Search Results (604)

Pedestrian safety in developing countries faces critical challenges from rapid urbanization and infrastructure deficiencies. This study investigates how visual context influences pedestrian crossing preferences through a controlled stated preference experiment in multiple Ecuadorian cities. A sample of 875 participants was randomly assigned to view either non-compliant (mid-block crossing) or compliant (signalized crosswalk) imagery before evaluating six hypothetical scenarios involving three crossing alternatives. Multinomial logit models reveal that waiting time, traveling with a minor, and walking distance are primary determinants of choice. Visual context showed systematic associations with choice patterns: compliant imagery was associated with increased preference for safer alternatives (50.5% versus 43.8% prediction accuracy) and larger safety-related parameter magnitudes. Principal Component Analysis identified two latent perception constructs, safety/security and bridge-specific convenience, providing behavioral interpretation of choice patterns. Substantial spatial heterogeneity emerged across cities (χ² = 124.10 and 84.74, p < 0.001), with larger urban centers showing stronger responsiveness to formal infrastructure cues. The findings demonstrate that visual stimuli systematically alter choice distributions and attribute sensitivities through normative activation and perceptual recalibration. This research contributes methodologically by establishing visual framing effects in stated preference frameworks and provides actionable insights for pedestrian infrastructure design, emphasizing alignment of objective safety improvements with perceived risk and contextual behavioral cues. Full article

In the face of escalating environmental crises, sustainable development is becoming one of the key global challenges. A growing body of research indicates that transitioning to plant-based diets, including a vegan diet, can significantly improve environmental sustainability. Young people from Generation Z play a crucial role in shaping future consumption patterns, and their beliefs and attitudes toward sustainable food may serve as an important indicator of social changes in the area of nutrition and the potential for implementing pro-ecological practices. The aim of the study is to assess students’ perceptual attitudes toward plant-based products, which constitute an integral part of vegan diets, addressing a significant gap in the literature on sustainable consumption among Generation Z in emerging economies. The study allows for the identification of the main sources of information, psychosocial barriers, and motivational factors underlying the adoption of a vegan diet, situating them within sustainable development paradigms. The research group consisted of 263 university students in Warsaw (Poland). A CAWI survey method was used, with a proprietary questionnaire. The study shows that more than 60% of respondents were not interested in this dietary option, and a similar proportion did not expect to adopt veganism in the future. Students’ attitudes toward the vegan diet are shaped primarily by their self-assessment of nutritional knowledge, previous experiences with plant-based diets, and socio-cultural factors. Although many respondents recognize the health and environmental benefits of a plant-based diet, the lack of reliable knowledge, concerns about deficiencies, higher product costs, and social pressure remain key barriers limiting their willingness to change eating habits. From a practical perspective, the findings highlight the need to develop nutrition education focused on the competencies required to properly balance plant-based diets, to increase the economic and sensory accessibility of vegan food, and to counteract persistent stereotypes and misconceptions about veganism, especially on social media, which is the main source of information for this age group. Full article

This paper proposes E-MOTE (Emotion-aware Teacher Education Framework), an ethically grounded conceptual model aimed at enhancing teacher education through the integrated use of the Facial Action Coding System (FACS), Artificial Intelligence (AI), and Virtual Reality (VR). As a conceptual and design-oriented proposal, E-MOTE is presented as a structured blueprint for future development and empirical validation, not as an implemented or evaluated system. Grounded in neuroscientific and educational research, E-MOTE seeks to strengthen teachers’ emotional awareness, teacher noticing, and social–emotional learning competencies. Rather than reporting empirical findings, this article offers a theoretically structured framework and an operational blueprint for the design of emotion-aware teacher training environments, establishing a structured foundation for future empirical validation. E-MOTE articulates three core contributions: (1) it clarifies the multi-layered construct of emotion-aware teaching by distinguishing between emotion detection, perception, awareness, and regulation; (2) it proposes an integrated AI–FACS–VR architecture for real-time and post hoc feedback on teachers’ perceptual performance; and (3) it outlines a staged experimental blueprint for future empirical validation under ethically governed conditions. As a design-oriented proposal, E-MOTE provides a structured foundation for cultivating emotionally responsive pedagogy and inclusive classroom management, supporting the development of perceptual micro-skills in teacher practice. Its distinctive contribution lies in proposing a shift from predominantly macro-behavioral simulation toward the deliberate cultivation of perceptual micro-skills through FACS-informed analytics integrated with AI-driven simulations. Full article

Urban street greening structure plays a crucial role in promoting environmental justice and enhancing residents’ daily well-being, yet existing studies have primarily focused on vegetation quantity while neglecting how perception and governance interact to shape fairness. This study develops an integrated analytical framework that combines deep learning, machine learning, and spatial analysis to examine the impact of perceptual experience and socio-economic indicators on the equity of greening structure distribution in urban streets, and to reveal the underlying mechanisms driving this equity. Using DeepLabV3+ semantic segmentation, perception indices derived from street-view imagery, and population-weighted Gini coefficients, the study quantifies both the structural and perceptual dimensions of greening equity. XGBoost regression, SHAP interpretation, and Partial Dependence Plot analysis were applied to reveal the influence mechanism of the “Matthew effect” of perception and the Site governance responsiveness on the fairness of the green structure. The results identify two key findings: (1) perception has a positive driving effect and a negative vicious cycle effect on the formation of fairness, where positive perceptions such as beauty and safety gradually enhance fairness, while negative perceptions such as depression and boredom rapidly intensify inequality; (2) Site management with environmental sensitivity and dynamic mutual feedback to a certain extent determines whether the fairness of urban green structure can persist under pressure, as diverse Tree–Bush–Grass configurations reflect coordinated management and lead to more balanced outcomes. Policy strategies should therefore emphasize perceptual monitoring, flexible maintenance systems, and transparent public participation to achieve resilient and equitable urban street greening structures. Full article

Emotions are known to influence cognitive processes, yet the nature of this influence remains debated, particularly during childhood. According to the emotional congruence model, information congruent with an individual’s affective state is processed more efficiently than incongruent information. While this effect has been widely studied in adults, evidence in children is still limited. The present research investigates the influence of emotional congruence on selective attention in typically developing children from preschool to fifth grade, using a dual emotional induction paradigm based on music and color. In Study 1, classical music excerpts were used to induce pleasant or unpleasant emotional states and to validate the effectiveness of musical induction across age groups. In Study 2, this musical induction was combined with emotionally valenced color cues (yellow vs. gray) embedded in a visual search task to examine their impact on attentional performance. Results from Study 1 confirmed that music effectively modulated children’s emotional valence, although this effect was weaker in younger participants. In Study 2, attentional performance improved significantly when the task was presented on a yellow background, regardless of the valence of the previously induced musical emotion. No robust emotional congruence effect between music and color was observed, although performance was highest in the joyful music–yellow color condition. Overall, these findings suggest that perceptual emotional cues embedded in the task context, particularly positive color cues, exert a stronger and more persistent influence on children’s selective attention than transient affective states induced by music. This study contributes to developmental models of emotion–cognition interaction by highlighting asymmetrical valence effects and the predominant role of perceptual emotional signals in childhood attention. Full article

This study analyzes the socio-cultural and behavioral determinants of FinTech adoption and access to credit among Ecuadorian SMEs. A probabilistic sample of 600 firms, operating in the services, commerce, information and communication technologies (ICT), and industry sectors, was surveyed to ensure representation of the country’s productive structure. The model integrates financial literacy, institutional trust, and perceived accessibility as key independent variables, with FinTech adoption as a digital behavioral factor and access to credit and credit conditions as the primary dependent outcomes. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), complemented by multi-group invariance tests and cluster analysis, the study evaluates seven hypotheses linking cognitive, perceptual, and digital mechanisms to financing behavior and firm performance. Results show that financial literacy and institutional trust significantly improve access to formal credit, with perceived accessibility acting as a partial mediator. FinTech adoption enhances credit conditions but remains limited among micro and small firms. Based on these findings, the study recommends strengthening financial education programs, simplifying credit procedures to reduce perceived barriers, and developing trust-building regulatory frameworks for digital finance. The results highlight the importance of socio-cultural and behavioral factors in shaping SME financing decisions and contribute to the understanding of financial inclusion dynamics in emerging economies. Full article

Against the backdrop of rising global carbon emissions, promoting active transportation modes such as walking and cycling has become a key strategy for countries worldwide to meet carbon reduction targets and advance the goals of sustainable development. In China, the concept of low-carbon mobility has gained rapid traction, leading to a significant increase in public demand for non-motorized travel options like walking and cycling. From the perspective of inclusive urban development, gender imbalances in sample representation during design and evaluation processes have contributed to homogenization and a lack of diversity in urban slow-traffic environments. To address this issue, this study adopts a problem-oriented approach. First, we collect street scene images of slow-traffic environments through self-conducted field surveys. Concurrently, we gather satisfaction survey responses from 511 urban residents regarding existing slow-traffic streets, identifying three key environmental evaluation indicators: safety, liveliness, and beauty. Second, an experimental analysis is conducted to compare machine-generated assessments based on self-collected street view data with manual evaluations performed by 27 female participants. The findings reveal significant perceptual differences between genders in the assessment of slow-moving environments, particularly regarding attention to environmental elements, challenges in utilizing non-motorized lanes, and overall environmental satisfaction. Moreover, notable discrepancies are observed between machine scores and manual assessments performed by women. Based on these findings, this study investigates the underlying causes of such perceptual disparities and the mechanisms influencing them. Finally, it proposes female-inclusive strategies aimed at enhancing the quality of slow-traffic environments, thereby addressing the current absence of gender considerations in their design. This research seeks to provide a robust female perspective and empirical evidence to support improvements in the quality of slow-moving environments and to inform strategic advancements in their design. The findings of this study can provide a theoretical and empirical basis for the optimization of gender-inclusive non-motorized transportation environment design, policy formulation, and subsequent interdisciplinary research. Full article

Background/Objectives: Children born small for gestational age (SGA) are at increased risk for impaired growth, metabolic disturbances, and neurodevelopmental difficulties. Although previous research has examined cognitive and behavioral outcomes in this population, findings remain inconsistent. Moreover, limited evidence is available regarding the potential effects of recombinant human growth hormone (rhGH) therapy on cognitive development. We aimed to assess cognitive performance, emotional–behavioral functioning, and neonatal predictors of neurocognitive outcomes in term SGA children compared with age- and sex-matched peers born appropriate for gestational age (AGA). We also explored potential differences in cognitive outcomes between rhGH-treated and untreated SGA children. Methods: A total of 18 term SGA children and 23 AGA controls underwent anthropometric measurements, biochemical evaluation, cognitive testing using the Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV), and behavioral assessment through the Child Behavior Checklist (CBCL). Birth weight, length, and head circumference were analyzed as potential predictors of cognitive performance. Results: SGA children demonstrated significantly lower Intelligence Quotient (IQ) scores than AGA peers, with marked weaknesses in Perceptual Reasoning index (PRI) and Processing Speed index (PSI), while Verbal Comprehension and Working Memory were preserved. They also exhibited higher internalizing behavioral symptoms, whereas externalizing behaviors did not differ between groups. Birth head circumference emerged as a strong predictor of PRI and a modest predictor of PSI. No associations were found between rhGH treatment parameters and cognitive outcomes. Larger longitudinal studies are needed to clarify how early growth restriction affects brain development and cognition and whether GH therapy influences these processes. Full article

The gastronomic identity represents a blend of tradition, local resources, and cultural values that shape the authenticity and distinctiveness of a region’s gastronomy. Mačva, as an area in western Serbia, possesses an exceptionally rich gastronomic heritage whose tourism potential has not been sufficiently valorized. The subject of this research is the examination of the gastronomic identity of Mačva, and the purpose of the study is to determine how domestic tourists perceive the region’s gastronomic identity, which factors shape this identity, and the extent to which socio-demographic and perceptual characteristics influence the likelihood of purchasing traditional food products. The aim of this research is to develop an analytical framework to identify the key factors shaping the gastronomic identity of the Mačva region and to examine their influence on domestic tourists’ perceptions and consumer behavior related to the consumption and purchase of traditional food. The data were processed using exploratory factor analysis and binary logistic regression. The results indicate that respondents recognize the gastronomic culture of Mačva as an important component of the region’s cultural identity. The factor structure confirmed a three-dimensional model of gastronomic identity, comprising cultural–gastronomic heritage, authenticity and the promotion of gastronomy, and the region’s economic and social development. The results suggest that tourists’ intention to purchase traditional products is shaped by selected socio-demographic and perceptual factors, particularly gender and perceptions of gastronomy as a driver of economic and social development. The findings highlight the need for a differentiated approach to the development and positioning of the gastronomic offer, which may serve as a basis for formulating strategies for the development and branding of the Mačva region. Full article

Inclusive graphic design has emerged as a relevant approach within contemporary visual communication studies, driven by the need to ensure that graphic messages can be understood and used by diverse groups of users. Within this context, the present study conducted a systematic literature review with the aim of identifying the advances, trends, and recommendations that support the development of inclusive practices in graphic design. Using the PRISMA methodology, 85 primary studies were selected and analyzed, providing evidence to address the proposed research questions. The findings indicate a concentration of applications in digital interface design and visual communication, alongside the recurrent use of perceptual, cognitive, and semiotic theories, as well as principles of universal design. The analysis also reveals emerging trends related to new technologies, participatory approaches, and multisensory interactions, in addition to strategies that prioritize legibility, contrast, diverse representation, and user-centered design. Altogether, these findings depict a consolidating field that integrates technical, cultural, and social dimensions, highlighting the importance of continuing to develop research and tools that strengthen accessibility and inclusion in visual communication. Full article

Semantic communication frameworks aim to convey the underlying significance of data rather than reproducing it exactly, a perspective that enables substantial efficiency gains in settings constrained by latency or bandwidth. Motivated by this shift, we study the rate–distortion–perception (RDP) trade-off for image compression, a setting in which reconstructions must be not only accurate but also perceptually faithful. Our analysis is carried out through the lens of randomized distributed function computation (RDFC) framework, which provides a principled means of synthesizing randomness and shaping output distributions. Leveraging this framework, we establish finite-blocklength characterizations of the RDP region, quantifying how communication rate, distortion, and perceptual fidelity interact in non-asymptotic regimes. We further broaden this characterization by incorporating two practically relevant extensions: (i) scenarios in which encoder and decoder share side information, and (ii) settings that require strong secrecy guarantees against adversaries, which might include those with quantum capabilities. Moreover, we identify the corresponding asymptotic region under a perfect realism constraint and examine how side information, finite blocklength effects, and secrecy demands influence achievable performance. The resulting insights provide actionable guidance for the development of low-latency, secure, and realism-aware image compression and generative modeling systems. Full article

Background/Objectives: Lung cancer is the leading cause of cancer-related mortality worldwide, and early detection using low-dose computed tomography (LDCT) substantially improves survival outcomes. However, variations in CT acquisition and reconstruction parameters including Hounsfield Unit (HU) calibration, reconstruction kernels, slice thickness, radiation dose, and scanner vendor introduce significant intensity and contrast variability that undermine the robustness and generalizability of deep-learning (DL) systems. Methods: This systematic review followed PRISMA 2020 guidelines and searched PubMed, Scopus, IEEE Xplore, Web of Science, ACM Digital Library, and Google Scholar for studies published between 2020 and 2025. A total of 100 eligible studies were included. The review evaluated preprocessing and harmonization strategies aimed at mitigating CT intensity variability, including perceptual contrast enhancement, HU-preserving normalization, physics-informed harmonization, and DL-based reconstruction. Results: Perceptual methods such as contrast-limited adaptive histogram equalization (CLAHE) enhanced nodule conspicuity and reported sensitivity improvements ranging from 10 to 15% but frequently distorted HU values and reduced radiomic reproducibility. HU-preserving approaches including HU clipping, ComBat harmonization, kernel matching, and physics-informed denoising were the most effective, reducing cross-scanner performance degradation, specifically in terms of AUC or Dice score loss, to below 8% in several studies while maintaining quantitative integrity. Transformer and hybrid CNN–Transformer architectures demonstrated superior robustness to acquisition variability, with observed AUC values ranging from $0.90$ to $0.92$ compared with $0.85$–$0.88$ for conventional CNN models. Conclusions: The evidence indicates that standardized HU-faithful preprocessing pipelines, harmonization-aware modeling, and multi-center external validation are essential for developing clinically reliable and vendor-agnostic AI systems for lung-cancer screening. However, the synthesis of results is constrained by the heterogeneous reporting of acquisition parameters across primary studies. Full article

Youth soccer requires an integrated approach combining technical–tactical, physical, and psychological components to enhance performance and long-term engagement. Although Repeated Linear Sprint Training (LRST) and Repeated Change of Direction Speed (RCOD) training are widely used to improve fitness, direct comparisons of their effects on physical performance and perceptual responses in adolescent players remain limited. This study compared the effects of an 8-week LRST versus RCOD training program on physical performance, perceived exertion, and enjoyment in youth soccer players. Twenty-six male players were randomly assigned to an LRST group (n = 13) or an RCOD group (n = 13). Both groups completed two weekly sessions of their assigned training in addition to regular soccer practice. Pre- and post-intervention assessments included acceleration and sprint speed, change-of-direction (COD) performance (T-Half Test [THT], Illinois Agility Test [IAT]), lower-limb power (Five-Jump Test [5JT], Squat Jump [SJ], Countermovement Jump [CMJ]), and endurance-intensive fitness. Enjoyment and session-RPE were recorded after each training session. Both groups improved across all physical measures (main effect of time, p < 0.0001). Significant time × group interactions favored RCOD for THT (~1.6%), IAT (~1.1%), 5JT (~2.3%), CMJ (~5.2%), and SJ (~6.3%), with no overall main effect of group. Enjoyment was consistently higher in the RCOD group (p < 0.0001), while session-RPE did not differ between groups. In youth soccer, both LRST and RCOD effectively enhance physical performance. However, RCOD appears more effective for improving pre-planned COD and explosive performance while eliciting greater enjoyment without increasing perceived exertion. Incorporating structured RCOD training alongside linear sprint work may represent a practical strategy to optimize physical development and sustain player engagement. Full article

Background: Physical inactivity during adolescence remains a major public health concern, yet its multifactorial determinants are not fully understood in low- and middle-income settings. Objective: To identify and quantify the determinants of physical activity (PA) among Brazilian adolescents using a hierarchical logistic regression model that reflects the theoretical ordering of distal to proximal factors. Methods: A cross-sectional study was conducted with 856 adolescents (13–19 years). Data were obtained from the validated Brazilian Youth Risk Behavior Survey and the Brazilian Economic Classification Criteria (ABEP) socioeconomic questionnaire. PA was dichotomized according to World Health Organization recommendations. Hierarchical logistic regression examined five theoretical blocks: sociodemographic, anthropometric, substance use, weight/diet, and sedentary behavior. Results: Overall, 5 out of 17 predictors were significant in the full model. extended Body mass index (eBMI) was negatively associated with physical activity (OR = 0.331, 95% CI: 0.169–0.647, p = 0.001), while body mass was positively associated (OR = 2.078, 95% CI: 1.045–4.135, p = 0.037). Working status (OR = 1.235, 95% CI: 1.035–1.475, p = 0.019) and weight loss attempts (OR = 1.327, 95% CI: 1.042–1.690, p = 0.022) increased the odds of being active, whereas current smoking reduced it (OR = 0.715, 95% CI: 0.517–0.990, p = 0.043). Model discrimination improved progressively (AUC = 0.577 to 0.692). Conclusions: Physical activity among Brazilian adolescents was primarily influenced by behavioral and perceptual rather than demographic factors. These findings highlight the need for integrated interventions promoting muscle development, body positivity, and smoking prevention. Full article

With the rapid advancements in technology, there has been a noticeable increase in phishing attacks that exploit users by impersonating trusted entities. The primary attack vectors include fraudulent websites and carefully crafted emails. Early detection of such threats enables the more effective blocking of malicious sites and timely user warnings. One of the key elements in phishing detection is identifying the entity being impersonated. In this article, we conduct a comparative analysis of methods for detecting phishing websites that rely on website screenshots and recognizing their impersonation targets. The two main research objectives include binary phishing detection to identify malicious intent and multiclass classification of impersonated targets to enable specific incident response and brand protection. Three approaches are compared: two state-of-the-art methods, Phishpedia and VisualPhishNet, and a third, proposed in this work, which uses perceptual hash similarity as a baseline. To ensure consistent evaluation conditions, a dedicated framework was developed for the study and shared with the community via GitHub. The obtained results indicate that Phishpedia and the Baseline method were the most effective in terms of detection performance, outperforming VisualPhishNet. Specifically, the proposed Baseline method achieved an F1 score of 0.95 on the Phishpedia dataset for binary classification, while Phishpedia maintained a high Identification Rate (>0.9) across all tested datasets. In contrast, VisualPhishNet struggled with dataset variability, achieving an F1 score of only 0.17 on the same benchmark. Moreover, as our proposed Baseline method demonstrated superior stability and binary classification performance, it should be considered as a robust candidate for preliminary filtering in hybrid systems. Full article