Search Results (8,720)

All over the world, the problem of ensuring the safety of pedestrians, who are the most vulnerable road users, is becoming more acute due to urbanization and the growth of micromobility. In 2013, according to WHO data, more than 270 thousand pedestrians were dying each year worldwide (accounting for 22% of all traffic accidents). Currently, experts report that around 1.3 million people die every year globally from road crashes. The roads in developing countries are particularly hazardous, according to experts, because the increase in the number of vehicles far exceeds the development of road infrastructure and safety systems. Since the risk of hitting a pedestrian depends on many factors that can have different natures, and the severity of the consequences can be determined by a set of other factors, the risk of an accident can only be reduced by influencing all these factors in a comprehensive manner. The novelty of our approach is to create an intelligent system that will gradually accumulate all the best practices into a single complex aimed at reducing the risk of an accident with pedestrians and the severity of the consequences if an accident does occur. The distinction lies in offering an integrated system where each module addresses a particular task, so by mitigating risks at every stage, one achieves a synergistic outcome. From the analysis of existing and applied developments, it is known that many specialists mainly solve a narrowly focused problem aimed at ensuring the one subsystems sustainability in the “vehicle-infrastructure-driver-pedestrian” system. Some of these ideas are given as practical examples. The relevance of the designated problem increases with the emergence of autonomous vehicles and smart cities, the sustainability of which depends on the sustainable interaction between all road users. As experience shows, only the implementation of comprehensive solutions allows us to solve strategic problems, including improving road safety. Here, by complex solutions we mean solutions that combine technical issues, as well as environmental, social, and managerial aspects. To account for different kinds of effects, indicator systems are developed and composite indices are computed to choose the most rational solution. The novelty of our approach consists in combining within a unified DSS algorithms for assessing the efficiency of the proposed solution with respect to technological soundness, environmental sustainability, economic viability, social acceptability, as well as administrative rationality and computation of interrelated effects resulting from implementing any given project. In our opinion, the proposed system will lead to a synergistic effect due to the integrated application of various developments, which will ensure increased sustainability and safety of the transport system of smart cities. Our paper proposes a conceptual approach to addressing pedestrian safety, and the examples provided illustrate how the same model or algorithm can lead to positive changes from different perspectives. Full article

As cattle are criticized for contributing to environmental problems by emitting pollutants, it is expected that environmental regulations on livestock will be strengthened. This will lead to an increase in the costs and benefits associated with these regulations. This paper develops a model that clearly shows the effects of environmental regulations on the production costs for cattle-breeding farmers and the changes in social welfare, as well as environmental benefits. The benefits associated with the regulation are measured by evaluating reductions in both greenhouse gas (GHG) and ammonia emissions. These benefits are then compared to the reduction in social welfare. According to the analysis, the reduction in social welfare, in terms of consumer and producer surplus, outweighs the environmental benefits. These results suggest that, in designing environmental regulations, policy measures are needed to alleviate producers’ economic burdens and minimize reductions in social welfare through byproduct utilization and technical support. Furthermore, this study contributes to laying the institutional foundation for the sustainable development of the livestock industry and the reduction in management costs associated with manure treatment. Full article

Background: Health problems can be an impediment during aging to political participation (PP), including voting. Furthermore, factors such as income, education, and level of physical activity (PA) also influence the PP of older adults. We examined whether income, education, and PA mediated the relationship between self-rated health (SRH) and PP in voters and non-voters aged 50 and over from 20 European countries. Methods: Data were taken from the European Social Survey. We included 14,701 individuals (64.63 ± 9.69 years), of which 52.5% were women. Results: Multivariate analyses suggested that increased SRH, income, education, and PA scores represented greater odds for intensifying PP in voters and non-voters. Mediation analyses showed that income, education, and PA partially mediated the association between SRH and PP among voters. Among non-voters, income was not a significant mediator of the association between SRH and PP. The largest mediated proportion occurred in the SRH → PA → PP path of voters at 35.34% and non-voters at 36.38%. The direct effect of SRH on the PP was verified only among voters. Conclusions: The findings contribute to a better understanding of the PP of individuals aged 50 and over and may contribute to planning strategies to increase PP in Europe. Full article

Fostering mathematical thinking, communication, and creativity has become a central goal in mathematics education as these competencies are strongly linked to flexible problem solving and innovative engagement. Prior research has shown that students’ beliefs and dispositions play a crucial role in shaping their learning, strategy use, and persistence, yet limited evidence exists on how these constructs interrelate among pre-service elementary mathematics teachers. Addressing this gap, the present study examines the relationships among mathematical thinking perceptions, mathematical communication dispositions, and creative thinking dispositions. A correlational survey design was employed to test a hypothetical model developed within the framework of structural equation modeling (SEM). Data were collected from 615 pre-service teachers. Analyses involved descriptive statistics, correlations, and predictive algorithms via IBM SPSS Statistics 24, along with standardized regression coefficients and fit indices using AMOS. The results revealed that while perceptions of problem-solving and higher-order thinking predicted creative thinking dispositions both directly and indirectly, perceptions of reasoning did so only indirectly through mathematical communication. Mathematical communication dispositions had the strongest direct effect on creative thinking dispositions, underscoring their mediating role. These findings highlight the importance of fostering communication alongside creativity in teacher education, thereby equipping future teachers to promote creative thinking through cognitive, social, and representational processes. Full article

Social communication difficulties characterize autism spectrum disorders (ASD). Gastrointestinal (GI) symptoms are more common in ASD than in the general population. The identification of GI problems in individuals with ASD is challenging due to their altered pain perception and irregular behaviors. Importantly, GI symptoms and ASD can potentially aggravate each other. However, it is unclear if GI problems cause ASD symptoms or vice versa. A crosstalk between the digestive system, gut microbiota, and the central and enteric nervous systems (CNS and ENS, respectively) has been repeatedly reported. The ENS regulates the GI tract with the CNS and the autonomic nervous system (ANS), as well as independently through specific neural circuits. Several mechanisms contribute to GI problems in ASD, including genetic mutations that affect the ENS, dysregulation of the ANS, alterations in gut microbiota, unhealthy dietary preferences, and changes in metabolomic profiles. Furthermore, studies have shown molecular and cellular differences in the GI biopsy of children with and without ASD. These findings highlight the unique nature of GI issues in ASD, underscoring the importance of further investigating the changes that occur in the digestive system and ENS in ASD models. Full article

Background: Self-medication (SM) among women during pregnancy poses a critical risk to maternal health, and SM is still commonly practiced in Saudi Arabia. Therefore, this study aims to assess the factors, attitudes, and prevalence of SM among pregnant women in the Ministry of Health (MOH) First Health Cluster. Methods: A cross-sectional design was used among 400 pregnant women who received care at primary, secondary, and tertiary healthcare levels. A structured tool was adopted and modified based on the literature review, expert and focus group interviews, and the experiences of the target participants. The dependent variables included history of illness, access to healthcare services, medication usage, and perception of SM, while the independent variables included socioeconomic status. Statistical Package for the Social Sciences (SPSS), Version 25 was used for analysis. Results: The prevalence of SM was 36.5%. Cough syrup and antipyretics were the most commonly used medications, while hair problems and weight loss were the most frequently reported reasons for SM. The primary sources of information guiding SM behavior were prior prescriptions and previous experience. Education level, occupation, age, number of pregnancies, and miscarriage history were all significantly associated with SM (p < 0.05). Conclusions: SM was found to be frequent among pregnant women in the First Health Cluster, highlighting the need for educational interventions and regulatory measures to reduce unsafe practices and improve maternal health. Full article

The rapid rise of e-commerce is intensifying pressure on last-mile delivery networks, making the strategic placement of parcel lockers an urgent urban challenge. In this work, we adapt multilayer two-mode Social Network Analysis to the parcel-locker siting problem, modeling city-scale systems as bipartite networks linking spatially resolved demand zones to locker locations using only open-source demographic and geographic data. We introduce two new Social Network Analysis metrics, Dual centrality and Coverage centrality, designed to identify both structurally critical and highly accessible lockers within the network. Applying our framework to Milan, Rome, and Naples, we find that conventional coverage-based strategies successfully maximize immediate service reach, but tend to prioritize redundant hubs. In contrast, Dual centrality reveals a distinct set of lockers whose presence is essential for maintaining overall connectivity and resilience, often acting as hidden bridges between user communities. Comparative analysis with state-of-the-art multi-criteria optimization baselines confirms that our network-centric metrics deliver complementary, and in some cases better, guidance for robust locker placement. Our results show that a network-analytic lens yields actionable guidance for resilient last-mile locker siting. The method is reproducible from open data (potential-access weights) and plug-in compatible with observed assignments. Importantly, the path-based results (Coverage centrality) are adjacency-driven and thus largely insensitive to volumetric weights. Full article

Objective: The objective of this exploratory pilot study was to examine the relationship between coping strategies and perceived quality of life in adolescents diagnosed with oncological diseases, with attention to the potential role of psychosocial factors in emotional adaptation. Method: The study included 20 adolescents (12 boys, 8 girls), aged 12–18 years, enrolled in the hospital school program in Bucharest, Romania, while receiving active oncological treatment. Participants completed two validated instruments: the Pediatric Quality of Life Inventory (PedsQL—Cancer Module) and the KidCOPE questionnaire. Results: The mean quality of life score was 70, indicating a moderately good level of quality of life. Emotion-focused and avoidance-based strategies (distraction, social withdrawal, and acceptance) were most frequently reported, while problem-focused coping was less common. Regression analysis showed that coping dimensions explained approximately 26% of the variance in quality of life (R² = 0.26, F(3,16) = 1.83, p = 0.183). Although the overall model was not statistically significant, an observed negative association was found between avoidant coping and quality of life (p = 0.037). These results should be interpreted with caution given the small sample size and cross-sectional design. Discussion: The findings suggest that adolescents with cancer may maintain a functional level of adaptation despite medical and emotional challenges, supported by medical staff and social resources. The predominance of avoidant strategies highlights the need for further investigation of their long-term implications. Conclusions: These preliminary results generate hypotheses and underline the importance of future research on psychological and educational interventions aimed at fostering more active coping strategies and supporting resilience in adolescents with cancer. Full article

Caregiver self-regulation may be a critical component of caregivers’ effective delivery of caregiver-mediated interventions (CMIs). CMIs are a highly evidence-based group of interventions that target a broad range of challenges, including social communication, emotion regulation, and externalizing behaviors, for autistic and neurotypical children. CMIs teach caregivers to be “coaches” to help their children learn and practice skills in daily life. However, being a good “coach” likely requires caregivers to optimally self-regulate their emotions, thoughts, and behaviors when working with their children in moments that are often emotionally heightened. Caregiver self-regulation is a set of skills that promote parenting autonomy and confidence: self-sufficiency, self-efficacy, self-management, personal agency, and problem solving. This conceptual paper will briefly discuss the literature on the role of caregiver self-regulation in CMIs and argue that future implementation research on CMIs should measure caregiver self-regulation because, in line with recent expansion of the theory of planned behavior, caregiver self-regulation may predict more effective implementation of CMIs. We also argue, in line with CFIR 2.0, that supporting caregiver self-regulation could ultimately improve the implementation of CMIs with regard to each implementation outcome in the Implementation Outcomes Framework. For example, enhancing caregiver self-regulation may improve CMI appropriateness (by increasing alignment with each caregiver’s values and culture), adoption (by increasing engagement to finish the full CMI protocol), and even CMI sustainability (by increasing caregivers’ ability to problem-solve and generalize to new child challenges independently, freeing up provider time to work with new caregivers and allowing the agency to provide the CMI for a reduced relative cost). Should future research demonstrate that caregiver self-regulation is an implementation determinant, future implementation strategies may need to include support for caregiver self-regulation, because it may explain or enhance the implementation of CMIs across early intervention and community mental health systems. Full article

Objectives: Periapical periodontitis, which is a periodontal dysfunction, is a current clinical problem. Due to the frequency of occurrence and the adverse effects they cause, they are considered a social disease. They require detailed diagnostics to implement appropriate treatment. Mathematical calculations based on data obtained from radiological images used in routine clinical practice may help differentiate the forms of periodontitis. This study aimed to evaluate the areas affected by periodontitis in comparison to the healthy tissues of the periapical area. Methods: The study analyzed texture components using the gray-level co-occurrence matrix (GLCM) and the gray-level run-length matrix (GRLM) on an orthopantomogram (OPG) from 50 patients with clinically confirmed periodontitis treated at the Department of Maxillofacial and Plastic Surgery, University of Bialystok. Texture analysis was performed on defined regions of interest (ROIs) to distinguish diseased from healthy tissues. We employed four classification algorithms to assess model performance. Results: The data set included 50 patients, with 76 cases of periodontitis and 50 healthy ROIs. The reference standard was clinical diagnosis confirmed by two specialist doctors. The best-performing algorithm achieved an AUC of 98%. Conclusions: The obtained results showed significant statistical differences in the inflamed regions compared to the control, which may aid in diagnosing and selecting the treatment method for periodontitis. Full article

Integrating information and communication technology (ICT) into STEM education enhances instructional quality and cultivates students’ interdisciplinary problem-solving. STEM teachers’ attitudes—driven by perceived ease of use (PEOU) and perceived usefulness (PU)—are pivotal in ICT adoption, and pre-service training offers a vital opportunity to shape these attitudes. Yet, empirical studies investigating how specific training strategies influence ICT attitudes via PEOU and PU remain scarce. Using a mixed-methods approach combining questionnaires and interviews, the results indicate that pre-service training significantly improved STEM teachers’ attitudes toward ICT-enhanced teaching. Socially interactive strategies (role models and collaboration) enhanced attitudes via PEOU by boosting confidence and reducing technology-related anxiety, cognitive design strategies (reflection and instructional design) operated through PU by emphasizing ICT’s pedagogical value, and experiential feedback strategies (authentic experience and feedback) influenced attitudes through both PEOU and PU, fostering integrated technical and pedagogical development. These findings support an integrated SQD–TAM framework and provide practical guidance for designing pre-service STEM teacher programs to promote sustained ICT adoption in China, and meanwhile highlights the importance of strategically sequencing training to cultivate both technological competence and pedagogical insight among future STEM educators. Full article

This study investigates the adoption of PyChatAI, a bilingual AI-powered chatbot for Python programming education, among female computer science students at Jouf University. Guided by the Technology Acceptance Model 3 (TAM3), it examines the determinants of user acceptance and usage behaviour. A Solomon Four-Group experimental design (N = 300) was used to control pre-test effects and isolate the impact of the intervention. PyChatAI provides interactive problem-solving, code explanations, and topic-based tutorials in English and Arabic. Measurement and structural models were validated via Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM), achieving excellent fit (CFI = 0.980, RMSEA = 0.039). Results show that perceived usefulness (β = 0.446, p < 0.001) and perceived ease of use (β = 0.243, p = 0.005) significantly influence intention to use, which in turn predicts actual usage (β = 0.406, p < 0.001). Trust, facilitating conditions, and hedonic motivation emerged as strong antecedents of ease of use, while social influence and cognitive factors had limited impact. These findings demonstrate that AI-driven bilingual tools can effectively enhance programming engagement in gender-specific, culturally sensitive contexts, offering practical guidance for integrating intelligent tutoring systems into computer science curricula. Full article

The global textile industry has a significant environmental impact, driven by fast fashion and rising consumption, which leads to large amounts of waste. In Chile, this problem is especially visible, with thousands of tons of discarded clothing accumulating in open areas and landfills. This study explores how to design a practical textile revalorization system grounded in local reality. We used a qualitative mixed-methods approach, combining semi-structured interviews with six experts in textile circularity and an online survey completed by 328 people. Thematic analysis revealed low public awareness of textile recycling, limited consumer participation, and major structural barriers, including scarce infrastructure and unclear regulations. Experts emphasized the importance of coordinated action among government, industry, and grassroots recyclers, while survey respondents highlighted the need for education and easier recycling options. Based on these insights, we propose an integrated framework that combines education campaigns, better recycling systems, and formal recognition of informal recyclers’ work. While centered on Chile, the study offers ideas that could support textile circularity efforts in other countries facing similar challenges. By merging expert knowledge with everyday public perspectives, the approach helps design more realistic and socially grounded solutions for textile waste management. As with many exploratory frameworks, external validation remains a necessary step for future research to strengthen its robustness and applicability. Full article

Digital transformation (DT) is rapidly reshaping education at multiple levels, including curriculum, instructional practices, and institutional culture. Within this context, entrepreneurship education has become a key field for preparing individuals to navigate uncertainty and generate social and economic value in a digital society. Entrepreneurial competencies are increasingly conceptualized as a multidimensional construct that encompasses creativity, problem-solving, critical thinking, collaboration, and digital literacy. This study aims to identify core entrepreneurial competencies relevant to the digital era and examine how technology-integrated instructional strategies contribute to their development. A systematic literature review was conducted in accordance with PRISMA 2020 guidelines, analyzing 72 peer-reviewed journal articles published between January 2021 and June 2025. The findings indicate that DT drives structural changes in education beyond tool adoption, with technologies such as artificial intelligence (AI), data analytics, and digital collaboration platforms serving as catalysts for innovative thinking and entrepreneurial behavior. These technologies are not merely supportive tools but are embedded in competency-based learning processes. This review provides a comprehensive competency framework integrating three domains, AI-collaborative pedagogy validation, and implementation strategies, enabling educators, curriculum developers, and policymakers to redesign entrepreneurship education that aligns with the realities of digital learning environments and fosters future-ready entrepreneurial capabilities. This conceptual framework theoretically systematizes the integration of innovative thinking and ethical execution capabilities required in the digital era, contributing to defining the future direction of entrepreneurship education. Full article

The university period is a transitional stage during which students develop heterogeneous interpersonal styles to navigate complex social demands. While prior studies have linked interpersonal functioning to adaptability and mental health, structural differences across interpersonal style groups remain underexplored. Therefore, the current research was designed to examine whether and how adaptability is differentially related to mental health symptoms when considered within the framework of distinct interpersonal style profiles. Using K-means clustering, we identified three distinct interpersonal profiles: the withdrawn and avoidant type, the overinvolved and compliant type, and the well-adjusted interpersonal type. Based on this classification, network analyses were conducted to examine how six dimensions of adaptability related to three core mental health symptoms within each group. The results showed a consistent pattern across all profiles, with emotional adaptability negatively associated with depression, anxiety, and stress. Subsequent network comparison analyses demonstrated that the withdrawn and avoidant group differed significantly in structure from the well-adjusted interpersonal group, particularly in the connections involving emotional, interpersonal, and economic adaptability. By uncovering meaningful differences in adaptability-mental health associations across interpersonal style, this study provides a foundation for designing targeted strategies that address the unique adaptabilities and mental health problems of distinct interpersonal profiles. Full article