Search Results (17,414)

The rapid advancement of connected and autonomous vehicles (CAVs) has the potential to revolutionize road transportation, promising significant improvements in safety, efficiency, and sustainability. However, traditional CAV architectures are predominantly modular and rule-based. They struggle with interaction, cooperation, and adaptability in complex mixed-traffic environments. Moreover, the substantial infrastructure investment required and the absence of compelling killer applications have limited large-scale deployment of CAVs and roadside units (RSUs), resulting in insufficient penetration to realize the full safety benefits of CAV applications and creating a deployment stalemate. To address the above challenges, this paper proposes an innovative connected autonomous vehicle system, termed AQ-CAV, which leverages recent advances in AI agents and QR codes. AI agents are employed to enable cooperative, self-adaptive, and intelligent vehicular behavior, while QR codes provide a cost-effective, accessible, robust, and scalable mechanism for supporting CAV deployment. We first analyze existing CAV systems and identify their fundamental limitations. We then present the architectural design of the AQ-CAV system, detailing the components and functionalities of vehicle-side and infrastructure-side agents, inter-agent communication and coordination mechanisms, and QR code-based authentication for AQ-CAV operations. Representative applications of the AQ-CAV system are investigated, including a case study on emergency response. Preliminary results demonstrate the feasibility and effectiveness of the proposed system, which achieves significant safety improvements at low system cost. Finally, we discuss the key challenges faced by AQ-CAV and outline future research directions that require exploration to fully realize its potential. Full article

Efficient waste management is a critical challenge in urban areas. This paper explores the optimization of power consumption in a smart bin management system using LoRa (long-range) communication technology. LoRa’s low-power, wide-area capabilities make it an ideal choice for IoT-based waste management systems. However, energy efficiency remains a crucial factor for ensuring the long-term sustainability of such systems, to avoid frequent intervention and reduce operating costs. This study employs advanced optimization techniques to minimize the energy usage of LoRa nodes while maintaining a reliable data transmission and system performance. By integrating a dynamic scheduling algorithm based on the usage of bins, and a custom adaptive data rate and power algorithm, the proposed solution significantly reduces the system’s energy impact. The performance of the system is evaluated through simulations and real-world deployment, where the results demonstrate a significant reduction in energy usage, over 84%, a longer battery life, and fewer maintenance interventions. The findings provide a scalable and energy-efficient framework for deploying smart waste management systems in resource-constrained environments. Full article

The integration of extended reality (XR) into industrial robotics requires robust middleware solutions capable of bridging heterogeneous systems, protocols, and user interactions. This paper presents a novel middleware framework designed to connect industrial robots with XR devices such as the HoloLens. The architecture employs a hybrid communication layer that combines MQTT (Message Queuing Telemetry Transport) and ØMQ (Zero Message Queue), leveraging the Sparkplug Robotics API model for robot data and publisher–subscriber streaming for XR camera feeds. A Redis cache database is introduced to ensure efficient data handling and prevent data corruption. On the robot side, the system is built on ROS 2 (Robot Operating System) and connects to proprietary industrial protocols through dedicated bridges, enabling seamless interoperability. Spatial alignment between physical robots and XR overlays is achieved using ArUco marker-based synchronization, while real-time kinematic and process data are visualized directly in XR. The middleware further supports bidirectional interaction, allowing users to adjust parameters and issue commands through XR devices. Beyond functionality, safety considerations are incorporated by integrating human–robot interaction safeguards and ensuring compliance with industrial communication standards. The proposed solution demonstrates how middleware-driven XR integration enhances transparency, control, and safety in robotic manufacturing processes, laying the foundation for greater efficiency and adaptability in Industry 4.0 environments. Full article

Unmanned Aerial Systems (UASs) are playing an increasingly critical role in both civilian and defense applications. However, their heavy reliance on unencrypted Global Navigation Satellite System (GNSS) signals, particularly GPS, makes them highly susceptible to signal spoofing attacks, posing severe operational and safety threats. This paper introduces a comprehensive, AI-driven multi-layer sensor framework that simultaneously enables real-time spoofing detection and secure command-and-control (C2) communication in lightweight UAS platforms. The proposed system enhances telemetry reliability through a refined preprocessing pipeline that includes a novel GPS Drift Index (GDI), robust statistical normalization, cluster-constrained oversampling, Kalman-based noise reduction, and quaternion filtering. These sensing layers improve anomaly separability under adversarial signal manipulation. On this enhanced feature space, a differentiable architecture search (DARTS) approach dynamically generates lightweight neural network architectures optimized for fast, onboard spoofing detection. For secure command and control, the framework integrates a low-latency cryptographic layer utilizing PRESENT-128 encryption and CMAC authentication, achieving confidentiality and integrity with only 1.79 ms latency and a 0.51 mJ energy cost. Extensive experimental evaluations demonstrate the framework’s outstanding detection accuracy (99.99%), near-perfect F1-score (0.999), and AUC (0.9999), validating its suitability for deployment in real-world, resource-constrained UAS environments. This research advances the field of AI-enabled sensor systems by offering a robust, scalable, and secure navigation framework for countering GPS spoofing in autonomous aerial vehicles. Full article

The Social Internet of Things (SIoT) enables collaborative service provisioning among interconnected devices by leveraging socially inspired trust relationships. This paper proposes a socially driven SIoT protocol for trust-aware service selection, enabling dynamic friendship formation and ranking among distributed service-providing devices based on observed execution behavior. The protocol integrates detection accuracy, round-trip time (RTT), processing time, and device characteristics within a graph-based friendship model and employs PageRank-based scoring to guide service selection. Industrial computer vision workloads are used as a representative testbed to evaluate the proposed SIoT trust-evaluation framework under realistic execution and network constraints. In homogeneous environments with comparable service-provider capabilities, friendship scores consistently favor higher-accuracy detection pipelines, with F1-scores in the range of approximately 0.25–0.28, while latency and processing-time variations remain limited. In heterogeneous environments comprising resource-diverse devices, trust differentiation reflects the combined influence of algorithm accuracy and execution feasibility, resulting in clear service-provider ranking under high-resolution and high-frame-rate workloads. Experimental results further show that reducing available network bandwidth from 100 Mbps to 10 Mbps increases round-trip communication latency by approximately one order of magnitude, while detection accuracy remains largely invariant. The evaluation is conducted on a physical SIoT testbed with three interconnected devices, forming an 11-node, 22-edge logical trust graph, and on synthetic trust graphs with up to 50 service-providing nodes. Across all settings, service-selection decisions remain stable, and PageRank-based friendship scoring is completed in approximately 20 ms, incurring negligible overhead relative to inference and communication latency. Full article

Background: Pharmacists in Saudi Arabia are assuming increasingly diverse and specialized roles amid rapid healthcare transformation. However, evolving expectations and expanding responsibilities may influence their job satisfaction, well-being, and career stability. This study aimed to assess job satisfaction, burnout, well-being, and career intentions among pharmacists across multiple practice sectors in Saudi Arabia. Method: A nationwide cross-sectional survey was conducted between December 2024 and January 2025 using an electronic questionnaire distributed to licensed pharmacists. The instrument assessed mental well-being, job satisfaction, burnout, workplace environment, and career mobility. Descriptive and inferential analyses were performed using SPSS version 20.0. Results: A total of 531 pharmacists completed the survey; 65% were male, and 89.3% were Saudi nationals. Sector distribution differed significantly by gender (p < 0.001): females were more represented in clinical and hospital pharmacy, while males predominated in the pharmaceutical industry–related roles. Male pharmacists reported higher work environment scores (p = 0.028) and greater sector mobility (34.2% vs. 23.7%, p = 0.012). Approximately 30.5% of participants had changed their employment sector at least once. Community pharmacists reported the highest burnout levels, whereas those in regulatory and administrative roles demonstrated the greatest job satisfaction (both p < 0.001). Participation in professional development showed strong positive associations with job satisfaction and intention to remain in the current role. Conclusions: Marked variations exist in pharmacists’ well-being, satisfaction, and career mobility across sectors in Saudi Arabia, with notable gender differences. Enhancing professional development, ensuring equitable work environments, and promoting sector-specific support strategies may help inform discussions on pharmacist engagement and retention within the evolving national healthcare system. Full article

Extended reality (XR), encompassing virtual reality (VR), augmented reality (AR), and mixed reality (MR), is rapidly reshaping the landscape of digital interaction and immersive communication. As XR evolves toward ultra-realistic, real-time, and interactive experiences, it places unprecedented demands on wireless communication systems in terms of bandwidth, latency, and reliability. Conventional RF-based networks, constrained by limited spectrum and interference, struggle to meet these stringent requirements. In contrast, visible light communication (VLC) offers a compelling alternative by exploiting the vast unregulated visible spectrum to deliver high-speed, low-latency, and interference-free data transmission—making it particularly suitable for future XR environments. This paper presents a comprehensive survey on VLC-enabled XR communication systems. We first analyze XR technologies and their diverse quality-of-service (QoS) and quality-of-experience (QoE) requirements, identifying the unique challenges posed to existing wireless infrastructures. Building upon this, we explore the fundamentals, characteristics, and opportunities of VLC systems in supporting immersive XR applications. Furthermore, we elaborate on the key enabling techniques that empower VLC to fulfill XR’s stringent demands, including high-speed transmission technologies, hybrid VLC-RF architectures, dynamic beam control, and visible light sensing capabilities. Finally, we discuss future research directions, emphasizing AI-assisted network intelligence, cross-layer optimization, and collaborative multi-element transmission frameworks as vital enablers for the next-generation VLC–XR ecosystem. Full article

Background/Objectives: The Thriving at Work model proposes that organisations have a responsibility to provide supportive work environments that identify individual health outcomes, which organisations can use to determine where workforce support is needed. The aims of this study are to (1) identify and compare the predictors of early-career nurses’ thriving at work in New Zealand and Australia and (2) provide innovative and theory-informed recommendations to improve organisational support of early-career nurses to increase retention in the profession. Design: A multinational cross-sectional study design was followed. Methods: The methods include a sub-study of an international action research programme to support the thriving of early-career nurses, which evaluates and compares results from surveys of nurses at approximately three months post-registration in 2024 and 2025. A theory-informed survey assesses predictors and outcomes of thriving at work. Results: Early-career nurses (N = 320) from New Zealand (n = 277) and Australia (n = 43) completed the survey. New Zealand early-career nurses experience greater quality of care and authenticity at work; however, they also report greater burnout. For Australian early-career nurses, authenticity at work is the greatest predictor of thriving. In New Zealand, thriving is linked to burnout and colleague support. Conclusions: New Zealand must focus on reducing burnout and fostering workplaces that value social connection if it wants to mitigate early-career nurse attrition to Australia for better working conditions. In Australia, the value of authenticity at work highlights the importance of organisational cultures that enable nurses to express their true selves and professional identity. The findings highlight the need for tailored approaches in each country to strengthen workforce sustainability and improve nurse wellbeing. Implications for the Profession: In New Zealand, additional funding to bolster the recruitment and retention of the nursing workforce is crucial to improve patient ratios and reduce workloads. The remuneration of nurses must also remain competitive with Australia. Additionally, workplaces should incorporate Māori values and practices into workplace policies to strengthen social connections. Australian organisations should include authentic management training, psychological safety initiatives, and policies that value diversity and encourage open communication. Full article

Elder abuse is an increasingly common problem in modern society, in the context of rapid population aging. Despite increasing awareness, this phenomenon remains heavily underreported, and effective interventions are yet to be made, thus leading to significant medical, social, and legal implications. The purpose of this review is to present an updated situation of the depths of elder abuse, presenting its prevalence both at the global and European level, the two main environments in which it is the most common (community and institutional settings), different forms of abuse, risk factors, and consequences for each one of them, as well as medico-legal aspects on the matter. A narrative review was conducted based on PubMed/MEDLINE, Scopus, and Web of Science databases, in association with data presented in reports from international organizations. The review included only articles published in English, in peer-reviewed journals, addressing elder abuse in adults aged 60 years and older, and those that didn’t respect the criteria were excluded. Elder abuse comes in different forms, most of the time overlapping, with psychological abuse being the most prevalent. Each one of them has its own risk factors and specific consequences, but all of them will eventually lead to increased morbidity, accelerated cognitive impairment, and functional decline. In community settings, the elders usually experience abuse related to dependency on the family and social isolation, while in institutional settings, abuse is frequently associated with understaffing and inadequate care. From a forensic perspective, functional and cognitive decline complicate the proper documentation of the abuse. Thus, the role of the physician in providing legal support to the victim is essential. Elder abuse continues to be heavily overlooked, losing sight of the fact that its consequences extend beyond immediate physical harm, affecting the general physical and mental health of the victims. A possible solution to this problem is envisioned, with the purpose of raising awareness of this situation and contributing to a change in the perspective from which society looks at the elderly. Full article

Yi’an Reservoir is located on a major tributary of the Baoquan River and hosts abundant aquatic resources, with Cyprinus carpio, Carassius auratus, and Hemiculter leucisculus as the dominant fish species. Water quality parameters significantly shape fish gut microbiota, which in turn plays a crucial role in host physiological functions. This study aimed to characterize the water quality parameters in Yi’an Reservoir and identify the microbial communities in both the aquatic environment and fish guts (C. carpio, C. auratus, and H. leucisculus) through 16S ribosomal RNA sequencing. The objective was to examine the associations of water quality parameters and aquatic environmental microbiota with the assembly of gut microbial communities in fish inhabiting this reservoir system. The water quality parameters showed significant site-specific differences, of which temperature and dissolved oxygen were highest at Location B, while pH was highest at Location A. The Cyanobium_PCC-6307 was identified as a major differentially abundant taxon at the genera level across different sampling sites. Furthermore, the gut microbiota of the same fish species exhibited substantial variation across different sampling sites. Redundancy analysis identified distinct environmental drivers at each location. Specifically, pH, conductivity, and total dissolved solids (TDS) showed positive correlations with the gut microbiota at Location A. In contrast, temperature, dissolved oxygen (DO), and the environmental abundance of Cyanobium PCC-6307 were positively correlated with the gut microbiota at Locations B and C. This study provides important insights for the conservation and management of aquatic resources in reservoir ecosystems. Full article

Hybrid work not only redistributes where employees work; it also reshapes how they stay connected to their colleagues. Drawing on Communicate–Bond–Belong (CBB) theory, we examine how daily work location shapes employees’ team commitment in hybrid work environments through informal communication and knowledge sharing, and how these daily links depend on task interdependence. Using a daily diary study with 219 employees who work at least one day a week from home and one day a week in the office (1655 day-level observations), we applied multilevel structural equation modeling in Mplus 8.8 to capture within-person day-to-day fluctuations. Our findings show that on days when employees worked from home rather than in the office, they reported less informal communication and less knowledge sharing with colleagues, which in turn related to lower team commitment. These indirect effects suggest that it is not physical distance per se, but the loss of cue-rich, relationship-building and task-related exchanges that erodes commitment on remote days. We further show that task interdependence differentially qualifies these daily relationships: for informal communication, the positive association with commitment is stronger when task interdependence is low and weaker when interdependence is high. In contrast, the positive association between knowledge sharing and commitment becomes stronger at higher levels of task interdependence. Together, the results advance understanding of social dynamics in hybrid work environments and offer actionable guidance for leaders and organizations. Full article

Next-generation wireless communication 6G systems are expected to operate under diverse channel conditions and structures, requiring flexible and data-driven communication schemes. As traditional techniques face limitations in complex and dynamic environments, trained communication architectures have emerged as promising alternatives. In this paper, we present a thorough study on deep learning trained physical layer components, focusing on autoencoder-based transceivers and neural network modules that enhance the receiver’s intelligence. We further investigate two essential deep learning capabilities for modern receivers—modulation classification using neural architectures and generative data synthesis for channel estimation training. Moreover, the proposed models and simulation framework provide insight into how deep learning can be systematically integrated into the physical layer to improve adaptability, robustness, and efficiency. Full article

Background/Objectives: Across geographical and cultural contexts, how individuals identify, communicate and help-seek for distress is often shaped by how mental health itself is understood. Insight into how adolescents and adults in their routine environment, such as teachers, understand mental health is crucial for developing context-specific mental health promotion strategies to young people. Sri Lanka, a country that navigates the dual legacies of pre-and-post-colonial mental health frameworks, has this need. The aim was to explore Sri Lankan school-going adolescents’ and their teachers’ perspectives of mental health and its determinants. Methods: Semi-structured interviews were conducted with 28 school-going adolescents in grades 10–12/13 and 14 of their school teachers, from seven secondary schools in Gampaha District, Sri Lanka. Interviews were transcribed, translated, coded inductively and analysed thematically. Results: All participants drew on culturally meaningful language that is rooted in Buddhist perspectives to conceptualise mental health. Causes and risk factors of poor mental health were attributed to individual, immediate environmental and structural factors. School environment played a central role in exacerbating other risk factors. Adolescents exhibited more knowledge of informal care avenues for mental health-related concerns. Conclusions: Findings highlight several implications including opportunities to leverage culturally contextualised language/frameworks when promoting mental health to Sri Lankan adolescents, diversifying mental health research and initiating school-based mental health programmes that integrate mental health promotion into routine educational practice to transform learning institutions across Sri Lanka to become mental health-promoting schools. Full article

Background/Objectives: Oral frailty and hypofunction in older adults are strongly associated with declines in nutritional status, physical function, swallowing ability, and overall health. Isolated interventions usually fail to achieve sufficient improvement since these conditions result from interrelated biological, psychological, and social factors. Multidisciplinary approaches combining oral management, nutritional support, and physical rehabilitation have shown promise. This narrative review synthesized evidence from 15 studies examining multifaceted interprofessional interventions across hospitals, communities, long-term care facilities, and home-care settings. Methods: A structured search of PubMed and Web of Science (2000–2025) identified original studies assessing oral, nutritional, or physical outcomes in older adults post-interprofessional interventions. Fifteen eligible studies were extracted; the findings were integrated using narrative synthesis owing to design and outcome heterogeneity. Results: Educational multidisciplinary interventions improved oral hygiene, caregiver awareness, and oral motor function. Multidisciplinary rehabilitation and multidomain programs consistently improved tongue pressure, swallowing function, mastication ability, appetite, body composition, activities of daily living, and oral intake resumption. Nutrition support team-delivered interventions reduced aspiration risks and improved oral environment and swallowing function. Community-based programs using munchy meals and combined exercises enhanced oral and physical functions. Social participation provided psychological benefits. Home-care dysphagia rehabilitation enabled 69% of tube-fed patients to resume oral intake. Conclusions: This narrative review supports a triadic, interprofessional approach in geriatric care, highlighting consistent improvements in oral function through integrated oral, nutritional, and rehabilitative interventions. Full article

Federated learning (FL)-based vehicular edge computing networks (VECNs) are emerging as a key enabler of intelligent transportation systems, as their privacy-preserving and distributed architecture can safeguard vehicle data while reducing latency and energy consumption. However, conventional roadside units face processing bottlenecks in dense traffic and at the network edge, motivating the adoption of unmanned aerial vehicle (UAV)-assisted VECNs. To address this challenge, this paper proposes a UAV-assisted VECN framework with FL, aiming to improve model accuracy while minimizing latency and energy consumption during computation and transmission. Specifically, a reputation-based client selection mechanism is introduced to enhance the accuracy and reliability of federated aggregation. Furthermore, to address the channel dynamics induced by high vehicle mobility, we design a robust reinforcement learning-based resource allocation scheme. In particular, an asynchronous parallel deep deterministic policy gradient (APDDPG) algorithm is developed to adaptively allocate computation and communication resources in response to real-time channel states and task demands. To ensure consistency with real vehicular communication environments, field experiments were conducted and the obtained measurements were used as simulation parameters to analyze the proposed algorithm. Compared with state-of-the-art algorithms, the developed APDDPG algorithm achieves 20% faster convergence, 9% lower energy consumption, a FL accuracy of 95.8%, and the most robust standard deviation under varying channel conditions. Full article