Search Results (829)

This research examines road users’ willingness to pay for enhanced active mobility infrastructure at King Mongkut’s Institute of Technology Ladkrabang (KMITL), a suburban university campus in Bangkok, Thailand. The study addresses the need for sustainable transportation solutions in middle-income urban environments by analyzing factors that influence walking and cycling adoption among university community members. The research employed a comprehensive mixed-methods framework combining qualitative SWOT analysis, a stated preference survey of 400 participants, and regularized logistic regression modeling with cross-validation. The analysis revealed that specific infrastructure improvements significantly increase the likelihood of active mobility adoption. Rest areas demonstrated the strongest positive association (OR = 2.15, 95% CI: 1.08–4.27, p = 0.029), followed by CCTV security systems (OR = 1.89, 95% CI: 0.98–3.65, p = 0.047), and improved public transport connectivity (OR = 2.84, 95% CI: 1.42–5.68, p = 0.003). Demographic analysis uncovered notable resistance patterns, with male participants (OR = 0.48, 95% CI: 0.26–0.89, p = 0.020) and higher-income individuals showing reduced willingness to transition from motorized transportation. Using the Contingent Valuation Method with proper bias mitigation strategies, the study quantified potential behavioral changes, projecting a 12–18 min daily increase in active mobility engagement. This enhancement would generate measurable health benefits valued at 2840–4260 THB per person annually using WHO-HEAT methodology. The research contributes valuable insights to the limited body of active mobility literature from Southeast Asian suburban contexts, providing a replicable framework for similar investigations. Full article

This study investigates how land access, inheritance expectations, and socio-economic conditions influence migration intentions of rural youth in central Vietnam. Drawing on survey data from 200 young respondents and employing logistic regression analysis, the research reveals that youth with higher levels of education and income exhibit a greater propensity to migrate in pursuit of improved livelihoods. Male respondents were significantly more likely to migrate, reflecting gender norms and unequal access to opportunities. Crucially, secure land tenure—measured through formal land titles and perceived inheritance rights—was strongly associated with lower migration intentions. Conversely, tenure insecurity emerged as a significant push factor, undermining youth confidence in long-term rural investment and contributing to land use instability. This study argues that secure land access is not only vital for sustaining rural livelihoods but also foundational for youth and women’s engagement, socio-economic stability, and long-term community resilience. From this viewpoint, this study highlights the need for youth-inclusive land reforms, the promotion of rural entrepreneurship, and expanded access to vocational training as critical policy interventions. Full article

Image encryption plays a critical role in ensuring the confidentiality and integrity of visual information, particularly in applications involving secure transmission and storage. While traditional cryptographic algorithms like AES are widely used, they may not fully exploit the properties of image data, such as high redundancy and spatial correlation. In recent years, chaotic systems have emerged as promising candidates for lightweight and secure encryption schemes, but comprehensive comparisons between different chaotic maps and standardized methods are still lacking. This study investigates the use of three classical chaotic systems—Henon, tent, and logistic maps—for image encryption, and evaluates their performance both visually and statistically. The research is motivated by the need to assess whether these well-known chaotic systems, when used with proper statistical sampling, can match or surpass conventional methods in terms of encryption robustness and complexity. We propose a key generation method based on chaotic iterations, statistically filtered for independence, and apply it to a one-time-pad-like encryption scheme. The encryption quality is validated over a dataset of 100 JPEG images of size $512\times 512$, using multiple evaluation metrics, including MSE, PSNR, NPCR, EQ, and UACI. Results are benchmarked against the AES algorithm to ensure interpretability and reproducibility. Our findings reveal that while the AES algorithm remains the fastest and most uniform in histogram flattening, certain chaotic systems, such as the tent and logistic maps, offer comparable or superior results in visual encryption quality and pixel-level unpredictability. The analysis highlights that visual encryption performance does not always align with statistical metrics, underlining the importance of multi-faceted evaluation. These results contribute to the growing body of research in chaos-based image encryption and provide practical guidelines for selecting encryption schemes tailored to specific application requirements, such as efficiency, visual secrecy, or implementation simplicity. Full article

In the face of growing climate, economic, and social challenges, an integrated strategy is required to ensure the resilience of food systems in vulnerable regions is strengthened. This study aims to formulate strategies for increasing food security in Mercosur countries amid extreme climate events and socio-economic and environmental crises. These strategies are based on an analysis of the following: (i) changes in food security levels (Global Food Security Index); (ii) self-sufficiency in major agricultural products; (iii) key economic and environmental drivers between 2012 and 2022; and (iv) an assessment of the effectiveness of public policies aimed at alleviating the effects of poverty and drought between 2022 and 2023. A SWOT analysis was conducted to identify the strengths and weaknesses of food systems, as well as the opportunities and threats facing Mercosur countries. Significant differences in food systems’ availability and resilience have been revealed by the results, and the need for integrated regional policies in the countries studied has been highlighted. Recommendations for the region include developing infrastructure and logistics; investing in research and innovation; combatting poverty and inequalities; adapting to the effects of climate change; promoting the local production of fertilisers and biofuels; and implementing coherent monitoring mechanisms (GFSI). Full article

Workplace violence (WPV) against healthcare workers (HCWs) in infectious disease hospitals, particularly in high-risk settings, remains a critical yet understudied occupational hazard. A mixed-methods study was conducted at a Chinese infectious disease hospital, combining quantitative surveys (N = 675) and semi-structured interviews (28 HCWs, 17 patients/families). Logistic regression was used to analyze WPV incidence and predictors, while a thematic analysis of interview data identified contextual drivers. Psychological violence (34.1%) was significantly more prevalent than physical violence (2.2%), with outpatient departments (44.1%) and temporary staff (OR = 1.72) at the highest risk. Qualitative themes revealed systemic triggers, including communication breakdowns, environmental stressors, and organizational gaps in safety protocols and reporting. This study addressed a critical gap by incorporating the perspectives of HCWs and patients, revealing that WPV perceptions vary due to differing expectations and experiences. From these results, the CARE (Communication, Advocacy, Respect, Education) framework proposes actionable strategies: standardized SBAR communication protocols, enhanced security protocols in high-risk units, and mandatory anti-violence training. These findings underscore the need to strengthen the occupational health system to mitigate WPV and to improve healthcare quality. Full article

Introduction: Prior research underscores self-esteem as a core determinant of life satisfaction and overall well-being. However, few studies have examined this relationship within the unique sociocultural context of Saudi Arabia. This study assesses the relationship between self-esteem and life satisfaction in adolescents, as well as the potential moderating effects of demographic factors. Methods: A cross-sectional study was conducted involving 502 adolescents aged 13–18, selected from urban and rural regions of Saudi Arabia. Participants completed the Rosenberg Self-Esteem Scale and the Satisfaction with Life Scale. Data were collected via online survey platforms. Descriptive statistics, correlation analyses, chi-square tests, and multivariate logistic regressions were performed using SPSS version 26. Ethical approval was obtained, and informed consent was secured from all participants. Results: A significant positive correlation was found between life satisfaction and self-esteem scores (r = 0.37, p < 0.001). Adolescents reporting dissatisfaction with life had over seven times greater odds of low self-esteem (OR = 7.2; 95% CI: 3.75–13.83). Higher life satisfaction was associated with being in secondary education, having a family income of 10,000 Saudi Riyal (SR) or more, and living with both parents. Additionally, prior contact with a psychologist was linked to lower self-esteem and reduced life satisfaction. Conclusions: Findings confirm self-esteem as a strong predictor of life satisfaction among Saudi adolescents. Socioeconomic status, family structure, and previous psychological consultation also influenced outcomes. These results emphasize the critical need for culturally sensitive mental health interventions tailored to the Saudi context. Furthermore, they highlight the importance of implementing early mental health screening and support programs within schools to provide accessible and preventive care for youth. Full article

As the demand for context-aware services in smart environments continues to rise, Indoor Positioning Systems (IPSs) have evolved from auxiliary technologies into indispensable components of mission-critical infrastructure. This paper presents a comprehensive, multidimensional evaluation of IPSs through the lens of critical infrastructure, addressing both their technical capabilities and operational limitations across dynamic indoor environments. A structured taxonomy of IPS technologies is developed based on sensing modalities, signal processing techniques, and system architectures. Through an in-depth trade-off analysis, the study highlights the inherent tensions between accuracy, energy efficiency, scalability, and deployment cost—revealing that no single technology meets all performance criteria across application domains. A novel evaluation framework is introduced that integrates traditional performance metrics with emerging requirements such as system resilience, interoperability, and ethical considerations. Empirical results from long-term Wi-Fi fingerprinting experiments demonstrate the impact of temporal signal fluctuations, heterogeneity features, and environmental dynamics on localization accuracy. The proposed adaptive algorithm consistently outperforms baseline models in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), confirming its robustness under evolving conditions. Furthermore, the paper explores the role of collaborative and infrastructure-free positioning systems as a pathway to achieving scalable and resilient localization in healthcare, logistics, and emergency services. Key challenges including privacy, standardization, and real-world adaptability are identified, and future research directions are proposed to guide the development of context-aware, interoperable, and secure IPS architectures. By reframing IPSs as foundational infrastructure, this work provides a critical roadmap for designing next-generation indoor localization systems that are technically robust, operationally viable, and ethically grounded. Full article

The road transport sector is currently facing significant challenges, due in part to CO₂ emissions, high fuel prices, and a shortage of staff. These issues are partially caused by more than 40% of truck journeys being “empty runs” in some member states of the European Union and heavy under-utilization of deck space for non-empty runs. In order to overcome said inefficiency, this paper proposes a decentralized platform to facilitate collaborative transport networks (CTNs), i.e., to enable horizontal collaboration to increase load factors and reduce costs and CO₂ emissions. Our solution leverages secure multi-party computation (MPC) to guarantee that no sensitive business information is leaked to competing hauliers. The system optimizes truck assignments by modeling logistics as a weighted graph that considers orders and truck capacities while maintaining strict confidentiality. Our approach addresses key barriers to CTN adoption, such as lack of trust and data privacy. Implemented using MPyC without extensive optimizations, we demonstrate the efficiency and effectiveness in increasing the average load factor, while achieving acceptable running times (in the order of hours) for arguably meaningful instance sizes (up to 1000 orders). After leveraging a rather simplistic modeling inspired by previous work, we finally give an outlook of possible extensions toward more realistic models and estimate their impact on efficiency. Full article

International air traffic has contributed to the global spread of SARS-CoV-2 and its variants. In early 2023, wastewater-based epidemiology (WBE) has been implemented at airports as a surveillance tool to detect emerging variants at short notice. This study investigates the feasibility and challenges of applying WBE at Berlin Brandenburg (BER) Airport, including a rapid implementation of wastewater sampling and analysis under unprecedented circumstances. For this purpose, aircraft and airport wastewater was sampled over 13 weeks. Established sampling and analysis protocols for municipal wastewater treatment plants (WWTPs) had to be adapted to the specific conditions of the airport environment. SARS-CoV-2 RNA was quantified and sequenced, revealing SARS-CoV-2 mutations not previously observed in clinical surveillance data in Germany. Despite the logistical and methodological challenges, the study demonstrates that WBE can serve as an early warning system for pathogen introduction. However, our study also underscores the need for realistic timelines for the establishment and validation of WBE monitoring strategies in new contexts. Investments in the establishment of WBE systems, e.g., infrastructure, protocols, trained personnel, and a network of stakeholders at strategic nodes including airports, can act as an effective tool for pandemic preparedness and global health security. Full article

This work formulates and solves the actual problem of studying the logistics of unmanned aerial vehicle (UAV) operations in facility security planning. The study is related to security tasks, including perimeter control, infrastructure condition monitoring, prevention of unauthorized access, and analysis of potential threats. Thus, the topic of the proposed publication is relevant as it examines the sequence of logistical actions in the large-scale application of a swarm of drones for facility protection. The purpose of the research is to create a set of mathematical and simulation models that can be used to analyze the capabilities of a drone swarm when organizing security measures. The article analyzes modern problems of using a drone swarm: formation of the swarm, assessment of its potential capabilities, organization of patrols, development of monitoring scenarios, planning of drone routes and assessment of the effectiveness of the security system. Special attention is paid to the possibilities of wave patrols to provide continuous surveillance of the object. In order to form a drone swarm and possibly divide it into groups sent to different surveillance zones, the necessary UAV capacity to effectively perform security tasks is assessed. Possible security scenarios using drone waves are developed as follows: single patrolling with limited resources; two-wave patrolling; and multi-stage patrolling for complete coverage of the protected area with the required number of UAVs. To select priority monitoring areas, the functional potential of drones and current risks are taken into account. An optimization model of rational distribution of drones into groups to ensure effective control of the protected area is created. Possible variants of drone group formation are analyzed as follows: allocation of one priority surveillance zone, formation of a set of key zones, or even distribution of swarm resources along the entire perimeter. Possible scenarios for dividing the drone swarm in flight are developed as follows: dividing the swarm into groups at the launch stage, dividing the swarm at a given navigation point on the route, and repeatedly dividing the swarm at different patrol points. An original algorithm for the formation of drone flight routes for object surveillance based on the simulation modeling of the movement of virtual objects simulating drones has been developed. An agent-based model on the AnyLogic platform was created to study the logistics of security operations. The scientific novelty of the study is related to the actual task of forming possible strategies for using a swarm of drones to provide integrated security of objects, which contributes to improving the efficiency of security and monitoring systems. The results of the study can be used by specialists in security, logistics, infrastructure monitoring and other areas related to the use of drone swarms for effective control and protection of facilities. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease. It has known multifactorial pathophysiology, but the impact of social determinants of health (SDOH) on the rising prevalence of MASLD is poorly understood. We conducted a retrospective cross-sectional study to examine the influence of SDOH on MASLD using nationwide data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES) study. Methods: We identified participants with MASLD based on liver ultrasound-based controlled attenuation parameter measurements consistent with diagnostic guidelines. We then used logistic regression models to examine associations between SDOH variables and MASLD, with a pre-specified focus on education and income, sequentially adjusting for sociodemographic factors, medical comorbidities, and other SDOH. Results: Our study found that higher education (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.62–0.97, p = 0.024) but not higher income (OR 1.12, 95% CI 0.91–1.37, p = 0.3) was associated with lower odds of MASLD in multivariable adjusted models. We also identified a significant interaction between education level and food security, as well as interactions between food security and other significant SDOH. In the stratified analyses, higher education was significantly associated with lower odds of MASLD among participants with food security (OR 0.71, 95% CI 0.55–0.91, p = 0.007) but not among those with food insecurity (OR 1.26, 95% CI 0.76–2.11, p = 0.4). Conclusions: Our findings identify the potential impact of SDOH on odds of MASLD and suggest increased importance of food security relative to other SDOH. Full article

Salinization of olive orchards constitutes a front-line agronomic challenge for farmers, consumers, and the scientific community as food security, olive logistics, and land use become more unsustainable and problematic. Plantlets of two olive varieties (var. Kalamon and var. Koroneiki) were tested for their performance under soil saline conditions, in which L-methionine, choline-Cl, and L-proline betaine were applied foliarly to alleviate adverse effects. The ‘Kalamon’ variety ameliorated its photosynthetic rates when L-proline betaine and L-methionine were administered at low saline exposure. The stressed varieties achieved higher leaf transpiration rates in the following treatment order: choline-Cl > L-methionine > L-proline betaine. Choline chloride supported stomatal conductance in stressed var. Kalamon olives without this pattern, which was also followed by var. Koroneiki. Supplementation regimes created a mosaic of responses on varietal water use efficiency under stress. The total phenolic content in leaves increased in both varieties after exogenous application only at the highest levels of saline stress. None of the substances applied to olive trees could stand alone as a tool to mitigate salinity stress in order to be recommended as a solid agronomic practice. The residual exploitation of amino acids by the olive orchard microbiome must also be considered as part of an environmentally friendly, integrated strategy to mitigate salinity stress. Full article

In an era where digitalization shapes economic and social landscapes, the intersection of digital skills, ethics, and integrity plays a crucial role in understanding the vulnerability of youth classified as NEET (Not in Education, Employment, or Training). This study explores how risky internet use and digital skill gaps contribute to socio-economic exclusion, integrating a multivariate and spatial approach to assess regional disparities in Europe. This study adopts a systems thinking perspective to explore digital exclusion as an emergent outcome of multiple interrelated subsystems. The research employs logistic regression, Principal Component Analysis (PCA) with Promax rotation, and Geographic Information Systems (GIS) to examine the impact of digital behaviors on NEET status. Using Eurostat data aggregated at the country level for the period (2000–2023) across 28 European countries, this study evaluates 24 digital indicators covering social media usage, instant messaging, daily internet access, data protection awareness, and digital literacy levels. The findings reveal that low digital skills significantly increase the likelihood of being NEET, while excessive social media and internet use show mixed effects depending on socio-economic context. A strong negative correlation between digital security practices and NEET status suggests that youths with a higher awareness of online risks are less prone to socio-economic exclusion. The GIS analysis highlights regional disparities, where countries with limited digital access and lower literacy levels exhibit higher NEET rates. Digital exclusion is not merely a technological issue but a multidimensional socio-economic challenge. To reduce the NEET rate, policies must focus on enhancing digital skills, fostering online security awareness, and addressing regional disparities. Integrating GIS methods allows for the identification of territorial clusters with heightened digital vulnerabilities, guiding targeted interventions for improving youth employability in the digital economy. Full article

Radio Frequency Identification (RFID) technology is widely applied in various scenarios, including logistics tracking, supply chain management, and target monitoring. In these contexts, the malicious cloning of legitimate tag information can lead to sensitive data leakage and disrupt the normal acquisition of tag information by readers, thereby threatening personal privacy and corporate security and incurring significant economic losses. Although some efforts have been made to detect cloning attacks, the presence of missing tags in RFID systems can obscure cloned ones, resulting in a significant reduction in identification efficiency and accuracy. To address these problems, we propose the block-based cloned tag identification (BCTI) protocol for identifying cloning attacks in the presence of missing tags. First, we introduce a block indicator to sort all tags systematically and design a block mechanism that enables tags to respond repeatedly within a block with minimal time overhead. Then, we design a superposition strategy to further reduce the number of verification times, thereby decreasing the execution overhead. Through an in-depth analysis of potential tag response patterns, we develop a precise method to identify cloning attacks and mitigate interference from missing tags in probabilistic cloning attack scenarios. Moreover, we perform parameter optimization of the BCTI protocol and validate its performance across diverse operational scenarios. Extensive simulation results demonstrate that the BCTI protocol meets the required identification reliability threshold and achieves an average improvement of $24.01\%$ in identification efficiency compared to state-of-the-art solutions. Full article

Background: Prematurity and low birth weight (LBW) drive infant morbidity and mortality, requiring nutritional interventions, especially in food-insecure settings. In Indonesia, regional disparities in food security hinder adequate nutrition for premature and LBW infants, exacerbating health challenges. The aim of study is to investigate and determine factors associated with prematurity and LBW in children from food-insecure and food-secure households. Methods: This research employed a cross-sectional study with 657 mothers of children aged 36–59 months, conducted using random sampling. Data was collected via standardized questionnaires and analyzed using Chi-square tests and logistic regression. Results: The adjusted model showed that children of food-insecure households had a higher risk of LBW (AOR = 0.54; 95% CI: 0.29–0.99; p < 0.05). LBWs were found to significantly less occur in food-insecure households. Low maternal education was associated with an increased risk of preterm birth (AOR = 3.23; 95% CI:1.78–5.84; p < 0.001). Furthermore, prematurity correlated with house ownership (p < 0.01), indicating the household’s wealth condition. Maternal education and house ownership were linked to prematurity, indicating the risk to child health outcomes. In summary, maternal education, employment status, and household income were linked to food insecurity, indicating the risk to child health outcomes. Conclusion: Strategies to improve child health outcomes are essential, including enhancing maternal nutrition knowledge to improve child feeding practices, promoting gender equality in career development, and reducing food insecurity in households. Full article