Creative Science

Impact of alkaline salts loading on structural, optical and Near-infrared shielding properties of potassium tungsten bronze materials

2026-02-18T12:46:19+07:00

Increasing heat emissions through windows directly affect energy consumption in air conditioner systems. To address this challenge, potassium tungsten bronze (K_xWO₃) materials are used for near-infrared shielding. The materials provide high transmission in the visible region and strong absorption at infrared wavelengths. The optical properties of these materials depend on the ratio of alkali metal to tungsten, which determines the number of donor electrons available from the alkali metal, and also the extent of reduction of tungsten from its W⁶⁺ oxidation state to its W⁵⁺ state. This interplay between oxidation states gives rise to the phenomena of localized surface plasmon resonance (LSPR) and small polaron absorption. In this work, we investigated various values of x in K_xWO₃ where x = 0.1, 0.3, 0.5, and 0.7, using a high-energy ball milling method to synthesize the K_xWO₃powders. Characterization was conducted using X-ray diffraction (XRD) for crystalline structure, field emission scanning electron microscopy (FESEM) for powder morphology determination, X-ray photoelectron spectroscopy (XPS) for the study of the oxidation states of tungsten (W), and ultraviolet–visible–near-infrared) spectroscopy (UV–vis–NIR) for optical property investigation. The results provide correlations between the potassium ratio, the crystal structure, and the NIR shielding performance of potassium tungsten bronze materials.

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Hexagonal tungsten bronze particles were successfully synthesized by a facile ball milling process.
The optimal potassium loading with K/W ratio at 0.3 stabilized the hexagonal structure, which induced near-infrared absorption efficiency.
3-KWO film exhibited near-infrared shielding performance, which reduced indoor temperature by up to 4.6 °C compared with blank glass.

Calcination temperature-dependent structural and photocatalytic properties of green-synthesized ZnO nanostructures using Mitragyna speciosa leaf extract

2026-02-23T13:25:52+07:00

ZnO nanostructures were prepared by a green synthesis route using Mitragyna speciosa Korth. leaf extract as a natural reducing agent in deionized (DI) water. The effect of calcination temperatures on the material properties of green-synthesized ZnO was systematically investigated. Calcination temperatures ranging from 250 to 550 °C were selected to facilitate the complete decomposition of precursor compounds and residual organic components, considering the thermal stability of ZnO and plant-derived organic species. ZnO nanostructures were characterized by XRD to identify crystallinity, FE-SEM to observe surface morphology, FTIR to confirm chemical bonding, and BET analysis to measure specific surface area. The obtained ZnO photocatalyst was evaluated through rhodamine B (RhB) dye degradation assisted by the piezo-catalytic effect. The crystallinity, morphology, chemical bonding, surface area, and photocatalytic activity of naturally derived ZnO nanostructures were significantly altered by the calcination temperature, demonstrating their promise for environmental remediation

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Green synthesis of ZnO nanostructures was achieved using Mitragyna speciosa leaf extract in an environmentally friendly and sustainable approach.
Calcination temperature plays a key role in tailoring the crystallinity, morphology, and specific surface area of green-synthesized ZnO nanostructures.
Enhanced photocatalytic and piezo-assisted performance of green-synthesized ZnO nanostructures at low calcination temperature was observed.

Formulation development, physical stability, and preliminary safety screening of cosmetic emulsions containing banana peel extract

2026-02-26T14:29:30+07:00

The purpose of the present study was to prepare and evaluate a lotion and cream containing banana peel extract for cosmetic application. The developed prototype formulations contained thickeners and emollients, and their physical, chemical, and preliminary sensory characteristics were evaluated. Experimental techniques used particle size analysis, viscosity and pH measurement as well as in vitro irritancy on reconstructed human epidermis (OECD 439). Cytocompatibility was also evaluated using HaCaT cell lines through the MTT assay. Both lotion and cream formulations containing banana peel extract (0.1% w w^-1) showed consistent appearance and physical properties under the tested conditions. Skin irritation test results showed that the formulations are classified as non-irritant (viability > 50% relative to the negative control) according to OECD TG 439 criteria. Cytotoxicity studies revealed that all formulations at 1000 µg mL⁻¹ (extract-equivalent) were non-cytotoxic, maintaining cell viability above 70% in accordance with ISO 10993-5. These results suggest preliminary feasibility and in vitro safety under the tested conditions, indicating the potential of banana peel extract as a sustainable cosmetic ingredient for further dermatological development.

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Both the lotion and cream formulations with banana peel extract demonstrated excellent physical stability, uniform particle distribution, and superior skin-friendly sensory attributes, confirming their suitability as safe topical cosmetic products.
In vitro safety testing showed that all developed formulations were non-cytotoxic (viability >80% and <20% cytotoxicity at 1,000 µg ml^-1), with cream exhibiting the lowest cytotoxicity—highlighting the potential of banana peel extract as a biocompatible ingredient for advanced dermatological applications.

Studies morphological and determination of folic acid, β-glucans, protein and fiber of local edible mushrooms in Loei province

2026-01-25T20:17:04+07:00

This study examined the morphology and quantified folic acid, β-glucans, protein, and fiber contents in 25 species of local edible mushrooms from Loei Province. This study aimed to analyze the functional nutrients of local edible mushrooms collected from Loei Province. Morphological characteristics of the cap/pileus, stem, gills, flesh, and special features like veils and rings were analyzed, revealing distinct differences useful for effective species classification and reflecting the biodiversity adapted to varied local environments. Quantitative analysis was performed in triplicate using high-performance liquid chromatography for folic acid and beta-glucan. The results showed that folic acid ranged from 0.09 to 1.52 mg 100g^-1, β-glucans from 183.46 to 1197.41 mg 100g^-1, protein from 1.31 to 35.88%, and fiber from 0.15 to 9.49%. The highest folic acid content was found in Coprinus fimetarrius, β-glucans in Lentinus squarrosulus, protein in Tylopilus plumbeoviolaceus, and fiber in Phallus indusiatus. Variations in these nutritional components were influenced by physiological traits, nutrient accumulation capacity, environmental conditions, soil fertility, temperature, and rainfall in the collection areas. The research findings hold scientific value and can serve as baseline data for further development into products that enhance the economic value of local edible mushrooms while expanding consumer choices for diverse mushroom consumption.

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Morphological traits (cap, gills, stipe, base) enable precise identification of 25 Loei Province edible mushrooms, distinguishing safe species from toxic relatives for food safety.
Coprinus fimetarrius exhibited highest folic acid (0.15 mg/100g); lowest in Russula virescens (Schaeff.) Fr., Russula emetic (Schaeff. & Fr.) S.F.Gray., Boletus edulis Bulliard ex Fries., Craterellus odoratus (Schwein.) Fr., Russula foetens (Pers.) Fr., and Russula cyanoxantha (Schaeff. Ex Secr.) Fr. (0.01 mg/100g).
Lentinus squarrosulus showed peak β-glucan content (11.97 mg/g); Boletellus emodensis (Berk.)Sing. lowest (1.83 mg/g), highlighting species-specific soluble fiber variation.
Tylopilus plumbeoviolaceus contained highest protein (26.39%); Amanita hemibapha (Berk.& Br.) Sacc. lowest (1.31%), reflecting genetic and environmental protein accumulation differences.
Phallus indusiatus had maximum fiber (9.49%); Galiella rufa (Schweinitz) Nannfeldt & Korf. minimum (0.15%), demonstrating dietary fiber diversity for functional food applications.
Nutrient variations driven by genetics, soil fertility, temperature, humidity, and growth stage align with global research, supporting biodiversity conservation and economic utilization.

Development of strategies for promoting early childhood development by elderly village health volunteers

2026-05-07T06:27:39+07:00

This mixed-methods study aimed to develop strategies for promoting early childhood development (ECD) by elderly Village Health Volunteers (VHVs) in Phetchaburi Province, Thailand. The study addressed limited evidence on how elderly VHVs can practically support ECD through intergenerational community-based work. Pender’s Health Promotion Model explained elderly VHVs’ participation in ECD promotion, while Giddens’ Structuration Theory explained structural and social conditions affecting community-based practice. Quantitative data were collected from 400 elderly VHVs and analyzed using frequency, percentage, mean, standard deviation, and Pearson’s correlation coefficient. Qualitative data were obtained from 30 key informants through in-depth interviews and analyzed using content analysis until data saturation was reached. The quantitative findings showed that elderly VHVs had a moderate overall level of readiness for ECD promotion (mean = 3.03, SD = 0.48). Their main strengths were willingness to participate, awareness of child development, and pride in community contribution, whereas their main limitations included physical constraints, limited ECD skills, weak peer-learning mechanisms, and low digital communication access. Pearson’s correlation analysis indicated that past ECD promotion activities (r = .505), formal training (r = .468), and direct childcare experience (r = .425) were significantly associated with the ECD promotion situation (p < .01). Qualitative findings confirmed the need for practical manuals, mentoring, safe activity spaces, digital support, and social recognition. The study produced six strategies: defining common goals, disseminating positive attitudes, developing practices and intergenerational interaction, delivering empowerment and digital resources, determining standards and procedures, and dignifying social recognition and values. At the policy level, these strategies can be integrated into local quality-of-life development plans, DSPM-based child development surveillance systems, and local budget allocation. At the community level, they provide an operational model for co-creating child-development activities, referral pathways, community mentor systems, and age-friendly volunteer roles.

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Developed the 6-D Strategy to strengthen elderly VHVs’ capacity in ECD promotion.
Identified past ECD activities, formal training, and childcare experience as key associated factors.
Integrated digital support and intergenerational activities to address operational barriers.
Proposed multisectoral collaboration among public health agencies, local authorities, universities, families, and community networks.

Effects of processing methods of dried black soldier fly larvae as top-dressing replacement in layer diets on performance, egg quality, and economic returns

2026-05-11T10:13:34+07:00

Feed cost is a major egg production expense. This study evaluated the effects of differently processed dried black soldier fly larvae (BSFL) on laying performance, egg quality, and economic returns. Forty commercial brown laying hens (30 weeks old) were assigned to four treatments with 10 replicates each in a completely randomized design for 6 weeks. Treatments comprised a commercial diet (control) and diets with 10% top-dressing replacement using hot-air dried larvae (T2), boiled and hot-air dried larvae (T3), or autoclaved and hot-air dried larvae (T4). Data were analyzed using repeated measures ANOVA. Hen-day egg production, egg weight, egg mass, and feed conversion ratio were significantly affected by treatment, time, and treatment × time interaction (p<0.001). T2 and T3 generally showed improved production performance and feed efficiency compared with the control. Egg weight was affected by treatment (p=0.003) and treatment × time interaction (p=0.025), whereas albumen and yolk proportions were unaffected (p>0.05). Shell proportion (p=0.024), yolk color (p=0.035), and shell thickness at the sharp end (p=0.045) differed among treatments, whereas most internal egg quality and eggshell traits were unaffected. BSFL reduced feed cost per egg by 0.25, 0.37, and 0.05 THB per egg, equivalent to approximately 0.008, 0.012, and 0.002 USD per egg, for T2, T3, and T4, respectively, compared with the control. Net return increased by 109.44, 119.90, and 42.36 THB, equivalent to approximately 3.50, 3.83, and 1.35 USD, respectively. T3 had the highest benefit–cost ratio. Because top-dressing increased dietary protein and fat contents relative to the control, responses may partly reflect differences in nutrient density among treatments. Overall, the results suggest that replacing 10% of commercial feed with dried BSFL using a top-dressing approach can maintain laying performance and may improve economic efficiency, particularly with boiled and hot-air dried larvae, under the conditions of this study.

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Replacement of commercial feed with 10% dried black soldier fly larvae using a top-dressing approach
Processing methods of larvae influenced production performance, egg quality, and economic returns
Boiled and hot-air dried larvae showed the most favorable overall performance and benefit–cost ratio

Parametric study of wall-mounted annular ring fins for heat transfer enhancement in a flat-bottom cookstove using CFD

2026-05-05T11:15:28+07:00

Flat-bottom biomass cookstoves, widely used in developing countries, typically achieve thermal efficiencies below 20% because most combustion energy is lost with the exhaust gas before reaching the pot. Enhancing convective heat transfer at the pot wall therefore represents the most direct pathway to improved efficiency. Although annular fins are well-established passive heat transfer enhancers in industrial heat exchangers, their geometric design space remains unexplored within cookstove combustion chambers. This study addresses that gap through a parametric computational fluid dynamics (CFD) investigation of wall-mounted ring fins in a flat-bottom biomass cookstove. A three-dimensional steady-state CFD model, developed in ANSYS Fluent using the SST k–ω turbulence model with enhanced wall treatment, was validated against measured temperatures at three vertical levels and the chimney outlet. The model showed close agreement at the outlet (2.21% error), while larger discrepancies at the interior levels (16–28%) were attributed to the simplified uniform-inlet boundary condition. Using a one-factor-at-a-time design, thirteen configurations were evaluated across four geometric parameters: fin height, blockage ratio, tier count, and installation height. Fin height showed a non-monotonic effect, with thermal performance peaking at a moderate height before excessive blockage limited further gains. Tier count showed a monotonic trend, reaching a thermal performance factor (TPF) of 1.118 with three tiers. Installation height emerged as the most influential parameter: a single fin positioned near the hot gas inlet achieved the highest performance, with a TPF of 1.138, corresponding to a 14.1% increase in heat transfer to the pot at a pressure-drop penalty of only 0.68%. These findings identify axial position as the primary parameter governing thermal performance. A single fin near the hot inlet offers a low-cost, retrofit-ready route to higher cookstove efficiency, aligned with Sustainable Development Goal 7.

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Annular ring fins welded to the inner wall of a flat-bottom cookstove are proposed as a passive heat transfer enhancement strategy.
A parametric CFD study covering 12 fin configurations plus a baseline examines the effects of fin height (20–50 mm), number of tiers (1–3), and installation height.
Blockage ratios of 0.20–0.50 are evaluated using the SST k-ω turbulence model with enhanced wall treatment in ANSYS Fluent.
Thermal Performance Factor (TPF) is used to identify the optimal configuration balancing heat transfer enhancement against pressure drop penalty.

Tree species diversity and aboveground carbon stocks in Ban Nong Nae community forest: implications for ecosystem rehabilitation

2026-05-07T11:23:30+07:00

This study investigated tree species diversity, forest structure, and aboveground carbon stocks in the Ban Nong ÍNae Community Forest, Chachoengsao Province, Thailand. The objective was to quantify ecological attributes and examine the relationships between species diversity, forest structure, and carbon storage within a community forest ecosystem. Field data were collected from a 0.4 ha (4,000 m²) permanent plot by recording tree species composition and structural measurements. Aboveground biomass was estimated using the allometric equations developed by Ogawa et al. (1965) combined with standard carbon fraction values. A total of 27 tree species belonging to 19 families and 258 individuals were recorded, corresponding to a stand density of 645 individuals ha⁻¹. The Shannon–Wiener diversity index (H′) was 2.59, and the evenness index (E) was 0.795, indicating moderate species diversity with a relatively even distribution of individuals among species. Total aboveground biomass was estimated at 48,384.24 kg, resulting in a carbon stock of 23,353.87 kg C (58.38 Mg C ha⁻¹). Carbon stocks were unevenly distributed, with 77.8% concentrated in six dominant species, notably Pterocarpus macrocarpus. This pattern indicates that carbon storage was strongly influenced by stand structural composition and species dominance, particularly the contribution of a small number of canopy-forming species. Overall, the findings suggest that aboveground carbon storage is closely associated with forest structural characteristics and dominant species composition. These findings provide baseline data for ecological assessment and carbon accounting in community forest ecosystems and highlight the importance of species diversity and forest structural in supporting ecosystem rehabilitation.

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Ban Nong Nae Community Forest exhibits moderate-to-high tree diversity (H' = 2.590) and high evenness (E = 0.795), indicating a stable and resilient ecosystem structure.
Aboveground carbon stocks are primarily driven by six key framework species, which account for 77.8% of the total carbon despite high overall species richness.
Aboveground carbon stocks are primarily driven by six key framework species, which account for 8% of the total carbon despite high overall species richness.

Multidimensional livelihood-capital deprivation and income-defined household poverty in Sakon Nakhon, Thailand: Explanatory, predictive, and association-rule evidence

2026-06-18T15:34:55+07:00

This study examines household poverty in Sakon Nakhon province, Thailand, using a livelihood-capital household survey containing 2,128 records and 73 variables. Household poverty in Sakon Nakhon, Thailand, remains a pressing policy concern, yet existing evidence rarely integrates explanatory, predictive, and co-occurrence evidence within a single locally grounded study. Poverty status was derived by comparing per-capita monthly income with the constant poverty-line field in the dataset; after preprocessing, 1,562 households were classified as poor and 497 as non-poor (poor-class share: 75.86%). Three evidence streams were separated: explanatory statistical analysis, leakage-controlled predictive modeling, and association rule mining (ARM). Group comparisons and robust logistic regression showed that Human Capital (OR = 0.318), Social Capital (OR = 0.568), Physical Capital (OR = 0.513), and agricultural green-book status (OR = 0.721) were associated with lower poverty odds, while household size (OR = 1.487) was associated with higher odds. Extra Trees achieved the strongest ROC-AUC (0.730); L2-regularized logistic regression achieved the strongest balanced accuracy (0.658). ARM identified recurring poverty-associated profiles in Kusuman district, characterized by low social participation and large households with low physical or social capital. This study demonstrates a reproducible, data-driven workflow for community-level poverty screening and policy prioritization in resource-constrained provincial settings. Its creative science contribution lies in integrating livelihood-capital theory, explainable statistical modeling, leakage-controlled machine learning, and association-rule mining into a single practical framework for identifying locally relevant poverty profiles and supporting sustainable community development.

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Human Capital, Social Capital, and household size are the strongest non-income correlates of income-defined poverty in Sakon Nakhon, Thailand, with logistic regression confirming lower poverty odds for higher human (OR = 0.318) and social capital (OR = 0.568), and higher odds for each additional household member (OR = 1.487).
Extra Trees achieved the best predictive discrimination (ROC-AUC = 0.730) among leakage-controlled machine-learning models, demonstrating that non-income livelihood-capital features carry meaningful poverty-screening signal, though moderate performance cautions against automated eligibility decisions.
Association rule mining revealed interpretable deprivation co-occurrence profiles, particularly involving Kusuman district with low social participation and large households with low physical or social capital, providing actionable patterns for local poverty screening and policy prioritization.

Performance evaluation of machine learning models for multi-output building energy prediction

2026-05-20T09:27:33+07:00

Accurate prediction of building heating and cooling loads is central to energy-efficient design, and because these loads are strongly correlated, they represent a suitable multi-output regression problem. This study compares six models from three families—linear (Linear Regression, Polynomial Regression), kernel-based (Support Vector Regression, Kernel Ridge Regression), and gradient-boosting ensembles (XGBoost, LightGBM)—for predicting the heating (y1) and cooling (y2) loads, and additionally evaluates a joint neural network (Joint NN) that predicts both outputs together. The models were assessed on the publicly available Energy Performance of Buildings dataset, comprising 768 samples with eight input variables and two highly correlated outputs (r = 0.98). Performance was measured by mean absolute error (MAE), mean relative error (MRE), and mean squared error (MSE) using 10-fold cross-validation repeated 100 times, reported as mean ± standard deviation. LightGBM achieved the lowest error on both outputs (MAE = 0.0077 ± 0.0009 for heating and 0.0173 ± 0.0022 for cooling), reducing MAE by 15.4% and 37.5% relative to the next-best model, XGBoost. Paired statistical tests confirmed that this advantage was significant across models. Although the two outputs are strongly correlated, the joint neural network did not outperform the independent ensembles on this moderate-sized dataset, suggesting that strong per-output models are better suited to data of this size. Residual analysis supported these findings, with LightGBM producing residuals randomly dispersed around zero. Overall, the study combines multiple error metrics, statistical testing, and residual diagnostics to guide model selection in correlated multi-output energy prediction.

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Compared six independent models and a joint neural network for multi-output building energy prediction.
LightGBM gave the lowest error on both heating and cooling loads, confirmed by paired statistical tests.
Joint modeling did not outperform independent models on this moderately sized, strongly correlated dataset.
The cooling load was consistently harder to predict than the heating load across all models.
Feature importance identified relative compactness and glazing variables as the main load drivers.

Development and performance evaluation of an innovative community-scale single-pillar pyrolysis reactor for converting plastic waste into alternative liquid fuel

2026-07-22T08:46:05+07:00

Plastic waste accumulation has become a critical global environmental challenge due to the increasing generation of non-recyclable plastics and the growing demand for sustainable waste-to-energy technologies. This study developed and evaluated an innovative community-scale single-pillar pyrolysis reactor for converting non-recyclable polypropylene (PP) and polystyrene (PS) waste into alternative liquid fuel under catalyst-free, oxygen-limited conditions. The system integrates a pyrolysis chamber, an externally heated combustion chamber fueled by waste lubricating oil, a vertical water-cooled condenser, and a vapor-recycling unit into a compact configuration suitable for decentralized applications. Reactor performance was evaluated using two PP:PS feedstock compositions (50:50 and 60:40, w w^-1). Each batch processed 10 kg of plastic waste (n = 3), producing 8.03 – 8.27 L of pyrolysis oil within 190 – 200 min. The 60:40 feedstock yielded numerically higher liquid fuel production (67.00 ± 1.91 wt.%), fuel conversion efficiency (73.85 ± 2.31%), oil productivity (3.73 ± 0.23 L h⁻¹), and higher heating value (45.73 ± 0.23 MJ kg⁻¹), together with a lower estimated gas yield (23.73 ± 2.16 wt.%). However, these differences were not statistically significant (p > 0.05), indicating stable and reproducible reactor performance across both feedstock compositions. Field validation following technology transfer was conducted in
19 communities in Loei Province, Thailand. The system achieved an average plastic reduction efficiency of 92.96 ± 0.87%, reduced accumulated plastic waste by 55.51 ± 22.41%, and demonstrated successful utilization of the recovered fuel in agricultural machinery and municipal crematoriums. These findings demonstrate that the proposed single-pillar reactor provides a practical, low-cost, and scalable decentralized waste-to-energy technology that supports circular economic implementation and sustainable community-based plastic waste management.

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A single-pillar reactor converted PP–PS waste into alternative liquid fuel.
Liquid fuel yield reached 67.00 wt%, with plastic reduction above 90%.
Pyrolysis oil achieved a heating value of up to 45.73 MJ kg⁻¹.
Blended fuels operated successfully in agricultural equipment.
The reactor was validated across 19 communities in Thailand.

A health planning expert system for promoting quality of life among older adults in Buriram province

2026-06-19T20:07:52+07:00

This study aimed to (1) develop a knowledge base for health planning among older adults and (2) develop and transfer an expert system to support personalized health planning and promote the quality of life of older adults in Buriram Province, Thailand. This applied research adopted the System Development Life Cycle (SDLC), comprising five main phases: Knowledge Acquisition and Contextual Requirements Analysis; Ontology Design and Knowledge Base Construction; System Analysis, Design, and Development based on object-oriented principles; System Testing and Performance Evaluation; and Technology Transfer. The knowledge base was developed using an ontology-based approach and was grounded in three core health planning principles: diet, exercise, and emotional well-being. It comprised 18 main classes and 12 rule sets containing a total of 144 inference rules. The developed expert system was implemented as a mobile application for managing personal profiles, health histories, dietary behaviors, and exercise habits. Based on these data, the system generates personalized recommendations for food, exercise, and recreational activities according to the individual health conditions of older adults. The performance of the inference mechanism was evaluated using six case studies by comparing system-generated recommendations with expert judgments. The results showed an average Recommendation Matching Rate (RMR) of 0.567, with average precision, recall, and F1-score values of 0.893, 0.788, and 0.836, respectively. These findings indicate that the system achieved high precision in generating recommendations and demonstrated a good overall level of agreement with expert judgments. The usability evaluation yielded a high overall mean score (X̄ = 3.92), indicating favorable user acceptance of the developed system. The developed technology was subsequently transferred to the target users to support its practical application in health planning for older adults.

GRAPHICAL ABSTRACT

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An expert system was developed to transform elderly health information into personalized lifestyle recommendations.
The system integrates 144 clinical knowledge-based rules for adaptive health planning in older adults.
Validation with expert judgments demonstrated high recommendation reliability and strong user acceptance.