-correlational design involving 85 staff nurses in a government hospital in Surigao City. Data were collected using an adapted Standard Shiftwork Index (SSI). Descriptive and inferential statistics, including frequency, percentage, weighted mean, standard deviation, Chi-square, and Cramer’s V, were used for analysis. The qualitative component involved in-depth interviews with purposively selected nurses to explore their experiences regarding shift transitions, and the data were analyzed using thematic analysis. The findings revealed varying levels of health and well-being among nurses following the shift pattern transition, with experiences of sleep disruption, fatigue, and stress, while others reported improved work-life balance and adaptation over time. Qualitative themes highlighted physical and psychological effects, coping strategies, and the role of social and organizational support. Overall, shift pattern transitions influence nurses’ health, well-being, and work performance. The integration of quantitative and qualitative findings informed the development of a Health and Well-Being Enhancement Plan to support nurses in adapting to shift changes.
Alexander A. Willoughby, Ayodele O. Soge, Boluwatife E. Adewoye, Oluwaseyi A. Ilori
This paper presents the modelling and simulation of electrical parameters of dye-sensitized solar cells (DSSCs) utilising MATLAB/Simulink. An equivalent single-diode circuit model was developed to represent the physical parameters influencing electron dynamics within the DSSC. The absorption coefficients of three natural dyes extracted with acetone were analyzed: Vernonia amygdalina (VAA), Geoppertia macrosepala (GMA), and Cnestis ferruginea (CFA). These coefficients were determined from existing UV-Vis analysis data. The model simulated the I-V and P-V characteristics of DSSCs sensitized with natural dyes across varying temperatures (275 - 325 K) and solar irradiance (320 - 1000 W/m²). Results indicated temperature increases slightly to enhance voltage output, while higher solar irradiance significantly boosts current across all dyes. Comparative analysis showed that dyes with higher absorption coefficients, such as GMA and VAA, produced greater current and power outputs than CFA. The model's validity was confirmed through experimental data, with minor discrepancies attributed to lower operating temperatures and greater TiO₂-layer thickness in the experimental setup. A functional DSSC solar panel comprising 500 GMA-sensitized cells was designed, achieving a maximum output of approximately 0.01 W. This research provides an effective MATLAB/Simulink model for predicting the performance of DSSCs with natural dyes and enhances understanding and optimization prior to fabrication.
Ambati Satya Sai Vaishnavi, Ch. Adhi Seshu, G. Pavan Kiran, K. Akash Sai, M. Veera kumari, T. Sai Kumar, T. Venkatesh
Peer-to-peer (P2P) energy trading has emerged as an innovative solution to modern energy challenges by enabling decentralized electricity exchange among users. The Small-scale market allows prosumers to sell excess energy directly to consumers without relying on centralized authorities. Blockchain ensures transparency, security, and immutability of transactions, while smart contracts automate trading operations based on predefined conditions. A MATLAB-based simulation environment is developed to model energy generation, consumption, and transaction processes, along with a digital ledger for recording trades. The results of different case studies demonstrate efficient energy utilization, reduced transaction costs, and improved reliability. The system promotes renewable energy adoption and supports the transition toward decentralized smart grids. This work highlights the feasibility of integrating blockchain technology with energy systems for sustainable and scalable power trading solutions.
Anvita Chougule, Milind Kulkarni, Raj Damle, Rajeshwar Chintawar, Shivam Chouhan, Siddhesh Chavan
Urban mobility platforms primarily focus on transporting passengers rather than enabling individuals to safely use their own vehicles when they are temporarily unable to drive due to impairment, fatigue, or medical constraints. This paper presents SoberFolks, an on-demand driver allocation system that dispatches verified drivers equipped with foldable electric scooters to operate users’ personal vehicles. The system integrates geohash-based spatial indexing, Haversine distance computation, and a queue-based driver allocation strategy to minimize assignment latency while ensuring fairness and scalability. Implemented using a distributed client-server architecture with secure authentication and real-time tracking, the framework demonstrates improved driver discovery efficiency compared to naive proximity search approaches. The proposed model introduces a novel paradigm in urban mobility by combining micro-mobility logistics with ride assistance services.
Eric J. Irungu, Solomon N. Kimaita
This paper explores how social media has provided a platform for tech savvy Generation Z (Gen Z) youths to engage in the competitive world of Kenya’s political activism. It draws from the recent push by Gen Z activists to push for anti-government protests geared towards a reformation of Kenya’s political and governance landscape. It draws primarily on the ungendered dimension of these activities via a robust reliance on social media platforms for political mobilisation, organisation, political messaging and gender barrier breaking among the youthful activists. It recognises that Gen Z activism cuts beyond gender barriers and this contributes to a deconstruction of the narrative that Kenyan political activism is male dominated. The paper argues that this has been possible via the faceless and genderless medium of social media platforms that many Gen Z techizens belong to. The paper is guided by the following objectives: to assess the extent to which social media has provided a genderless platform for political activism in Kenya; to analyse how social media has revolutionised the politics of protest in Kenya; and, to evaluate the deconstructive capacity of social media in the portrayal of the gender-neutral nature of political activism in Kenya. For its theoretical framework, the paper is guided by the Framing theory as propounded by Goffman and the Constructivist theory as propounded by Wendt. The paper argues that social media is providing a critical tool towards the deconstruction of existing social constructs in the political realm of explaining Kenyan politics particularly from its gendered connotation. Social media is presenting new avenues for political activism anchored on digital platforms. These platforms have aided in the framing of political narratives that challenge the status quo and resonate with the Gen Z populace in a way that they best understand each other. The paper finds that this will refine the reframing of political messaging towards political communication in a manner that exemplifies the inherent voices of protest of Gen Zs. This will be transformative as it will introduce a new construct as Kenya moves to the upcoming 2027 political contest. The paper recommends a robust rethinking of the socio-political construct emerging from the Gen Zs in terms of the evolutionary realities emerging and how these will shape political expression in this technologically driven space.
Temitope Sarah OGUNGBAIGBE
Social well-being is critical to individual's overall well-being and daily functioning. This study assessed the prevalence of social media usage among undergraduate students of Obafemi Awolowo University (OAU). It investigated the level of social well-being of the students and examined the influence of social media usage on social well-being of the undergraduates. The study employed a descriptive survey research design. The population for this study comprised the undergraduates of the university. A sample of 300 undergraduates was selected from the population (females = 57%; age range 22-27 years; favourite social media platform = Whatsapp) using convenience sampling technique. Data were collected using two research instruments, titled Social Media Use Integration Scale (α = 0.82) and Social Wellbeing Scale (α = 0.78). The Data were analysed using both descriptive and inferential statistics. Results revealed that there is a prevalence of social media usage among the undergraduates and the social well-being of the undergraduates is high. Furthermore, a positive relationship was found between social media usage and social well-being (R = 0.672, p < 0.001). Based on these findings, it is recommended that school administrators integrate digital wellness modules into orientation and general courses to further enhance student’s social wellbeing.
Dr. A. Lovelin Jerald, Nagalakshmi S, Santhiya N
Banana peeling is a primary operation in banana processing industries used for chips, flour, and other value-added products. Conventional manual peeling methods are labor- intensive, time-consuming, and unsuitable for continuous processing. To improve efficiency and hygiene, a tabletop banana peeling machine was designed and fabricated using air powered mechanism and sensor-based detection. In the developed system, pre-trimmed bananas are placed on the adjustable base. When the sensor detects the material, it triggers the mechanical actuation. The peeling unit consisting of sharpened edges which removes the peel from the pulp. This machine provides improved peeling efficiency, reduced manual handling, and better process hygiene. The compact and low-cost design makes the system suitable for small- and medium-scale banana processing units.
Akinpelu, A. A., Amusa, I. A., Ibe, P. O., Onosemuode, C.
The study used Geospatial technology to assess the closest facilities in an emergency in Oyo Federal Constituency, Oyo State of Nigeria with a view to determine the distances between the potentially violence prone polling units amongst the 551 polling units spread across the study area. Geographic Information System methods were applied. Locations of the Police formations and the hospitals serving as the emergency facilities were acquired directly from the field using a handheld GPS while the other secondary data sets were acquired from statutory bodies especially the geographic coordinates of the polling units from Independent National Electoral Commission, Abuja. The datasets were projected to the same coordinate system. Topology was used in data validation to check for gaps at the road junctions. Network analyst tool in ArcGIS Pro was used to generate the best routes and the closest facilities. Findings showed that 5 hospitals can manage emergencies effectively and efficiently. 5 police divisions are located in the study area with an Area Command Office. Best routes were determined between the polling units and the hospitals with minimum being 1.6Km and maximum gotten to be 10.5Km. The closest hospital is Peamark Hospital and is 1.06Km from Mabolaje polling unit. The study was concluded after best routes to the critical election infrastructures were determined and also closest facilities to the violence prone polling units were established. The study recommends splitting the over-crowded polling units, establishments of more secondary provider public hospitals and more personnel in the police formations.
Dr. Avani N. Doshi, Ms. Honey Patel
The growing need for effective analytical techniques for combination drug therapy has led to the development of reliable and stability-indicating methods for quantitative estimation. The present work was aimed at developing and validating a reverse phase high performance liquid chromatographic (RP-HPLC) method for the simultaneous estimation of dapagliflozin propanediol monohydrate and eplerenone in a synthetic mixture. The chromatographic separation was achieved using a Cosmosil C18 column (250 mm × 4.6 mm, 5 µm) with a mobile phase consisting of phosphate buffer and methanol in the ratio of 30:70 % v/v. The detection was carried out at 228 nm. The retention times of dapagliflozin propanediol monohydrate and eplerenone were found to be 6.2 min and 2.6 min, respectively, indicating satisfactory separation of both analytes. The developed method was validated as per ICH guidelines for various parameters such as linearity, accuracy, precision, specificity, robustness, and system suitability. The method showed good linearity with correlation coefficients close to unity for both drugs. The accuracy of the method was confirmed by recovery studies, and precision studies showed %RSD values within acceptable limit indicating reproducibility. The specificity of the method was established by the absence of interference from excipients and degradation products. Forced degradation studies were performed under acidic, alkaline, oxidative, thermal, and photolytic conditions, and the results confirmed that the method is capable of effectively separating degradation products from the analytes, thereby demonstrating its stability-indicating nature. The developed RP-HPLC method was found to be simple, precise, accurate, and robust, making it suitable for routine quality control analysis and stability studies of dapagliflozin propanediol monohydrate and eplerenone in synthetic mixtures.
Agbede Caleb Oluwole, Olutoge Festus. Adeyemi
This study investigates the potential of crushed cow horns (CCH) as a partial replacement for fine aggregates in concrete production. Six concrete mixes were prepared with varying replacement levels of sand by CCH (0%, 20%, 40%, 60%, 80%, and 100%). Standard tests were conducted on fresh and hardened concrete, including slump, density, compressive strength, split-tensile strength, and flexural strength. Results show that replacement levels above 60% led to specimen failure under self-weight. At 20% and 40% replacement, compressive strength decreased by 15.74% and 16.86%, respectively, compared to the control. The study concludes that CCH has potential as a lightweight aggregate in concrete production at low replacement levels, contributing to sustainable waste management.
James L. Paglinawan, Jessica T. Badar
Struggles and Coping Mechanisms of Inexperienced Festival of Talent Coaches represent critical gaps in the Philippines’ public school extracurricular support systems. This qualitative study explored the lived experiences of 30 inexperienced coaches from the Department of Education, Division of Malaybalay City, who served in different Festival of Talents events during the Division Festival of Talents. Using open‑ended questionnaires supplemented by follow‑up interviews, the study generated four core themes: (1) assignment based on perceived expertise and availability, (2) multidimensional struggles in coaching first‑time festival participants, (3) resourceful, structured, and emotionally grounded coping strategies, and (4) guided patience, structured preparation, and student‑centered coaching. Findings show that coaches were assigned informally, often because of subject‑matter alignment, administrative trust, and who was available or willing to volunteer, rather than through formal training or selection. In the process, they faced multifaceted challenges rooted in resource scarcity, time conflicts with teaching duties, student inexperience and anxiety, and inconsistent or unclear competition mechanics. In response, coaches exhibited resilience through a combination of practical improvisation, such as borrowing materials and personal financial support, systematic planning, like task breakdowns, timelines, and role assignments, and psychological coping, such as purpose‑focused reframing, celebrating small wins, and self‑learning via digital platforms. Despite the absence of formal coaching induction, these mentors transformed systemic constraints into opportunities for holistic student development in events such as Impromptu Speech, Bayle sa Kalye, STEMAZING, and other Festival of Talents components. The study culminates in four key recommendations for novice coach sustainability: mastering scoring rubrics and preparing early, implementing graduated skill‑building with stress‑tested performances, building collaborative support networks, and cultivating a relational, confidence‑centered coaching culture. These insights underscore the urgent need for Department of Education‑developed technical assistance protocols, structured onboarding for festival coaches, and targeted resource allocation to professionalize an otherwise informal yet highly impactful mentoring role in resource‑constrained provincial schools.
Alkhaser V. Sappayani, Loredel A. Alicante, MAEd, Lourdes Angelica B. Ugpo, MAEd
Student satisfaction in higher education under flexible learning remains inadequately explained, particularly regarding the predictive role of Student Affairs and Services (SAS) in compliance with CMO No. 8, s. 2021. This study aimed to determine the relationships and influences among student welfare, student development, and institutional programs and services on student satisfaction at Davao Central College. A quantitative correlational design was employed with a stratified sample of 358 students, and data were analyzed using descriptive statistics, correlation, and multiple regression. Results revealed high levels of SAS implementation and student satisfaction, with significant differences across sex, department, and year level, and a strong combined influence of SAS components explaining 91.7% of the variance in satisfaction. It is recommended that institutions strengthen student development services, enhance counseling and financial assistance programs, and adopt data-driven, student-centered strategies to sustain and improve satisfaction in flexible learning environments.
Dr. James L. Paglinawan, Jarren Y. Herbieto
The study investigates how senior high school students view digital games. Although students report that digital games provide opportunities for relaxation, enjoyment, and a connection to peers as the primary motivators driving play, they also highlight problematic aspects of use including gaming addiction, which may impact academic motivation and learning outcomes in negative ways. The findings present accounts from qualitative interviews with Grade 11 students from Silae National High School who recounted playing digital games after school on personal devices such as mobile phones, while balancing classroom obligations, homework, and family responsibilities. This occurred in resource-poor contexts where institutional guidelines for responsible gaming and digital well-being rarely exist. While many Philippine studies have quantified the link between online gaming and academic performance, generally reporting moderate negative impacts of regular gaming on grades, attention, and classroom participation (DepEd Region VIII, 2023; Rufo, 2023; Sumibcay, 2024; see also Mahmud et al., 2023), relatively few have qualitatively examined how senior high school students themselves make sense of digital games both as stress relief and academic risk in their everyday school lives. Although recent qualitative research on the lived experiences of online gaming among Filipino senior high school students offers a glimpse into the rich and complex tapestry of habitual pleasure, social connectedness, stress relief, as well as preliminary signs of addiction, such studies are limited in number and typically focus on single or bimodal states. The students’ narratives suggest that, while they often seek relief from stress, boredom, loneliness, and pressure from studies and family by playing digital games for escape or relaxation (echoing some local evidence [e.g., DepEd Region VIII, 2023] as well as international research [e.g., Mahmud et al., 2023; Rufo, 2023; Sun et al., 2023]), excessive gaming is reported to cause significant problems with time management and distract them from school tasks, leading to sleep deprivation or missed opportunities for academic engagement. This research aims to describe and explore the perspectives and experiences of senior high school students in a Filipino public school concerning digital games, and how their engagement with digital games relates to balancing gaming time with academic performance and learning outcomes. This study concludes with important suggestions for digital game engagement in a senior high school setting. It highlights students' perspectives, offering contextualized information that enriches findings beyond correlational statistics by illustrating how gaming, stress, family matters, and schooling intersect within real-life contexts. Findings specific to school-based guidance programs, as well as the role of the home in advocating responsible gaming, time management, and self-regulation strategies for students, would benefit homeroom advisories and parent-teacher initiatives promoting digital well-being in senior high school. Senior high schools should also ensure that discussions of digital well-being are incorporated into existing academic work and pastoral care structures. Future prospects may involve designing and piloting such targeted interventions as structured time-management workshops, digital wellness modules, or game-oriented learning approaches to harness student interest in digital games while counterbalancing their deleterious impacts on academic engagement and health, supported by emerging evidence from the Philippines and elsewhere that properly guided student engagement can alleviate the negative academic impact of online gaming (Mahmud et al., 2023; Online Gaming Addiction…, 2024; Sun et al., 2023).
Nivethini K., S. Mahalakshmi, Shivani R.
This research examines the integration of artificial intelligence (AI) in the healthcare industry, with specific reference to AI-based dietary recommendation systems. This research seeks to establish the key factors that affect user trust, attitudes toward information sharing, and user preferences. A questionnaire-based research method is adopted to collect data from the participants, who are asked about their engagement with mobile health applications, their willingness to share information, their level of trust in traditional dietitians, and their perceptions about AI-based dietary recommendation systems. The research results show that how familiar users are with diet application software differs. Trends suggest that familiarity may be linked to how often people use the application. However, this connection is mostly examined through correlation analysis and not backed by more thorough methods like regression. Also, while more frequent application usage seems to relate to greater user trust in AI-based dietary recommendation systems, this conclusion relies on correlation findings, not solid causal evidence. Although the participants showed comfort with information sharing, they showed reluctance in sharing information about their dietary history. The results show that the level of trust in traditional dietitians is relatively high, indicating the significant role played by traditional dietitians in dietary recommendation. The results show that the cost-effectiveness of AI-based dietary recommendation systems is an important motivational factor, with the majority showing unwillingness to adopt AI-based dietary recommendation systems without professional counselling, even if the costs are reduced. Moreover, the results show that the participants show a preference for flexible dietary plans over rigid dietary plans.
Dr. James L. Paglinawan, Jollibe B. Adlawan
The lived experiences of non-language teachers who served as tutors in the Academic Recovery and Accessible Learning (ARAL) Program at several Philippine public secondary schools during the academic year 2025–2026 were explored in this qualitative phenomenological study. The study aimed to comprehend how these teachers embraced, contended with, and carried out their ARAL tasks, drawing on policy instructions that mobilize teachers beyond their areas of expertise to combat continuing reading gaps. In particular, it posed the following questions: (1) Why did non-language instructors agree to serve as ARAL tutors? (2) What difficulties or obstacles did they face? (3) How did they handle these difficulties? And (4) What advice and insights might they give other non-language ARAL tutors? Data were collected using concurrent written open-ended questions and a semi-structured interview guide created by the researcher. Four main themes surfaced: a transformative ethic of care and advocacy, proactive pedagogical and contextual adaptation, multidimensional strain in teaching beyond specialization, and an altruistic–compliant commitment to ARAL. Despite struggling with basic literacy skills, a heavy workload, and a lack of resources, teachers accepted ARAL because of moral obligation and professional expectations. Despite these challenges, they adapted imaginatively, worked with colleagues, and viewed their work as part of fixing a societal reading problem. These results highlight the necessity of providing non-language ARAL tutors with context-sensitive literacy instruction, protected time, suitable locations and resources, and organized teamwork. Additionally, these results offer recommendations for future qualitative research on out-of-field instruction, teacher well-being, and the long-term effects of ARAL on students' and teachers' professional identities.
Dr. James L. Paglinawan, Dr. Marichu A. De Los Reyes
Good school governance is fundamentally about effective principal leadership that establishes appropriate processes, systems, and management mechanisms to ensure the sustainability and continuous improvement of schools. This study investigated the relationship among techno-stress resilience particularly on techno-overload, techno-complexity, techno-insecurity, and techno-uncertainty; fiscal management capability in terms of in financial planning and budget management, resource generation and compliance, monitoring, reporting, and asset management, and stakeholder-involvement, and leadership competence based on adaptability, decision-making practices, planning and implementation, and supportive leadership in shaping the school governance implementation of educational leaders regarding management of policies and programs, partners and donor’s engagement, school compliance with quality standards and technical assistance, focusing on the schools in Region X for the academic year 2025–2026. Findings Revealed that educational leaders demonstrated a very high level of leadership competence and high levels of fiscal management capability and techno-stress resilience. School governance implementation was also rated as highly implemented. Correlation analysis indicated that all correlations were positive and highly significant, with leadership competence emerging as strongest correlate, followed by fiscal management and techno stress resilience. Regression analysis further identified techno‑uncertainty, monitoring, reporting and asset management, stakeholder involvement, decision‑making practices, supportive leadership, adaptability, and planning and implementation as key predictors of school governance implementation, jointly explaining a large proportion of variance.
Andy Ayu Shabila, Candra Ayu, Tajidan Tajidan
Village superior products play an important role in driving the regional economy by optimizing the management of small industries, agriculture, and handicrafts. This study analyzes the competitiveness of village superior products in Gunung Sari District, West Lombok Regency. This type of research is a descriptive, quantitative study involving 16 respondents and using both primary and secondary data. The analysis includes sorting methods, Composite Performance Index (CPI), and Domestic Resource Cost (DRC). The results show the types of village superior products based on the criteria of the number of Small and Medium Industries (SMEs) and production value, the level of competitiveness of village superior products based on five main criteria (number of Small and Medium Industries (SMEs), production value, percentage of local raw material use, percentage of regional and export marketing, and net B/C ratio) in Gunung Sari District, West Lombok Regency, and the competitiveness of village superior products in utilizing domestic resources and having a comparative advantage. Based on the results of sorting the types of village superior products in Gunung Sari District, West Lombok Regency, the agro-industry sector is dominated by agricultural and plantation-based food processing. Ten villages develop food craft products, and six villages develop non-food craft products. Based on the CPI analysis, the priority for developing superior village products is carving wood-cukli products in Midang Village (ranked highest at 3,634.09), berugaq in Taman Sari and Ranjok Villages (2,851.51 and 2,830.75), and palm sugar in Gelangsar Village (1,662.51). The results of the DRC analysis show that three superior village products are highly competitive, with DRC values < 1: palm sugar (0.11), carving wood-cukli (0.32), and berugaq (0.44). These findings indicate that superior village products in Gunung Sari District can efficiently utilize domestic resources and are highly competitive. Therefore, business actors are expected to maintain the efficient use of domestic resources by continuously improving product quality, workforce skills, and the application of appropriate technology, thereby enabling sustainable development and contributing to regional economic growth.
Mostafa Hassan Mohamed El Khayat
This study investigates the profound correlation between political authoritarianism and the creedal foundations promoted by the "Al-Madkhaliyya Al-Jamiyya" current in contemporary Arab societies. While existing literature often views this movement through a purely theological lens, this research argues that it functions as a strategic intellectual framework designed to stabilize despotic regimes. Using a conceptual-analytical approach, the study deconstructs how core creedal concepts—such as "Absolute Obedience" (Sam’ wa Ta’ah) and "The Sanctity of the Ruler"—have been instrumentalized to paralyze political consciousness and dismantle any legitimate resistance. The research reveals that this discourse creates a "creedal shield" that immunizes power from accountability. Finally, the study proposes a revitalized Da’wah methodology that seeks to reclaim the "Objectives of Sharia" (Maqasid) and empower the Muslim mind with a critical, independent perspective, effectively countering the systematic use of religion to sustain oppression.
Christopher Odhiambo, Dr. Janis Marangu, Prof. Lois Musikali
Purpose: This study examined the effect of drug-related crime on community cohesion among residents of Kibra Sub-County, Nairobi County. The study was guided by Social Disorganization Theory, which explains how structural disadvantages such as poverty, overcrowding, and weak social institutions create environments where crime persists and weakens community social bonds. Materials and Methods: The study adopted a convergent mixed-methods research design, combining quantitative and qualitative approaches. The quantitative component used a descriptive survey design, while the qualitative component employed a phenomenological approach to capture residents lived experiences. The target population consisted of 185,777 residents of Kibra, from which a sample size of 396 participants was determined using Yamane’s formula. Data were collected using semi-structured questionnaires and interview guides, with 338 residents participating in the survey and 29 key informants interviewed. Quantitative data were analyzed using SPSS version 26 through descriptive statistics, Pearson correlation, and linear regression analysis, while qualitative data were analyzed using thematic analysis. Findings: The results revealed that drug-related crime significantly affects community cohesion. Correlation analysis showed a weak but statistically significant relationship between drug-related crime and community cohesion (r = -.297, p < .001). Regression analysis further confirmed that drug-related crime significantly predicts community cohesion (F (1,336) = 32.507, p < .001), explaining 8.8% of the variation in community cohesion. Qualitative findings indicated that visible drug selling, youth involvement in drug networks, and the presence of drug hotspots contribute to erosion of trust, fear of retaliation, reduced community participation, and weakened social cooperation. Conclusion: The study concludes that drug-related crime undermines community cohesion in Kibra by weakening trust, reducing social interaction, and disrupting informal social control mechanisms necessary for maintaining neighborhood safety. Recommendations: The study recommends the implementation of integrated community-based drug prevention and control strategies, including dismantling drug hotspots through coordinated law enforcement and expanding rehabilitation.
Dr. Ilenre, A.E, Dr. Tashok, Y. H
This paper investigates the impact of climate change on desertification in Auchi, Edo State, Nigeria. Climate change can be described as the technical term used to denote significant and long-term alterations in the statistical distribution of weather patterns over decades to millions of years. Desertification refers to land degradation in arid, semi-arid, and dry sub-humid areas resulting from climatic variations and human activities. This paper identified the natural and anthropogenic causes of desertification in Auchi, the major climatic indices accelerating desertification in Auchi, the impact of desertification on the environment of Auchi, and the adaptation, and mitigation strategies in place at Auchi, Edo State, Nigeria. To achieve these objectives, the researcher used both primary and secondary research methods to collect the data required for the study. Four hundred (400) respondents which represent 0.16% (zero point one six percent) of the population in the study area were considered. Following the above, four hundred (400) questionnaires were administered in the study area. The preliminary and actual field surveys revealed that there are 25 communities in the study area, and that the population is unevenly distributed across the study area. Following the above observation, the questionnaires were distributed in the various communities in reflection of their population sizes. The data obtained were analysed using tables, graphs and, percentages. The results reveal the natural and anthropogenic causes of desertification in Auchi, the major climatic indices accelerating desertification in Auchi, the impact of desertification on the environment of Auchi, and the adaptation and mitigation strategies in place at Auchi, Edo State, Nigeria. Based on the findings of this paper, the following actionable policy recommendations are made: effective and regular creation and promotion of community environmental education on climate change and desertification, cover cropping, irrigation, afforestation, rotational cropping/grazing, controlled lumbering, law against bush burning, controlled use of wood as fuel, planting of drought resistant crops, artificial recharge of water, enforcement of environmental regulation, adoption of environmental building codes, implementation of green building initiatives, and creation of shelter belt in Auch, Edo State, Nigeria. This paper is therefore, concluded by imploring the governments at all levels to implement the list of recommendations made by the researcher.
Yaling Lin
This study explores the impact of the shift from call auction to continuous trading in the Taiwan stock market's order matching mechanism on investor order placement behavior. The study selects intraday order and transaction data, covering 481 listed companies, and analyzes the data in 30-minute intervals. An "order activity" index, weighted by order quantity and considering price and volume, is constructed to measure order placement strategies under different matching mechanisms. Empirical results show that with shorter matching times, more immediate information disclosure, and increased market transparency, overall investors order activity significantly increases. Individual investors show the most significant increase across all time periods, while institutional investors exhibit higher activity before the market closes. Faster information transmission and improved transaction efficiency encourage investors to adopt more aggressive order placement strategies to increase trading opportunities and react to market information more promptly.
Oguntimehin Abiodun S, Oluwole Toluwalase Gregory
This paper assesses the influence of space optimisation on facility management in Nigerian universities. The rapid increase in student enrolment without equivalent infrastructure development has put significant pressure on existing facilities, leading to overcrowded lecture halls, underutilised spaces, and operational inefficiencies. This paper explores ways to enhance the operational efficiency of Nigerian universities through the effective use of space. It looks at the literature on space utilisation, facility management performance, and optimisation strategies in the context of Nigerian universities. Main results show that space optimisation has a very strong impact on operational efficiency and that efficient space utilisation not only improves service delivery but also helps to reduce congestion and lower maintenance costs. The paper also identifies challenge areas such as unavailability of planning frameworks, lack of accurate utilisation data, short supply of professional expertise, and funding constraints. It suggests strategies to address these challenges including: the use of data driven management systems, the development of institutional policies, the conduct of regular space audits, the capacity building of facility managers, the promotion of flexible space design, and the improvement of funding allocation. This study points out that making the most of available space is a strategic requirement for boosting the performance of facility management in Nigerian universities. Institutions that focus on using space effectively experience superior operational results despite being in resource-constrained environments. These results offer hands-on assistance to university leaders and authorities who want to improve the efficiency of educational infrastructure.
Dr. Eyo, Bassey Ekpe, Dr. Owan, Harold-Joe Eban, Ebe, John Ashiwel
This study explores the impact of spiritual accounting on Value Added Tax (VAT) compliance among small and medium-sized enterprises (SMEs) and informal sector operators in Nigeria. VAT remains a critical source of government revenue, yet compliance levels are persistently low due to evasion, weak enforcement, and limited tax morale. Spiritual accounting, which integrates ethical, moral, and religious values into financial reporting, offers a potential solution by reframing VAT obligations as both legal and moral duties. Using survey data from 200 respondents, the study employed descriptive statistics, correlation analysis, regression, and ANOVA to test six hypotheses. Results indicate that spiritual accounting practices, ethical values, religiosity, and transparency significantly predict VAT compliance, with the regression model explaining 31% of the variance in VAT compliance. Findings confirm that moral responsibility and religious convictions discourage evasion, while transparency fosters trust between businesses and tax authorities. Challenges such as a lack of standardized frameworks and resistance from profit-driven enterprises were noted. The study concludes that integrating spiritual accounting into tax education and compliance strategies can strengthen VAT collection, improve accountability, and enhance fiscal sustainability in Nigeria.
Ahmad Zabadi, Suwandi S. Hardjo
This study is carried out to show the impact of COVID-19 on business performance and resilience characteristics of savings and loan cooperatives during the early stages of the pandemic's declaration in Indonesia. Furthermore, this study focuses on savings and loan cooperatives in the food, batik craft/industry, and tourism clusters. The results show that (1) there are contractive (decreasing) and expansive (increasing) impacts of the pandemic during its early period on the business performance of savings and loan cooperatives in terms of assets, capital, volume, collectability, and profit surplus. (2) Contractive impacts are observed in the tourism and food clusters, while normal-expansive impacts are reported in the batik craft/industry cluster. (3) The resilience response characteristics include uncontrollable and well-controllable cooperatives.
Dr. Mohammad Ishaque, Dr. Mostafa Hassan Mohamed El Khayat, Dr. Rabie Ibrahim Mohamed Hassan
This study investigates the phenomenon of "cognitive dependency" among Arab academics and intellectuals, highlighting what is termed the "Psychology of Domestication" and how the university institution has been transformed into a "conditioning environment" that produces a justificatory elite. The problem centers on the functional shift of the intellectual from a "guardian of values" and producer of free knowledge to a "functional agent" who harnesses methodological tools to legitimize despotism and rationalize injustice under slogans of "stability" and "blocking the means to evil" (Sadd al-Dhara’i
Olamide Emmanuel Ayodele, Olufunke Olupero Ajibade, Temiloluwa Iyanuoluwa Ajibade
Regardless of the growing availability of digital financial technologies, achieving full financial inclusion for Small and Medium Enterprises (SMEs) remains a major challenge in many developing economies, including the North Central States of Nigeria. In response, this study evaluates the factors influencing FinTech adoption by examining the effects of Perceived Ease of Use, Perceived Usefulness, Perceived Security, and Trust on SMEs’ financial inclusion, while also analyzing the moderating roles of Digital Financial Literacy (DFL) and Perceived Regulatory Support (PRS). A purposive sample of 200 SME owners and managers with prior exposure to FinTech services participated in the study. Data were collected using structured questionnaires, and statistical techniques including descriptive analysis, correlation, regression, and PROCESS macro were applied to test the research model. The results indicate that although DFL and regulatory support are valuable elements in the FinTech ecosystem, they do not meaningfully alter the relationship between FinTech adoption and SMEs’ financial inclusion within the study context. Overall, the study confirms that FinTech adoption serves as a strong catalyst for improving access to financial services among SMEs in the region. The outcomes provide practical implications for FinTech providers, regulators, and SME stakeholders, emphasizing the need for user-friendly and secure digital platforms and initiatives that better engage underserved communities. Enhancing these elements can further accelerate financial inclusion efforts across rural and semi-urban areas of the North Central States of Nigeria.
Dr. Shilpa Choudhary
The rapid emergence and global spread of antimicrobial-resistant microorganisms—commonly termed “superbugs”—pose a critical threat to public health, modern medicine, and global economies. This integrated review examines the multidimensional factors driving antimicrobial resistance (AMR), including microbial evolution, misuse and overuse of antibiotics in humans and animals, inadequate infection control, and environmental dissemination of resistance genes. Key pathogens such as MRSA, VRE, CRE, ESBL-producing Enterobacteriaceae, and drug-resistant Mycobacterium tuberculosis are discussed in terms of their epidemiology, mechanisms of resistance, and clinical impact. The review also highlights the role of horizontal gene transfer, mobile genetic elements, and biofilms in accelerating resistance. Current diagnostic challenges, treatment limitations, and the socio-economic implications of AMR are explored. Finally, emerging solutions—including rapid diagnostics, antimicrobial stewardship, novel drug discovery, bacteriophage therapy, probiotics, vaccines, and global policy initiatives—are evaluated. This comprehensive synthesis underscores the urgent need for coordinated global action to control the rise of superbugs and safeguard the effectiveness of existing antimicrobials.
Chanturia, Mineda, PhD
The article examines the role of the Analytical Chemistry course in the formation of professional competencies of future chemistry teachers within a competence-based education framework. Cognitive, activity-based, and motivational components of teacher preparation are analyzed as key elements of professional readiness. Special attention is given to the methodological significance of analytical chemistry, particularly the teaching of analytical methods as a foundation for scientific thinking, research skills, and evidence-based reasoning. To strengthen the conceptual discussion, a case-based empirical approach is incorporated, demonstrating how analytical chemistry instruction supports competency development through real-world environmental analysis tasks. The integrative potential of analytical chemistry in environmental, biological, and educational contexts is highlighted. Analytical chemistry is presented not only as a specialized scientific discipline but also as a universal educational tool that ensures the systematic development of professional competencies and promotes environmental awareness among future teachers.
Affa Rozana Abdul Rashid, Muhammad Nil Yafiq Mohd Yusof, Wan Maisarah Mukhtar
Carboxymethyl cellulose (CMC) is a polysaccharide polymer derived from plant fibrous tissues, while chitosan (CS) is a biopolymer obtained from chitin present in the exoskeletons of crustaceans and insects, as well as fungal cell walls. This study focuses on the synthesis and characterization of CMC, CS, and their composite films (CMC–CS), with emphasis on how material integration influences structural and electrical properties. The films were fabricated using a solution casting technique followed by a triple-cycle freeze-thaw process to enhance structural stability and reduce solubility. Fourier Transform Infrared (FTIR) analysis confirmed successful interaction between the polymers, evidenced by a peak shift to 3346 cm-1 for the CMC-CS composite, indicating strong intermolecular hydrogen bonding between hydroxyl (OH) and amino (NH2) groups. Additionally, the merging of peaks at 1560 cm-1 suggests electrostatic attraction between the anionic carboxylate groups of CMC and the cationic amino groups of CS. This interaction contributes to improved compatibility and structural integrity of the composite films. Electrical characterization demonstrated that the CMC-CS composite films exhibited the highest electrical conductivity, with conductivity increasing linearly as a function of applied current. In contrast, pure CMC showed the highest resistivity. The enhanced electrical performance of the composite is attributed to synergistic interaction between CMC and CS, which facilitate more efficient charge transport pathways. Overall, the findings indicate that CMC–CS composite films possess promising potential for applications in conductive biopolymer systems, particularly in environmentally friendly and flexible electronic materials.
Deeraj Saini, Shivam Kashyap
Sustainable catalysis has become an essential strategy in modern chemical science due to growing environmental concerns, increasing industrial demand, and the necessity for efficient chemical transformations. Transition metal complexes are among the most widely used catalysts because of their variable oxidation states, flexible coordination environments, and strong catalytic activity. These properties allow transition metals to facilitate a wide variety of reactions such as hydrogenation, oxidation, and carbon–carbon bond formation. In the framework of green chemistry, catalytic systems based on transition metals help reduce waste generation, improve reaction efficiency, and minimize energy consumption. The development of environmentally friendly catalytic systems is an important goal for modern chemical industries. This research paper reviews the role of transition metal complexes in sustainable catalysis, focusing on their structure, properties, reaction mechanisms, and industrial applications. Additionally, the paper discusses challenges and future directions including the use of computational chemistry and artificial intelligence in catalyst discovery. Sustainable catalysis has emerged as a cornerstone of green chemistry, aiming to minimize environmental impact while maximizing efficiency in chemical processes. Transition metal complexes play a pivotal role in achieving these goals due to their unique electronic configurations, tunable coordination environments, and high catalytic activity. This paper explores the application of transition metal complexes in sustainable catalysis, emphasizing atom economy, waste prevention, energy efficiency, and the use of environmentally benign solvents. Key catalytic systems, including palladium, ruthenium, iron, and copper complexes, are discussed in the context of industrially relevant transformations such as cross-coupling reactions, hydrogenation, and oxidation. Recent advancements in ligand design, recyclable catalysts, and heterogeneous catalysis are also highlighted. The study demonstrates that transition metal-based catalysis significantly contributes to greener chemical processes and offers promising pathways toward sustainable industrial chemistry. Transition metal complexes play a vital role in modern catalysis due to their unique ability the Facilitate a wide range of chemical transformations with high efficiency, selectivity, and Sustainability. This study explores the fundamental mechanisms by which transition metal Complexes function as catalysts and highlights their extensive industrial applications. The catalytic Activity of these complexes arises from the variable oxidation states, coordination geometries, and Electronic properties of transition metals, which enable them to activate substrates and stabilize Reactive intermediates during chemical reactions. Mechanistic pathways such as oxidative Addition, reductive elimination, insertion, and ligand exchange are central to the catalytic cycles of Many metal-based systems. Well-known examples include palladium-catalyzed cross-coupling Reactions, rhodium- and ruthenium-based hydrogenation and hydroformylation, and vanadium or Molybdenum complexes used in oxidation reactions. These reactions are foundational in the Synthesis of pharmaceuticals, polymers, agrochemicals, and fine chemicals. From an industrial Perspective, transition metal catalysts contribute significantly to green chemistry by reducing Energy consumption, minimizing waste, and improving atom economy. Homogeneous and Heterogeneous catalytic systems utilizing metals such as nickel, cobalt, platinum, and copper have Revolutionized large-scale processes like petroleum refining, ammonia synthesis, and polymer Production. This paper emphasizes the importance of understanding catalytic mechanisms at the Molecular level to design more efficient and environmentally friendly catalysts. Continued research In this area holds promise for the development of novel catalytic systems tailored to meet the Demands of sustainable chemical manufacturing and energy transformation.
Maria Cristina S. Dela Cerna, Rose Ann W. Prado
This study examined the level of school safety and its influencing factors within the school community of Bangsud Integrated School, Tago, Surigao del Sur. Specifically, it determined the profile of respondents in terms of years in service, educational background, relevant trainings attended, and level of School-Based Management (SBM), and assessed their perception of school safety across five dimensions: emotional safety, physical safety, bullying and cyberbullying, substance use, and emergency readiness. The study employed a quantitative descriptive research design and utilized a researcher-made questionnaire administered to 140 respondents, including teachers, school heads, and stakeholders. Data were analyzed using frequency count, percentage, and weighted mean.
Jayashree MK, Karan S, Manan Jain, Manish, Manisha Kunwar, Praveen Kumar K
Unemployment is a serious social and economic issue that affects people and society in many ways. It goes beyond just losing income; it also harms mental health, physical well-being, social connections, and economic security. This paper looks at various research studies to explore the broad effects of unemployment from psychological, medical, social, and economic angles. The findings show that unemployment is closely linked to higher levels of stress, depression, anxiety, and emotional instability. It also leads to physical health issues like heart disease and weakened immunity. Additionally, unemployment is associated with increased substance abuse as individuals turn to unhealthy coping methods. The study points out that unemployment results in loss of identity, decreased social involvement, and economic problems. In developing countries like India, issues such as population growth, skill mismatches, and limited industrial development make the situation worse. Overall, the paper stresses that unemployment must be addressed as a complex issue that needs combined solutions like creating jobs, developing skills, supporting mental health, and implementing effective policies. Furthermore, this study reveals a cycle between unemployment and its effects. Psychological stress, poor health, and substance abuse lower a person's chances of getting a job again. This cycle harms both personal well-being and the productivity of society. The paper also underscores the need for early intervention strategies, such as career guidance, vocational training, and awareness programs to boost employability. Strengthening the link between education and job market needs can help close skill gaps and provide better job prospects. By offering a clearer understanding of unemployment and its connected effects, this study helps shape more effective and lasting solutions aimed at improving people's quality of life and fostering economic growth.
Cherise Joy B. Equipado, James L. Paglinawan, PhD
This research investigates the complex and challenges faced by untrained mathematics teachers when handling learners with special educational needs within mainstream classrooms, specifically under the Philippine MATATAG curriculum framework. As the Philippine educational landscape shifts toward total inclusivity mandated by Republic Act No. 11650, general education teachers are increasingly tasked with instructing learners with disabilities in regular settings despite lacking specialized Special Education (SPED) training. Utilizing a qualitative phenomenological descriptive approach, the study explored the lived experiences of fifteen teacher-respondents at Bukidnon Faith Christian School, Inc. to identify specific pedagogical, emotional, and institutional barriers preventing effective educational inclusion. Key findings reveal that educators encounter significant barriers in pedagogical adaptation, specifically struggling to balance the rigorous, stepby-step instruction of the standard curriculum with the simplified, individualized support required by students with special needs to grasp abstract concepts. Furthermore, a chronic lack of specialized manipulatives and curriculum-aligned tools forces teachers to spend extra hours creating personalized resources, leading to persistent feelings of stress, frustration, exhaustion, and inadequacy. Despite these, professional challenges simultaneously foster resilience, creativity, and increased patience among staff. The study concludes that the mainstream setting risks becoming an environment of "exclusion within inclusion" due to these systemic gaps and the absence of institutional support systems. Recommendations include mandatory professional development workshops, the provision of specialized instructional tools, and improved collaboration between teachers, parents, and special education specialists to alleviate the administrative and emotional burden on regular educators. Ultimately, targeted institutional changes are required to ensure the educational needs of all learners are equitably met in an inclusive environment. By addressing these systemic gaps, schools can better support both teachers and learners in a mainstreamed environment.
Enemchukwu Onyinye Victory, Enemuo Emeka H., Enemuo Ijeoma C., Mbamalu Delight C., Okafor Henry, Udonna-Ogbue Faith A.
There is increasing concern over body image dissatisfaction, unhealthy dietary patterns, and sedentary lifestyles among university students despite the growing emphasis on fitness and wellness. This study investigated variations in somatotypes among young adults in the College of Health Sciences, Nnewi. Somatotype classifications which categorize individuals based on their physical build into three primary types- ectomorph, mesomorph and endomorph provide valuable insights into body composition and health. A cross-sectional survey design was adopted, involving structured questionnaires and anthropometric assessments of 400 students aged 18–25 years. The mean age of participants was 20.71 years, with a female predominance (56.00%). Results revealed significant gender-based differences in anthropometric indices. Male participants exhibited higher mean values in weight (75.50 kg), height (178.21 cm), waist width (80.93 cm), and hip circumference (96.86 cm) compared to females (p < 0.05). Somatotype analysis showed that 68.75% of respondents displayed endomorphy, 42.50% mesomorphy and 50.00% ectomorphy, indicating a predominance of balanced body types within the population. Males were significantly more mesomorphic (6.00) than females (3.60), while females exhibited higher endomorphic (4.30) and ectomorphic (2.90) components (p < 0.05). These findings highlight notable gender-related variations in somatotype distribution and underline the influence of lifestyle, and diet, on body composition and self-perception.
Raja Singh, Ravindra Chauhan, Vaibhav Sharma, Yash Choudhary
Heart disease is one of the leading factors of death in whole world. Yet, predicting it early remains a huge setback. Doctors face two main problems in hospitals: patient files usually contain empty fields and complex AI models act like black boxes, making them hard to trust for users. VitalPath AI is designed to solve these issues in efficient and reliable manner. First, we tackle data gaps using the MICE algorithm. This lets us fill in missing patient details without throwing away valuable data. Next, we use SMOTE to balance the dataset classes and level the playing field, ensuring the model learns fairly and prevents any model from generating biased outcomes. Instead of just guessing settings, we used Bayesian Optimization to hunt down the optimal configurations for several machine learning models. When evaluated on the UCI Heart Disease dataset, AdaBoost came out on top by ending up attaining an AUC-ROC score of 0.963. This performance metrics surpassed what we originally hoped for, though accuracy alone isn't the only objective for this work to accomplish. To make the model easy for doctors to trust, we need transparency. That’s why we integrated SHAP, which breaks down exactly why each prediction was made, letting doctors and patients see if factors like cholesterol or chest pain drove the decision.