Using methanol, this study examined the hydroxylation process of epoxidized tamanu seed oil (ETSO), with an oxirane number of 3.92 to 4.04 mmol/g, under the catalyzation of sulfuric acid (H2SO4). The objectives of this study were, first, to synthesize polyol from ETSO, and, second, determine how temperature and catalyst concentration play a role in the hydroxylation process. During the experiment, a second-order reaction kinetic model was used for analysis. The hydroxylation process was conducted in a batch reactor for 4 hours under constant temperatures and stirring speed. During the experiment, the samples were taken every 30 minutes. The oxirane number of ETSO and the concentration of polyols were used to the reaction rates. The optimal conditions were found at a temperature of 65°C, with a methanol-to-epoxide mole ratio of 4:1 and a catalyst concentration of 3%. The pre-exponential factor (A) and the calculated activation energy (Ea) were found to be 59,041.74 g.mmol-1.min-1 and 44.69 kJ/mol, respectively. This research, therefore, has successfully identified the optimal conditions for the synthesis of bio-based polyols from tamanu oil.

This present study aims to evaluate the effect of administering natural growth regulators (PGRs) based on bean sprout extract (Vigna radiate) on vegetative growth, total phenolics, and antioxidant activity of chili pepper (Capsicum frutescens L.), soybean (Glycine max (L.) merrill), and potato (Solanum tuberosum L.) plants. Bean sprout extract was synthesized through maceration, employing 96% ethanol solvent with a ratio of solvent and simplicia at 1:5. The resulting extract was administered to the plant by means of watering starting at 7 days after planting (DAP) and continuing once every 7 days until the 13th week. Vegetative growth parameters, including plant height and number of leaves, were measured on a weekly basis. At the thirteenth week, the wet biomass, total phenolic content, and antioxidant activity were analyzed under various PGR treatments. All data were subjected to normality testing, followed by ANOVA or Kruskal–Wallis analysis. This was followed by DMRT or the relevant post-hoc tests. The results demonstrated that the application of bean sprout extract PGRs significantly enhanced plant growth, number of leaves, wet biomass, and total phenolic content in soybean plants. In addition, the application of bean sprout extract PGRs significantly enhanced the antioxidant activity of chili pepper and soybean plants. These findings highlight the advantages of bean sprout extract as a low-cost, renewable, and eco-friendly natural PGR, offering a sustainable alternative to synthetic growth regulators while enhancing plant growth and functional quality. The utilization of this natural PGR also supports eco-friendly agricultural practices and has the potential to increase horticultural crop productivity with minimal environmental impact.

The depletion of bauxite reserves has prompted the research of various types of soil as alternative sources of aluminum, such as the peat clay used in this study. The complexity of the minerals requires a more efficient leaching methods, while microwave-based leaching offers a potential approach through rapid and uniform heating. This study examines the effect of microwave power, HCl concentration, operating temperature, and particle size on the leaching efficiency of aluminum from peat clay soil. The leaching process was modeled using two approaches, namely the shrinking core (SC) model and the broken-intact cell (BIC) model under pseudo-steady state conditions. The results showed that increasing HCl concentration, microwave power, and temperature accelerated leaching, while increasing particle size decreased leaching efficiency. Optimum conditions were achieved at 4 M HCl concentration, 100 W power, 40 °C temperature, and 0.0074 cm particle size. The shrinking core (SC) model showed better fit under most conditions, while the intact-broken cell (BIC) model was more accurate at lower temperatures and particle sizes. The simulation results showed that the most suitable parameter values in the SC model were De = 0.0049 cm2/s, k = 10.5 cm/s, and kc = 2.49 cm/s, while in the BIC model De = 0.04808 cm2/s and K = 0.02689 g/cm3 were obtained. These results confirm the superiority of the SC model in representing microwave-based leaching mechanisms in general, while the BIC model provides additional insights under diffusion-limited conditions. Process Performance Index (PPI) analysis showed that optimum conditions were achieved at 4 M HCl and 40 °C, but lower acid concentrations also yielded competitive PPI. This confirms that leaching effectiveness is determined by a combination of alumina recovery and reagent consumption efficiency. These findings contribute to the development of leaching kinetics models and the optimization of more efficient and energy-saving aluminum extraction processes.

This study investigates the material properties (permittivity, dissipation factor, and conductivity) of mango leaves (Mangifera indica) over the 26–40 GHz Ka-band frequency based on a waveguide measurement system with a vector network analyzer instrument to capture the data. The data analysis employs the Nicolson-Ross-Weir method to extract material properties. The result reveals that the real part of permittivity decreases from about 11.0 to 5.0 with increasing frequency. Meanwhile, the imaginary part of permittivity remains low and stable, suggesting minimal absorption losses. The dissipation factor is consistently below 0.05 along the band. Effective conductivity ranges from 0.2 to 0.6 S/m, with a slight increase at higher frequencies. These findings suggest that at Ka‐band frequency, signal degradation through mango foliage is primarily driven by dispersion and scattering rather than strong dielectric absorption. The results provide essential information for improving foliage attenuation models and designing 5G and 6G communication systems in tropical regions. This study provides a reliable Ka-band dielectric dataset for mango leaves that improves the accuracy of tropical foliage-attenuation models and supports more robust 5G/6G link design and deployment in vegetation-dense environments.

The Chan–Evans–Lam coupling refers to a valuable method for constructing C–O and C–N bonds under mild conditions. Nevertheless, the development of efficient and reusable heterogeneous catalysts remains limited. In this study, we investigated copper-based metal–organic frameworks as catalysts for C–O bond formation between 4-methoxyphenylboronic acid and phenol. The study revealed that HKUST-1 exhibited a significant enhancement in performance when compared to Cu-BDC, yielding up to 86% at room temperature and demonstrating superior accessibility of Cu2+ active sites. A systematic optimization of reaction parameters identified NEt3 as the most effective base, DCM as the optimal solvent, and a mild temperature increase to 40 °C as the key factor enabling a maximum yield of 94%. Studies on recyclability demonstrated that HKUST-1 exhibited high catalytic performance over multiple cycles without significant structural degradation, as confirmed by PXRD analysis. Overall, this work highlights HKUST-1 as an efficient, robust, and reusable heterogeneous catalyst for Chan–Evans–Lam C–O coupling, thus demonstrating its potential for sustainable synthetic applications.

This paper proposes a high-capacity reversible watermarking method using adaptive bit-level expansion and pixel-class-guided shifting. Pixels are classified into expandable (P0) and non-expandable (P1) according to their 2-bit LSB patterns, and a lightweight reversible transformation converts P1 into P0 with minimal distortion. A shifting map enables exact recovery and avoids overflow/underflow. Secret data are embedded through a 2-bit LSB expansion rule that ensures full reversibility. Experiments on common and medical images demonstrate a consistent embedding capacity of 1.0 bpp, achieving PSNR values above 46 dB and SSIM above 0.97. In addition, the scheme exhibits low computational overhead (<0.7s per image, >380 kbps) while preserving the original histogram distribution. These results demonstrate that the proposed scheme provides an effective balance between embedding capacity, visual quality, and computational efficiency for secure medical imaging and authenticated reversible data embedding.

This present study develops an analytical model for mutual visibility in perturbed Low Earth Orbit (LEO), explicitly accounting for Earth’s oblateness (J2 and J3) and atmospheric drag. The framework extends classical geometric visibility calculations to include long-term perturbation effects, thus enabling rapid and reliable prediction of visibility intervals. A series of numerical simulations were conducted on three LEO satellite configurations and revealed that perturbations have the capacity to shift rise–set times, alter event frequency and duration, and generate new visibility intervals. These effects are of particular significance for satellites operating at lower altitudes and those characterized with moderate semi-major axis differences and large inclination disparities. The results of the study underscore the importance of considering secular and long-period perturbations into the planning of reliable communication relay, the management of constellation, and the scheduling of autonomous mission. Importantly, the closed-form formulation enables fast visibility and rise–set prediction without full numerical orbit propagation, supporting preliminary constellation design, inter-satellite link scheduling, and onboard visibility assessment in large LEO networks.

Cumulonimbus (CB) clouds are vertically developed convective systems that are capable of producing severe weather phenomena, including turbulence, heavy rainfall, and lightning. These phenomena pose a significant threat to aviation safety. This paper considers an automated CB cloud detection approach using the deep learning algorithm You Only Look Once version 8 on NOAA-19 satellite imagery. The images of 640 × 640 pixels each were labeled into two classes: CB and non-CB. In general, rotation, flip, and random brightening are performed to develop a more robust model. After 100 training epochs, the proposed model produced reliable detection performance, as evidenced by 1,694 TP (true positives), 438 FP (false positives), and 304 FN (false negatives) cases, with a precision of 0.79, recall of 0.84, and an F1-score of 0.81. Validation using METAR reports from the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG) confirmed the consistency of the model with observed weather conditions. The results demonstrated that YOLOv8 could provide a rapid and reliable framework for real-time detection and classification of CB clouds, thereby enhancing situational awareness for aviation operations and facilitating the effectiveness of satellite-based early warning systems in convectively active tropical regions.

This study highlights the critical role of oxygen-functionalized hierarchical nanofiber structures derived from kulim wood waste in improving the electrochemical performance of symmetric supercapacitors. A one-step catalyst-assisted method was developed to synthesize these carbon nanofibers. The synthesized material exhibited well-defined oxygen functionalities (9.34% oxygen content) and exceptional porosity (1070 m2/g), demonstrating a micro-mesoporosity ratio of nearly 4:1. This structural design led to enhanced capacitive properties, achieving a capacity of 172 F/g in acid media and a rate capability of 81.2% at 10 A/g. The oxidation reactions indicated a mixed energy storage mechanism, with 83% EDL-controlled and 22% redox-controlled processes. Additionally, the material showed an energy output of 19.91 Wh/kg and a power density of 1.02 kW/kg, showcasing its potential for sustainable energy storage applications. Importantly, this work offers a scalable, low-cost, and biomass-driven strategy for producing high-performance carbon electrodes, advancing sustainable supercapacitor technologies.

The 5G internet network has been proven to facilitate daily life for people and render electronic devices such as smartphones as an integral component of people's daily routine. However, in conjunction with the ease of use, there is an issue of electromagnetic radiation. To cope with this issue, magnetic and dielectric composite microwave absorber materials have been undertaken. To address this, we investigated the limitations of activated carbon composite material from Gnetum gnemon seed shells (AC) on the microwave absorption ability of (La0.7Sr0.3MnO3)1-y/(AC)y. The composite material (La0.7Sr0.3MnO3)1-y/(AC)y (y = 0; 0.3; 0.5; 0.7) was synthesized through a stirring process with a 96% ethanol catalyst using La0.7Sr0.3MnO3 synthesized by sol-gel method and activated carbon material from Gnetum gnemon seed shell (AC) synthesized by chemical activation method. The XRD and SEM characterizations indicated a single-phase structure, with smaller crystals and particles that were uniformly distributed throughout the composite sample. The presence of activated carbon grains from Gnetum gnemon seed shells (AC) were observed between the La0.7Sr0.3MnO3 grains in the composite sample. The EDS results confirmed the material’s purity. VNA characterization demonstrated that (La0.7Sr0.3MnO3)1-y/(AC)y was capable of producing two reflection loss troughs with the largest absorption percentages recorded at 82.99% and 85.82% respectively within the frequency range of 8 – 12 GHz. This research highlights the significance of controlled composite composition in enhancing microwave absorption capability, particularly in perovskite-based composites with biomass-activated carbon, which holds a considerable promise for applications in electromagnetic wave attenuation and absorption technologies.