20 Articles
Emmanuel Bamidele Ajulo, Qayyum Adekunle Tiamiyu
Football stands as the world's most popular sport, captivating billions globally. The English Premier League, in particular, is widely regarded as the pinnacle of professional football, boasting immense global viewership and attracting widespread interest. Its dynamic and unpredictable nature fuels a massive industry built around match analysis, reflecting the deep desire to anticipate match outcomes. Early attempts at football match prediction often relied on static historical data, assumed independence among events, failed to adapt quickly to football's rapid evolution, and lacked the capacity to capture complex nonlinear interactions among multiple features. This study develops a machine learning model for football match analysis in the English Premier League to predict match outcomes, addressing gaps in previous models by using ensemble machine learning algorithms to provide timely, accurate, and real-time analysis. The study utilised Random Forest (RF), XGBoost, and LightGBM. Performance evaluation using standard classification metrics, including Accuracy, Precision, Recall, F1-Score, and ROC-AUC, showed that Random Forest achieved the best overall performance, with an accuracy of 87.14% and an ROC-AUC of 99.00%. The ensemble model further enhanced prediction consistency by combining the strengths of the three machine learning models. This study demonstrates the effectiveness of machine learning for match predictions and, from an industry perspective, offers practical recommendations for football to enhance retention, efficiency, and competitiveness.
Aditi Kaushik, Sanjay Kaushik
Claims that blindfolded youngsters can identify items, read text, or describe images are widely promoted in educational and commercial programs, which are commonly referred to as "midbrain activation" or intuition training. Proponents of these programs frequently interpret such examples as proof of extrasensory perception (ESP), nonverbal cognition, or enhanced intuitive ability. However, these ideas are unsupported by actual evidence and contradict well-established sensory neuroscience principles. Recent research in vision science, cognitive psychology, and neuroimaging suggests that even severely degraded visual input can be sufficient for object recognition when paired with predictive coding and memory-based template matching. Peripheral vision and low-resolution retinal input, which are frequently disregarded in lay explanations, provide partial information that the brain can use for shape, contour, and color processing. Furthermore, top-down modulation from the prefrontal, orbitofrontal, and parietal cortex aids in the reconstruction of missing information, allowing for quick perceptual inference from partial sensory data. Furthermore, cognitive and social factors such as ideomotor effects, attentional bias, expectancy, and reinforcement can exaggerate perceived task accuracy, creating the appearance of exceptional ability. In this study, we investigate these assertions using a rigorous neuroscientific approach. We propose a mechanistic model that incorporates low-level visual leakage, coarse peripheral cue extraction, predictive coding, and memory-driven template matching into the ventral visual stream. We highlight the functions of V1-V4, the inferotemporal cortex, the lateral occipital cortex, and higher-order top-down networks in reconstructing object identity from degraded or incomplete sensory input. By mapping these brain and cognitive processes, we provide a holistic framework for explaining actions that are frequently misattributed to non-visual or psychic powers, highlighting the value of controlled experimental paradigms and evidence-based evaluation in educational and training settings.
Abeki, J.P., A, Adedokun, I.O, Alkali, A, Bunonyo, Y. T, Udensi, E. E
The geophysical interpretation of Aeromagnetic data over the study area bounded by longitude 4°00′–5°00′ and latitude 5°30′–6°30′ provides crucial insights into the subsurface geological configuration, with significant implications for hydrocarbon exploration. Reduced-to-Equator (RTE) map reveals magnetic values ranging from 32,869.16 nT to 33,037 nT, reflecting the influence of subsurface lithology and tectonic structures. High magnetic intensities in the East–central and South Western part of the map, often correlate with the presence of ferromagnetic minerals, such as magnetite-rich mafic and ultramafic rocks, suggesting potential igneous intrusions or lithological boundaries, the lower magnetic zones, illustrated in blue west–central part of the map, indicate nonmagnetic sedimentary units, deep basement rocks, or zones of weathering and alteration. The high magnetic intensity closures observed within the basin are likely associated with the underlying basement rocks or with igneous intrusions that may have penetrated the sedimentary sequence. Depth estimation techniques such as Euler Deconvolution utilize a structural index (SI = 1) to delineate linear geological features like faults and dykes, with clustered solutions indicating complex basement architecture. Source Parameter Imaging (SPI) analysis estimates source depths exceeding 3.0 km, confirming the presence of thick sedimentary basins critical for hydrocarbon maturation. Spectral analysis indicates basement depths between 8.7 and 11.6 km, with deeper zones concentrated centrally and southeast part, aligning with potential depocenters. The First Vertical Derivative (FVD) map indicates the passage of the paleo-fracture zone through the area. This is also indicated in the discontinuity shown in the Total Magnetic Intensity (TMI) map. These datasets improve the geological interpretation of the region, reveal structurally controlled sedimentary basins, and help outline prospective zones for hydrocarbon exploration and development within the Niger Delta.
D.N.S.Perera, Y.A.A.Kumarayapa
Paddy cultivation is vital for Sri Lanka’s food security, but increasing plant diseases due to adverse climate, declining soil health, irregular water availability, and unpredictable weather have caused a continuous drop in yield, highlighting the need for effective disease detection. This study presents an integrated paddy disease detection system that combines Internet of Things based environmental sensing with drone-based remotesensing imagery and artificial intelligence techniques. The proposed system employs an ESP32 microcontroller interfaced with more accurate sensors to monitor soil, water, and agro-climatic parameters in real time. Machine learning models are applied to analyze the collected sensor data and predict potential paddy diseases based on environmental conditions. In parallel, a drone imaging system captures high-resolution images of paddy fields, which are processed using deep learning models developed with Keras and TensorFlow to detect and classify disease symptoms. A Flask-based web application is developed to visualize sensor data, display disease predictions, and provide actionable recommendations for farmers and agricultural officers. Experimental results demonstrate that the proposed system achieves an overall disease detection accuracy of 98%, with additional evaluation using precision, recall, F1-score, and confusion matrix analysis confirming its robustness and reliability. The practicality of the proposed system is enhanced by its low cost, portability, and modular design, enabling easy deployment in small and large paddy fields and allowing scalability to regional and national agricultural monitoring systems.
Bhargavi Rajarathinam, Imbaasree Rajavelu
Hepatocellular carcinoma (HCC) is a highly aggressive cancer associated with chronic liver diseases, posing significant treatment challenges. This study explores the apoptotic potential of ethanolic leaf extracts from Plectranthus amboinicus and Hibiscus rosa-sinensis on HepG2 cell lines, aiming to elucidate their mechanisms of action and comparative efficacy. Both extracts underwent phytochemical analysis, antioxidant activity assessment using the DPPH assay, and safety evaluation through haemolytic activity determination. Apoptosis was visualized using acridine orange/ethidium bromide dual staining and quantified with propidium iodide/annexin V-FITC staining and flow cytometry. The regulation of key apoptotic genes, BAX and BCL-2, was analysed in treated HepG2 cells. Preliminary results indicate that both extracts exhibit significant antioxidant activity, with P. amboinicus demonstrating robust effects and a favourable safety profile. In contrast, H. rosasinensis showed increased cytotoxicity, raising concerns regarding its therapeutic application. This comparative analysis highlights the potential of P. amboinicus as a promising candidate for novel HCC therapeutic strategies, while underscoring the need for further investigation into the apoptotic mechanisms and safety of H. rosasinensis. The P. amboinicus extract effectively induces apoptosis in HepG2 cells by modulating the expression of key apoptosis regulators, BAX and BCL-2, without significant haemolytic toxicity at lower concentrations. These findings provide a strong foundation for further research into the therapeutic applications of P. amboinicus in liver cancer treatment.
Angel M. Bontilao-Gayrama, Monera A. Salic-Hairulla
The study aimed to develop and validate a professional training manual integrating Pedagogical Content Knowledge (PCK) and Science, Technology, Engineering, and Mathematics (STEM) education teaching approach (PCK+STEM) to enhance the instructional competence of public school Biology teachers in Iligan City. Guided by the ADDIE model-Analyze, Design, Develop, Implement, and Evaluate. The study employed a mixed-method research design, integrating both quantitative and qualitative approaches to systematically develop and comprehensively evaluate the training manual. The manual was conceptualized based on the identified needs of Biology educators and encompasses the topics of 1st quarter of Grade 9 Science following the essential domains of PCK and seven (7) stages of STEM Education by Sutaphan & Yuenyong, (2019). The validation process involved six PhD experts specializing in STEM and PCK education who evaluated the manual’s content, structure, and instructional coherence. Quantitative data were collected using a validated instrument across the domains of Analyze, Design, and Development, while qualitative feedback was gathered from open-ended expert comments to improve clarity, relevance, and usability. The evaluation results revealed that the training design manual achieved overall “Excellent” quality, with a grand mean of 3.53. These findings indicate that the training manual meets expert expectations in terms of pedagogical soundness, content validity, and practical applicability for teacher training. Moreover, the training manual serves as a validated resource for professional development programs in promoting Biology teachers’ integrated understanding of disciplinary knowledge, pedagogy, and STEM-based instruction. It is recommended to implement and assess the manual’s effectiveness in actual teacher training and classroom settings, focusing on its impact on teachers’ PCK enhancement and students’ engagement and achievement in Biology.
Genelyn R. Baluyos, Jaycee C. Yulo, Merlie M. Ayop
This action research focused on improving Labo National High School’s Grade 10 students’ critical thinking skills in Statistics and Probability using board games during the 2024–2025 school year. Engaging students in more active and critical thinking in mathematics is needed for data interpretation and decision making. However, many traditional methods of teaching fail to capture students’ active participation and critical thinking. This investigation utilized a quasi-experimental framework and comprised two sets of participants: one set practiced critical thinking using board games, while the other received traditional instruction. Each set of participants underwent assessments before and after the intervention. Outcomes indicated that, while students in all groups made improvements to their critical thinking skills, the group that instruction included board games made more significant gains and participated more actively. The use of board games was observed to enhance student motivation, teamwork, and problem-solving skills. In light of these findings, it can be concluded that board games can promote students’ analytical thinking and understanding of more complex statistical concepts. Engaging students using board games into the mathematics curriculum is recommended to promote critical thinking. Learning through games is less monotonous and more meaningful. The provision of resources and materials needed for this effort should come from the school administration.
Dr. J. Abiraami
Literary studies have undergone significant epistemic transformations over the past century, moving beyond aesthetic appreciation towards interdisciplinary, politically conscious, and culturally grounded modes of inquiry. This paper examines the epistemic shifts within literary studies with special reference to Indian literary texts, aligning with contemporary academic expectations in UGC and Scopus-indexed journals. By incorporating case studies from Indian English and regional literature—particularly the works of Mahasweta Devi, Arundhati Roy, and Bama—the paper demonstrates how literary knowledge production has evolved to foreground marginal voices, challenge canonical authority, and interrogate power structures. The study argues that present-generation literary scholarship is marked by ethical engagement, cultural specificity, and social responsibility, reflecting a decisive departure from Eurocentric and purely formalist paradigms.
Irene A. Estrada, Sulpecia L. Ponce
This paper is an examination of the gender-based needs of the displaced Maranao families affected by the 2017 Marawi Siege who are still in Iligan City at the time of the survey in March to July 2019. This study included 144 internally displaced people (IDPs) residing in unrecognized evacuation centers, renting, or staying with relatives. Findings show that the IDPs suffered from the collateral damage of war, living in extreme poverty due to the absence of livelihood opportunities. To survive, they resorted to reducing their food intake, borrowing from relatives, or sending their children to live with relatives. Some Meranao children are seen doing child labor, a sight not seen prior to the siege. They were not prioritized for support and services, as they are staying in spaces defined by the government as private areas. Regardless of gender and age, the IDPs generally need shelter, livelihood assistance, food, and health care to bounce back. They need a sustainable, culture-sensitive intervention program to aid their recovery.
M. M. Kasdekar, P. N. Chikhalkar, Y. K. Mawale
Lonar Crater Lake (19°58′N, 76°31′E) is a ~52 ka meteorite impact structure developed within the Deccan Traps basaltic province and represents an important natural archive for understanding crater-lake hydrology and geomorphic evolution. This study investigates short-term morphometric and hydrological variations in Lonar Crater Lake during the period 2019–2024, with particular emphasis on the role of rainfall variability and groundwater dynamics. Lake boundaries and morphometric parameters were extracted using high-resolution Google Earth Pro satellite imagery, while rainfall data for 2018 and 2023 were obtained from the Maharashtra Rainfall Monitoring Portal. Standard limnological indices, including Depth Ratio (Rz), Relative Depth (Zr), Shoreline Development Index (DSI), and Index of Basin Permanence (IBP), were calculated following established morphometric methodologies.
Hyeladzira Garba Mshelia, Maryam Musa Machina, Musa Adamu Machina
Armed conflict is one of the major challenges of today and in most of the time, the construction sector is the second most affected area after human lives with economic impact of losses incurred in the sector always mirrored in the perspective of fixing back the wreckages in their original forms, rather than fixing back their improved and more secured versions. The study bridges this crucial gap with a new valuation order in which it surveyed, identified and enumerated all public buildings destroyed during Boko Haram insurgency in Borno state and, using ‘enhanced bottom-up’ method of costing violence, designed and evaluated their improved and more secured versions for reconstruction. It is expected to serve as a blueprint for policy formation. Field information for the study were sourced through physical inspection of destruction sites and the use of self-administered questionnaires. Analysis indicated that, public buildings destroyed during Boko Haram insurgency in Borno State require the sum of N3, 614,653,400,000.00 to be replaced with their improved and more secured versions. It is concluded that this amount could have been curtailed with the provision of enhanced community-based custody and security to the buildings. Recommendations therefore include among others, the formal entrustment of every community with security affairs of all public buildings in their jurisdictional areas and the provision of security personnel to assist the communities in security strategies.
Darnetty, Jumsu Trisno, Rahmad Faizan
Neoscytalidium dimidiatum fungus is the cause of stem cancer disease on dragon fruit plant. This disease is a major disease of dragon fruit plants that is economically detrimental. The use of Saccharomyces cerevisiae is an environmentally friendly control alternative. This study aimed to determine the potential of S. cerevisiae in suppressing the growth of N. dimidiatum which causes dragon fruit vine cancer. The antagonistic tests of S. cerevisiae against N. dimidiatum were carried out in vitro and in vivo. The experimental design used in this research was a Completely Randomized Design (CRD) with 4 treatments and 6 replications. The treatments consisted of several different inoculation time of S. cerevisiae namely A (S. cerevisiae was inoculated 2 days after N. dimidiatum inoculation), B (S. cerevisiae was inoculated simultaneously with N. dimidiatum inoculation), C (S. cerevisiae was inoculated 2 days before N. dimidiatum inoculation) and D ( Control, without S. cerevisiae). The results of the research showed that treatment B (application of S. cerevisiae simultaneously with inoculation of N. dimidiatum ) and C (application of S. cerevisiae 2 days before inoculation of N. dimidiatum inoculation) inhibited the growth of N. dimidiatum in vitro and in vivo. The best treatment was C (the inoculation of S. cerevisiae 2 days before inoculation of N. dimidiatum with the persentage of inhibition by 57.8% and 87.88%. respectively.
D. K. Monday, N. F. Micah, O. Adeyanju, Q. J. Mawak, S. Tanko
Phytochemical screening and antimicrobial activities of aqueous and ethanol leave extract of U. chamae, were studied using paper disc diffusion method against Streptococcus pyogen, Escherichia coli and Salmonella thypi. The results of the antimicrobial studies indicated that the extracts inhibited the growth of one or more tested pathogens. The ethanolic extract showed a broad spectrum of antimicrobial activity. Phytochemical investigation revealed the presence of tannins, alkaloids, glycosides, flavonoids, carbohydrates and terpenes. Anthraquinone and glycoside were not present. Inhibition zone by the extracts ranges from 6.0 mm to 29 mm. The Minimum Inhibitory concentration (MIC) ranges from 100 mg/mL to 6.25 mg/mL. Uvaria chamae leave may be able to produce antimicrobial agents in drug delivery.
Md Azmal Hossain, Zubair Mustahid
Non-communicable diseases (NCDs) are chronic and often progressive disorders that pose a major burden on global health systems. Long-term conventional management may be limited by adverse effects, polypharmacy, adherence challenges, and impaired quality of life. Homeopathy, developed by Samuel Hahnemann (1755– 1843), is widely used as a complementary modality and emphasizes individualized treatment and the principle of similitude. This review summarizes foundational homeopathic concepts relevant to chronic disease management and outlines current hypotheses proposed to explain homeopathic effects, including nanoparticlebased models and immunomodulatory mechanisms. Three illustrative clinical cases are presented, including an ovarian mass and two malignancies, each with baseline investigations and long-term follow-up. While these cases demonstrate sustained symptomatic improvement over extended periods, robust evidence requires welldesigned prospective studies using standardized outcomes and transparent reporting.
I. C. Eli, Jephter J. Dika
This paper presents a comprehensive sensitivity and threshold analysis of the basic reproduction number (R₀) for a deterministic model describing the transmission dynamics of Lassa fever between human and rodent populations. The next-generation matrix approach is employed to derive an explicit expression for R₀, which quantifies the average number of secondary infections generated by a single infectious individual in a fully susceptible population. Analytical differentiation of R₀ with respect to each model parameter yields normalized forward-sensitivity indices that measure the relative contribution of epidemiological and demographic parameters to disease transmission. The results indicate that transmission rates between humans and rodents (βHV and βVH) and population recruitment rates (ΛH and ΛV) exert the most positive influence on R₀, while the recovery rate (γH) and natural mortality of rodents (μV) produce the strongest negative effects. Threshold analysis further reveals that when R₀ < 1, the disease-free equilibrium is locally asymptotically stable, whereas for R₀ > 1, an endemic equilibrium emerges. These findings highlight that targeted interventions such as enhancing recovery through medical treatment and reducing human rodent contact are the most effective strategies for lowering R₀ below unity and achieving disease eradication.
Dr Devidutta Maurya
The present study reports a comprehensive theoretical investigation of the molecular structure, electronic distribution, and spectroscopic properties of molecule 1CVY (C₃₁H₄₂O₅) using Density Functional Theory (DFT). Geometry optimization was carried out to obtain the most stable molecular conformation, and the optimized structural parameters, including bond lengths, bond angles, and dihedral angles, were analyzed in detail. The electronic properties of the molecule were explored through frontier molecular orbital analysis, providing insight into the HOMO–LUMO energy gap, charge distribution, and chemical reactivity. Molecular electrostatic potential (MEP) mapping was employed to identify potential electrophilic and nucleophilic sites within the molecule. Vibrational frequency calculations were performed to simulate the infrared (IR) spectrum, and all computed frequencies confirmed the stability of the optimized structure with no imaginary modes. The theoretical IR assignments were correlated with characteristic functional group vibrations. The results highlight the relationship between molecular geometry, electronic structure, and spectroscopic behavior of 1CVY, offering valuable insight into its physicochemical properties. This DFT-based study provides a reliable theoretical framework for further experimental investigations and potential applications of the molecule in molecular recognition and related fields.
Allan Mufumbiro
The rise of the gig economy which is characterized by short-term, platform-mediated work which includes but not limited to ride-hailing, food delivery, online freelancing, transportation, domestic services, and micro-tasking has transformed Uganda’s labour market. Yet, existing laws on employment, social protection, digital platforms, consumer protection, and taxation were designed for traditional employment relationships and therefore struggle to regulate this new digital labour employment. This review examines the regulatory gaps, institutional challenges, and enforcement limitations affecting Uganda’s ability to govern gig work. Using labour law theory, platform governance theory, and regulatory compliance frameworks, the study highlights contradictions in worker classification, weak social security coverage, limited tax enforcement, consumer risks, and gaps in data protection. Case studies from ride- hailing, digital freelancing, and delivery platforms illustrate persistent issues of misclassification, power asymmetries, algorithmic control, and contractual opacity. The review concludes by recommending a hybrid regulatory model incorporating clarifications in worker status, portable benefits, digital platform obligations, and strengthened enforcement systems to ensure fairness, innovation, and sustainable digital labour markets in Uganda.
Arturo B. Cunanan, Lucy M. Blanco, Marvin M. Abreu, Mary Jane F. Somao-I
This paper presents a conceptual and theoretical framework for an integrated school safety system designed to address persistent safety and accountability challenges in Philippine public schools. The situation regarding students' safety in Philippine public schools has raised issues that are difficult to overlook, as they persist and remain unaddressed. Among other incidents, there have been problems with students getting in and out of the school without proper authorization, violent actions being taken, and even the attendance of students being managed inefficaciously by the administration because of poor monitoring. The manual systems currently in place struggle with errors; they're mainly reactive and mostly isolated from a wider accountability of the institutions. The present paper proposes a theoretical framework for an integrated campus access and attendance management system. The framework is based on the Sociotechnical Systems Theory, Ecological Systems Theory, Technology Acceptance Model (TAM), and Agile-SCRUM implementation principles. Combining these perspectives results in a multidimensional model that considers school safety not merely as a tech add-on but as a co-produced sociotechnical process that is at the heart of the educational ecosystem, not outside it. The paper presents an argument for transforming school safety and accountability into a holistic approach, where inclusivity, transparency, gender responsiveness, and ethical data governance serve as guiding principles. The framework is in sync with the Sustainable Development Goals (SDGs 4, 9, and 16) and national digital transformation policies. The theoretical design proposed here is a replicable and scalable model for resource-poor educational contexts, thus contributing to the discourse on technology in education, governance, and human security.
Hajar Dewantara, Muhammad Rakib, Muhammad Rizky Fahrezi
This study aims to determine the effect of service robot utilization on the competitiveness of culinary businesses at Okinawa Sushi Trans Studio Mall (TSM) Makassar. Independent variables are service speed, service reliability, comfort and safety, and innovative value, the dependent variable is business competitiveness. The study used a quantitative associative approach with accidental sampling, involving customers who were incidentally encountered during fieldwork. A total of 98 respondents which has been served directly by a robot waiter. Validity, reliability, classical assumptions, multiple linear regression, and hypothesis tests were conducted on data collected through a Likert scale questionnaire. The study results show that service speed and service reliability have no significant effect on business competitiveness, while comfort and safety and innovative value have a positive and significant effect. Simultaneously, the four variables significantly affect business competitiveness. These findings suggest that service robots improve competitiveness mainly by enhancing comfort, safety, and innovation, strengthening Okinawa Sushi TSM Makassar’s competitive position.
Krishtel Joyce C. Clenuar, Rn
Purpose of the Study: This study explored the lived experiences of Filipino pediatric palliative care nurses working at the New Hope Foundation in China. It sought to understand how these nurses deliver holistic care to terminally ill children while managing emotional strain, ethical dilemmas, and cultural challenges in a multicultural setting. Research Method: A qualitative phenomenological approach was employed, using semi-structured interviews with six purposively selected nurses. Colizzi’s method guided the data analysis process.