Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is a serious-global public health issue. A total of 292 E. coli isolates obtained from fecal samples of pigs in Central (n = 103) and Northeastern (n = 189) provinces of Thailand were included in this study. Eighty-six E. coli isolates were phenotypically confirmed to be β-lactamase producers (29.5%) and screened for the presence of β-lactamase genes. The genes in CTX-M family was most frequently found (90.7%). The blaCTX-M-15 gene (59.3%) was predominantly identified CTX-M genotype, followed by blaCTX-M-14 (31.4%) and blaCTX-M-4 (25.6%). The blaTEM-1 gene was prevalent (75.6%). The blaCTX-M-4 and blaCTX-M-14 genes were located on conjugative plasmid. The results highlight healthy pigs as reservoirs of ESBL-producing E. coli carrying ESBL genes that could be horizontally transferred.

Background: Monk healers provide an accessible and popular service in Southeast Asia, but little is known on the substance use status of their clients. This investigation intended to assess and compare the rate and correlates of substance use disorders in two different treatment settings (monk healers=MH and primary health care=PHC) in Thailand. Methods: In a cross-sectional study, 1024 patients (591 of MH and 613 of PHC) responded to screening measures of the “World Health Organization Alcohol, Smoking, and Substance Involvement Screening Test Lite”, and two common mental disorders (major depression and generalized anxiety disorder) from November 2018 to February 2019. Logistic regression was used to estimate the determinants of any substance use disorder in the MH and PHC setting. Results: The prevalence of substance use disorder was higher in MH clients than PHC patients: any substance use disorder 11.7% (95% Confidence Interval-CI: 9.3%-14.5%) vs 5.4% (95% CI: 3.9%-7.5%), tobacco use disorder 7.6% (95% CI: 5.7%-9.9%) vs 2.5% (95% CI: 1.5%-4.0%), alcohol use disorder 10.0% (95% CI: 8.4%-13.6%) vs 4.3% (95% CI: 3.0%-6.3%), any drug use disorder 4.2% (95% CI: 2.8%-6.1%) vs 0.3% (95% CI: 0.08%-1.3%), and any past three months drug use 8.2% (95% CI: 6.2%-10.7%) vs 1.5%, 95% CI: 0.8%-2.8%). In adjusted logistic regression analysis, among MH clients, male sex (Adjusted Odds Ratio-AOR: 9.52, 95% Confidence Interval-CI: 5.06-17.92) was positively, and were married (AOR: 0.32, 95% CI: 0.16-0.61) and high social support (AOR: 0.40, 95% CI: 0.16-0.99) were negatively associated with any substance use disorder. Among PHC patients, male sex (AOR: 7.05, 95% CI: 2.99-16.63) was positively and age (AOR: 0.95, 95% CI: 0.92-0.98) was negatively associated with any substance use disorder. Conclusion: The proportion of substance use disorders among MH attendees was more than twice that of PHC attenders in Thailand, calling for collaboration in controlling substance use disorders between the two treatment systems.

Despite the importance of influenza vaccination for healthcare workers (HCWs), their uptake remains challenging. This study aimed to measure influenza vaccine hesitancy among HCWs in Nakhon Phanom province, Thailand. A representative cross-sectional survey was conducted at six hospitals during August – September 2020 using a self-administered questionnaire. HCWs delaying getting influenza vaccines, accepting but unsure, or refusing with doubts were categorized as hesitant. Those accepting without any doubts were classified as non-hesitant. Vaccine hesitancy determinants were identified by multivariable logistic regression analysis. A total of 338 participants (97%) completed the questionnaires; most were female nurses working at district hospitals without pre-existing chronic medical conditions. Nearly 60% of participants (197/338) exhibited influenza vaccine hesitancy, and significant factors included age above 50 years adjusted odds ratio [aOR] 3.2, 95% CI 1.3-8.5), fair knowledge of influenza/vaccination (aOR 0.4, 95% CI 0.2-0.8), and negative influence of other HCW (High level– aOR 2.3, 95% CI 1.1-4.8; Moderate level- aOR 2.1, 95% CI 1.1-4.4). Imparting updated information to the HCW combined with positive guidance from influential peers may help reduce this hesitancy.

This study examines the prevalence and determinants of smartphone addiction (SA) in a sample of 825 Muslim secondary school students from three provinces along the southern border of Thailand. Employing purposive sampling, the research highlights a concerning 70% rate of SA, surpassing the rates observed in other Asian demographics. The investigation reveals a robust link between parental education levels and smartphone usage among adolescents. Utilizing a structural equation model (SEM), family functioning dimensions such as ‘Emotional Status’ and ‘Discipline’ are shown to have a considerable impact on SA. Contrary to expectations, enhanced ‘Family Support’ has emerged as a potential risk factor, suggesting nuances in family dynamics that may contribute to SA. The findings advocate for the reinforcement of family functioning and call for initiatives to improve digital literacy and foster open communication between parents and children. However, the reliance on self-reported measures and the cross-sectional nature of the study underlines the necessity for more expansive future research to validate these findings and explore underlying mechanisms.

Rapid urbanization has changed the structure and function of natural ecosystems, especially the floodplain ecosystems in SE Asia. This paper describes the ecological structure of vegetation stands and the usefulness of satellite images to characterize a disturbed tropical urban forest located in the lower floodplain of the Chao Phraya River, Thailand. Nine representative plots were established in Bang Kachao peninsula in 4 tropical urban forest types: rehabilitation forest, home-garden agroforestry, mangrove and park. The correlation between NDVI and LAI obtained from satellite images and plant structure from field surveys were analyzed. The NDVI had the highest relationship with stand factors for the number of families, number of species, Shannon-Weiner’s diversity index and total basal area. The LAI had the highest correlation with total basal area, number of canopy layers, stand density and canopy density. Linear regression predicted the correlation between NDVI and LAI with stand factors as show above. The trend in NDVI and LAI reflected the urban forest type, being high in rehabilitation and mangrove forests, moderate in home-gardens and low in parks. Future urban planning of the Bang Kachao peninsula should focus on rehabilitation to increase the biodiversity and complexity of the urban forest.

Organic agriculture based on participatory guarantee system (PGS) has been promoted as a tool for sustainable ecosystem, self-reliance and poverty alleviation of smallholder farmers in Thailand. However, specific criteria are required to certify as organic products. In this paper, the researchers present the collaboration of smallholder farmers practicing organic farming based on participatory guarantee system in four Thai provinces: Nong Bua Lam Phu, Nakhon Phanom, Ubon Ratchathani and Nakhon Ratchasima. One hundred thirty-five smallholder farmers were purposively selected as the informants. In depth interviews were conducted to conceptualize. The participatory guarantee system management considering their diverse agricultural background and socio-economic conditions. Main findings concluded that motivations for PGS were restoration soil quality and decreasing yield. Key factors for sustainable adaptation are policy support in terms of financial measures and capacity building.

Over the past decade, Thailand has experienced a rapid increase in its elderly population. Many unfavorable health outcomes among elderly people are associated with nutrition. Nutrition in elderly people is affected by physical, mental, and social factors. This study explored the food choices and dietary practices among community-dwelling elderly people in Thailand from the perspective of both caregivers and the elderly people themselves. Six focus group discussions and six semi-structured interviews were conducted in the Samut Sakhon Province of Thailand. A combination of deductive and inductive thematic analyses was adopted, and the results show that physical and mental factors and societal factors are important determinants of food choices. Moreover, a changing food environment and economic factors were found to affect food choices. Issues of trust in food safety and food markets were highlighted as growing issues. Therefore, fostering healthy food choice interventions that consider both environmental and societal aspects is necessary.

Three decades ago, human arsenic (As) contamination has been recognized in Ron Phibun, a sub-district with tin mining activity in southern Thailand. Since then different government bodies have attempted to mitigate the As-contamination problem by providing safe water in households. The most recent study conducted during 2000-2002 reported only a small fraction of population still had high urinary As level. Less attention has been paid to this issue afterwards. The present study aimed to re-assess the current situation, including human As contamination, water use behavior as well as identify risk factors of elevated As concentration among residents of Ron Phibun. The survey of 560 participants living in Ron Phibun with urinary As assessment was conducted. The median urinary As concentration of study participants was higher than normal. Consumption of shallow well water, a source generally considered as As-contaminated, was higher than a previous survey. A significant association was observed between urinary As concentrations and water sources for drinking and cooking. Gender and educational level were found to be associated with urinary As concentration. Significant associations between urinary As concentration and certain diseases (respiratory diseases, dermatitis, and dyslipidemia) were observed. The findings suggested further investigation of all water sources in the area for As contamination.

Aim: This research is aimed at examining the cost-effectiveness of olanzapine versus risperidone in dementia patients with behavioural and psychological symptoms in Thailand. Methods: An existing Markov model based on a critical review through the comprehensive literature search and a justification for the most appropriate model for a Thai setting was adapted to simulate the disease progression of patients with dementia with behavioural disturbances until their need for full-time care (FTC). The time to the FTC state was estimated by a predictive equation developed by Rive et al. (2010). The model was conducted to assess the expected costs and outcomes associated with olanzapine compared with risperidone for Thai patients with BPSD aged 60 years and above. This model performed over a five-year time horizon with a one-month cycle length based on a societal perspective. The incremental cost-effectiveness ratio was used as the estimated outcome. Sensitivity analyses were also conducted to demonstrate the robustness of the results. Results: Over 5 years, olanzapine was found to be a cost-effective therapeutic option for the treatment of behaviourally disturbed patients with dementia compared with risperidone, in Thailand from a societal perspective (ICER < THB 160,000). The model underwent extensive sensitivity analyses, which also confirmed that olanzapine was the dominant strategy following the base-case findings. Conclusions: By comparison with risperidone, the model suggests that olanzapine can be regarded as a cost-effective therapeutic strategy for the management of patients with behavioural and psychological symptoms in Thailand.

Infection of liver flukes (Opisthorchis viverrini) is partly due to their suitability for habitats in sub-basin areas, which causes the intermediate host to remain in the watershed system in all seasons. Spatial monitoring of fluke infection at the small -basin analysis scale is important because this can enable analysis at the level of the spatial factors involved and influencing infections. A geographic weighted regression model was developed to analyze the spatial characteristics of liver fluke infection, aiming to 1. analyze the spatial factors associated with human liver fluke infection according to sub-basin boundaries and 2. generate an alternative model for enhancing the effectiveness of preventive public health management to reduce the risk of liver fluke infection in humans. The number of infected persons was obtained from local authorities and converted into a percentage of infected people and generated as raster data with a heat map so that the data were continuous and defined as dependent variables. The independent set consisted of nine variables, both vector and raster data, that correlated the location with the village location of an infected person. The results showed that the variables X5stream, X7ndmi, and X9savi were statistically significantly correlated to the percentage of infected people, with the t-stat and p-value being (-2.068, 1.875, and -2.661) and (0.048, 0.034, and 0.021), respectively. The GWR model was able to increase accuracy more than the comparable models such as OLS, in all tests of the four alternative models, with an accuracy increase in R2 of 7.69% (0.576 to 0.624). This study confirms that the development of spatial models with GWR models can screen for factors associated with liver fluke infection at the level of small spatial units such as sub-basins.

Shales are well known for their strong anisotrophic properties. The classical Athy’s model on the exponential porosity reduction with the depth commonly uses based on localities only. Shale compaction curve affects the results of the basin modeling as it is important input data, thus the standard compaction curve of shales needs to be established. This study provided a new data and complies available data of Thailand shales to propose the new empirical relationship among porosity, burial depth, and geological age. The numerical data of the geological time were estimated by the application from the relationship of velocity and depth in each geological ages. The variation of the Thailand shale data due to the different geological ages was found in this study. Finally, the standard curve of shale compaction proposed by Puttiwongrak et al. [9] was examined and confirmed by this research findings.

The escalating concerns over climate change have propelled industries worldwide to seek innovative strategies for mitigating greenhouse gas emissions. Within the energy sector, Carbon Capture and Storage (CCS) technology emerges as a promising solution to curtail emissions and foster sustainable development aims for net zero approach. The research delves into the role of government support in expediting CCS adoption for the maximum potential of 9.79 MtCO2 storage from six major refinery plants. The refineries mentioned above are anticipated to necessitate an initial capital investment of approximately 18,307 million THB. This research focuses on potential business model proposals appropriate for a country's context, specifically applying CCS technology to Thai oil refining sector. To achieve the realization of CCS within the context of this study, a combination of three essential measures will be required: tax incentives, carbon credits, and grants. This process will commence with the implementation of tax incentives, followed by an increase in the carbon price within the country. Finally, the establishment of a dedicated fund, funded through deductions from oil excise tax revenue, will play a pivotal role in facilitating the necessary financial support for the emergence of CCS.

This study aims to identify the optimal combination of microphysics (MP) and cumulus (CU) parameterization schemes for accurately simulating heavy to violet rainfall events associated with Tropical Cyclones (TCs) and atmospheric disturbances in Thailand using the coupled Weather Research and Forecasting (WRF) and Regional Oceanic Model (ROMS), hereafter referred to as WRF-ROMS. Three CU schemes, namely Betts–Miller–Janjic (BMJ), Grell 3D Ensemble (G3), and Kain–Fritsch (KF), along with three MP schemes, namely Eta (ETA), Purdue Lin (LIN), and WRF Single-moment 3-class (WSM3), are selected for the sensitivity analysis. Seven instances of heavy to violent rainfall in Thailand, occurring during summer season of 2020 and associated with tropical storms and atmospheric disturbances, are simulated using all possible combinations of the chosen physics schemes. The simulated rain intensities are compared against observations from the National Hydroinformatics Data Center. Performance was assessed using the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) metrics. The models showed proficiency in predicting light to moderate rainfall, with certain combinations performing better in specific rainfall categories. However, forecasting heavy and violent rainfall proved challenging for all models and lead-time forecasts. Specific combinations, particularly those incorporating the KF scheme, demonstrated superior prediction of heavy to violent rainfall. The FAR values increased with lead-time and rain intensity, and the KF scheme combinations showed improved predictions of intense rainfall with lower FAR values. The CSI values indicated comparable performance between the control model and combination models across light to heavy rain categories, with the KF scheme showing better predictions for longer lead-times. However, accurately predicting intense rainfall remained limited. These findings highlight the need for further improvements, including refining model parameters and exploring advanced techniques to enhance accuracy and skill, particularly for longer-term forecasts. Sub-seasonal to seasonal prediction should be considered to extend forecast capabilities.

This study addresses the limited coverage of regulatory monitoring for particulate matter 2.5 microns or less in diameter (PM2.5) in Thailand due to the lack of ground station data by developing a model to estimate daily PM2.5 concentrations in small regions of Thailand using satellite data at a 1-kilometer resolution. The study employs multiple linear regression and three machine learning models and finds that the random forest model performs the best for PM2.5 estimation over the period of 2011-2020. The model incorporates several factors such as Aerosol Optical Depth (AOD), Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Elevation (EV), Week of the year (WOY), and year and applies them to the entire region of Thailand without relying on monitoring station data. Model performance is evaluated using the coefficient of determination (R2) and root mean square error (RMSE), and the results indicate high accuracy for training (R2: 0.95, RMSE: 5.58 μg/m3), validation (R2: 0.78, RMSE: 11.18 μg/m3), and testing (R2: 0.71, RMSE: 8.79 μg/m3) data. These PM2.5 data can be used to analyze the short- and long-term effects of PM2.5 on population health and inform government policy decisions and effective mitigation strategies.

From the standpoint of Neoliberal Institutionalism, this study explores Malaysia's participation in activities that make energy the topic and/or object of foreign policies, whether through bilateral or multilateral engagements. This research, which aims to evaluate the relevance of energy in Malaysia's economy and diplomacy and to explain Malaysia's reason for its involvement in these cooperations, is necessary because of Malaysia's growing involvement in the global energy market. Information for this study was gathered from a variety of government sources, interviews, published statistical data, and previous studies. The study demonstrates how vital energy is to Malaysia's economy. The Lao PDR-Thailand-Malaysia-Singapore Power Integration Project (LTMS-PIP) initiative, in which Malaysia is participating, is evidence of the viability of multilateral power commerce in the area. The Peninsula Gas Utilisation (PGU) pipeline in Peninsular Malaysia and the Four-Fuel Diversification Policy 1981 (4FDP 1981), which increases natural gas utilisation, are related to Malaysia's participation in the Malaysia-Thailand Joint Development Area (MT-JDA). Malaysia would want to think about streamlining its energy administration.

Soil moisture plays a crucial role in various hydrological processes and energy partitioning of the global surface. The Soil Moisture Active Passive-Sentinel (SMAP-Sentinel) remote sensing technology has demonstrated a great potential in monitoring soil moisture at a scale greater than 1 km. This capability can be applied to improve weather forecast accuracy, enhance water management for agriculture, and climate-related disasters. Despite the techniques increasing used worldwide, its accuracy still requires field validation in specific regions like Thailand. In this paper, we report on extensive in-situ monitoring of soil moisture (from surface up to 1 m depth) at 10 stations across Thailand spanning the years 2021 to 2023. The aim was to validate SMAP surface soil moisture (SSM) Level 2 product over a period of two years. Using one month averaging approach, the study revealed linear relationships between the two measurement types, with the coefficient of determination (R-squared) varying from 0.13 to 0.58. Notably, areas with more uniform land use and topography such as croplands tended to have a better coefficient of determination. We also conducted detailed soil core characterization, including soil-water retention curves, permeability, porosity, and other physics properties. These soil properties were then used for estimating the correlation constants between SMAP and in-situ soil moistures using multiple linear regression. The results demonstrated R-squared values between 0.933 and 0.847. An upscaling approach of SMAP was proposed which showed a promising results when using 3-month average of all measurements in cropland together. The finding also suggest that the SMAP-Sentinel remote sensing technology exhibits significant potential for accurate soil moisture monitoring in diverse applications. Further validation efforts and research, particularly in terms of root zone depths and area-based assessments, especially in the agricultural sector, can greatly improve the technology’s effectiveness and usefulness in the region.

This study focuses on cardiovascular effects, particularly myocarditis and pericarditis events, after BNT162b2 mRNA COVID-19 vaccine injection in Thai adolescents. This prospective cohort study enrolled students from two schools aged 13–18 years who received the second dose of the BNT162b2 mRNA COVID-19 vaccine. Data including demographics, symptoms, vital signs, ECG, echocardiography and cardiac enzymes were collected at baseline, Day 3, Day 7, and Day 14 (optional) using case record forms.We enrolled 314 participants; of these, 13 participants were lost to follow up, leaving 301 participants for analysis. The most common cardiovascular effects were tachycardia (7.64%), shortness of breath (6.64%), palpitation (4.32%), chest pain (4.32%), and hypertension (3.99%). Seven participants (2.33%) exhibited at least one elevated cardiac biomarker or positive lab assessments. Cardiovascular effects were found in 29.24% of patients, ranging from tachycardia, palpitation, and myopericarditis. Myopericarditis was confirmed in one patient after vaccination. Two patients had suspected pericarditis and four patients had suspected subclinical myocarditis. Conclusion: Cardiovascular effects in adolescents after BNT162b2 mRNA COVID-19 vaccination included tachycardia, palpitation, and myocarditis. The clinical presentation of myopericarditis after vaccination was usually mild, with all cases fully recovering within 14 days. Hence, adolescents receiving mRNA vaccines should be monitored for side effects. Clinical Trial Registration: NCT05288231

Climate change effect on human-living in verities of way such as health and food security. This study presents predicting crop yields, and production risk in the near future (2020-2029) in northern Thailand using coupling 1 km resolution of regional climate model which is downscaled using a conservative remapping method and the Decision Support System for the Transfer of Agrotechnology (DSSAT) modeling system. The accuracy of the climate and agricultural model was appropriate compared to the observations with Index of Agreement (IOA) in ranges of 0.65 - 0.89. The DSSAT modeling system predicts that rice, and maize production will decrease by 5% and 4% in northern Thailand. In addition, a short-term risk analysis of rice and maize production has shown that, in the context of climate change, maize production appears to be at a high risk of low production in the near future, while rice cultivation might be a low risk.

Migrant population have always been vulnerable for high burden of social exclusion, mental disorders, physical illness and economic crisis. The current COVID-19 pandemic has further created the frantic plight among them, particularly for the undocumented migrant workers in global south. We have conducted a mixed method study among the undocumented Myanmar migrant workers (UMMWs) in Thailand to explore how the COVID-19 disruption has impacted on their mental health and what are the coping strategies adopted by them. Following the onset of COVID-19 and the recent coup d'etat in Myanmar, our current study is the first attempt to understand the mental health status and predicament of this neglected migrant group. A total of 398 UMMWs were included in the online survey among whom 23 participated in qualitative interviews. The major mental health issues reported by the study participants were depression, generalised anxiety disorder, frustration, stress and panic disorder while loss of employment, worries about the pandemic, social stigma, refused access to healthcare, lockdown and fear of detention were the predominant contributing factors. In response, we identified two key coping mechanisms- coping at personal layer (listening to music, playing online game, praying, self-motivation) and social layer (chatting with family and friends, visiting religious institutions). These findings point to the importance of policy and intervention programs aimed to uphold mental health at such humanitarian conditions. Sustainable institutional mental health care support and social integration for the migrant workers irrespective of their legal status should be ensured.

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This research focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It extended the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thai recruitment practices. The study explores the factors influencing users' intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literatures and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in Bangkok metropolitan area supplied comprehensive responses. The research reveals that several factors, including Perceived Value, Perceived Autonomy, Effort Expectancy, and Facilitating Conditions, significantly impact the intention to adopt AI for recruitment. While Social Influence and Trust in AI Technology do not have a direct influence on intention, Social Influence directly affects Perceived Value. Trust in AI Technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

Nanoparticles (NP), Nanoaerosols (NA), ultrafine particles (UFP), and PM0.1 (particles with a diameter ≤ 0.1 µm or 100 nm) are interchangeably used in the field of atmospheric studies. PM0.1 are emitted from both natural and anthropogenic sources. The main emission sources of PM0.1 are combustion processes, including biomass and fossil fuel. Moreover, secondary formation via atmospheric photochemical reactions can also occur depending on meteorological conditions and the suspended pollutant species. Identifying the physical and chemical characteristics and spatial and temporal variations is vital in terms of understanding the effect of NPs on the environment, the global climate, and human health risks. This review article summarizes recent research on PM0.1 in Thailand. The review involves peer-reviewed papers from Scopus and the Web of Science databases, and includes the most recently published articles in the past ten years (2013-2022). UFPs mainly come from the combustion processes such as motor vehicles. The high mass concentration of PM0.1 that occurs during the dry season in which open fires depend on the specific region of Thailand. Particulate pollution from local and cross-border countries also needs to be considered in terms of the concentrations of ambient nanoparticles. The overall conclusions reached will likely have a beneficial long-term impact on achieving a blue sky over Thailand through the development of coherent policies and managing new air pollution challenges and sharing knowledge with a broader audience.

Conducted within the scope of geochemical exploration in Eastern Thailand, this study aims to detect geochemical anomalies and potential mineral deposits. The objective was to interpret intricate spatial dispersion patterns and concentration levels of deposit pathfinder elements, specifically arsenic (As), copper (Cu), and zinc (Zn), using a comprehensive array of stream sediment geochemistry data. Methodologies involved integrating multifractal properties and traditional statistics, facilitated by the GeoDAS and ArcGIS platforms as instrumental analytical tools. In total, 5,376 stream sediment samples were collected and evaluated, leading to the development of an in-depth geochemical map. The results indicated distinct geological units marked by substantially elevated average values of the aforementioned elements. Identification of geochemical anomalies was achieved through the spatial distribution method and the subsequent application of the Spectrum-Area (S-A) multifractal model. An intriguing link was found between high As concentrations and gold deposits in the area, suggesting As as a viable pathfinder element for gold mineralization. The anomaly maps, generated from the stream sediment data, spotlighted potential zones of interest, offering valuable guidance for future mineral exploration and geological inquiries. Nonetheless, it is vital to recognize that the increased values noted in these maps may be influenced by regional geological factors, emphasizing the necessity for a diverse set of analytical methods for accurate interpretation. The study's significance lies in its pioneering use of the S-A multifractal model in geochemical data analysis. This innovative approach has deepened our comprehension of geochemical dispersion patterns and improved the precision of mineral exploration.

Public Health Officers' (PHO) experiences in reaction to the COVID-19 pandemic can be based on whether the PHO is passive or active. Therefore, the study’s objectives are to identify the types of experiences and analyse the predictors of proactive practical experiences in solving COVID-19 among PHOs in the upper southern region of Thailand. Methods: An explanatory mixed-methods approach was used to collect data, through questionnaires and online in-depth interviews. The study was conducted from August 4, 2020, to August 3, 2021. Results: The results included 60 PHOs from 60 PCUs in 6 provinces, with 41 (68.3%) females and an average age of 35.57 years (SD = 11.61). The PHOs’ knowledge, understanding, and participation experience aspects were mostly proactive rather than passive. Factors that significantly predicted proactive practical experiences included sex (ORadj = 1.52, 95% CI = 1.04–2.21), age (ORadj = 1.69, 95% CI = 1.16-2.48), married status (ORadj = 1.69, 95% CI = 1.16-2.48), education level (ORadj = 1.50, 95% CI = 1.02–2.20), and position for work (ORadj = 1.69, 95% CI = 1.16-2.48). Conclusions: PHOs’ knowledge, understanding, opinion, and participation experiences were significant predictors of practical experience. Primary health care systems should promote proactive experiences in all four aspects to increase proactive practical experiences.

Thailand has formulated her climate change policy and updated relevant plans and policies to align with the goal of achieving carbon neutrality and net zero GHG emissions. This study investigates the optimal level of GHG mitigation in Thailand, taking into account the marginal abatement cost (MAC) and social cost of carbon (SCC). It evaluates how energy efficiency and renewable energy technologies influence GHG reduction in the power and industrial sector and illustrates policy recommendations that align with the 2020 to 2050 policy and plan period. The findings indicate that there may be instances where GHG mitigation potential is insufficient to reach the national mile-stone. In such cases, it becomes imperative to leverage all technologies within the marginal abatement cost curve (MACC) and also utilization of the social cost of carbon for policy decision making and meeting the desired goals. In certain scenarios, the adoption of additional technologies or measures may be necessary, such as flexible power generation and deploying carbon capture and storage or hydrogen which are high-cost technologies. Furthermore, preparations should be made for multiple levels of climate change policies and plans beyond 2030.

The Doughnut Economy is a new approach for the inclusion of planetary boundaries and social foundation in the development of societies. The Sustainable Development Goals of the UN determine another view for development targets. The developed Sustainability Window approach provides a means for operationalisation and quantification of the Doughnut Economy. The developed method calculates minimum economic development to guarantee sustainable social development and maximum economic development not to exceed environmental sustainability. The developed method, ASA Doughnut, is illustrated with case data from Thailand. The sustainability Doughnut for Thailand has been calculated for both weak and strong sustainability criteria. It seems that strong sustainability is a too strict requirement regarding several environmental dimensions of development while the weak sustainability criteria are fulfilled. The developed method and tool is flexible and can be used for comparative analysis of different countries or regions, for dynamic analysis of sustainability development, for gap analysis of the required improvement of environmental or social efficiency, and analysis of degrowth possibilities. The selection of indicators for the analyses and their reliability is crucial for the validity of the results and usefulness in policy planning.

Researchers have reported various impacts of the COVID-19 outbreak on small-scale fishers, such as stagnating market demands, reduction of market price and income, etc. While literature have heeded to these impacts in a relatively short time frame, scant evidence exists on the changing impacts over time and on the detailed processes of how fishers have been coping with the challenges in a longer time period. Furthermore, few studies have comprehensively analysed the impacts and strategies from multiple perspectives. This study aims to explore the perceived impacts of the COVID-19 outbreak on small-scale fishing communities and to highlight the coping strategies adopted by fishers over a year since the initial outbreak, through a case study in Trang Province, Thailand. Analysis of both qualitative and quantitative data obtained through semi-structured interviews indicated that fishers wisely utilised natural, financial and social capitals at the early stages of the outbreak, while human capitals were essential for recovering from the impacts in the later stages. Our findings suggest that the adaptive capacity to flexibly change livelihood strategies are crucial, while alternative income source may not necessarily help small-scale fishers under stagnating global economy.