University of the City of Manila

Abstract Background: Schistosomiasis has long been endemic in South Cotabato. Fourteen barangays in Koronadal City and Tantangan, covering over 82,000 people at risk, had received more than a decade of mass drug administration with praziquantel when a focal prevalence survey was conducted in 2016. The survey aimed to update local prevalence estimates, document other helminth infections, and assess the Kato–Katz technique. National data since then have shown declining prevalence in many endemic areas, although persistent animal reservoirs continue to be reported. As the Department of Health pursues transmission interruption by 2025, reporting the 2016 findings remains important for assessing progress and guiding elimination strategies. Methods: Individuals aged 5-65 years from households selected through stratified cluster sampling were invited to submit stool specimens. Local medical technologists were recruited and trained to conduct parasitologic assessment using Kato-katz technique. Each specimen from the 4,387 samples (2,344 from Koronadal and 2,043 from Tantangan) was tested for the presence of Schistosoma japonicum , soil-transmitted helminths, and other intestinal parasite ova. The sensitivity of the field testing was determined through validation of the slides by reference microscopists of the College of Public Health/National Institutes of Health, University of the Philippines Manila. Results: No schistosomiasis cases were detected in Koronadal City. In Tantangan, nine cases were identified in four barangays, corresponding to a prevalence of 3.6 per 1,000 population (95% CI: 1.7–7.8 per 1,000). After adjustment for sampling weights and non-response, the combined prevalence for both municipalities was 0.098%. One barangay, New Lambunao (1.87%), exceeded the <1% near-elimination threshold. Eight infections were of light intensity and one was moderate; no heavy-intensity infections were detected. Soil-transmitted helminths were also identified, with Ascaris lumbricoides (7.29%) being most prevalent. Validation showed high specificity (>98%) and sensitivity of 88.9% for schistosomiasis. Conclusion: The 2016 focal survey demonstrated very low schistosomiasis prevalence in South Cotabato following long-term MDT, with most endemic barangays meeting the <1% near-elimination threshold. However, given the limitations of Kato–Katz in low-intensity settings and the potential influence of post-treatment timing on egg detection, updated focal surveys incorporating more sensitive diagnostic tools are recommended. Strengthened surveillance, integrated helminth control, and a One Health approach will be essential to verify transmission status and guide decisions on sustaining or modifying MDA as the country works toward its 2025 elimination goal.

The continuous advancement of educational technologies has led to the development of innovative academic tools aimed at enhancing assessment methods and student performance analysis. This study introduces the Decision-Based Grading Model System and Student Performance Analysis Using Rule-Based Algorithm, a system designed to modernize the grading process and provide tailored academic support. The system features a flexible grading simulator that allows educators to set minimum passing scores based on predefined parameters such as course requirements, learning outcomes, and institutional policies. It also integrates a rule-based recommendation system that suggests appropriate learning materials and assessments for students who require remediation. The study utilized both qualitative and quantitative approaches, involving expert validation, user feedback, and system evaluation through the ISO/IEC 25010 Software Quality Model. Results show high levels of effectiveness in functionality, performance efficiency, usability, reliability, security, maintainability, and portability. Additionally, accuracy metrics revealed 80% precision, 89% recall, and an F1-score of 84% for the recommendation system, confirming its capacity to deliver relevant interventions. The system promotes academic transparency, reduces manual workload, and aligns grading and assessment strategies with actual student needs. Overall, the study contributes to the evolving landscape of educational technology by offering a dynamic, data-driven approach to academic management.

In today's hypercompetitive and rapidly changing business environment, organizations are increasingly turning to advanced technologies to maintain and enhance their market positions. Business intelligence (BI) systems have long been central to corporate strategy by providing data-driven insights. Recently, the integration of artificial intelligence (AI) into BI has heralded a new era of predictive analytics, enabling organizations to forecast market trends with unprecedented precision and agility. While the promise of AI-driven BI is substantial, its effective implementation requires a confluence of technological prowess, human capital development, and supportive organizational culture. Executives must navigate the challenges of integrating new technologies with legacy systems, upskill their workforce, and foster a data-centric mindset across the organization. Consequently, the competitive advantage derived from AI-driven BI is not merely a function of technology adoption but also a reflection of an organization's ability to leverage its human and organizational resources effectively. Despite the burgeoning literature on AI and business intelligence, there remains a significant gap in understanding the precise mechanisms by which AI-driven market prediction models contribute to competitive advantage. In particular, the interplay between technological integration, human capital development, and strategic outcomes warrants further empirical exploration. The present study addresses the following overarching research problem: How does the integration of AI into business intelligence systems optimize market prediction models, and what is its impact on achieving competitive advantage? JEL Codes: O33, M15, L25 Keywords: Business Intelligence, Artificial Intelligence, Market Prediction, Competitive Advantage, Descriptive Correlational Study, Digital Transformation.

Streptococcus pneumoniae is a high-mortality pathogen with broad-spectrum antibiotic resistance, necessitating the development of alternative therapies, such as antigenic protein-based vaccines, which have recently gained interest due to their novelty. Here, we characterized antigenic hypothetical proteins (HPs) of S. pneumoniae and determined their potential as vaccine construct targets. Subcellular localization reported 10 extracellular proteins, six of which were antigenic and non-allergenic, thus making them ideal vaccine construct targets. Functional annotation through conserved protein domain and motif prediction identified a unique, atypical Rib (aRib) domain from WP_001166178.1, widely distributed on bacterial cell surface proteins. A comparison with a native Rib domain showed domain atrophy, highlighting the lack of structural core elements. Further analysis revealed non-covalent interactions of Thr47, Ala48, Val41, and Phe38 interacting with an alpha-D-mannopyranose ligand, triggering S. pneumoniae colonization and capsule synthesis mechanism, with highly dynamic and flexible residues present on the ligand binding site. A robust immune response was observed from an immune response simulation, likely attributed to the presence of predicted 4 cytotoxic T lymphocyte (CTL), 10 helper T lymphocyte (HTL), and 5 B-cell lymphocyte (BCL) epitopes. Therefore, the study presents a novel protein for designing a vaccine construct against S. pneumoniae, thus offering a new target for future vaccinology studies

This study explores how the PHILGEPS system was used by municipal employees and its impact on the Fourth District of Laguna. Because the government relies more on technology to ensure transparency and accountability in their procurement activities, its now essential to examine and explore local government unit (LGU) efforts to do the same. The data was collected by conducting surveys and interviews with officers, staff and relevant employees in the organization. According to the findings, different cities have achieved more or less success with implementing the program, depending on training, available technology, assistance from higher administration and employees readiness. Although PHILGEPS is commonly in use, the study leads us to believe there is limited knowledge, a lack of enthusiasm for updates and network interference to be aware of. The outcome is that applying PHILGEPS is largely possible as long as capacity is built continually, digital infrastructure is supported and respected institutions are involved. Training programs are prepared, systems are often updated and the local government encourages its workers to think digitally.

This study addresses busy individual’s challenges in maintaining plants, specifically watering and pest control. PLANTery automates plant care by using IoT sensors (for soil moisture, temperature, and humidity) to activate irrigation as needed and a Convolutional Neural Network (CNN) for real-time pest detection, alerting users, and recommending anti-pest measures. The system received an excellent rating from respondents, with an overall weighted mean of 4.74, indicating high functionality, efficiency, reliability, and usability. This result reflects intense user satisfaction and demonstrates that the system effectively achieves its objectives, providing robust solutions for plant care.

Pet owners face challenges with managing their pets’ urination behavior, particularly when they are unable to consistently monitor and manually deter urination in unwanted areas in their homes. The study aimed to aid with the responsibilities of pet ownership, specifically in managing their pets’ urinary activity even without owner intervention. The objective was to develop a system that would benefit not only individual pet owners but also the majority of the pet care community facing similar challenges.This study developed a Smart Pet Micturition Behavior Corrector system that utilizes computer vision technology for the detection of pet urinary activity along with adaptive audio deterrence features and progress monitoring capabilities. The system employs a customtrained object detection model in YOLOv8 for real-time identification of pet urination events and triggering adaptive audio alerts through an ESP32-controlled Bluetooth speaker. The model achieved detection accuracy with 76% precision and 77% recall rates, and [email protected] of 77% through 270 epochs of training. An assessment was conducted using the ISO 25010:2023 quality model, with feedback collected from 60 pet owners. The results demonstrated strong performance across key attributes. Functional Suitability received a score of 4.62 (Very Satisfied), while Interaction Capability achieved a score of 4.45 (Satisfied), and Reliability received a score of 4.44 (Satisfied). The overall system rating of 4.45 (Satisfied) indicates that the implementation of the system was a success.

This study examined the relationship between human resource behaviours and firm growth in IT enterprises in Beijing, China. Specifically, it evaluated the effects of innovative working behaviour, organisational citizenship, and employee resilience on firm growth. Using cluster sampling, 220 managers from selected IT enterprises responded to a survey questionnaire. Multi-regression analysis revealed that innovative working behaviour and organisational citizenship positively impact firm growth, while employee resilience showed no significant effect. The findings highlight the importance of employees' ability to generate innovative ideas, perform beyond formal responsibilities, and adapt to change in driving firm success. Interestingly, resilience did not translate into measurable growth benefits, suggesting its role may be indirect or context-dependent. This study is unique in applying multiple regression to assess the combined effects of these behaviours on firm growth and is the first in China to explore how human resource behaviours influence organisational performance.