Search Results (541)

Charitable giving plays a vital role in advancing sustainable development, yet little is known about its determinants in transitional economies. This study addresses this gap by examining the socioeconomic and psychological drivers of prosocial financial behavior in Uzbekistan, integrating the Theory of Planned Behavior (TPB), Norm Activation Theory (NAT), and Well-Being Theory. Data from a sample of 348 individuals reveal two distinct pathways of giving: one shaped by resources (income, age) and another by subjective well-being (happiness). While income, age, and happiness emerged as significant positive predictors of charitable behavior, traditional TPB factors such as attitude, subjective norms, and perceived behavioral control were not supported in this context. A surprising finding was the negative association between personal norms and charitable giving, challenging assumptions of Western-centric models and pointing to the importance of cultural and institutional conditions, such as trust in charities and informal giving practices. The study contributes to sustainability research by showing that fostering well-being and targeting specific demographic groups can enhance philanthropy, while also emphasizing the need for culturally sensitive approaches in understanding prosocial behavior within emerging economies. Full article

This work presents a validation process of a Helmholtz cage developed by the authors at AGH University of Krakow. This type of test stand can generate a near-uniform, precisely controlled magnetic field inside its workspace. This is a crucial tool for several applications, including calibration of magnetic sensors, testing magnetorquers, and hardware-in-the-loop tests of attitude determination and control systems of small satellites. Although many institutions develop Helmholtz cages, we found the literature on methods of validating the final accuracy and uniformity of the generated magnetic field somewhat lacking. In this research, we showcase an approach to perform 3D scans of the magnetic field inside the cage using a probe actuated by a robotic arm. With that method, we verified that the magnitude and angle nonuniformity of the magnetic field vectors in our cage are below 2 percent and 0.4°, respectively, for a wide range of control inputs. We also perform background magnetic field measurements to identify and quantify sources of magnetic disturbances coming from the outside of our system and propose methods of minimizing their impact. It turns out that careful design and building process of the cage and its power driver might not be sufficient to achieve the optimal performance. In our case, we found that some factors, if unmitigated, can cause an error of a few milligauss. Hopefully, this work will help other teams developing similar devices avoid at least some of the possible pitfalls. Full article

This study aims to examine the determinants of tourist continuance intention in halal tourism in Indonesia and extend the Theory of Planned Behavior (TPB) model by incorporating sustainable tourist citizenship behavior (STCB) and tourists’ emotional events and past halal experiences to provide a rounded understanding of Muslim tourists’ revisit intentions. This quantitative study employed partial least squares structural equation modeling (PLS-SEM) to analyze the data collected from 500 Muslim tourists who visited halal destinations in West Sumatra. The findings reveal that their STCB, attitudes, subjective norms, and perceived behavioral control significantly influence their continuance intention. Moreover, the empirical findings indicate that tourists’ emotional events and past halal experiences positively affect the TPB constructs, further strengthening the behavioral outcomes. All the proposed hypotheses were supported by the model and highlight the critical roles of psychological, experiential, and behavioral factors in shaping tourist loyalty. The results of this study contribute to the theoretical advancement of halal tourism behavior and offer practical suggestions for destination management to enhance sustainable engagement and repeat visitation among Muslim travelers. Full article

Plant-based meat alternatives (PBMAs) are gaining momentum in response to rising demand for sustainable and healthier diets. Drawing on an integrated framework combining the Theory of Planned Behavior (TPB) and the Value–Attitude–Behavior (VAB) model, this study explores key determinants shaping consumers’ purchase intention towards PBMAs in Taiwan. This study performed Partial Least Squares Structural Equation Modelling (PLS-SEM), fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) to evaluate the formation of consumers’ PBMA purchase intention. The PLS-SEM results revealed that both environmental consciousness and health consciousness exert a significant influence on consumer attitudes, which, together with subjective norms and perceived behavioral control, positively predict purchase intention. fsQCA revealed six distinct combinations of conditions leading to high purchase intention, while NCA identified environmental consciousness, health consciousness, and the three TPB components as necessary conditions. The results highlight the mediating role of attitude and underscore the value of integrating multiple analytical perspectives to capture the complexity of consumer decision-making. This research advances both theoretical understanding and practical application by elucidating the psychological mechanisms underpinning PBMA adoption and by providing evidence-based implications for strategic marketing within the plant-based food sector. Full article

The issue of modeling the personal innovativeness of project team members is determined in this study. Findings from prior research on social capital associated with innovations and innovative activities reveal that social capital factors such as trust, social networks and connections, and social values determine a person’s attitude to innovations. Different connections involved in bridging (external) and bonding (internal) social capital can create conflict between project team members in different ways. To stimulate innovation in a conflict environment, a specially configured conflict management system is required that is capable of regulating the strength and intensity of the relationship between project team members. This paper analyzes the relationship between three constructs—innovativeness, social capital, and conflict. The existence of these latent constructs, which are formed by observable indicators of employees, is proven using confirmatory factor analysis (CFA). The construct of innovativeness depends on indicators such as creativity, risk propensity, and strategicity. Social capital includes observable indicators such as trust, social networks and connections, and social norms and values. Conflict consists of observable indicators of conflict between tasks, processes, and relationships. Using structural equation modeling (SEM), the causal relationship between social capital and innovativeness is substantiated with the mediating role of conflict in project groups between its participants—innovators and adaptors. The developed sociodynamic model for measuring conflict between innovators and adapters examines the required values of the controlled parameters of intra-group and inter-group connections between innovators and adapters in order to achieve equilibrium conflict dynamics, resulting in cooperation between them. This study was conducted using data from a survey of employees of a research organization. All model constructs were tested on a sample of employees as a whole, as well as for groups of innovators and adaptors separately. Full article

The main objective of this study is to determine the knowledge and awareness levels of climate change among preparatory class students at Zonguldak Bülent Ecevit University in the Western Black Sea Region of Türkiye using an unsupervised clustering approach. Within this scope, a survey was administered to university students (n = 280). Participant scores for the survey sections containing five-point Likert-type questions on climate change awareness were calculated using min–max normalization. The normalized data was then processed using the k-means algorithm, a well-known technique in unsupervised machine learning. This resulted in a classification (clustering) related to climate change awareness. The number of clusters was determined using the Silhouette index. Three clusters identified using k-means and Silhouette index ($S\approx 0.55)$ revealed the knowledge and application levels of student groups regarding climate change awareness. As a result of clustering, it was determined that Cluster-3 students (n = 134, 47.9%), defined as having a high level of knowledge and application, had a higher impact value in their overall assessments of green space-focused issues related to climate change awareness compared to the overall assessments of students in other clusters. Some notable findings concerning the attitudes of Cluster-3 students highlight climate change awareness-related practices. These include minimizing water consumption to levels necessary for ecosystem water management (mean = 95.7, std. deviation = 10.9) and exercising controlled, sustainable daily energy use to alleviate pressure on green spaces (mean = 94.4, std. deviation = 12.5). This study offers practical insights for policymakers, educators, and institutions, emphasizing the need to enhance climate education and to promote the active involvement of younger generations in shaping sustainable environments. Full article

Background: Euthanasia and physician-assisted suicide (EPAS) are highly contentious topics with significant medical, legal, and cultural implications. Previous research suggests that various sociodemographic, health, and psychosocial factors determine attitudes toward EPAS. This study set out to identify psychosocial predictors of support for EPAS. We hypothesized that perceived control, self-efficacy, and social support would each predict support for EPAS after controlling for sociodemographic and health-related variables. Methods: For this study, we recruited 446 Jewish Israeli adults who were 82.32 years of age on average (SD = 5.99; range 65–101 years). Participants completed a battery of questionnaires including a series of vignettes featuring hypothetical family members with a terminal illness (i.e., cancer, dementia, Parkinson’s disease). We performed a three-step hierarchical regression equation, controlling for demographic factors (age, gender, education, relationship status, economic status, and religiosity) as well as perceived and relative physical health. Results: As hypothesized, both self-efficacy and (the absence of) social support predicted support for EPAS; perceived control did not. Religiosity was the strongest predictor of opposition to EPAS. Fully 31% of variance in support for EPAS was predicted by this regression model. Conclusion: Support for EPAS does not appear to reflect a pervasive need for control over all aspects of life (i.e., perceived control) but a more specific need for personal autonomy (i.e., self-efficacy). Longitudinal research is required over multiple points of data collection to ascertain how change in social support affects support for EPAS in late life. Policy makers should embrace these findings when formulating end-of-life care policies, ensuring that both social support and personal autonomy are prioritized in the care of older adults. Full article

Practising the calculation of determinants is important in linear algebra. A pioneering study involving 580 first-year university students evaluated the impact of game-based learning in higher mathematics education. The participants formed two groups: an experimental group of 279 students and a control group of 301. The experimental group students played the non-digital educational card game DETerminator, designed to help students learn and practise calculating determinants in small square matrices. In contrast, the control group received no intervention, allowing for a clear outcome comparison. Students in the experimental group worked in smaller teams during didactic gameplay sessions that involved solving matrix-determinant problems in a competitive and collaborative classroom setting, enhancing their understanding through interaction and teamwork. The objective of this paper is to provide a detailed presentation of the DETerminator game and showcase its integration as an effective teaching tool for practising essential concepts and theorems related to determinants. Moreover, a quasi-experiment was conducted to explore how incorporating game-based learning can lead to successful and enjoyable mathematical education experiences for students. We used a quantitative approach to assess the effectiveness of the card game on academic achievement. At first, a pre- and post-test design was employed with the experimental group of 279 participants to evaluate the short-term effects of game-based learning. The Wilcoxon test was utilised for hypothesis testing, revealing a large effect size of 0.63. Moreover, the results from related midterm exam problems were statistically analysed to obtain the medium-term impact. The outcomes were compared using the Mann–Whitney U-test. The results demonstrated that the experimental group statistically outperformed the control group, but achieving a small effect size of 0.16, with a mean score of 3.14 out of 7 on the designated midterm exam tasks, compared to the control group’s mean score of 2.5. The small effect size suggests that, although the intervention had a positive effect, it is worth considering what other options there are for increasing the medium-term effect. A Likert-scale questionnaire was used to evaluate students’ attitudes towards the game. Our findings show the importance of incorporating game-based learning strategies in mathematics education at the university level, especially for enhancing students’ proficiency in key topics such as the determinant of a matrix. Full article

Background: Lower respiratory tract infections (LRTIs) are one of the leading causes of mortality. Pharmacist-led interventions can enhance adherence to antibiotics; the present study aims to determine adherence to the antibiotics prescribed for LRTIs and related factors. Methods: An individual randomized controlled trial was conducted with 1:1 (intervention = 205, control = 205) participants aged >18 years. The primary outcomes included adherence to therapy at weeks 1 and 2, awareness of antibiotic use, and appropriate discontinuation as prescribed. The secondary outcome measures were the overall clinical outcomes of the therapy and the effectiveness of educational interventions assessed at the final week 7 (overall assessment checked and treatment was not continued). The data were analyzed using different statistical methods, including descriptive statistics for data summarization, and inferential techniques were used. Results: Finally, 187 patients remained in the intervention group, and a total (n = 18) lost to follow-up. The awareness was significantly increased through pharmacist-led interventions (n = 106, 56.7%; p = 0.01), along with the factors leading to antibiotic resistance knowledge. Overall, adherence to antibacterial therapy for the LRTIs has improved (p ≤ 0.01), and a significant correlation exists between overall MMAS-8 mean scores and other demographic factors; interventions improved [0.441–2.151] with adherence (post-intervention). Higher adherence was found (p ≤ 0.05) among the participants in the intervention group compared to the control group and with (OR: 1.050; CI: 0.150–1.024) demographics (education, p = 0.05). Conclusions: Overall, the intervention group showed better awareness, understanding, and attitudes about antibiotics, and their adherence to antibiotic therapy improved significantly, along with the overall clinical outcomes. Full article

This study interrogates whether Augmented Reality (AR) enhances vocabulary and content acquisition within Content and Language Integrated Learning (CLIL), situating the question in the broader debate on how immersive, multimodal technologies shape achievement and engagement. This study’s novelty lies in its direct AR-versus-print comparison in a real CLIL classroom using markerless, smartphone-based technology. Using a mixed-methods, classroom-based experiment, we drew on a convenience sample of 129 secondary students (ages 16–18), assigning them to an AR intervention (n = 64) or a print-based control (n = 65). Both cohorts received parallel instruction covering identical objectives and materials; vocabulary attainment was gauged using matched pretest and post-test measures, while engagement, attitudes, and perceived usefulness were captured through paired pre- and post-surveys and open-ended prompts. Quantitative analyses compared change scores across conditions and were complemented by qualitative summaries of learner comments. Results indicate that exposure to AR exerted a positive influence on learners’ engagement and supported learning processes, with perceptible shifts in students’ views of AR between baseline and post-intervention; nevertheless, effects were heterogeneous across instruments, items, and subgroups, suggesting that benefits accrued in a targeted rather than uniform fashion. Compared to the print-based group, students using AR demonstrated greater gains on visually supported vocabulary and content items, while other items showed no significant differences between groups. We conclude that AR constitutes a promising pedagogical resource for CLIL, capable of scaffolding vocabulary/content development and motivating participation, while the observed variability underscores the need for principled, context-sensitive integration. Future work should specify boundary conditions—such as task type, prior proficiency, cognitive load, and technology familiarity—and employ robust mixed-methods designs to determine for whom, and under which instructional circumstances, AR yields the greatest and most sustainable gains. Full article

Small satellites or CubeSats orbiting in low Earth orbit (LEO) have become increasingly popular in Earth Observation missions, where high-resolution imaging is essential. Due to the lower mass of these spacecrafts, they are more sensitive to vibrations, and image quality can be particularly negatively affected by micro-vibrations. These vibrations originate from on-board subsystems, such as the Attitude Determination and Control System (ADCS), which uses reaction wheels to change the orientation of the satellite. The main goal of our research was to analyze these micro-vibrations so that the acquired data could be used for post-correction of camera images. Obuda University, as a participant in a research project, was tasked with designing and building a micro-vibration measuring device for the LEO CubeSat called WREN-1. In the first phase of the project, the satellite was launched into orbit, and test data were collected and analyzed. The results are presented in this article. Based on the data obtained in this way, the next step will be to analyze the images taken at the same time as the vibration measurements and to search for a correlation between the image quality and the vibrations. Based on the results of the entire project, it could be possible to improve the image quality of the onboard cameras of microsatellites. Full article

This research explores the complex relationships between tourism, economic factors, environmental sustainability, and transportation infrastructure within the European Union (EU), as the tourist scene changes globally. Our research uses a comprehensive model to investigate the factors that influence the number of tourists arriving in the EU, focusing on the years 1990 to 2022. The model considers transportation infrastructure, environmental sustainability indices, and economic variables as major determinants of tourism flows. Economic variables encompass exchange rates, the Consumer Price Index (CPI), and per capita income, while environmental sustainability indicators include carbon footprint and renewable energy usage. Additionally, the model considers transportation infrastructure by assessing the quality and availability of transportation modes. We use a two-way fixed effect to account for any unobserved heterogeneity. Fixed effects give control over nation-specific factors that might affect tourism, as they are a reliable method to deal with potential biases in the estimated parameters. Our study aims to provide insightful information about the sustainable growth of tourism in the European Union, providing policymakers, scholars, and industry stakeholders with a comprehensive understanding of the variables influencing visitor arrivals. This research contributes to the tourism literature by integrating CE principles with behavioral insights from the theory of planned behavior, highlighting how tourists’ pro-environmental attitudes, social norms, and perceived behavioral control influence travel choices. In the framework of the circular economy, the authors hope to inform policy choices and advance a more environmentally conscious travel industry in the EU by examining the points where economic, environmental, and transportation aspects converge. Full article

This study provides an experimentally validated workflow for the development and model-in-the-loop (MIL) validation of flight control laws for a small, low-cost fixed-wing UAV within a model-based design (MBD) framework, addressing the limitation that previous workflow demonstrations largely remain conceptual or simulation-only and that systematic processes for low-cost UAVs are lacking. A key advantage is that control law methods or parameters can be determined prior to flight testing, avoiding on-site tuning, a major challenge in UAV deployment. The Skysurfer X8 UAV served as the experimental platform. Linearized dynamic models were derived to design rate and attitude controllers using frequency-domain techniques, where loop shaping was applied to meet U.S. military flight quality standards. The control algorithms were validated in an MIL environment, enabling early evaluation of control logic, dynamic response, and robustness under idealized and perturbed conditions. Following MIL verification, the control logic was generated via Simulink Coder and deployed on a Pixhawk 6C flight controller with the PX4 autopilot. Flight test results on the Skysurfer X8 showed good agreement with MIL simulations, confirming the reliability and consistency of the proposed methodology in both simulated and real domains, while also demonstrating a systematic workflow that fills a practical gap in low-cost UAV development. Full article

In countries facing physical water shortages, the safe use of treated wastewater can increase agricultural yields. However, farmers’ willingness to reuse water in agriculture is very low. Therefore, the purpose of this study is to determine the factors that influence 217,215 Iranian farmers who use treated wastewater to adopt safe irrigation practices. This study, which developed the Theory of Planned Behavior (TPB) by including risk perception (RP) and knowledge factors, is a groundbreaking endeavor in the field of the safe use of treated wastewater at the farm level in Iran and around the world. The final model analysis was conducted based on structural equation modeling (SEM). The findings reveal that attitudes, perceived behavioral control (PBC), RP, and knowledge significantly influence farmers’ behaviors regarding safe wastewater use, while subjective norms did not impact intentions. The subjective norm in this study includes the perceived social pressure by farmers (through family, friends, the farming community, and local authorities) to perform or not perform safe behavior in using treated wastewater for irrigation. Notably, PBC was the most important component in the original TPB model, because intention has a beneficial impact on behavior. In the extended model, knowledge and risk perception emerged as critical elements. Therefore, intervention policies should prioritize enhancing farmers’ knowledge, risk perception, and perceived behavioral control to promote safe treated wastewater usage. This study offers valuable insights for developing countries in agricultural practices. Full article

We propose a novel systematic approach for the deployment optimization of unmanned aerial vehicles (UAVs). In this context, this study focuses on enhancing the coverage of UAV-mounted 6G mobile base stations. The number and placement optimization of UAV-mounted 6G mobile base stations, deployed to support terrestrial base stations during periods of increased population density in a given area, are addressed using a symbolic limited optimal discrete controller synthesis technique. Within the scope of this study, the UAVs’ altitude and attitude behaviors are optimized to ensure the most efficient trajectory toward the designated base station coordinates. Additionally, at their new locations, these behaviors are adjusted to facilitate accurate coverage estimation from the base stations they serve. In the deployment optimization of UAVs, the placement of base stations is determined using received signal strength data obtained through the ray-tracing-based channel modeling technique. The channel model considered critical parameters such as path loss, received power, weather loss, and foliage loss. Final average path loss values of 102.3 dB, 111.7 dB, and 127.4 dB were obtained at the carrier frequencies of 7 GHz, 26 GHz, and 140 GHz, respectively. These findings were confirmed with MATLAB-based ray tracing simulations. Our proposed approach is validated through experimental evaluations, demonstrating superior performance compared to existing methods reported in the literature. Full article