Nickel-iron (Ni-Fe) batteries are emerging as a safer and more sustainable alternative to lithium-ion batteries, due to their aqueous electrolytes, long cycle life, robustness, and use of earth abundant materials. However, their performance is critically limited by the iron anode, which suffers from poor conductivity, sluggish redox kinetics, electrode surface passivation, and parasitic hydrogen evolution reaction (HER). In this work, a dual strategy approach was employed to overcome these challenges. First, Fe3O4 nanoparticles were hydrothermally grown on acid-treated multi-walled carbon nanotubes (Fe3O4@MWCNT) to improve electronic conductivity and electrochemically active surface area. Second, metal sulfide additives (ZnS, Bi2S3, and FeS) were introduced into the electrode formulation to suppress HER and reduce electrode surface passivation. Among these, ZnS exhibited the best overall electrochemical performance. The Fe3O4@MWCNT electrode with 5 wt% ZnS achieved a specific capacity of 400.86 mAh g-1 at 1 A g-1, which is more than twice that of bare Fe3O4 (193.27 mAh g-1) electrode. Further investigation into the ZnS loading revealed that while the 3 wt% (408.44 mAh g-1) and 5 wt% ZnS-containing electrodes exhibited higher initial capacities at 1 A g-1, the 7 wt% ZnS electrode offered the best cycling stability, retaining 78.48% of its capacity (383.83 mAh g-1) after 100 cycles. Notably, the 7 wt% ZnS electrode developed a new discharge plateau after 35 cycles, which is attributed to the Fe0/Fe2+ oxidation facilitated by the in situ formation of FeS. As a result, the passivation of the iron-based electrode surface was reduced. The stable supply of sulfide ions at higher ZnS content likely supports this phenomenon and improves cycling stability. These findings highlight the synergistic effect of conductive nanostructures and metal sulfide additives in enhancing the electrochemical performance of iron-based anodes for high-performance Ni-Fe batteries.

Road safety incident data remain challenging to manage and analyze, particularly in large urban areas such as Metro Manila. This dissertation presents a data model and storage architecture to support road safety analysis and inter-agency data integration. The study analyzes existing road safety incident datasets and international standards to examine data fields, entity types, and their relationships. Based on this analysis, a unified data model is proposed using the Data Vault 2.0 methodology. The proposed model supports complex incident scenarios, explicit semantic relationships and incremental data integration from multiple agencies. To implement and evaluate the model, this study develops a data lakehouse architecture based on opensource technologies. Apache Iceberg and Nessie are used within the Dremio platform to manage structured data and support batch and near-real-time workflows. Apache Spark and Jupyter Notebook are used for data ingestion and processing, while Apache Superset supports data exploration and visualization. The proposed framework addresses key challenges in public-sector data systems, including data fragmentation, limited interoperability, and slow analytics. It also provides a foundation for future extensions, such as advanced analytics and automated event detection, to further
support road safety planning and decision-making.

Persistent organic pollutants (POPs) are substances that are resistant to degradation and bioaccumulate in living organisms and the environment. Semiconductors are among the products that still contain trace amounts of POPs, specifically perfluorooctane sulfonate (PFOS) and polybrominated diphenyl ethers (PBDEs). This study aims to estimate PBDE/PFOS emissions from semiconductor exports of the Philippines from 2025 to 2034 using an artificial neural network coded in MATLAB. Semiconductor imports, producer price, competitive industrial performance index, volume of net sales and production indices, plant capacity utilization, production turnover, and GDP from 2006 to 2024 were used to train, validate, and optimize the artificial neural network. Neural networking training determined that the optimum setup to utilize is 0.4 as the learning rate and 0.5 as the momentum coefficient. Comparison of the training output to the actual historical sales in the Philippines from 2006 to 2024 demonstrated high accuracy. Semiconductor exports were predicted to increase in 2025 before taking a downward trend and flattening in 2030 to 2034. PBDE and PFOS emissions initially followed the same trend as unit production, before the implementation of stricter thresholds on POPs result in large decrease of estimated emissions, particularly in PFOS. It is recommended to collect data more specific to the semiconductor industry, adding more relevant input factors, investigating other data normalization methods, and further optimization of the MATLAB neural network in order to further improve the accuracy and reliability of the results.

A wide range of natural phenomena involves thermally driven fluid flows, where temperature-induced density variations lead to organized flow patterns once stability in the system is achieved. This interaction, under a gravitational field, form what is known as the Rayleigh – Benard Convection (RBC). In RBC, emergence of convective cells is triggered by an instability called the elevator mode (EM), characterized by vertical columns of ascending hot fluid and descending cold fluid. Recently, a novel periodic solution distinct from EM has been identified at low Rayleigh Number (Ra), exhibiting quiescent energy behavior and indicating the existence of a new basin of attraction. Transition between these two flow states – EM and the periodic solution (PS) – are of particular interest in understanding flow regulation. To explore these transitions, this study employs an edge-tracking method to identify the edge state that delineates the basins of attraction. A set of new initial conditions is calculated through the use of the gradual descent within bisection, and the system’s evolution is analyzed via direct numerical simulation (DNS). The simulations use a spectral method for velocity and temperature fields, implemented in the FORTRAN programming language. Three key findings are reported: (1) identification of the edge state between EM and PS, (2) detection of both stable and unstable toroidal structures which emanates from a doubly periodic solution, and (3) observation of a bifurcation scenario occurring at a constant control parameter Ra – an instability hallmark in RBC. These results indicate that sensitivity to initial conditions can lead to distinct flow behaviors, i.e., solutions which also occur at other Ra values, even at fixed control parameters. Furthermore, the possibility of similar bifurcation phenomena across different Rayleigh numbers (Ra), as well as the potential presence of homoclinic tangency arising from the interaction of stable and unstable tori, is proposed for future investigation.

Local Government Units (LGUs) in the Philippines play a vital role in promoting development, ensuring accountability, and addressing specific needs of their constituents. To sustain efficiency and transparency in public service, government personnel in LGUs are evaluated through performance management systems. The Individual Performance and Commitment Review (IPCR) serve as a formal mechanism for linking individual accomplishments with organizational goals to ensure alignment between local actions and broader governance objectives.

This study presents the development and evaluation of the IPCR Assist Tool, a prototype designed to streamline the preparation of IPCR forms for LGU employees in the Philippines. This study focused on ICT personnel and was carried out in three phases. Phase 1 involved the collection of responsibilities and success indicators from LGU ICT personnel which resulted in a broad set of preliminary data. In Phase 2, the raw dataset is consolidated using thematic analysis and validated by LGU experts using online surveys. This resulted in a comprehensive list of ICT roles, responsibilities, and success indicators. Lastly, Phase 3 developed the IPCR Assist Tool using the identified list as the foundation and employed the System Usability Scale (SUS) survey to evaluate it. Usability testing suggested that the tool is functional and well-received. This has the potential for future expansion to other LGU departments.