The present study investigates the valorization of coco peat, a by‑product of coconut processing, into a viable bioenergy feedstock through sequential pretreatments of water‑washing, torrefaction, and pelletization. Baseline characterization revealed raw coco peat contains 41.22 % lignin, 19.71 % hemicellulose, 19.74 % α‑cellulose, an HHV of 17.04 MJ/kg, and 10.10 % ash, and a two‑level factorial wash (1:15 or 1:30 ratio, 10 or 20 min) identified a 1:15 ratio for 10 min (S15T10) as optimal, reducing ash to 3.64 %, retaining 34 % of wet mass, and consuming only 30 Wh per 2.68 kg batch with phenolics <0.00006 mg/L. The low‑ash material then underwent torrefy‑then‑pelletize (TTP) and pelletize‑then‑torrefy (PTT) sequences at 225 °C and 275 °C for 15–30 min under oxidative conditions. TTP at 275 °C for 30 min yielded brittle pellets with an HHV of 18.42 MJ/kg, 12.8 % moisture, 46.6 % volatile matter, 33.9 % fixed carbon, 8.67 % ash, 56.5 % mass yield, and 54.1 % energy yield. In contrast, PTT at the same conditions produced dense pellets with an HHV of 21.12 MJ/kg, 3.2 % moisture, 44.1 % volatile matter, 36.0 % fixed carbon, 10.7 % ash, 66.9 % mass yield, 74.5 % energy yield, and the lowest O/C (0.79) and H/C (0.13) ratios (CHO = 1.46). Both methods exceeded commercial wood‑pellet HHV standards (≥16 MJ/kg) but had elevated ash (8.7–10.7 %), indicating further ash‑reduction is needed, and PTT at 275 °C for 30 min is recommended for high‑energy, low‑moisture applications while TTP offers a more coal‑like char for ash‑sensitive processes.

As the immediacy of the climate crisis becomes ever more apparent, battery energy storage systems can hold the key to transitioning to a renewable-fueled world. Sodium-ion batteries (SIBs) are next-generation batteries that can supplement lithium-ion batteries and are a sustainable technology that relies on earth-abundant resources such as sodium. One promising class of SIBs’ cathode active materials (CAMs) is layered transition-metal oxides (LTMOs) with chemical formula NaxMO2 (x ≤ 1 and M = transition metal/s). Although LTMOs have excellent specific capacities due to their light elemental composition and high packing densities, these materials suffer from chemical instabilities due to air exposure and from capacity degradation during cycling operation. Thus, this work evaluated LTMOs [Na(NixFe(1–x)/2Mn(1–x)/2)1–yCuyO2] by investigating the effects of (1) post-synthesis treatment, (2) nickel concentration, and (3) copper concentration on the electrochemical performance of LTMOs as CAMs for SIBs. First, NaNi0.30Fe0.35Mn0.35O2 was synthesized through the scalable method of hydroxide coprecipitation followed by calcination and was subjected to different post-synthesis treatments (i.e., recalcination, water washing, ethanol washing, and ethylene glycol washing) to reduce residual Na species introduced during synthesis. Among the materials, the ethylene glycol-washed NaNi0.30Fe0.35Mn0.35O2 had the highest initial discharge capacity of 123.9 mAh g–1 (vs. 103.5 mAh g–1 of the as-synthesized material), due to the removal of most residual alkali with minimal extraction of active Na+ from the LTMO structure. Second, NaNixFe(1–x)/2Mn(1–x)/2O2 was synthesized with varying Ni amount (x = 0, 0.1, 0.2, 0.3, 0.4, 0.5, and 0.6) to study the electrochemical contribution of Ni in the Ni-Fe-Mn system. Among the materials, the NaNi0.20Fe0.40Mn0.40O2 delivered an initial discharge capacity of 120 mAh g–1 and the highest capacity retention of 73% after 100 cycles. The low valency of Ni2+ increased the average oxidation state of Mn for charge balance and rendered Mn redox inactive, as observed in the disappearance of the Mn3+/Mn4+ redox peaks, which suppressed Jahn-Teller distortion effects of Mn3+ centers. Lastly, Na(Ni0.20Fe0.40Mn0.40)1–yCuyO2 was synthesized with varying Cu amount (y = 0, 0.05, 0.10, 0.15, and 0.20) to study the structural stabilizing effects of Cu in the Ni-Fe-Mn-Cu system. Na(Ni0.20Fe0.40Mn0.40)0.95Cu0.05O2 exhibited an initial discharge capacity of 125.1mAh g–1 and an impressive capacity retention of 76.2% after 100 cycles. The introduction of Cu, with its low valency, large ionic radius, and Cu2+/Cu3+ activity at the high-voltage region, established more local interactions among Ni, Fe, Mn, and Cu in the MO2 sheets and alleviated abrupt lattice strain changes during cycling, thus stabilizing the LTMO structure. Overall, this study developed LTMOs by reducing residual alkali to minimize chemical instability issues and by refining the Ni, Fe, Mn, and Cu amounts to minimize capacity degradation during cycling, thus making LTMOs as promising CAMs for SIBS.

The study shall develop a sustainability measurement system in the implementation of infrastructure projects in the Philippines. With the establishment of the Sustainable Development Goals, developing a Philippine-based metrics in assessing sustainability are more important than ever to ensure consistency with the sustainable development requirements under Philippine laws. The current approach in managing the sustainability of infrastructure projects is for government to regulate its implementation through its agencies and other legal requirements of law, such as the Philippine Environmental Impact
Statement System in the case of the Philippines.

While regulations and legal requirements set by the government provide general guidelines in implementing infrastructure projects, these often provide little guidance in addressing goals in relation to the sustainability of an infrastructure project. The proposed study shall build upon from the systematic literature review of related studies, the different environmental and social safeguards frameworks, the mainstream sustainability infrastructure rating systems, and from the existing policies in the Philippines, which then shall be used to craft a refined sustainability measurement system tool that can be used for
infrastructure projects in the Philippines.

This study utilized the Soil and Water Assessment Tool+ (SWAT+) to evaluate the impact of changes in agricultural land cover on streamflow and sediment output. The watershed has seen substantial changes in land use, most notably the conversion of open forest into agricultural land. In 2010, 2015, and 2020, land cover data indicated a 59.05% decrease in open forest areas over the decade, while annual and perennial agricultural areas experienced significant increases. Daily streamflow data from 2007 to 2018 were used to calibrate and validate SWAT+, and the model performed well (R² ranged from 0.75 to 0.83; NSE ranged from 0.76 to 0.78; PBIAS ranged from 24.63 to 18.89; RSR ranged from 0.64 to 0.51). Simulations of sediment yield showed an increasing tendency, increasing by 63% from 20.564 t/ha/yr in 2010 to 33.524 t/ha/yr in 2020. A study of Landscape Units (LSUs) revealed localized increases in sediment yield. For example, LSU 2210 saw a rise from 12.2 t/ha/year to 17.7 t/ha/year, and LSU 2160 saw an increase from 5.28 to 8.96 t/ha/year within the same period. Significantly, in several LSUs, scenarios that simulated the conversion of forests to perennial crops yielded larger sediment outputs than those that simulated the conversion to annual crops. This was because the land location in these scenarios was on steeper slopes. As the Department of Agriculture–Western Visayas indicated that Aklan was the leading producer of cassava, eggplant, and irrigated palay, with corresponding growth rates of 15.71%, 13.21%, and 7.13%, the selection of BMPs was in line with regional agricultural priorities. The study demonstrated the effectiveness of Best Management Practices (BMPs) in reducing sediment
yield. In particular, mulch tillage of eggplant (BMP 2) decreased sediment yield by 33.106 t/ha/year, whereas conservative tillage of cassava (BMP 1) decreased by 32.172 t/ha/year. Dense grass waterways (BMP 4) accomplished the most notable reduction, lowering sediment yield down by 29.294 t/ha/yr, while medium grass waterways (BMP 3) also decreased sediment yield by 30.156 t/ha/yr. These BMPs can be incorporated into regional agricultural extension initiatives and landuse planning. This study confirms the use of SWAT+ as a decision-support tool for sustainable watershed planning and demonstrates that land cover change has a considerable impact on sediment output.

Kolmogorov-Arnold Networks (KANs) replace fixed activation functions with learnable spline-based functions on network edges, enabling flexible, interpretable function approximation inspired by the Kolmogorov-Arnold representation theorem. This work explores KANs for class-incremental learning (CIL), where models learn new classes sequentially without access to prior data. We propose a dynamic KAN architecture that grows and prunes both network structure and spline grids to optimize generalization across incremental tasks. To en hance stability, we introduce magnitude-based regularization that limits large changes in spline coefficients, and apply a gradual early-stopping strategy to reduce overfit ting. Experiments show our dynamic KAN performs comparably to exemplar-based state-of-the-art methods, and outperforms others in exemplar-free settings. An abla tion study confirms the effectiveness of the grow-and-prune method, which supports knowledge retention via subnetwork freezing. While magnitude-based regularization can further improve results, it is sensitive to hyperparameter settings. Results also confirm a strong correlation between exemplar quantity and model accuracy, underscoring the challenge of catastrophic forgetting with limited exem plars. Overall, KANs demonstrate strong potential as a flexible, adaptive framework for continual learning.