Journal of Applied Science and Emerging Technology

Thermodynamic Modeling of Experimental Data for the Adsorption of Ternary Antibiotic Mixture from Aqueous Solution Using Flamboyant-Pod-Based Activated Carbon

Sat, 27 Dec 2025 00:00:00 +0700

Antibiotic contamination in water poses significant environmental and public health risks, necessitating low-cost and sustainable treatment solutions. This study explores the development of Flamboyant-Pod-based Activated Carbon (FPAC), a bio-based adsorbent, for the removal of a Ternary Antibiotic Mixture (TAM). Raw Flamboyant Pods (FPs) were pretreated, chemically activated with Potassium Hydroxide (KOH), and carbonized at 500 °C for 40 min. The structural and surface modifications of FPAC were characterized using Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray (EDX) analysis and Fourier Transform Infrared Spectroscopy (FTIR) analysis. Batch adsorption experiments were performed under varying conditions of contact time (10-240 min), initial concentrations (20-100 mg/L), and temperatures (40-60 °C). Adsorption thermodynamic parameters, including Gibb’s Free Energy (ΔG°), Enthalpy Change (ΔHo), Entropy Change (Δ𝑠°), Isosteric Heat of Adsorption (ΔHx), Activation Energy (Ea), Sorption Probability (S*), Surface Coverage (θ), and Hopping Number (n), were evaluated to determine adsorption feasibility and mechanisms. FPAC exhibited a porous structure with enhanced carbon content and new functional groups, promoting chemical interactions with antibiotics. Adsorption proceeded rapidly within the first 100 min, achieving maximum capacities of 9.371 mg/g (Amoxicillin, AMO), 9.310 mg/g (Tetracycline, TETRA), and 8.733 mg/g (Ampicillin, AMP). Corresponding removal efficiencies were 85.91, 91.24, and 78.67%. Thermodynamic analysis revealed negative ΔG° and ΔHo values, confirming a spontaneous and exothermic process, while ΔHx and Ea values indicated predominantly physisorption-driven adsorption. The findings establish FPAC as an efficient, low-cost, and environmentally friendly adsorbent with strong potential for the remediation of antibiotic-contaminated wastewater.

Geopolymer as a Viable Alternative for Moisture Control and Partial Discharge Mitigation in Buildings of Electrical Substations

Sat, 27 Dec 2025 00:00:00 +0700

Partial discharges (PDs) accelerate insulation degradation and threaten the reliability and life-span of high-voltage substations. While PD mitigation studies largely focus on insulation materials and operating conditions, the role of substation building materials in controlling internal humidity remains underexplored. Conventional ordinary Portland cement (OPC) concrete is prone to moisture ingress, resulting in elevated humidity levels that intensify PD activity. This study review materials–environment–PD relationship by examining the properties of geopolymer concrete as an alternative to OPC. The conceptual proposal highlights the permeability, moisture resistance, and sustainability of geopolymer materials, and their potential to stabilise internal substation environments and mitigate humidity-driven PD risks are discussed. The study positions geopolymer concrete as a viable construction material for improving the long-term reliability of electrical substation infrastructure.

Forecasting the Elderly Population in Songkhla Province Using the Box-Jenkins Method

Jutamas Boonradsamee, Kulteera Thongyai, Rugkita Ieamwijarn — Sat, 27 Dec 2025 00:00:00 +0700

This research aimed to quantitatively forecast the elderly population in Songkhla province using the Box-Jenkins (Autoregressive Integrated Moving Average - ARIMA) method. This method is based on the assumption that the past behavior of a time series is sufficient to predict future behavior. This study used historical monthly time series data of the elderly population in Songkhla province from 2017 to 2024 to determine the most appropriate ARIMA model. The results showed that the most appropriate model was ARIMA(4,2,0)(2,0,0)12, which exhibits a clear and consistent seasonal pattern (seasonal data). The AIC value was 1181.419, and the estimated variance of error (white noise) was 14188. Projections indicate a significant and continuous increase in the elderly population over the next five years, with an expected rise of more than 50,000 people between 2025 and 2029. The resulting forecast provides a quantitative estimate of the future elderly population size in Songkhla province. The research findings aim to provide valuable insights for local and provincial policymakers in Songkhla for effective resource allocation, health care planning, and development of comprehensive social welfare strategies to address the impacts of an aging society.

Forecasting the Number of Road Accidents in Major and Secondary Tourist Cities in Thailand

Yupaporn Areepong, Kanmalin Jaroenchasri — Thu, 18 Dec 2025 00:00:00 +0700

This study purpose to identify the most suitable forecasting model and compare the forecasting performance of different methods to determine the best approach for predicting the number of road accidents in Thailand. Additionally, this study considers the impact of tourism promotion and regional income distribution by categorizing data into two groups, following the classification of the Tourism Authority of Thailand (TAT): (1) Major Tourist Cities and (2) Secondary Tourist Cities. The forecasting models were developed using monthly road accident data collected from the Ministry of Transport’s accident reporting system, managed by the Information and Communication Technology Center, Office of the Permanent Secretary, Ministry of Transport. The dataset spans from January 2019 to December 2024, Totaling 72 months. This study employs 3 individual forecasting methods based on time series analysis: (1) Exponential Smoothing Method, (2) Time Series Regression Method, and (3) Box-Jenkins Method. Additionally,
5 combined forecasting methods: (1) Simple Average Method or Equivalent Weighted method: EW,
(2) Regression-Based combination, (3) MAPE-Based combination, (4) Unequivalent Weighted Method: UNEW, and (5) Weighted Ranking method: WR. The forecasting accuracy of each method was assessed using the Mean Absolute Percentage Error (MAPE) criterion, with the model yielding the lowest MAPE being selected as the most effective.

The findings indicate that for Major tourist cities, the most efficient forecasting approach was the Unequivalent Weighted Method (UNEW). While, Secondary tourist cities, the best-performing method was the Regression-Based Combination. The results of this study are expected to be beneficial for relevant authorities in formulating effective road accident prevention measures and response strategies to enhance public safety and regional planning.

A Model for Analyzing Shuttlecock Landing Position Using Real-Time Object Detection Techniques

Mathuros Panmuang, Chonnikarn Rodmorn — Mon, 29 Dec 2025 00:00:00 +0700

This research aims to develop an Artificial Intelligence (AI) system for detecting and analyzing badminton shuttlecock positions to enhance the efficiency of game planning and training (Scouting). The researchers developed an object detection model based on the YOLOv8 architecture and conducted comparative performance tests under various conditions. The results indicated that the model trained with a dataset of 9,800 images for 300 epochs yielded the highest performance, achieving a Precision of 95%, a Recall of 92%, and a minimum Validation Loss of 2.07. When integrated into a web application and tested by experts and sports science students, the system demonstrated the ability to accurately identify shuttlecock landing positions, classify court zones, and display statistical results. Overall user satisfaction was rated at a very good level, particularly regarding its utility for learning and the convenience of data utilization. However, limitations regarding processing speed and tracking stability in certain scenarios remain.

Extending the Legacy: A Journey into the Emerging World of Fractional Quantum Calculus

Thanin Sitthiwirattham — Fri, 26 Dec 2025 00:00:00 +0700

This paper provides a comprehensive and rigorous exposition of Fractional Quantum Calculus (FQC), a sophisticated mathematical framework that systematically extends classical integer-order quantum calculus to the realm of arbitrary fractional orders. We delineate the construction of five interconnected yet distinct types of fractional difference operators: the foundational Fractional Difference Calculus (FDC), Fractional -Difference Calculus (FqDC), and Fractional Hahn Difference Calculus (FHDC), complemented by the advanced generalizations Fractional Symmetric Hahn Difference Calculus (FSHC) and Fractional -Calculus (FpqC). The unifying principle undergirding all five frameworks involves the non-integer generalization of iterated summation, leading to the derivation of both Riemann-Liouville and Caputo operators. Fractional quantum calculus furnishes an indispensable analytical instrument for modeling intricate physical and biological phenomena characterized by inherent non-locality, memory-dependent behavior, and discrete dynamical evolution, capabilities that transcend the limitations of conventional integer-order mathematical models.