Search Results (7,215)

Progressive advancements in the global economy and technology have propelled human civilization forward; however, they have also inflicted significant harm on the global ecological environment. In the present era, electric vehicle (EV) technology is playing a vital role due to its environmentally friendly technological advances. However, widespread adoption of EVs has been hindered by their limited travel range, inadequate charging infrastructure, and high costs. This can be closely observed when we assess the adoption of electric vehicles (EVs) among motorcycle taxi drivers, commonly called ‘pilots,’ in Goa, India. Motorcycle taxis are crucial in Goa’s transportation network, providing affordable, efficient, and door-to-door services, especially in regions with limited public transport options. However, the rising costs of petrol and vehicle maintenance have adversely affected the income of these pilots, prompting concerns about their willingness to adopt EVs. This study aims to analyze the factors prompting the behavioral intention to adopt EVs by motorcycle taxi pilots in Goa, India, focusing on six key determinants: charging infrastructure, effort expectancy, performance expectancy, price value, social influence, and satisfaction with incentive policies. A quantitative approach was employed, utilizing stratified proportionate random sampling techniques to collect data from 242 motorcycle taxi pilots registered with the Goa State Government Transport Department. It was analyzed using partial least squares-structural equation modeling (PLS-SEM) through Smart-PLS 4.0 software. The research highlights that performance expectancy and price value are the potential motivators for the adoption of electric vehicles. These findings suggest that pilots are more likely to embrace EVs when they perceive tangible benefits in performance and find the cost reasonable in relation to the value offered. The results offer actionable insights for policymakers, manufacturers, and other stakeholders. These insights can guide strategic decisions and policy frameworks aimed at fostering a sustainable and user-centric transportation ecosystem. Full article

The restaurant industry, especially fine dining, is characterized by intense competition and an increasing number of closures. Wine is a profit lever, but the exploitation of sales potential can present a challenge. As consumers encounter more extensive wine lists, they often find themselves overwhelmed. A restaurant experiment in Stuttgart, Germany, examined strategies to simplify decision-making for customers and their impact on wine purchases and the dining experience. This experiment, conducted at a small fine-dining establishment, aimed to understand how wine descriptions and pairing recommendations influence customer choices and behavior, revealing key insights that wineries and restaurants can leverage to boost wine sales. The findings underscore the power of wine descriptions and strategic pairing recommendations in enhancing customer engagement. They suggest that restaurants can increase their wine sales by integrating well-crafted wine descriptions into menus, while wineries can benefit by providing comprehensive tasting notes and pairing suggestions that align with restaurant offerings. For both sectors, understanding the sensory and psychological factors that shape wine appreciation can offer a competitive edge. Full article

Over the past two decades, transitional justice has become a central concern in Taiwan’s cultural and political landscape. This study investigates how 1029 visitors from Taiwan, Sinophone regions (China, Hong Kong, Macau, Malaysia), and international backgrounds engage with digital interpretation systems at the Chiang Kai-shek Memorial Hall (CKSMH)—a politically sensitive site associated with Taiwan’s authoritarian past. Using a mixed-methods approach combining surveys and qualitative responses, the study analyzes cross-cultural differences in visitor motivation, use of digital tools, perceived experiential value, satisfaction, and behavioral intention. Results show that international visitors reported higher levels of engagement and satisfaction, particularly in educational, esthetic, entertainment, and escapist dimensions. In contrast, Sinophone visitors expressed lower satisfaction and more frequent discomfort with the site’s historical narrative. Key factors such as language accessibility, cultural proximity, and usability influenced how visitors perceived the digital content. The findings suggest that interactive digital tools can support both cultural engagement and critical reflection while also revealing tensions in memory politics at sites of transitional justice. Full article

Objectives: The Human papillomavirus (HPV) vaccine is a cornerstone of cancer prevention, yet uptake remains suboptimal in many countries. This study analyzed the factors influencing HPV vaccine acceptance among adults, including a focused analysis of parental behaviors. Methods: Data were collected through a web-based survey using a questionnaire. We performed univariable analysis and three logistic regression analyses to investigate the determinants in the overall sample and among parents. Results: A total of 1821 participants were surveyed. HPV vaccination uptake was low, with only 6.9% of the total sample and 7.6% of young adults (18–35 yo) vaccinated. Among parents, 47.9% had vaccinated children aged 12–17, and 21.1% those aged 18 and over. Higher health literacy was associated with positive attitudes (OR 2.03, 95% CI 1.48–2.79), while receiving information from pediatricians or gynecologists was linked to children’s vaccination status (OR 7.30, 95% CI 2.29–23.31) and parents’ intentions for future HPV vaccination (OR 5.86, 95% CI 1.85–18.50). Adequate knowledge emerged as a strong predictor of positive attitudes (OR 6.50, 95% CI 4.91–8.61) and parents’ intentions (OR 4.89, 95% CI 2.21–10.84). Vaccination status was a key factor influencing parental decisions and overall vaccine acceptance. Conclusions: These findings highlight the critical role of health professionals and the need for targeted communication to address persistent knowledge gaps and promote HPV vaccine confidence within general population. Full article

Norite is a coarse-grained mafic igneous rock dominated by essential calcic plagioclase and orthopyroxene. Norite is known for its toughness, and it has a high compressive strength which makes it important in engineering. This paper examines the mechanical and petrographic properties of norite, including their relevance to geomechanical applications. Despite improvements in brittleness estimation, standardizing brittleness indices remains a challenge due to geological variability, incompatible petrographic techniques, and difficulties in relating mineral composition to mechanical behavior. Current brittleness models mainly rely on mechanical properties, often ignoring key petrographic factors like grain size, mineral composition, alteration, and porosity. This limits their accuracy, especially for complex rocks like norite. Few studies integrate both petrographic and mechanical data, creating a gap in fully understanding the geomechanical behavior of norite. This review was carried out by examining the origin, formation, and petrographic properties of norite, and a comparative analysis of its strength, flexibility, mineral structure, and fracture mechanics was conducted, highlighting their importance in the engineering and mining industries. The results of this study highlight how factors like strength, brittleness, and durability influence norite’s suitability for geomechanical applications in mining, tunneling, and construction. Furthermore, the results outline that the mineral composition of norite affects its strength, with quartz enhancing strength and altered minerals like feldspar, mica, and biotite weakening the rock and making it more prone to fracturing. These results are important for tunneling projects as they help predict how rocks will behave, ensuring tunnel stability and better design in underground support systems. Full article

Exercise suppresses appetite in individuals with obesity irrespective of the type, duration, or intensity of the exercise. This effect is mediated through various physiological and biochemical mechanisms. Exercise influences appetite-regulatory hormones such as ghrelin and leptin, reducing hunger signals. Additionally, exercise generates metabolites and myokines, along with hepatokines, which modulate appetite suppression. Brain-derived neurotrophic factor (BDNF) is also implicated in modulating appetite. Changes in eating behaviors, gastric motility, and gastric emptying further contribute to a reduced appetite. Mental stress and body temperature alterations during exercise can also impact hunger levels. This review synthesizes current evidence and provides specific biochemical, metabolic and molecular mechanisms of how exercise and obesity affect appetite regulation. More specifically, it is extensively discussed the effect of exercise and obesity on: 1, endocrine mediators (hepatokines, metabolites, myokines, and neurotrophins); 2, physiological modulators (gastric emptying and body temperature); and 3, behavioral influences (eating patterns and visual food cues) in association with appetite regulation. Collectively, these factors highlight the complex interplay between physical activity and appetite regulation, offering insights into potential therapeutic strategies for managing obesity through exercise. Full article

This study investigates the coupled hygrothermal behavior of mycelium-based composites (MBCs) as a function of their microstructural organization, governed by fungal species, substrate type, additive incorporation, and treatment method. Eleven composite formulations were selected and characterized using a multi-scale experimental approach, combining scanning electron microscopy, dynamic vapor sorption, vapor permeability tests, capillary uptake measurements, and transient thermal conductivity analysis. SEM analysis revealed that Ganoderma lucidum forms dense and interconnected hyphal networks, whereas Trametes versicolor generates looser, localized structures. These morphological differences directly influence water vapor transport and heat conduction. Additive-enriched composites exhibited up to 21.8% higher moisture uptake at 90% RH, while straw-based composites demonstrated higher capillary uptake and free water saturation (up to 704 kg/m³), indicating enhanced moisture sensitivity. In contrast, hemp-based formulations with Ganoderma lucidum showed reduced sorption and vapor permeability due to limited pore interconnectivity. Thermal conductivity varied nonlinearly with temperature and moisture content. Fitting the experimental data with an exponential model revealed a moisture sensitivity coefficient thirty times lower for GHOP compared to VHOP, highlighting the stabilizing effect of a compact microstructure. The distinction between total and effective porosity emerged as a key factor in explaining discrepancies between apparent and functional moisture behavior. These findings demonstrate that hygric and thermal properties in MBCs are governed not by porosity alone, but by the geometry and connectivity of the internal fungal network. Optimizing these structural features enables fine control overheat and mass transfer, laying the groundwork for the development of high-performance, bio-based insulation materials. Full article

Additive manufacturing (AM) is gaining widespread adoption in the manufacturing industry due to its capability to fabricate intricate and high-performance components. In parallel, the increasing emphasis on functional materials in AM has highlighted the critical need for accurate prediction of the mechanical behavior of composite systems. This study experimentally investigates the tensile strength and surface quality of carbon fiber-reinforced nylon composites (PA12-CF) fabricated via fused deposition modeling (FDM) and models their behavior using artificial neural networks (ANNs). A Taguchi L27 orthogonal array was employed to design experiments involving five critical printing parameters: layer thickness (100, 200, and 300 µm), infill pattern (gyroid, honeycomb, and triangles), nozzle temperature (250, 270, and 290 °C), printing speed (50, 100, and 150 mm/s), and infill density (30, 60, and 90%). An analysis of variance (ANOVA) revealed that the infill density had the most significant influence on the resulting tensile strength, contributing 53.47% of the variation, with the strength increasing substantially at higher densities. In contrast, the layer thickness was the dominant factor in determining surface roughness, accounting for 53.84% of the variation, with thinner layers yielding smoother surfaces. Mechanistically, a higher infill density enhances the internal structural integrity of the parts, leading to an improved load-bearing capacity, while thinner layers improve the interlayer adhesion and surface finish. The highest tensile strength achieved was 69.65 MPa, and the lowest surface roughness recorded was 9.18 µm. An ANN model was developed to predict both the tensile strength and surface roughness based on the input parameters. Its performance was compared with that of three other machine learning (ML) algorithms: support vector regression (SVR), random forest regression (RFR), and XGBoost. The ANN model exhibited superior predictive accuracy, with a coefficient of determination (R² > 0.9912) and a mean validation error below 0.41% for both outputs. These findings demonstrate the effectiveness of ANNs in modeling the complex relationships between FDM parameters and composite properties and highlight the significant potential of integrating ML and statistical analysis to optimize the design and manufacturing of high-performance AM fiber-reinforced composites. Full article

Accurate prediction of dam displacement is essential for structural safety and risk management. To comprehensively address the “accuracy–uncertainty–interpretability” trilemma in dam displacement prediction, this study proposes a deep learning framework that integrates Patch Time Series Transformer (PatchTST), Sand Cat Swarm Optimization (SCSO), Quantile Regression (QR), and SHapley Additive exPlanations (SHAP). The proposed framework first employs PatchTST to capture the nonlinear temporal dependencies between multiple monitoring factors and dam displacement, while SCSO is utilized to adaptively optimize key hyperparameters, enabling the construction of a high-precision point prediction model. On this basis, QR is introduced to model the distributional uncertainty of displacement responses and to generate confidence-based prediction intervals, facilitating the evaluation of displacement anomalies. Furthermore, SHAP is incorporated to quantify the marginal contribution of each input factor to the model outputs, thereby enhancing interpretability and aligning model behavior with physical domain knowledge. The framework is validated using multi-year monitoring data from a double-curvature arch dam located in Southwest China. Comparative experiments demonstrate that the proposed model outperforms five well-established machine learning methods and the traditional linear regression method in terms of point prediction accuracy, reliability of interval estimation, and false alarm rate, exhibiting strong generalization and robustness. The SHAP-based analysis further reveals that water pressure variations and seasonal temperature cycles are the dominant factors influencing radial displacement, consistent with known structural deformation mechanisms. These findings affirm the physical consistency and engineering applicability of the proposed framework, offering a deployable and trustworthy solution for intelligent dam health monitoring and uncertainty-aware forecasting in safety-critical infrastructures. Full article

Orphan nuclear receptor 4A1 (NR4A1, Nur77) plays a crucial role in regulating immune cell metabolism and function within the tumor microenvironment (TME), thus influencing cancer progression and serving as a potential therapeutic target for cancer immunotherapy. A comprehensive review discussing the multifaceted roles of NR4A1 in immune cells and the exploitation of that knowledge for therapeutic development is lacking in the field. This review explores diverse functions of NR4A1 in tumor-associated immune cells, including T cells, monocytes, natural killer cells, B cells, dendritic cells, macrophages, and neutrophils. NR4A1 contributes to immune regulation by impacting cytokine production, cell differentiation, and immune cell exhaustion. We highlight how NR4A1 in immune cells within the TME may be either a positive (e.g., macrophages in colon cancer) or negative prognostic factor (e.g., T cells in melanoma), depending on the cancer and immune cell context. Additionally, this review also highlights potential therapeutic strategies targeting NR4A1, leading to its inhibition, activation, or degradation to restore immune cell function and enhance anti-tumor immunity. Such therapies could potentially improve patient outcomes by altering immune cell behaviors, blocking intrinsic tumor growth pathways, or via both mechanisms. However, the development of NR4A1-targeted therapies will be dependent on further research to better understand lineage-specific roles of NR4A1 and the underlying mechanisms across different cancer types and immune cells. Full article

Digital transformation is reshaping educational methods and necessitates new institutional, teaching, and learning approaches. In Romania’s secondary school system, this process is particularly complex due to infrastructural disparities, uneven digital competencies, and limited policy guidance. This study investigates the factors influencing Romanian secondary school teachers’ adoption of digital technologies, addressing a gap in the literature regarding localized teacher behavior within under-digitalized educational environments. Using the Technology Acceptance Model (TAM), this research explores perceived usefulness, perceived ease of use, behavioral intention, and perceived quality as determinants of digital adoption. The analysis was conducted on a sample of 430 teachers utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM). The key findings reveal that behavioral intention strongly predicts actual usage (β = 0.791, p < 0.001), and perceived ease of use exerts a greater influence than perceived usefulness. Furthermore, perceived quality plays a modest but significant mediating role in enhancing digital engagement. These results suggest that user-friendly, intuitive technologies and targeted professional training are essential for sustained adoption. This study contributes to the field by offering a context-specific understanding of technology’s acceptance in Eastern European education and by extending the TAM framework through the integration of perceived quality. It provides actionable insights for policymakers and school leaders seeking to promote sustainable and inclusive digital transformation in schools. Full article

This paper explores the role of export-oriented firms in shaping regional economic development, with a focus on their operational footprint, strategic orientation, and interaction with institutional and infrastructural environments. Set within the broader context of regional competitiveness and sustainable growth, the study examines how firms in geographically peripheral and structurally challenged areas position themselves within global markets. Emphasis is placed on understanding the internal and external factors that influence export performance, innovation capacity, and the integration of sustainability principles into business practices. The research adopts a survey-based methodology, collecting data from firms located in a cross-border region to assess their perceptions of trade barriers, infrastructure needs, strategic values, and environmental awareness. The analysis draws on established frameworks in regional development, international business, and sustainability transitions, offering a multidimensional perspective on firm behavior. By linking firm-level insights with regional development policy, the study contributes to ongoing discussions around how enterprises in remote regions can overcome structural constraints and engage more fully with global value chains. It also supports the growing call for place-based, context-sensitive strategies that align economic competitiveness with innovation, digital transformation, and environmental responsibility. This integrated approach offers valuable implications for both policymakers and practitioners concerned with fostering inclusive and resilient regional economies. Full article

Electrostatic droplets can enhance deposition on target leaves. To comprehensively investigate the main factors affecting droplet adhesion and splashing after electrostatic droplet impact on pepper leaves, a specialized experimental platform was developed to capture the impact behavior of charged droplets on pepper leaves. The following four variables were examined: the applied voltage of the electrode ring, droplet size, impact velocity, and the relative distance from the impact point to the leaf tip (expressed as a percentage of the total leaf length). The results showed that all four factors had significant effects on droplet adhesion. The effect sizes (partial η²) of the four factors, in descending order, were impact velocity (0.935), applied voltage (0.907), impact position (0.895), and droplet size (0.505). Compared with non-electrostatic droplets, the increase in the maximum spreading factor of charged droplets was positively correlated with droplet size, impact velocity, and applied voltage but showed no significant correlation with the relative distance to the leaf tip. The critical velocity for splashing of electrostatic droplets decreased to a certain extent but increased with higher applied voltages. The influence of the four factors on droplet splashing decreases in the following order: impact velocity (odds ratio ≫ 1), charging voltage (odds ratio = 1.246), droplet size (odds ratio = 1.023), and impact position (odds ratio < 1). Among these, impact velocity has the most significant effect on splashing behavior. This study reveals the adhesion and splashing mechanisms of electrostatic droplets on flexible pepper leaves, providing theoretical support for the design of electrostatic spraying systems and the selection of operational parameters. The findings offer a scientific basis for optimizing droplet deposition, minimizing splash losses, and improving application efficiency in precision spraying. Full article

Background/Objectives: Obesity is a major contributor to cardiovascular disease, yet traditional risk assessment methods may overlook behavioral and circadian influences that modulate metabolic health. Chronotype, physical activity, sleep quality, eating speed, and breakfast habits have been increasingly associated with cardiometabolic outcomes. This study aims to evaluate the associations between these behavioral factors and both anthropometric and biochemical markers of cardiovascular risk among obese candidates for bariatric surgery. Methods: A cross-sectional study was conducted in a sample of 286 obese adults (78.3% females, mean 44.3 years, SD = 10.8, mean BMI = 42.5 kg/m², SD = 6.2) followed at a central Portuguese hospital. Chronotype (reduced Morningness–Eveningness Questionnaire), sleep quality (Pittsburgh Sleep Quality Index), physical activity (Godin–Shephard Questionnaire), eating speed, and breakfast skipping were assessed. Cardiovascular risk markers included waist-to-hip ratio (WHR), waist-to-height ratio, A Body Shape Index (ABSI), Body Roundness Index, atherogenic index of plasma (AIP), triglyceride–glucose index (TyG), and homeostatic model assessment for insulin resistance (HOMA-IR). Results: Men exhibited significantly higher WHR, ABSI, HOMA-IR, TyG, and AIP. Eveningness was associated with higher insulin (r = −0.168, p = 0.006) and HOMA-IR (r = −0.156, p = 0.011). Poor sleep quality was associated with higher body fat mass (r = 0.151, p = 0.013), total cholesterol (r = 0.169, p = 0.005) and LDL cholesterol (r = 0.132, p = 0.030). Faster eating speed was associated with a higher waist circumference (r = 0.123, p = 0.038) and skeletal muscle mass (r = 0.160, p = 0.009). Conclusions: Male sex, evening chronotype, and poor sleep quality were associated with more adverse cardiometabolic profiles in individuals with severe obesity. These findings support the integration of behavioral and circadian factors into cardiovascular risk assessment strategies. Full article

Background: The growth patterns of children and adolescents are influenced by multiple factors. This study employed structural equation modeling (SEM) to determine the primary factors influencing the growth of Palestinian children and adolescents in the West Bank (WB). Methods: A cross-sectional survey conducted in 2022 in the WB collected data from 1400 households, of which 500 with children aged 5–17 years and were selected for analysis. The survey assessed household food insecurity, socioeconomic status (SES), parental health history, nutritional awareness, food consumption patterns, and nutrient intake. The latent construct “Child Growth” was measured using Body Mass Index-for-age Z-score (BAZ), height-for-age Z-score (HAZ), and Mean Adequacy Ratio (MAR). SEM was employed to examine the interrelations among latent variables and their observed indicators. Results: Mineral intake showed the strongest direct effect on child growth (β = 0.812, p < 0.001), followed by food availability (β = 0.492), vitamin intake (β = 0.481), SES (β = 0.439), and macronutrient intake (β = 0.383). MAR exhibited the highest factor loading as a growth indicator, while HAZ had limited significance, suggesting its chronic nature. SES influenced growth both directly and indirectly through its effects on food availability and dietary intake pathways. Strong correlations between nutritional knowledge and nutrient classes reflect the interrelationship between behavioral and biological determinants. Conclusions: Both structural and immediate nutritional factors influence child growth. In Palestinian youth, mineral intake, food security, and SES have the greatest influence. These findings offer a framework for understanding the growth determinants of Palestinian youth in the WB and support the development of targeted interventions to improve dietary quality and overall nutritional status. Full article