Search Results (1,624)

Public transport systems in rapidly urbanizing Gulf cities confront the simultaneous challenge of decreasing emissions while guaranteeing equal access for riders, many of whom rely on transit for economic reasons. Sustainable smart city development necessitates bus services that are both efficient and sensitive to rider needs in adverse weather conditions. This study develops and evaluates a wellbeing-focused planning framework for Dubai’s bus network, filling gaps in prior research that primarily focuses on temperate, choice-based transport environments. The study uses Generalized Structured Component Analysis (GSCA) to analyze how Service Efficiency and Accessibility (SEA), Physical Environment and Passenger Comfort (PEPC), and Service Operations and Assurance (SOA) impact overall journey wellbeing, based on a cross-sectional survey of 491 riders collected from July–August 2024. Data were collected during peak summer conditions, and the analysis followed a structured workflow that operationalized the proposed constructs into measurable indicators and estimated both the measurement and structural components of the GSCA model to find planning relevant wellbeing drivers. The model shows a strong fit (FIT = 0.684; GFI = 0.991; SRMR = 0.056), with SEA (β = 0.504) having the greatest influence on wellbeing, followed by SOA (β = 0.344) and PEPC (β = 0.070). Affordability and information quality are key SEA metrics, highlighting the necessity of economic access and multilingual, real-time communication. Overall, the findings indicate that wellbeing is most strongly shaped by accessibility-oriented service experience attributes particularly affordability and information quality followed by operational assurance, while comfort-related conditions remain significant under high heat exposure during waiting and transfers. On the other hand, the research indicates that operational reliability helps mitigate environmental discomfort in hyper-arid areas. The report suggests focusing on equal prices, digital information accessibility, dependable operations, and climate-adaptive infrastructure to promote sustainable mobility and long-term public transport use. Full article

The Atlantic sharpnose (Rhizoprionodon terraenovae), blacknose (Carcharhinus acronotus), blacktip (Carcharhinus limbatus), and bonnethead (Sphyrna tiburo) sharks are commonly encountered large mobile consumers found in the estuaries along the western North Atlantic coast. The bulk of the dietary data for these species has been coarsely recorded at a broad taxonomic level (e.g., “teleost fish”). Here, we used DNA metabarcoding of fecal DNA collected using non-lethal cloacal swabs to identify the species of prey contributing to the diets of these shark species and measure the degree of trophic overlap. Samples were collected from 24 Atlantic sharpnose, 33 blacknose, six blacktip, and 17 bonnethead sharks in the summer of 2020. Based on previous dietary research on these shark species, we targeted teleost fishes and crustaceans using two previously published primer sets. From the 80 sharks sampled off the coast of North Carolina, we identified 38 prey taxa, with 82% classified to the species level and all assigned to at least the genus and family levels. The most common prey taxa found in the diet of the bonnethead was Atlantic blue crab (Callinectes sapidus; 44.75%, based on percent of occurrence) followed by penaeid shrimp (Penaeus spp.; 24.41%), mantis shrimp (Squilla empusa; 20.34%), and spot (Leiostomus xanthurus; 4.75%). Atlantic sharpnose and blacknose sharks had the largest Levin’s niche overlap, with both species relying on the same two most frequently consumed prey taxa: penaeid shrimp (Atlantic sharpnose: 33.33%, percent of occurrence, and blacknose: 34.78%) and spot (Atlantic sharpnose: 32.70% and blacknose: 22.32%). Bonnetheads and blacktips had the least amount of overlap between all shark species, where blacktips primarily consumed menhaden (Brevoortia spp.; 58.62%) and penaeid shrimp (26.44%). Our findings highlight the value of DNA metabarcoding in refining our understanding of predator diets, moving beyond broad taxonomic classifications to identify species-level prey associations and trophic interactions. As coastal habitats undergo increasing alteration due to anthropogenic impacts, such information is crucial for fisheries management, helping to identify key prey dependencies and anticipate potential ecosystem shifts. Full article

Background: This pilot study examined the feasibility, acceptability, usability, and preliminary outcomes of apt.mind, a mobile app-based mindfulness intervention with an exploratory smartwatch component, among healthcare worker families during the COVID-19 pandemic. Methods: Using a micro-randomized trial (MRT) design, 102 healthcare workers and co-parents of children aged 4–13 years were randomized once per day over 30 days to one of three conditions: (1) an audio-guided mindfulness exercise delivered via the apt.mind mobile app, (2) an in-app push notification prompting a brief mindfulness activity, or (3) no intervention. Feasibility was assessed through participant enrollment, retention, and daily engagement rates, while acceptability and usability were evaluated through qualitative and quantitative feedback. Exploratory multilevel analyses examined proximal effects of intervention conditions on momentary stress. Results: Retention was high, with all participants completing the 30-day protocol, and 80% of participants completed at least one daily survey. Participants reported moderate-to-high acceptability and usability. However, smartwatch battery life and sensor reliability limited the collection of usable physiological data. Multilevel analyses did not identify any significant main effects of intervention condition on momentary stress, but age moderated the association between the audio exercise condition and stress, benefiting older participants. Conclusions: Mobile-based mindfulness interventions appear feasible and acceptable for healthcare worker families in high-stress contexts. Although proximal stress effects were limited and exploratory, the findings inform future optimization of just-in-time adaptive interventions. Improvements in wearable technology and MRT implementation strategies are needed to enhance physiological data quality and reduce assessment-related anxiety. Full article

Autonomous mobile robots require robust localization in complex and dynamic environments, where single-sensor solutions often fail due to accumulated drift or signal degradation. LiDAR–inertial odometry provides accurate short-term motion estimation, but suffers from long-term error accumulation, whereas RTK-GNSS offers absolute positioning that becomes unreliable under occlusion or multipath effects. To solve the above problems, this paper proposes an adaptive multi-sensor fusion positioning framework that dynamically fuses LiDAR, IMU, and RTK-GNSS data based on the real-time quality evaluation of sensors. The system uses the front-end tightly coupled LiDAR–IMU iterative extension Kalman filter (IEKF) as the core estimator and combines loop detection with incremental factor graph optimization to suppress long-term drift. In addition, a degradation detection method based on the minimum eigenvalue of the Jacobian matrix is proposed to identify unreliable matching constraints in real time. In order to avoid abrupt changes in positioning results caused by fluctuations in sensor data quality, the system adopts a smooth fusion strategy based on covariance weighting. Experiments on the KITTI benchmark and self-collected datasets demonstrate that the proposed method significantly improves localization accuracy and robustness compared with pure LiDAR-based approaches, achieving stable centimeter-level performance while maintaining real-time capability on embedded platforms. Full article

Wheelchair users face environmental barriers that limit their mobility and social participation. Although existing navigation tools support urban mobility, they often lack clear orientation and confirmation cues, and information on accessible and safe routes to meet wheelchair users’ needs. This study aims to identify the most adapted route instructions for wheelchair users, examine characteristics’ (sociodemographic information and profiles) impact on their instructions’ choices, and evaluate instruction’s delivery modalities. An online questionnaire collected participants’ characteristics and agreement with the proposed route instruction formulations (different combinations of information like turn-by-turn instructions, landmarks, and accessibility information) regarding clarity, sufficiency, adaptability, and safety criteria. Formulations were evaluated across 14 navigation situations involving accessibility and safety challenges. Participants also rated communication modalities. 32 wheelchair-users (19 males, 13 females; mean age = 45.8 years; mean wheelchair experience = 23.5 years) participated. Data analysis reveals the importance of enriched turn-by-turn instructions, including non-turning actions, alerts, landmarks, and/or street names for participants. Alert-based formulations were favored in most situations, like uneven sidewalks, slopes and intersections. More enriched instructions were significantly acceptable among women and participants with greater wheelchair experience. Multimodal delivery, particularly visual and audio information, was also preferred. These findings help develop adaptive navigation tools, improving wheelchair users’ safe, confident mobility, autonomy, and social participation. Full article

Citrus production in Mexico relies predominantly on manual labor and traditional harvesting tools, which are often associated with physical overload, awkward postures, and reduced productivity. This study presents an exploratory, perception-based field evaluation of the BLIMPER, an early-stage ergonomic harvesting prototype designed for selective Persian lime collection. A total of 93 citrus harvesters participated through snowball sampling. A structured 33-item questionnaire was administered, covering five perception dimensions and open-ended comments. The instrument was expert-validated and demonstrated good internal consistency (Cronbach’s α = 0.85). Data analysis included descriptive statistics, Welch’s t-test for gender-based comparisons, and Hedges’ g to estimate the magnitude of the difference between groups. A modified Kano model was applied to classify perceived tool attributes and identify priorities for design refinement. The results indicated that 83–85% of respondents valued material strength, 64–70% approved of the unloading system, and 67–75% perceived reduced fatigue in the shoulders and lower back. The findings should be interpreted as an initial ergonomic validation based on user perceptions under real working conditions, rather than as evidence of readiness for large-scale deployment. The BLIMPER prototype shows potential to improve comfort and posture, while highlighting design aspects—weight distribution, mobility, and material selection—that require further optimization overall. Full article

This study examines the differences in sports learning among Generation Z based on digital literacy, using the Unified Theory of Acceptance and Use of Technology (UTAUT) and Media Richness Theory (MRT). As non-face-to-face sports learning—including online lectures, remote coaching, and virtual reality—rapidly expands, digital literacy has become a key factor influencing learning outcomes and equity. Data were collected from Generation Z adults engaged in sports learning through platforms including YouTube, social networking services, online lecture platforms, and mobile applications. Participants were classified into low (n = 87)-, medium (n = 80)-, and high (n = 70)-digital-literacy groups. A 32-item questionnaire adapted from prior studies assessed digital literacy (4 items), four UTAUT constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions; 16 items), and three media richness dimensions (multiple channels, immediacy of feedback, and personalness; 12 items). Confirmatory factor analysis demonstrated acceptable model fit (χ² = 779.013, df = 436, p < 0.001, NFI = 0.914, IFI = 0.960, TLI = 0.954, CFI = 0.960, SRMR = 0.037, RMSEA = 0.058), reliability (all ω and α > 0.70), and convergent/discriminant validity (all AVE > 0.50; C.R. > 0.70). Group comparisons indicated that higher digital literacy was linked to higher scores in technology acceptance and media richness perceptions (F = 40.364–64.150, p < 0.001, ηp² = 0.257–0.354) These findings indicate that intra-generational differences in digital literacy shape technology use and media experience in sports learning, highlighting the need to enhance media richness and systematically develop learners’ digital literacy to improve digital sports education’s effectiveness and equity. But causal inferences are limited by the cross-sectional design. Full article

This study provided county-level empirical evidence on how rural land institutional reform affected the urban–rural income gap, and offered policy implications for advancing rural revitalization and common prosperity. Utilizing panel data for 1380 counties in China from 2010 to 2020, this study treated the Market-Oriented Reform of Rural Collective Operational Construction Land in China (the Reform) as a quasi-natural experiment and used a multi-period difference-in-differences (DID) model as a quantitative approach to empirically examine the effect and underlying mechanisms of the Reform on the urban–rural income gap. The results indicated that: (1) The Reform significantly narrowed the urban–rural income gap and passed a set of robustness checks, with an average reduction of approximately 17.41%. (2) The Reform reduced the urban-rural income gap through multiple pathways, including “land supply expansion–value realization and appreciation”, “industrial structure upgrading–labor reallocation” and “efficient capital flows–infrastructure improvement”. (3) The narrowing effect of reform was more pronounced in eastern and western counties, counties with higher proportions of mountainous areas, and non-resource-dependent counties. (4) The Reform demonstrated diminishing marginal returns: the effect was larger in counties with wider initial urban–rural income gaps. In addition, more market-oriented land transfer methods were more conducive to land value realization. Accordingly, the government should advance the Reform prudently, adopt place-based implementation, promote two-way factor mobility, and improve benefit-sharing and regulatory mechanisms to sustain policy gains. Full article

Background/Objectives: A plethora of articles report the effectiveness of many different interventions for managing cerebral palsy (CP), but there are few long-term follow-up studies of children after an intervention designed to improve function in children with CP. This observational mixed-methods study examined the functional gains observed more than one year after toddlers completed a 48-week investigation that included 5 days per week for 12 weeks of occupational and physical therapy using the Perception-Action Approach (P-AA). The aim was to observe whether the functional gains made by the children continued to improve, plateaued, or declined at long-term follow-up. Methods: The sample was 23 children with a mild-to-moderate level of CP (Gross Motor Function Classification System I, II, or III) who completed the original study at least one year prior. The follow-up assessment included quantitative data using the Gross Motor Function Measure-66 (GMFM) and the Pediatric Evaluation of Disability Inventory-Functional Skills (PEDI-FS). Seventeen of 23 children were evaluated with both instruments. Qualitative data were collected from 14 of the 23 families who completed the PEDI-FS. Those families completed a survey with an open-ended questionnaire that assessed the caregivers’ perspectives about their children’s functioning and the impact of the intervention. Results: Findings from the quantitative data based on prognostic GMFM-66 developmental curves by age for children with CP: seven of the 17 children who had GMFM evaluations showed greater than expected improvement (all 5 with GMFCS II), four met the expected improvement, and six did not. Children with GMFCS II or III maintained their positions relative to the mean on the PEDI-FS mobility subset. Findings from the qualitative data revealed that some parents believed the intervention contributed to the changes in their children’s physical, mental, and social functioning. Many parents indicated that the study helped them overcome financial barriers related to accessing intensive therapies. Most parents reported that their child’s functioning was better than they expected when given the diagnosis of CP. Conclusions: Many months following an intense physical and occupational therapeutic intervention, based on predicted age-appropriate percentiles for motor function, roughly one-third of the children exceeded expectations, and one-third did not meet expectations. Despite the time invested in the intense protocol, caregivers felt the intervention was largely responsible for improvements in their children’s functioning. Full article

Farmers’ adoption of green grain production practices is essential for advancing China’s ecological civilization and achieving carbon neutrality. However, adoption remains uneven because farmers’ decisions are embedded in local social structures and shaped by short-term economic incentives and constraints. Drawing on an embeddedness framework, this study investigates how social mobilization influences farmers’ green grain production practices, while also examining the moderating role of household resource endowments and the mediating role of non-market value perceptions. Using multi-stage survey data collected in Heilongjiang Province between June and September 2023, the results show that grassroots cadres foster farmers’ green production adoption through four dimensions of social mobilization—technical, knowledge, cultural, and relational embeddedness. Moreover, household endowments positively moderate these effects, and non-market value perceptions partially mediate the relationship between social mobilization and green production practices. These findings are robust to alternative model specifications. This study provides micro-level evidence on how a cadre-led, governance-based social mobilization process is associated with farmers’ adoption of green production practices. Overall, this study advances understanding of the behavioral foundations of farmers’ green transitions and highlights actionable policy levers for grassroots governance, helping translate external policy directives into internalized and sustainable production practices. Full article

The mainstreaming of remote work has catalyzed the rise of the new tribe, the kinetic elite, a demographic comprising digital nomads and workationers who utilize technology to separate work from geography. Yet, this apparently free lifestyle often leads to a freedom trap, where the collapsing boundaries between work and leisure necessitate intense self-discipline within spaces originally architected for tourism. Drawing on an integrated framework of quality of destination features, service, and experience, this study investigates the antecedents of satisfaction and loyalty for this niche market of mobile workforce. Data were collected from 325 international digital nomads and workationers in Thailand using a purposive sampling approach. The proposed integrated model was empirically tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The analysis challenges the hardware-first paradigm of destination development. Findings indicate that while digital infrastructure (connectivity) and geoarbitrage (value) are non-negotiable baselines, they employ limited influence on ultimate satisfaction. Instead, human infrastructure, specifically the quality of staff and host–community interactions, emerges as the primary determinant in converting a location from a travel stop into a functional home base. These results advocate for a strategic plan toward precision niche marketing, moving beyond a homogenous view of the sector to target the community-seeking segment. Furthermore, the study frames community integration as a core practice of social sustainability, suggesting that for destinations to evolve into vibrant knowledge ecologies, Destination Management Organizations (DMOs) must prioritize community facilitation and smart policies that mitigate the social isolation inherent in nomadic life. Full article

Regional epidemic risk prediction requires holistic modeling of heterogeneous data sources such as demographic structure, health capacity, geographical features and human mobility. In this study, a unique and multi-modal epidemiological data set integrating demographic, health, geographic and mobility indicators of Türkiye and its neighboring countries was collected. Türkiye’s neighboring countries are Greece, Bulgaria, Georgia, Armenia, Iran, and Iraq. This dataset, created by combining raw data from these neighboring countries, provides a comprehensive regional representation that allows for both quantitative classification and spatial mapping of epidemiological risk. To address the class imbalance problem, Conditional GAN (CGAN), a class-conditional synthetic example generation approach that enhances high-risk category representation was used. In this study, we proposed a multi-view deep learning model named MV-RiskNet, which effectively models the multi-dimensional data structure by processing each view into independent subnetworks and integrating the representations with an attention-based fusion mechanism for regional epidemic risk prediction. Experimental studies were compared using Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Autoencoder classifier, and Graph Convolutional Network (GCN) models. The proposed MV-RiskNet with CGAN model achieved better results compared to other models, with 97.22% accuracy and 97.40% F1-score. The generated risk maps reveal regional clustering patterns in a spatially consistent manner, while attention analyses show that demographic and geographic features are the dominant determinants, while mobility plays a complementary role, especially in high-risk regions. Full article

The integration of electric micromobility into urban transportation systems can significantly reduce the energy consumption and emissions associated with short-distance travel. However, quantitative energy-based assessments remain limited, particularly in complex environments such as port–city interfaces. This paper presents a scenario-based energy assessment framework combining survey data and energy modelling. Empirical data were collected through a user survey (n = 138) targeting port workers and nearby residents, providing information on trip distances, travel frequency, modal choice, and willingness to shift from private car use. These data were combined with an energy modelling framework based on mode-specific energy intensity values expressed in kWh per passenger-kilometre. Three scenarios were analysed: a baseline scenario without intervention, a modal shift scenario supported by basic infrastructure measures, and an integrated scenario including transport management measures and local photovoltaic energy coupling. Results indicate that a moderate modal shift of 35% from private cars to electric micromobility for short-distance trips can generate aggregated annual energy savings of approximately 30 MWh and reduce CO₂ emissions by around 7 t per year across the analysed cases. According to the proposed energy model, electric micromobility achieves up to a 95% reduction in energy use per passenger-kilometre compared to private car travel. Furthermore, photovoltaic coupling could supply between 55% and 85% of the annual charging demand. The proposed framework is transparent and transferable, supporting energy-efficient and electrified future mobility planning. Full article

5G systems have delivered on their promise of seamless connectivity and efficiency improvements since their global rollout began in 2020. However, maintaining subscriber identity privacy on the network remains a critical challenge. The 3GPP specifications define numerous identifiers associated with the subscriber and their activity, all of which are critical to the operations of cellular networks. While the introduction of the Subscription Concealed Identifier (SUCI) protects users across the air interface, the 5G Core Network (CN) continues to operate largely on the basis of the Subscription Permanent Identifier (SUPI)—the 5G-equivalent to the IMSI from prior generations—for functions such as authentication, billing, session management, emergency services, and lawful interception. Furthermore, the SUPI relies solely on the transport layer’s encryption for protection from malicious observation and tracking of the SUPI across activities. The crucial role of the largely unprotected SUPI and other closely related identifiers creates a high-value target for insider threats, malware campaigns, and data exfiltration, effectively rendering the Mobile Network Operator (MNO) a single point of failure for identity privacy. In this paper, we analyze the architectural vulnerabilities of identity persistence within the CN, challenging the legacy “honest-but-curious” trust model. To quantify the extent of subscriber identities being utilized and exchange within various API calls in the CN, we conducted a study of the occurrence of SUPI as a parameter throughout the collection of 5G SBI (Service-Based Interface) Core VNF (Virtual Network Function) API (Application Programming Interface) schemas. Our extensive analysis of the 3GPP specifications for 3GPP Release 18 revealed a total of 4284 distinct parameter names being used across all API calls, with a total of 171,466 occurrences across the API schema. More importantly, it revealed a highly skewed distribution in which subscriber identity plays a pivotal role. Specifically, the “supi” parameter ranks 57th with 397 occurrences. We found that SUPI occurs both as a direct parameter (“supi”) and within 72 other parameter names that contain subscriber identifiers as defined in 3GPP TS 23.003. For these 73 parameter names, we identified a total of 8757 occurrences. At over 5.11% of all parameter occurrences, this constitutes a disproportionately large share of total references. We also detail scenarios where subscriber privacy can be compromised by internal actors and review future privacy-preserving frameworks that aim to decouple subscriber identity from network operations. By suggesting a shift towards a zero-trust model for CN architecture and providing subscribers with greater control over their identity management, this work also offers a potential roadmap for mitigating insider threats in current deployments and influencing specific standardization and regulatory requirements for future 6G and Beyond-6G networks. Full article

This paper presents an intelligent UAV-based parking occupancy monitoring system using a lightweight DJI Mini 3 UAV platform and the YOLOv11 object-detection model. A proprietary aerial dataset was collected from a university parking lot and augmented to address data scarcity, defining two task-oriented classes: vehicle and parking. The proposed framework integrates UAV data acquisition, annotation, data augmentation, training, real-time inference, and occupancy computation into a deployable end-to-end pipeline. Experimental results demonstrate strong detection performance and stable real-time inference, achieving competitive precision, recall, and mAP (mean Average Precision) metrics while maintaining high frame rates suitable for real-time deployment. Comparative evaluation against YOLOv8 and YOLOv9 highlights deployment-oriented advantages rather than architectural novelty. The study confirms that UAV-based vision systems can provide a scalable, low-infrastructure solution for real-time parking monitoring and urban mobility applications, contributing an applied, system-level framework focused on integration and deployment feasibility. Full article