High Influence Research Articles

How Do Trust on Dayah Leaders Influence Students Taking a Vaccination Against Covid-19 in Aceh?

The emergence of a policy on Covid-199 vaccination received massive rejection from the society. The government collaborated with opinion leaders who may have influence the society perception about the importance of Covid-19 Vaccination to solve the current problems. This study aims to examine the influence of trust on Dayah Leaders towards the level of students’ trust in Covid-19 vaccination. Using survey method, the study involved a sample of 500 students in 5 Dayah in Banda Aceh and Aceh Besar both who had implemented vaccination policies and/or had only suggested vaccination appeals for their students. Conditions in Aceh are unique, namely the distinctiveness of Aceh which is robust with Islamic nuances and religious leaders are believed to be a source of information who are able to foster public trust. Nevertheless, this study confirms that student participation in the Covid-19 Vaccination is not entirely based on the influence of trust on Dayah Leaders. The result suggested that there is an influence of trust on Dayah Leaders on students’ confidence in Covid-19 vaccination, but the correlation and the influence is low at 14 percent. This indicates there are several other factors which have higher influence in convincing vaccination policy for students. This research findings also contradict the assumption that has been believed that the influence of the Dayah leaders is very significant in the students' decision to vaccinate against Covid 19. Hence, it gives recommendation for policy makers particularly in Aceh to properly construct message of the Covid-19 vaccination or other sensitive vaccination in the future.

Groundwater Potential Mapping Using Random Forest and Extreme Gradient Boosting Algorithms

Abstract The availability of groundwater is a crucial solution to ensure the sustainability of water resources, including providing clean water. Therefore, efforts to map groundwater potential are required to enhance the efficiency of groundwater utilization and support achieving one of the Sustainable Development Goals (SDGs), particularly clean water and sanitation. This research aims to identify the distribution of the groundwater potential in Kediri Regency using the random forest (RF) and extreme gradient boosting (XGB) algorithms. This research utilizes 13 parameters, including elevation, slope, aspect, drainage density, river density, distance from rivers, lineament density, Topographic Wetness Index (TWI), Normalized Difference Vegetation Index (NDVI), land cover, soil type, lithology, and band 3 from Sentinel-2A satellite imagery. The coordinates of groundwater wells are used as training and testing data with ratios of 80:20, 70:30, and 60:40. Through the evaluation of each model’s performance using a confusion matrix, it is revealed that the best model is the RF 70:30 ratio model with Accuracy (Acc), Specificity (Spe), Sensitivity (Sen), Positive Predictive Value (PPV) values of 0.978, Cohen’s Kappa (CK) and Matthew’s Correlation Coefficient (MCC) of 0.956, and Area Under Curve (AUC) of 0.994. In this model, the elevation has the highest influence on the model, with a significance level equal to 100.

Empirical Study on Consumption Pattern of Poultry Meat in Srinagar City

The consumption pattern of chicken has witnessed significant changes over the years, reflecting shifting preferences, dietary habits, and socioeconomic factors. With an increasing emphasis on health and wellness, consumers are opting for chicken as a healthier alternative to red meat. In India, the meat products sector witnessed remarkable growth, with the Gross Value Added (GVA) surpassing INR 3 trillion in 2021. The market is projected to expand further at a CAGR of 9.2%, reaching INR 3133.41 billion by 2028, driven by the escalating demand for protein-rich foods. Notably, the poultry business is thriving in Jammu and Kashmir, particularly in Kashmir, contributing significantly to this growth. This study delves into the consumption patterns of poultry meat among residents of Srinagar city, focusing on Groups- Government Employees, Private Employees, and Self-Employed individuals. Utilizing a stratified sampling technique, the research ensures representation from diverse employment sectors. The survey, encompassing 152 respondents, revealed that majority (67.8%) consumed poultry on weekly basis, with an average monthly household consumption of 7.20 kilograms, translating to a monthly expenditure of Rs 1052.63 on poultry. The study identified broiler chicken as the preferred type . Interestingly, demographic factors such as age, gender, marital status, and education level demonstrated no significant impact on poultry consumption, while household size, employment nature, number of earners, and income exhibited notable associations. Regarding consumer preferences, internal factor smell and freshness was found to be the most influential while among external factors, affordability had the greatest impact on consumer preference. Overall, internal factors had a higher influence on consumer preference, with a total mean rating of 3.5184, compared to external factors, with a total mean rating of 3.3509. Recognizing substantial impact of internal factors on consumer preference, processing companies should prioritize aligning products with these preferences through market research, innovation, quality assurance, and heightened consumer education.

Effect of external magnetic field inhomogeneity on the nonlinear absorption of intense laser pulse in inhomogeneous warm plasma

This paper studies the propagation of an intense laser pulse and the collisional absorption in an inhomogeneous warm plasma by taking into account the external magnetic field inhomogeneity and the ponderomotive force. The calculations are carried out and compared for different magnetic field strengths and their various configurations. For this purpose, using the hydrodynamic equations, the electron density and hence the effective dielectric permittivity of the magneto-active warm plasma are derived and the nonlinear wave equation is solved through the numerical method of Runge–Kutta. The results show that increasing the strength of the external magnetic field causes an increase in the absorption coefficient and the linear magnetic field has a higher influence on the absorption coefficient with respect to the wiggler and constant magnetic fields. Moreover, when the electron temperature increases, the amplitude of the laser field and the absorption coefficient are increased and the spatial damping rate of the laser pulse takes a peak in the plasma. The results also indicate that increasing the energy of the laser pulse causes a decrease in the nonlinear absorption, and the laser energy spatial damping is significantly decreased in contrast to the growth of the amplitude of the laser field. A qualitative comparison of the results indicates that if a linear magnetic field is applied in the same direction of the laser propagation, the collisional absorption rate will be larger with respect to the other magnetic fields. Moreover, the difference in the influence of the mentioned magnetic fields on the collisional absorption increases with increasing the electron temperature and normalized cyclotron frequency and decreases with increasing laser intensity.

Technoeconomic analysis of supercritical water gasification of canola straw for hydrogen production

Production of hydrogen from renewable sources is gaining popularity to reduce our dependency on non-renewable fossil fuels to meet growing hydrogen demand. However, despite the great prospect of production of hydrogen from sustainable sources such as lignocellulosic biomass via supercritical water gasification (SCWG), it has not been commercialized at a large industrial scale. This is due to the lack of detailed economic analysis of SCWG of lignocellulosic biomass, owing to the complexity of the SCWG process and the heterogeneous nature of biomass. Therefore, to address this knowledge gap, in this study, a detailed technoeconomic analysis (TEA) of a conceptual SCWG pilot having the capacity to process 200 tons/day of canola straw for the production of green hydrogen was conducted. Mass and energy balance of conceptual pilot was performed using Aspen Plus ® simulation by utilizing experimental data and hydrogen yield of 41.62 mmol/g was obtained at optimized reaction conditions of 500 °C, 23 MPa, and 10 wt%. Economic analysis based on calculated mass and energy balance was performed using SuperPro software. Cash flow analysis for capital expenses (CAPEX) of 81 Million USD showed a high internal rate of return (IRR) of 38.9% and an undiscounted net present value (NPV) of 548 million USD. A minimum selling price (MSP) of 3.38 USD/kg H2 for produced hydrogen was estimated, which is lower than other renewable hydrogen production processes and comparable to non-renewable hydrogen production technologies. A high positive IRR and NPV, while a lower MSP showed that despite having a low technological readiness level (TRL) of 4, SCWG of lignocellulosic biomass is a technically feasible and economically viable process for the production of hydrogen. Furthermore, sensitivity analysis also revealed that capital expenses (CAPEX) and canola straw price had the highest influence on net present value (NPV) and MSP. However, overall NPV and MSP were highly stable to changes in parameters highlighting the robustness of the economic analysis.

The Value Relevance of Accounting Information in Iraq

The paper tests the value relevance of accounting information extracted from financial statements of 15 Iraqi companies listed on the Iraq Stock Exchange (ISX) for period 2010–2020. The relationships among accounting information (measured as earnings, book value, and cash flows) and company value (measured as stock prices) have been analyzed via descriptive statistics, correlation and regression. It is found that all these relationships are positive and significant in different levels. Compared with book value, earnings have the highest influence on stock price, while cash flows have the lowest influence on stock price. This study participates in the understanding of value relevance of accounting information in ISX as an emerging market and presenting peer insights to enhance the financial reporting standards in this country and in other similar countries in Middle East region.

Climatic factors, but not geographic distance, promote genetic structure and differentiation of Cleistogenes squarrosa (Trin.) Keng populations.

Climate can shape plant genetic diversity and genetic structure, and genetic diversity and genetic structure can reflect the adaptation of plants to climate change. We used rbcl and trnL-trnF sequences to analyze the genetic diversity and genetic structure of C. squarrosa under the influence of different environmental factors in Inner Mongolia grassland. The results showed that the genetic diversity of this species was low. (The trnL-trnF sequences have higher genetic diversity than rbcl sequences.) C. squarrosa had low genetic diversity compared to other prairie plants, but had a more pronounced genetic structure. The haplotype network diagram of the combined sequences could be divided into two categories, and the results of the NJ, MP, and ML trees also showed that the haplotypes were divided into two branches. The results of genetic structure analysis showed that that the populations located in the desert steppe fall into exactly one cluster, and the populations located in the typical steppe fall into exactly another cluster. The neutrality tests were all negative and the mismatch distribution also showed a single peak across the population, suggesting that C. squarrosa had undergone population expansion and was well adapted to the local environment. The results of the mantel test showed that climate had a greater influence on the genetic distance of C. squarrosa, with annual precipitation having a higher influence than mean annual temperature. This study provided basic genetic information on the genetic structure of C. squarrosa and contributes to the study of genetic adaptation mechanisms in grassland plants.

Sustainable Cutting Environment Evaluation for Drilling of Aluminum A380 Foam Produced by Semisolid Recycling

The development of sustainable cooling technologies and increased concern for recycled materials will affect the reduction of greenhouse gas emissions, which primarily originate from the production industry. In this research paper, a twofold contribution to sustainability is made through the efficient application of a workpiece, obtained by recycling waste in the form of metal chips, and the machining of the obtained workpiece by using alternative cooling techniques comparing them to cutting fluids. Minimum quantity lubrication and cold compressed air cooling were selected as two sustainable, alternative cutting environments. Using Taguchi’s L9 orthogonal array, the influence of cutting speed, feed rate and cutting environment on drilling thrust force, built-up edge formation and hole deviation was observed. Using the analysis of variance method, feed rate was identified to have the highest influence on the output parameters (31%), followed by cooling and lubrication techniques (18%) and lastly by cutting speed (5%). Based on the grey relation analysis, optimal controllable factors were identified. This analysis indicated that low cutting speeds and feed rates, coupled with the MQL cutting environment, produced the lowest thrust force, deviation of hole and built-up edge formation.

Pengaruh Kredibilitas Influencer dan Consumer Review Terhadap Minat Beli Produk Ms Glow pada Platform Shopee

This research aims to analyze the influence of influencer credibility and consumer reviews on buying interest. The sampling method was purposive sampling technique. The questionnaires were distributed via buying online to 100 respondents.The collected date were analysed using Partial Least Square (PLS) . The results show that both the influencer credibility and consumer review variables are positive and significant influence on buying interest in MS Glow products on the Shopee platform. Has the highest influence on buying interest.

GLP-1 and Body Weight: A Scientometric Analysis About How to Select the Best Articles Containing Pharmacological Treatment Methods

Background: Medications initially intended for diabetes treatment are now being used by other patients for weight loss. In the specialized literature, there are numerous meta-analyses investigating this aspect. Areas of Uncertainty: The authors aimed to explore whether the application of scientometric methods for literature review within meta-analyses could provide clear answers to specific research questions. This approach could help develop a rapid system for selecting articles to read during the information process for clinicians or researchers. Data Sources: We obtained research data from Web of Science Core Collection, using the search phrase “GLP-1 AND Body Weight,” reviews from the past 5 years. This approach led to the identification of 31 relevant articles in the field. Results: A total of 31 reviews were identified in the WOS database and investigated using the VOSviewer bibliographic coupling method. Among these, 7 reviews were found to have the highest influence. The authors analyzed these articles and determined that only these 7 reviews directly address the research question. In addition, an analysis of the impact factor of the journals where the articles are published, the influence power of these articles, and the countries of origin of the authors was conducted. A strong correlation was demonstrated between the impact factor and the total link strength for these 7 reviews. The correlation coefficient of 0.116709 between journal impact factor and number of citations suggests a very weak or nonexistent relationship. A strong positive correlation of 0.879736 exists between journal impact factor and total link strength, indicating a significant association. The correlation coefficient of −0.12505 between citations and total link strength shows a very weak or negligible relationship. Conclusions: Scientometric methods such as VOSviewer are useful in the work of both researchers and clinicians, highlighting the fact that articles in a research field can be identified by several criteria: impact factor, number of citations, authors from research teams that addressed this topic. The weak correlation between journal impact factor and number of citations implies that the prestige of the journal does not significantly affect the citation count of articles. Researchers should focus on the quality and relevance of their work rather than solely targeting high-impact journals. However, the strong positive correlation between impact factor and total link strength suggests that articles in prestigious journals are more likely to share content similarities. Researchers should consider this when selecting journals for publication and aim to contribute to impactful and interconnected research areas. This approach allows quick and easy identification of key articles, serving as a fundamental basis for rapid analysis of research in the field, starting from the analysis of authors' competence, degree of trust of the journal, or degree of interest that researchers have for that article.

Factors affecting the management of developing a quality cultural environment in Vietnam higher education institutions with the function of developing and training educational administrators

The more important quality culture plays in the existence and development of higher education institutions, the more essential managing the development of a quality cultural environment in higher education institutions is. Therefore, exploring the factors affecting the management of developing a quality cultural environment is one of the aspects interested in by researchers to improve the effectiveness of management. The purpose of the study is to find out the current status of factors affecting the management of building a quality cultural environment in higher education institutions with the function of developing and training educational administrators in Vietnam through quantitative research. Data was collected through a questionnaire survey with 1,047 administrators, lecturers and staff members, and students in six higher education institutions with the function of developing and training educational administrators. The main method used to analyze the data is the descriptive statistic. Research results show that the influences of all factors are from average to high. Factors belonging to human resources are the most important and highest influence, while objective factors such as facilities and policies also have widespread influences, the foundation for developing a quality culture.

Predictive Factors of State Licensure Board Disciplinary Actions in Occupational Therapy.

One primary function of occupational therapy state licensure boards (SLBs) is the discipline of ethical misconduct by licensed occupational therapy practitioners. However, SLB sanctioning is poorly understood by practitioners, regulators, and the public. To identify predictors of occupational therapy practitioner sanctioning outcomes in the United States. Retrospective study; all public final consent orders and database entries provided online by SLBs were analyzed. Supervised gradient boosting machine learning, logistic regression, and contingency tables were used to generate odds ratios for variables associated with each sanctioning outcome. Multinomial testing was used to identify attribute overrepresentation among cases and national practitioner distributions. A total of 2,400 cases were analyzed across 47 states and Washington, DC. None. Numerous complaint and respondent attribute variables were collected from final consent orders and database entries. Complaint reason, practice setting, and complaint source had the highest influence on predicting sanction outcome; geographic region, number of complaints in a given case, and length of investigation in months were secondarily influential. Being male or a certified occupational therapy assistant was associated with higher odds of severe sanctioning outcomes. Disciplinary actions against occupational therapy practitioners were determined by numerous contextual factors; however, the most influential factors were complaint reason, practice setting, and complaint source. These results provide direction for exploring factors that predict sanctioning outcomes in the United States and also provide occupational therapy practitioners and SLBs a basis of applied outcomes that may improve implementation and education regarding clinical practice ethics. Plain-Language Summary: Occupational therapy state licensure boards (SLBs) are responsible for disciplining licensed occupational therapy practitioners for ethical misconduct. SLB sanctioning is poorly understood by practitioners, regulators, and the public. In this study, we identify the factors that predict the sanctioning outcomes of occupational therapy practitioners. The results may help state regulators, educators, and national associations more effectively act in a way that protects the public faith in occupational therapy services by providing contextualized information on practitioner behaviors that result in specific sanctioning outcomes. The study findings also provide occupational therapy practitioners and SLBs a basis of applied outcomes that may improve the implementation of and education regarding clinical practice ethics.

Is Warm-Up Preservation Modulated by Biological Maturation and Sex? Effects on Lower Limbs Performance.

Children and adults may react differently to warm-up preservation due to different physical characteristics. This study aimed to: (i) assess the impact of different rewarm-up routines in swimmers during a transition phase (20-25 min), including passive rest (SWU) or dynamic activities (RWU), on countermovement jump and swimming start performances, and (ii) explore potential RWU adaptations considering maturity offset (peak height velocity-PHV) and sex. Performance was analyzed using mixed effect ANCOVA, considering protocol, maturity offset (pre-PHV, mid-PHV, post-PHV, and adv. post-PHV), and sex. Results favored RWU over SWU with substantial magnitudes for jump height: pre-PHV (min-20, ES = 1.21; min-25, ES = 1.65), mid-PHV (min-20, ES = 1.23; min-25, ES = 1.14), post-PHV (min-20, ES = 1.37; min-25, ES = 0.73), and adv. post-PHV (min-20, ES = 1.03; min-25, ES = 0.65). Significant interactions at 25 min (p = 0.033, 0.047) showed that RWU outperformed SWU, especially in younger groups (pre-PHV, mid-PHV). RWU was superior to SWU for the reactive strength index at 20 min (p = 0.042) and 25 min (p = 0.047), with females having lower RSI than males at 20 min (p = 0.008, p = 0.015) and 25 min (p = 0.049) in later developmental stages. The flight distance (p = 0.009) and horizontal hip velocity (p = 0.014) revealed significant three-way interactions, with the male adv. post-PHV group responding better to RWU. Knee angular velocity was also higher after RWU, with male adv. post-PHV group showing more pronounced improvements (p = 0.016). These results suggest that though RWU had higher influence in male adults, it is a valuable approach for varying ages athletes.

베이커리카페의 물리적 환경이 고객만족 및 재방문의도에 미치는 영향 - 수도권 윈도우 베이커리카페 중심으로

Objective : This study seeks to identify and study the impact of physical environmental factors of Window Bakery Cafe on customer satisfaction and revisit intention. Methods : The study was conducted using a total of 307 questionnaires. It also used the SPSS 25.0 statistical program to verify the hypothesis. Results : Among the physical environmental factors of the Window Bakery Cafe, aesthetics was found to have the highest influence, and customer satisfaction was found to have a positive effect on revisit intention. Implications : This study holds academic significance for providing theoretical data by conducting research on window bakery cafes in the metropolitan area, rather than franchise bakery cafes, in accordance with the bakery trend where competition is intensifying.

Factors influencing travel time and getaway time of helitack crews on wildfires in the province of Quebec

Background Reducing the delay between the detection of a fire and the arrival of the initial attack (IA) crew can have a significant impact on the likelihood of the IA’s success. Aims The objective of this study was to identify factors influencing same-day getaway time, next-day getaway time and travel time of helitack IA crews in the province of Quebec, Canada. Methods Using generalised linear modelling and model selection, we analysed the impact of multiple factors on these three distinct times. Key results Our results show that factors such as the distance between the departure base and the fire, the number of flight legs to reach a fire, dispatch hour, departure base location, the fire’s rate of spread, Julian date, the number of active fires, fuel type and the fire’s size at detection all influenced getaway time and travel time with varying degrees of influence. Conclusions The factors with the highest influence were distance for travel time and dispatch hour for both same-day and next-day getaway times. Implications Addressing these high-impact factors through the modification of deployment policies and the positioning of helitack crews could help reduce response times.

Incident atrial fibrillation prediction using ECG-based deep learning at a specialized tertiary cardiac care center

Abstract Background Deep learning (DL) applied to electrocardiograms (ECG) is an emerging modality in the prediction of incident atrial fibrillation or atrial flutter (AF). The generalizability of such methods to a tertiary heart center (THC) population has not yet been formally explored. Purpose Evaluate the performance of DL in predicting 5-year incident AF using a resting 12-lead ECG in sinus rhythm acquired at a THC. Methods In a retrospective study, we examined 1.4 million ECGs acquired from over 250,000 adults at a THC between 2004 and 2022. ECGs were excluded if they were performed within 30 days of cardiac surgery, captured a rhythm other than sinus rhythm, or were acquired in patients with pre-existing AF. Incident AF at 5 years was modelled as a binary outcome and was determined on the basis of available outpatient and inpatient clinical databases and ECG diagnoses. Included ECGs were randomly split by distributing patients into training (70%), validation (10%), and test (20%) sets. A ResNet-50 model was trained using the training set. Hyperparameters were optimized using the validation set. The tuned model's performance is reported on the test set. The results at the patient level were derived by averaging the model's probability outputs for ECGs grouped according to both their AF outcome and the patient's identity. Bootstrapping was used to report confidence intervals (CI). Sensitivity and specificity are reported at a classification threshold based on the Matthews correlation coefficient. Saliency maps were used to enhance the model’s explainability. Results A total of 669,782 ECGs (47% of the screened ECGs) were included among 145,323 patients. Mean age was 63±15 years and 62% were male. The 5-year incident AF outcome was observed in 12% of ECGs and 16% of patients. The performance of the tuned model was first evaluated at the ECG level on the test set demonstrating an area under the receiver operating curve (AUC) of 0.75 (95% CI: 0.745-0.753) and an integrated calibration index of 0.009 (95% CI: 0.008-0.011). When testing the model at the patient level to simulate a deployment scenario, the AUC improved to 0.78 (95% CI: 0.768-0.783) with a sensitivity of 50% (95% CI: 49-52) and specificity of 87% (95% CI: 86.5-87.3). Stratified results by sex showed a better AUC in females, 0.81 (95% CI: 0.80-0.82), compared to males, 0.75 (95% CI: 0.74-0.76). Subgroup analyses revealed a trend of improved performance at the patient level with an increasing number of ECGs. Saliency maps highlighted the P-wave area as having the highest influence on the model’s prediction, thereby enhancing the model’s plausibility and explainability. Conclusion A unimodal ECG-based deep learning model showed promising 5-year incident AF prediction performance in a cohort of all-comer patients at a tertiary heart center. Further studies could explore the use of multimodal prediction models that integrate ECGs with other clinical and imaging data.

Lessons from long‐term research: Diptera species turnover and dominance shifts with respect to climate‐driven changes

Abstract The diverse pressures of climate change have influenced many habitats, especially freshwater ones, due to their greater sensitivity to stressors. Aquatic Diptera make up more than 50% off all aquatic insect species described, which makes them an ideal group to monitor changing climate as their diverse assemblages can reflect functions within the entire community. The aim of this research was to identify variations in the aquatic dipteran community during a 15‐year period at a tufa barrier in a karst barrage lake system and to determine the environmental factors that have the highest influence on this community. We analysed monthly data collected between 2007 and 2021, when we collected adult specimens using 6 pyramid‐type emergence traps. In total, 167 taxa from 13 different families were gathered. NMDS based on Bray–Curtis similarity analysis amongst assemblages revealed the segregation of samples based on different current velocities and substrates, indicating the importance of microhabitats in dipteran community structuring. Dipteran taxa indicative of specific 5‐year time periods within the research were identified and were associated with changes in environmental conditions especially discharge. The threshold indicator taxa analysis revealed specific species' responses to changing discharge rates. The study shows that discharge rate, not water temperature, is the critical factor shaping dipteran composition, whether by removing or adding taxa to the community. Species turnover showed an overall decrease in species numbers, that is, species richness, throughout the research period. We conclude that changes in the dipteran community, because of the vast functional traits, niches, adaptations and species diversity of the group, are not visible when analysing just the diversity indices. When determining environmental influence on the community in long‐term research, they should be combined with other data such as the overall abundance, the total number of species, as well as the species turnover.

Quantifying Influence: Propensity Score Matching Unravels the True Effect Sizes of Learning Management Models on Students’ Analytical Thinking

<p style="text-align:justify">Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.</p>

Integrated Geospatial and Analytical Hierarchy Process Approach for Assessing Sustainable Management of Groundwater Recharge Potential in Barind Tract

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 × 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation.

Eversa transform 2.0 immobilized on a hydrophobic support enables the solvent-free almost quantitative esterification of the free fatty acids from soybean oil with neopentylglycol

The performance of Eversa Transform 2.0 (ETL) and lipase from Thermomyces lanuginosus (TLL) was compared in the solvent-free esterification of the free fatty acids (FFAs) from soybean oil with neopentylglycol (NPG) to produce NPG-diesters, which may be used as biolubricants. Enzymes were immobilized by interfacial activation on an octadecyl-coated methacrylate macroporous resin (C18) and compared to commercially immobilized TLL (Lipozyme® TL IM), free ETL and TLL. ETL@C18 surpassed the performance of all tested biocatalysts, reaching up to 98 % of FFAs conversion after 6 h of reaction at 50 °C and using a biocatalyst content of 9 wt% (related to the mass of FFAs). After optimization, the reactor temperature had a higher influence on the production of the NPG-diesters than the biocatalyst content, so that 45 °C and 3 wt% were determined to be the optimal values. Under such conditions, ETL@C18 retained approximately 88 % of its initial conversion into the NPG-diesters even after 10 consecutive reaction cycles. The biolubricant is composed mainly of NPG-diesters (∼91 %) and unreacted NPG (∼9 %), as confirmed by NMR analysis. The NPG-diesters exhibited a higher viscosity index (from 190.84 to 215.86) and oxidative stability (from 0.10 h to 1.34 h) than the starting material. The NPG-diesters biolubricant also exhibited a lower friction coefficient (0.049 against 0.064) and wear scar diameter (139.03 μm against 151.43 μm) than the 20W-50 mineral lubricant.