ASEAN Journal of Scientific and Technological Reports

Development of a Rework-Based Inventory Policy for Ordering Water Sports Equipment Bags: A Case Study of a Manufacturing Packaging Department

2026-03-08T13:29:59+07:00

Inventory management plays a critical role in reducing operational costs and maintaining efficiency in competitive manufacturing environments. In the production of water sports equipment, packaging bags are essential supporting materials; however, the absence of structured ordering policies often leads to uncontrolled purchasing, excessive inventory, and increased sunk costs. This study aims to develop an improved inventory policy for packaging bags by comparing three ordering approaches: the Traditional Ordering Method, the Fixed Time Period System (FTPS), and a proposed rework-based inventory policy that incorporates rework rate and rework time into inventory planning. The research was conducted at a water sports equipment manufacturing company in Chonburi, Thailand, focusing on eleven models of packaging bags used in the packaging process. Production and inventory data were collected over three months, and the performance of each ordering method was evaluated based on average inventory level, sunk cost, and service reliability. The results indicate that the Traditional Ordering Method generated the highest inventory cost of 353,307 Baht due to excessive overstocking. The FTPS approach, which applies periodic review and safety stock principles, reduced inventory costs to 200,691 Baht and improved stock control, although inventory levels remained higher than actual demand. In contrast, the proposed rework-based inventory policy achieved the lowest average cost of 57,209 Baht by incorporating production variability through defect rates and rework cycle times. This method reduced costs by approximately 300,000 Baht compared with the traditional method and by 146,000 Baht compared with FTPS, while preventing stockouts during the observation period. These findings demonstrate that integrating rework-related variability into inventory planning can significantly improve cost efficiency and operational reliability. The study contributes to the inventory management literature by bridging theoretical inventory models with practical industrial implementation and by highlighting the potential of rework-sensitive policies as an effective framework for managing packaging materials in manufacturing systems.

Effect of Plant Growth Regulators on In Vitro Shoot and Root Induction and Acclimatization of Gymnocalycium mihanovichii LB2178 Agua Dulce (Cactaceae)

2026-03-07T21:39:53+07:00

Gymnocalycium mihanovichii LB2178 Agua Dulce is a popular cactus still in demand, known for its distinctive shape and ease of growth. It can be propagated by tissue culture to produce strong, disease-free plants. Therefore, the aim of this research was 1) to study the effect of BA and IBA hormones and types of explants on the growth rate of G. mihanovichii LB2178 Agua Dulce cactus. and 2) to study suitable planting materials for survival and growth of G. mihanovichii LB2178 Agua Dulce cactus under natural conditions. After 3 months of culture, the results showed that the explant sectioned longitudinally were cultured on MS medium supplemented with 0 and 2 mg/L BA gave the highest survival, 100%, and shoot induction, 86.67%, the explant sectioned transversally were cultured on MS medium supplemented with 1 mg/L BA gave the highest number of shoot, 4.20 shoots/explant, and shoot length, 0.36 mm respectively, significant difference at p≤0.05. Following three months of cultivation, the findings indicated that shoot explants cultured on MS medium supplemented with 1 mg/L IBA showed the highest root induction (91.67%), average number of roots (20.47 roots/explant), and average root length (7.63 mm), with significant differences at p≤0.05. After 3 months, the rooted plants were removed from the tissue culture room and transferred to sterile plastic pots. The result showed that G. mihanovichii LB2178 Agua Dulce grown in potting soil: sand, showed the highest survival rate of 100%.

In vitro Degradability and Rumen Microbial Dynamics in Goats Supplemented with Pleurotus Spent Mushroom Substrate at Different Inclusion Levels

2026-03-14T18:05:50+07:00

This study evaluated the effects of Pleurotus spent mushroom substrate (PSMS) supplementation on in vitro degradability and rumen microbial dynamics in goats (Capra hircus). It aimed to determine the degradability of PSMS and its influence on gas production, nutrient degradability, and microbial composition. A Randomized Complete Block Design was employed with treatments: T0 – 0% PSMS (control), T1 – 3% PSMS, and T2 – 6% PSMS, all mixed with Napier grass. Parameters measured included in vitro gas production (IVGP), dry matter degradability (IVDMD), crude protein degradability (IVCPD), neutral detergent fiber degradability (IVNDFD), and acid detergent fiber degradability (IVADFD). Data were analyzed using Analysis of Variance (ANOVA) in SAS OnDemand, with differences determined using Tukey’s Honestly Significant Difference (HSD) test at α = 0.05. Microbial analysis showed the highest bacterial and protozoal populations in T1, whereas fungal populations were not detected in PSMS-supplemented treatments. This observation may be associated with the presence of phenolic compounds in PSMS, which originate from lignin degradation during mushroom cultivation and have been reported to exert antimicrobial or inhibitory effects on rumen microorganisms. Methodological factors, such as sampling rumen fluid and reliance on culture-based detection, may also have influenced fungal recovery. IVGP was numerically highest in T1 (52.39 cc), indicating enhanced fermentability. During the first digestion stage, the highest IVDMD occurred in T2 (54.85%), while IVCPD peaked in T1 (60.29%) but declined in T2 (37.60%), suggesting possible inhibitory effects at higher inclusion levels. IVNDFD and IVADFD were also higher in PSMS treatments, with IVADFD showing a significant linear increase (p=0.0294). In the second stage simulating abomasal digestion, DM degradability remained similar across treatments, while ADF degradability declined significantly in T2 (p=0.0035). Overall, 3% PSMS improved fermentability, digestibility, and microbial activity, indicating its potential as a sustainable ruminant feed supplement.

Whole-Genome Analysis of MR219 and Its Drought-Tolerant Mutant, NMR151 to Elucidate Drought Resistance Mechanisms

2026-01-24T14:16:32+07:00

Background: Drought is among the most severe abiotic stresses limiting global rice (Oryza sativa L.) productivity and threatening food security, particularly in high-yielding but stress-sensitive cultivars such as MR219. Understanding the genomic basis of drought tolerance is essential to support the development of resilient rice varieties. This study aimed to identify genome-wide variants and drought-responsive genes associated with induced drought tolerance in the mutant line NMR151 derived from MR219. Methods: Whole-genome resequencing was performed on the drought-tolerant mutant NMR151 and its parental line MR219. High-quality paired-end reads totaling 92.1 million (MR219) and 78.5 million (NMR151) were mapped to the O. sativa cv. Nipponbare reference genome with an alignment efficiency of 91.4% and coverages of 35.4× and 29.6×, respectively. Variant calling, functional annotation using SnpEff, and visualization through the Integrative Genomics Viewer (IGV) were employed to detect and characterize single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Results: A total of 4.27 million and 4.18 million polymorphisms were identified in MR219 and NMR151, dominated by SNPs and InDels with a transition-to-transversion ratio of 2.4. Comparative analysis revealed 3.01 million shared and 1.17 million unique SNPs in NMR151, indicating mutation-driven allelic diversification. Most variants occurred in intergenic (33.2 %), upstream (29.1 %), and downstream (24.6 %) regions, while six drought-responsive genes (OsDREB2A, OsNAC6, OsLEA3-1, OsAPX2, OsCPK21, and OsP5CS1) were uniquely mutated in NMR151. Conclusions: The drought resilience of NMR151 results primarily from regulatory fine-tuning rather than extensive coding alterations. These findings provide valuable molecular insights and genomic markers for breeding climate-resilient rice varieties through mutation and marker-assisted selection.

Factors Influencing the Incorporation of 2AP in Fluidized Bed Drying Processes

2026-04-08T17:47:38+07:00

Drying high-moisture paddy rice while retaining the quality of the grains and their natural aroma is one of the hardest things to perform in industrial processing. This study examines a hybrid drying system comprising drying units from Louisiana State University (LSU), a fluidized bed dryer, and a cyclone-based hot-air generator to reduce paddy moisture content from 25–30% to the safe storage level of 14% on a wet-basis. The cyclone furnace heated the air to 280°C using leftover charcoal. Before entering the fluidized bed dryer, the air was cooled to 101.7 °C. The grain's temperature was kept below 57.7 °C during this time, which helped preserve the rice's quality. After the rice had dried out a bit, it was put in six LSU (Louisiana State University) drying chambers. Each chamber could hold 37.5 tons of rubbish every hour and worked in groups for 10 hours. The procedure worked well to lower the moisture level in a single step, even when it reached 18%. By eliminating the middle resting stage, the drying process is easier and faster without affecting the final product's quality. The dried rice had 10.7% moisture, a grain temperature of 36.9°C, and 4.15 µg/g of 2-acetyl-1-pyrroline (2AP). This means that the rice still smelled good. These results show that using fluidized bed drying with LSU drying is a good approach to make large-scale commercial drying systems work better and be simpler while maintaining excellent rice quality.

Cleanliness, Crowds, and Conservation: A Multi-Method Approach using Sentiment Analysis and Spatial Mapping for Sustainable Tourism Management in Thailand

2026-03-11T13:27:05+07:00

Natural attractions are among Thailand’s most important tourism resources, drawing a large number of international tourists and contributing substantially to national revenue. However, persistent issues such as overcrowding, pollution, and declining environmental quality remain critical challenges for sustainable management. In the digital era, online reviews on travel platforms strongly influence destination choice, providing a rich source of behavioral insights. This study applies sentiment analysis to 124,066 TripAdvisor reviews of natural attractions across all 77 provinces of Thailand, collected between 2014 and 2023. The reviews were processed using text mining techniques—data cleansing, tokenization, lemmatization, and stop-word removal—and analyzed with the Pysentimiento model, a BERT-based deep learning framework, achieving an overall accuracy of 76% and a precision of 87% on the validation dataset in distinguishing positive, negative, and neutral sentiments. Beyond thematic analysis, this research employs Kernel Density Estimation (KDE) to visualize the geographical concentration of dissatisfaction. Results indicate that beaches and islands received the most negative reviews, with recurring issues related to cleanliness, pollution, overcrowding, and unregulated commercial activities. The KDE analysis further reveals that negative sentiment intensity is highly concentrated in specific coastal hotspots (e.g., Phuket, Krabi, and Pattaya). This study contributes methodologically by demonstrating the integrated effectiveness of large-scale sentiment analysis and spatial mapping in tourism research, effectively addressing the implementation gap, providing actionable, precision-based insights for the National Tourism Development Plan (2023–2027). The findings support policymakers and stakeholders in formulating strategies that align with the BCG (Bio-Circular-Green) economic model and balance economic growth with sustainable environmental management by enabling location-specific resource allocation.

Health Analysis for Ergonomic Risk Assessment among Rice and Sugarcane Farmers Using LINE Chatbot Application

2026-03-11T13:23:53+07:00

Farmers are at risk of exposure to a variety of health hazards, particularly unnatural and strenuous working postures in the fields. This study aimed to develop and evaluate a LINE-based ergonomic risk assessment application integrated with a chatbot recommendation system. Specifically, the study evaluated the application's validity, compared time efficiency between paper-based and application-based assessments, and assessed user satisfaction among health personnel and farmers. The sample consisted of 30 application users, including subdistrict health promotion hospital staff/public health officers, village health volunteers or farmer leaders, and research assistants, and 125 farmers as assessors. The tools used included the Rapid Entire Body Assessment (REBA), the application, and a questionnaire. Data were analyzed using descriptive statistics, a one-sample t-test, and a paired t-test (p<0.05). The study found that the chatbot application passed expert evaluation and passed the test. It performed the following functions: login, assessment based on observation images, selection of images for assessment, introduction of risk in the chatbot, and accurate recording of results. Experts assessed its suitability with an average score of 4.87 ± 0.11 (out of a full 5.00), which is considered the highest level. The application's effectiveness, when used with farmers, was significantly reduced in time compared to the traditional assessment (p<0.05). Scores obtained from the traditional and application methods were not significantly different. The results of the satisfaction assessment of the application among farmers showed that users were most satisfied with the benefits and application, with an average score of 4.80±0.36. In terms of ergonomics, farmers had a prevalence of right shoulder and neck pain of 17.6% (95% CI=12.0-24.8) and 16.8% (95% CI=9.9-24.5), respectively. The application can be easily used to assess ergonomic risks and takes less time than the previous format. Moreover, the results of the assessment are of the same quality as those assessed by experts using the previous format. Recommendations: The application should be expanded to farmers to obtain a comprehensive picture of the country. High-risk groups should be followed up with to reduce their risk levels.

Comparative Analysis Of Convolutional Neural Networks, Long Short-Term Memory Networks, and Bert For Text-Based Emotion Classification

2026-01-19T17:05:37+07:00

This paper presents a detailed experimental study and comparative analysis of three popular deep learning architectures (CNN, LSTM, and BERT) for emotion classification in written messages. Using a publicly available dataset of six unique emotional states (sadness, joy, love, anger, fear, and surprise), an effective ablation study was conducted to determine optimal architectural configurations, including a sequence length of 66 tokens and an embedding size of 200. To validate the results of a comparative analysis of model performance, a bootstrap technique (30 trials) and the Wilcoxon Signed-Rank test were used to eliminate potential bias. As shown by experiments, the tuned BERT architecture (with a learning rate of 2e-5) produced the most accurate and reliable result of 93.50% in classifying emotional states from texts. Moreover, with an appropriate sequence length configuration, the LSTM network (89.92%) significantly outperformed the CNN (89.65%), confirming the need to account for long-range dependencies in emotion classification. Overall, the research results show the key importance of hyperparameter tuning and the ability to handle complex information for emotion identification.

Driving Innovation Hybrid Mechanical Engineering Review Platform as Catalysts for Technology Diffusion

2026-03-11T13:01:11+07:00

Responding to the imperative of keeping pace with the dynamic nature of technological innovations in the field of mechanical engineering, the integration of e-learning emerges as a promising avenue. The study used a descriptive-analytic method, a survey questionnaire, and the ISO standard model, specifically ISO 25010, and distributed it to 110 randomly selected respondents. The findings indicate a consistently high rating for effectiveness from reviewees, reviewers, and newly qualified board passers. There was strong agreement among them regarding the platform's efficacy across various dimensions, including content design, media design, visual design, feedback mechanisms, and assessment items. The performance expectancy and effort expectancy did not exert a significant influence on the behavioral intention to use the hybrid mechanical engineering review platform.

Improving the Efficiency of Vermicompost Production by Using a Two-Step Composting Process with Agricultural Waste Materials

2026-01-31T18:53:19+07:00

This research aimed to improve the vermicompost production process by combining a two-step composting process with agricultural waste to enhance soil fertility, increase productivity, and reduce costs. The experiment was divided into three phases: Phase 1 tested the production of vermicompost using manure from cows, goats, and sheep. Cow manure (CM) was found to be the most suitable raw material due to its friability, ease of digestion, and high-quality fertilizer value. Phase 2 investigated the production of vermicompost using supplementary materials from local plants, including Azolla (AZ), Leucaena leaves (LL), and Palm leaves (PL), combined with five formulas of cow manure for growing kale. Formula 5, consisting of 75% Cow manure (CM), 15% Azolla (AZ), and 10% Palm leaves (PL) by weight, provided the highest nitrogen content at 852.57 ± 0.045 mg/kg. Finally, the growth of kale was studied using vermicompost from the second stage mixed with soil at a 1:1 ratio. Formula 7 (50% Vermicompost [CM+AZ+PL] and 50% NS) yielded the best kale growth, in terms of height, leaf width, weight, and fertility.

Factors Influencing the Use of Herbal Medicines in Public Health

2026-01-27T13:34:27+07:00

To foster independence and cut costs, Thai traditional medicine and herbs are becoming more well-known within Thailand's healthcare system. Nonetheless, Pathum Thani Province's use of herbal medicines remains lower than the national average, highlighting a discrepancy between policy and reality, especially in areas such as Keha Rangsit Khlong Hok. Factors associated with the use of herbal medicines for self-care include personal factors, predisposing factors, enabling factors, and reinforcing factors. A survey study was carried out. A survey with an Item-Objective Congruence index of 0.92 was used to randomly select 318 residents (aged 20–59) from Keha Rangsit Khlong Hok, Pathum Thani Province. Chi-square tests and descriptive statistics were used to assess the data; (3) Results: Use of herbal medicine was low (mean 1.55), despite moderate to high attitudes (mean 3.44) and knowledge (46% high). There was a substantial (p<0.05) correlation between usage and occupation, marital status, and gender; (4) Conclusions: Effective promotion strategies are needed to bridge the gap between the community's knowledge and attitudes on herbal medicine and its actual use.

Comparative Effects of Nano-NPK and Conventional NPK Fertilizers on Growth, Nutrient Content, and Seed Quality of Sesame (Sesamum indicum L.)

2026-03-01T09:02:24+07:00

The development of nanotechnology-based fertilizers represents a potential avenue for optimizing the efficiency of fertilizer application and increasing the yield of agricultural crops. The current study aimed at investigating the efficacy of nano-NPK fertilizer compared with conventional NPK fertilizer on vegetative growth, chemical analysis, and seed quality of sesame plant (Sesamum indicum L.). The experiment was conducted using RCBD with three replications, where different concentrations of nano-NPK (0, 1, 2, and 3 g/L) and conventional NPK (0, 5, 10, and 15 g/L) were applied through foliar spray. When treated with optimal nano-NPK (2 g/L), plant height (46.50 vs. 38.98 cm), leaf area (13.97 vs. 9.29 cm²), leaf number (27.25 vs. 19.50), fresh and dry weight (30.41 vs. 21.26 g and 3.73 vs. 2.16 g) were improved by 19, 51, 39, 43, and 73%, respectively. The combined treatment (10 g/L conventional NPK + 2 g/L nano-NPK) produced maximum chlorophyll content (42.68 mg/100g, 95% increase), nitrogen (2.90%, 48.7% increase), phosphorus (0.46%, 188% increase), potassium (0.54%, 86% increase), magnesium (1.98%, 383% increase), protein (18.12%, 48.2% increase), and oil content (33.68%, 39.2% increase) relative to untreated controls. It has been observed that the use of nano NPK fertilizers has shown great efficacy even at lower dosages (2 g/L compared to 15 g/L, which means seven-and-a-half times less), suggesting better availability and absorption of nutrients. It has been found from this experiment that use of nano fertilizers, especially in combination with the use of normal fertilizers, positively affects the growth of sesame plants and oil content in them.

Effect of Conventional and Nano Potassium on the Chemical Characteristics of Alfalfa (Medicago sativa L.) under Different Levels of Water Stress

2026-03-19T09:48:42+07:00

This study was conducted to evaluate the effect of conventional potassium fertilization and nano-potassium application on some chemical characteristics of alfalfa (Medicago sativa L.) under different levels of water stress. The experiment was carried out in a randomized complete block design (RCBD) with three replicates, using a factorial arrangement. The treatments included three concentrations of nano-potassium (1, 2, and 3 g L⁻¹), three levels of conventional potassium added to soil (4, 6, and 8 g kg⁻¹ soil), and a control treatment without potassium fertilization. Four irrigation levels representing water stress were applied: 100%, 75%, 50%, and 25% of field capacity. Several chemical characteristics were measured, including chlorophyll content, proline concentration, mineral nutrient content (N, P, and K), protein percentage, and total carbohydrates in the leaves. The results indicated that nano-potassium application significantly increased chlorophyll content, protein percentage, and total carbohydrates compared with the control treatment. Conventional potassium fertilization significantly improved mineral nutrient concentrations, particularly potassium in plant tissues. Water stress levels significantly affected most of the studied traits, with moderate levels enhancing some physiological responses. The interaction between potassium treatments and irrigation levels showed significant effects on several chemical characteristics of alfalfa plants. Overall, potassium nutrition, especially in nano form, improved chemical characteristics and enhanced alfalfa plants' tolerance to water stress. These findings highlight the potential role of nano-potassium fertilization in improving plant performance and forage quality under limited water availability.

Prevalence of AmpC β-Lactamase and Regulatory Genes (LysR, QseB, and QseC) in Multidrug-Resistant Klebsiella pneumoniae Clinical Isolates from Al-Hillah, Iraq

2026-04-07T23:08:54+07:00

Klebsiella pneumoniae is a critical opportunistic pathogen classified by the World Health Organization among priority drug-resistant organisms, owing to its capacity to acquire multidrug resistance (MDR) and express diverse virulence mechanisms. Understanding the molecular basis of resistance and the prevalence of regulatory genes in clinical isolates is essential for effective infection control. A total of 200 clinical samples (sputum and urine) were collected from hospitalized patients at two teaching hospitals in Al-Hillah, Iraq. Isolates were identified using the VITEK 2 Compact system, and antibiotic susceptibility testing was performed. Genomic DNA was extracted by the boiling method, and conventional PCR was used to detect five target genes: 16S rRNA, ampC, lysR, qseB, and qseC. Of 100 culture-positive samples, twenty (20%) were confirmed as K. pneumoniae with 99% probability. High resistance rates were recorded against cephalosporins (100%) and ceftazidime/ceftriaxone (90%), while amikacin showed the highest susceptibility (85%). The ampC gene was detected in 40% of isolates. All isolates (100%) carried 16S rRNA, lysR, and qseB genes, while qseC was present in 85%. The widespread resistance—even in isolates lacking the ampC gene—suggests the possible involvement of additional concurrent mechanisms, such as ESBLs, efflux pumps, and porin loss, although these were not directly tested in the present study. The universal prevalence of regulatory genes lysR and qseB underscores their role in bacterial adaptation and virulence. Combined molecular and phenotypic approaches are essential for comprehensive characterization of MDR K. pneumoniae in clinical settings.

Therapeutic Effects of Marjoram (Origanum majorana L.) Extract and Nano-Formulation on Hormonal Parameters and Ovarian Histology in Letrozole-Induced Polycystic Ovary Syndrome in Rats

2026-03-04T18:18:54+07:00

Polycystic ovary syndrome (PCOS) represents a prevalent endocrine disorder characterized by hyperandrogenism, hormonal imbalances, and ovarian dysfunction, affecting approximately 30% of female infertility cases globally. This study evaluated the therapeutic efficacy of marjoram (Origanum majorana L.) aqueous extract and zinc oxide nano-loaded marjoram formulation on letrozole-induced PCOS in female Wistar rats. Fifty rats (150-250 g) were randomly assigned to five groups (n=10): negative control (physiological saline), carboxymethylcellulose (CMC) control, PCOS induction (1 mg/kg letrozole for 58 days), marjoram extract treatment (45 mg/kg for 30 days post-induction), and nano-marjoram treatment (45 mg/kg for 30 days post-induction). Serum hormonal parameters and ovarian histology were assessed. Letrozole induction produced characteristic PCOS features with significant hormonal alterations: 44% FSH decrease (5.78 vs. 10.30 mIU/mL, p<0.05), 46% LH increase (20.07 vs. 13.71 mIU/mL, p<0.05), 43% progesterone decrease (6.87 vs. 12.07 mIU/mL, p<0.05), 32% estradiol decrease (72.91 vs. 106.66 pg/mL, p<0.05), 125% testosterone increase (0.45 vs. 0.20 pg/mL, p<0.05), and 158% inhibin-B increase (378.59 vs. 146.58 pg/mL, p<0.05) compared to controls. Nano-marjoram treatment demonstrated superior therapeutic effects, restoring FSH by 51% (8.73 mIU/mL), reducing LH by 18% (16.44 mIU/mL), increasing progesterone by 36% (9.33 mIU/mL), increasing estradiol by 24% (90.64 pg/mL), reducing testosterone by 42% (0.26 pg/mL), and reducing inhibin-B by 53% (179.35 pg/mL) relative to PCOS group. Histological examination revealed that nano-marjoram treatment significantly improved ovarian architecture, increasing the number of corpora lutea, restoring Graafian follicles, and reducing cystic follicles and inflammatory infiltration compared with the PCOS group. These findings demonstrate that marjoram, particularly in nano-formulation, effectively ameliorates PCOS-associated hormonal dysregulation and ovarian pathology through antioxidant and anti-androgenic mechanisms, suggesting potential clinical applications for PCOS management.

Enhancement of Cleaning-in-Place (CIP) Using Chemical Cleaning to Control Fouling and Scaling on Seawater Reverse Osmosis (SWRO) Membrane Full-Scale Plant Producing Demineralized Water in Central Java

2026-01-10T21:13:01+07:00

Despite recent advances in membrane technology for sustainable water treatment, fouling remains a key challenge to long-term performance, as it leads to surface deposits and concentration polarization. To address this issue, this study evaluates the effectiveness of cleaning-in-place (CIP) in controlling fouling and scaling in a seawater reverse osmosis system at Sumber Segara Primadaya Co. Ltd. Evaluation parameters include pressure drop, flux recovery ratio, salt rejection recovery, and membrane characterization before and after cleaning. The CIP process showed positive results, as indicated by the recovery of differential pressure (∆P) to its initial condition. The membrane flow rate also returned to its original value of 103–104 m³/h under the same operating pressure of 3.6 bar. Membrane productivity, which had declined by 19%, was successfully restored, with recovery improving from 38% to 40%. In addition, salt rejection increased from 98.8% back to approximately 99.03%, representing a 2% improvement toward the initial value of 99.1%. These findings demonstrate that CIP is an effective method for restoring membrane performance and extending operational lifespan.

Upgrading the Characterization of Spent Fluid Catalytic Cracking Catalyst into Functional Adsorbent via Hybrid Ultrasonic-Chemical Approach

2026-01-03T07:41:23+07:00

Fluid catalytic cracking catalysts (FCCCs) are essential in petroleum refining but become hazardous spent materials after deactivation due to heavy metal and coke deposition. Regenerating spent FCC catalysts (SFCCCs) is necessary to reduce hazardous waste and restore physicochemical properties. Conventional regeneration methods face limitations, such as high energy demand or potential structural damage, leaving a gap for more efficient and sustainable approaches. This study shows that a hybrid ultrasonic-chemical method can effectively regenerate SFCCCs, improving surface morphology, pore structure, and crystallinity, as evidenced by characterization using XRD, FTIR, BET, and SEM-EDS. The untreated SFCCCs exhibited a surface area of 27.255 m²/g, which increased to 33.508 m²/g after hybrid treatment and 34.344 m²/g after chemical treatment, indicating pore reopening and enhanced surface activity. FTIR analysis showed clearer Si-O-Si and –OH bands in hybrid-treated samples, suggesting improved recovery of the zeolite structure and reduced coke formation. XRD patterns showed sharper peaks in the 2θ = 22–30° range, indicating greater crystallinity in hybrid regeneration than in untreated samples. SEM-EDS showed cleaner, more porous morphologies with reduced Fe (3.25%) and exposure of hidden Ni (9.49%) after hybrid treatment. These findings underscore the effectiveness of ultrasonic-assisted chemical regeneration, which offers a promising pathway for sustainable catalyst waste management and potential future reuse applications.

The Corn Stalks as a Novel Source of Functional Dietary Fiber: Process Optimization and Product Characterization

2026-03-11T20:02:00+07:00

The growing demand for dietary fiber (DF) has encouraged the exploration of sustainable and low-cost sources from agricultural by-products. Corn stalks are an abundant agricultural residue that remains underutilized as a potential source of dietary fiber. This study aimed to optimize the alkali extraction of DF from corn stalks (Zea mays, L.) using Response Surface Methodology (RSM) with a Central Composite Design (CCD). Three independent variables, namely temperature (70-90°C), time (50-70 min), and NaOH concentration (15-25%), were investigated for their effects on DF yield. The model showed a high significance (p<0.0001) with R² = 0.99, indicating excellent predictive accuracy. The optimal extraction conditions were 82.29°C, 62.06 min, and 23.03% NaOH, resulting in a maximum DF yield of 25.75%. Verification experiments confirmed the model’s reliability, with an experimental yield of 25.43 ± 0.24%. The extracted DF exhibited favorable functional properties, including high water holding capacity/WHC (4.7 ± 0.08 g/g), water binding capacity/WBC (2.7 ± 0.05 g/g), swelling capacity/SW (5.12 mL/g), oil holding capacity/OHC (1.8 ± 0.07 g/g), and Fourier Transform Infrared Spectroscopy (FTIR) analysis confirmed the removal of lignin and hemicellulose. These characteristics highlight its potential as a functional ingredient in food formulations, particularly in meat- and fish-based products that require improved texture and moisture retention. This study demonstrates the valorization of corn stalk waste into a valuable DF source, supporting sustainable resource utilization and the development of clean-label, fiber-enriched food products aligned with circular economy principles.

Stock Price Prediction of TLKM and BBCA Using SVR, Random Forest, and LSTM

2026-01-10T18:01:56+07:00

Stock price prediction is a significant challenge in financial market analysis due to the influence of many dynamic and nonlinear factors. This study compares three machine learning methods, namely Support Vector Regression (SVR), Random Forest (RF), and Long Short-Term Memory (LSTM), in predicting the stock prices of PT Telekomunikasi Indonesia Tbk (TLKM) and PT Bank Central Asia Tbk (BBCA) for the period 2019–2023. Data were obtained from Yahoo Finance (15). Model Performance Comparison for TLKM Stock, the testing results show that LSTM achieved RMSE of 0.040093, MAE of 0.029849, and R² of 0.905330, indicating the best performance compared to SVR and Random Forest. Random Forest had an RMSE of 0.138295 and an MAE of 0.114423, while SVR had the highest RMSE at 0.238130. Model Performance Comparison for BBCA Stock: The testing results show that LSTM achieved RMSE of 0.055023, MAE of 0.048056, and R² of 0.657730, indicating the best performance compared to SVR and Random Forest. Random Forest had an RMSE of 0.252568 and an MAE of 0.236129, while SVR had the highest RMSE at 0.6211363. This confirms the LSTM model's effectiveness in capturing temporal patterns in stock data (5), (9), (13).

Noise and Air Quality from Traffic in Mueang Nakhon Si Thammarat, Nakhon Si Thammarat Province

2026-04-01T10:56:35+07:00

Noise pollution and poor air quality are growing environmental concerns in rapidly developing Thai cities. This study assessed traffic-generated noise levels and ambient air quality at four signalized intersections in Mueang Nakhon Si Thammarat district, Nakhon Si Thammarat Province, in September 2022. Measurements were conducted at three peak-hour periods (07:00–09:00, 11:00–13:00, and 15:00–17:00) on both weekdays and weekends. Parameters included equivalent continuous noise level (Leq), oxygen (O₂), carbon monoxide (CO), carbon dioxide (CO₂), sulfur dioxide (SO₂), relative humidity, wind speed, and temperature. All four sites exceeded the Thai national noise standard (24-hr average ≤70 dB(A)) on weekdays, with Site 1 (Hua Thanon) recording the highest average of 73.5 dB(A). On weekends, Site 2 (Fountain Circle–Kanlayanee School) was the only site within the standard at 69.9 dB(A). CO concentrations at all sites (26.0–27.3 ppm) exceeded the Thai 8-hour ambient standard of 9 ppm, though they remained within the 1-hour limit of 30 ppm. O₂ levels were below the atmospheric reference of 20.9% at every site, while SO₂ was undetectable throughout. Environmental factors—particularly relative humidity, wind speed, and temperature—influenced both noise propagation and pollutant dispersion. Site 3 (Khu Khwang) showed the highest CO and CO₂ concentrations, attributed to the dense surrounding buildings, which restricted ventilation. These findings highlight the need for continuous environmental monitoring and traffic management interventions in Nakhon Si Thammarat's urban core.