Search Results (6,713)

The objective of this paper is to propose a sociological and interdisciplinary framework for analyzing the digitization of emotions in adolescence. This contribution aims to promote theoretical reflection and inform educational and political interventions in the digital age, framing adolescents’ digital experiences as emotionally embodied and socially integrated processes. These aspects are of paramount importance due to the rapid proliferation of digital technologies and artificial intelligence, which have precipitated a profound transformation in the emotional, relational, and educational experiences of adolescents. The role of digital and AI-based environments in mediating communication is expanding beyond the scope of simple facilitation. These environments are increasingly implicated in the production, modulation, and regulation of emotions, thereby influencing developmental trajectories and identity formation processes. This phenomenon is theorized as a socio-technical process, wherein emotions are embodied, narrated, and governed within digital environments. The article introduces the concept of digital emotional embodiment, drawing on the sociology of emotions, theories of embodiment, and critical perspectives on artificial intelligence. Specifically, the concept refers to the manner in which adolescents experience and express emotions through avatars, images, emojis, algorithmic feedback, and AI-mediated interactions. Therefore, it is imperative to underscore the evolution of empathy, which is progressively configured as a virtualized and datafied process, diverging from the tradition established by Hume and characterized by sympathy. In contemporary processes, shaped by the logic of platforms, recommendation systems, and emotionally reactive technologies, conventional emotional concepts have undergone deconstruction, and digital constructs are undergoing a gradual restructuring. In this context, AI systems do not merely reflect adolescents’ emotions but rather actively contribute to the construction of emotional narratives, influencing emotional regulation, social connection, and future orientation. Digital environments have been shown to encourage emotional expressiveness, experimentation, and inclusivity. Conversely, they have the capacity to encourage emotional standardization, dependency, and forms of affective vulnerability, particularly during a sensitive developmental stage such as adolescence. Full article

This work proposes a fiber-tethered UAV-enabled adaptive aerial passive optical network (AA-PON) framework for rapid extension of optical access and backhaul in hard-to-reach or temporarily disrupted environments. The proposed architecture supports two distinct operating modes: (i) an aerial base station (ABS) mode for wide-area service extension and (ii) a ground-to-air-to-ground (G2A2G) mode for targeted high-speed optical bridging to ground terminal units. Unlike conventional UAV relay approaches, the proposed framework is developed as a network-level optical access/backhaul architecture based on tether-assisted aerial nodes and reconfigurable optical topology formation. In the ABS mode, representative Bus, Ring, and Star topologies are analyzed to evaluate serviceability, outage, deployment latency, and scalability as the number of UAV nodes increases. In the G2A2G mode, a stochastic-geometry-based analysis is used to characterize blockage-limited optical serviceability and infrastructure-density trade-offs. To complement the analytical study, a 2 Gb/s proof-of-concept FSO link between two fiber-tethered UAVs is demonstrated as an initial feasibility validation of the end-to-end optical link. The results show that the proposed AA-PON provides a flexible aerial optical networking framework that combines reconfigurable topology support with localized high-capacity optical access extension. Full article

This article is about the concept of external psychological control (having a sense of psychological control over the environment). This article examines the construct of external psychological control and differentiates it from similar concepts, showing its unique attributes and how it can help understand a diverse array of psychological phenomena. Of note, external psychological control differs from internal psychological control, which is about maintaining internal psychological equilibrium or being grounded. The term psychological control is similar to terms, but we show that it differs from them and is unique in how it is presently defined. Some of these terms include distress tolerance, self-efficacy, and many variations in terms of control as part of the terminology. Another term examined is related to psychological reserve, the depletion of which affects psychological control. The article presents an original questionnaire that could be used to research external psychological control. The article concludes with a formal mathematical representation of the interaction between psychological control and psychological reserve, and with simulation research that serves as a proof of concept of the constructs proposed. The concepts of psychological control and psychological reserve can help in understanding psychotherapeutic change mechanisms. The concepts of psychological control and psychological reserve are relatively novel terms that can help understand reactions to stress and consequent stress management. Full article

The Dammam Metropolitan Area (DMA) has been experiencing tremendous growth driven by increasing population and the oil industry. This has culminated in the development of the DMA, where the transportation system is reliant on automobiles, wide arterials, and a disjointed pedestrian environment. With the increasing progression of the Vision 2030 initiative, the Kingdom of Saudi Arabia (KSA) is focusing on livability and sustainable mobility. However, despite the massive efforts, the concepts of humanizing active mobility corridors remain insufficiently developed across Saudi cities. The paper will discuss the conceptual framework for developing the active mobility corridors of the DMA, an initiative of walkability, livability, and sustainable mobility with specific regard to the study region’s climatic and cultural environment. The methodology relies on qualitative desktop research supported by a structured and iterative literature synthesis using snowballing techniques. The resulting framework positions active mobility not merely as a transport function, but as a multidimensional system that promotes inclusion, comfort, and environmental resilience. Offering design and policy principles tailored to hot-arid Gulf contexts that contributes to national efforts to advance Quality of Life objectives under Vision 2030. Ultimately, this framework aims to contribute in human-centered mobility across the KSA and similar urban areas. Full article

Search and rescue (SAR) operations in mountainous terrain present significant challenges due to complex environments, time-critical decisions, and the need for effective human–AI collaboration. Existing approaches typically employ either fully autonomous systems that lack adaptability to varying task requirements, or fixed human–AI authority allocations that fail to leverage the distinct strengths of humans and AI across different mission phases. This paper proposes Phase-Aware Hierarchical Reinforcement Learning (PAHRL), a novel framework that dynamically allocates decision-making authority between human operators and AI agents based on identified task phases. First, we formulate the mountain SAR problem as a three-phase task structure: Wide Search (WS), Target Confirmation (TC), and Rescue Coordination (RC), and examine the consistency of this decomposition through unsupervised clustering analysis, supported by bootstrap stability (ARI = 0.983 ± 0.083) and multiple clustering metrics. Second, we design an adaptive authority mechanism with four levels (L1: Human-Led to L4: Full-Auto) that automatically adjusts human involvement based on current phase characteristics and environmental uncertainty estimates. Third, we introduce a priority-based task execution module that ensures efficient resource allocation across multiple rescue objectives while respecting authority constraints. Extensive experiments demonstrate that PAHRL outperforms baseline methods, achieving a 20.9% higher success rate compared to standard PPO (59.0% vs. 48.8%) and 66.7% improvement over heuristic approaches. PAHRL maintains 96.9% precision even under 60% noise conditions with only 0.09 false rescues per episode. Ablation studies further reveal that phase awareness serves as a critical robustness mechanism; removing phase detection causes complete mission failure under noisy conditions. These results evaluate that phase-aware dynamic authority allocation significantly enhances both efficiency and robustness in human–AI collaborative SAR missions. While demonstrated in a proof-of-concept simulation with computational human models, validation with real operators and more complex environments remains essential before operational deployment. Full article

Swallowing is a critical marker of neurological and emotional health. The ability to monitor it continuously and non-invasively, especially through smart ear-worn devices, holds significant promise for clinical applications. Despite this potential, no public audio datasets currently support reliable swallowing sound detection. Existing datasets focus primarily on speech and breathing, offering limited coverage and lacking detailed annotations for swallowing events. To address this gap, we introduce an in-ear audio dataset specifically designed to capture a wide range of verbal and non-verbal sounds. It includes comprehensive labeling focused on swallowing. The dataset was collected from 34 healthy adults (14 females and 20 males) between the ages of 20 and 29. Each participant performed a series of predefined tasks involving both non-verbal and verbal events. Non-verbal tasks included swallowing, clicking, forceful blinking, touching the scalp, and physical movements such as squatting or walking in place. Verbal tasks consisted of speaking (e.g., describing an image). Recordings were conducted in both quiet and noisy environments to better reflect real-world conditions. Data were captured using a combination of in-/outer-ear microphones, a chest belt to record electrocardiogram (ECG), respiration and acceleration signals, and an ultrasound probe to track tongue movement, which served as a reference for swallowing annotation. All signals were precisely synchronized. To ensure high data quality, the recordings were reviewed using both algorithmic analysis and manual inspection. Swallowing events were identified based on ultrasound signals and validated by an expert to guarantee accurate labeling. As a proof of concept that in-ear audio supports swallow classification, we fine-tune a fully connected neural network on YAMNet embeddings plus zero-crossing rate (ZCR) features. Across the completed folds, the model reaches an F1 score of 0.875 ± 0.013. Full article

A critical aspect of virtual reality is the extent to which the user forgets their real surroundings and becomes completely engaged within the virtual environment. Diverse factors affect this user perception, which are grouped into two main concepts: immersion and presence. Although the study of presence is extensive, researchers have not reached a consensus on a protocol with specific instruments and stages to evaluate it. This leads to a wide variety of results with different assessment methods, experimental setups, stimuli implemented, and applications. Therefore, this article aims to provide an analysis of the state-of-the-art methods for assessing presence in VR systems during the last few years. This study seeks to determine and improve the understanding of current techniques used for presence assessment, human data collected, data analysis methods, and the technologies and virtual environments implemented. In addition, four opportunities are discussed to provide researchers guidelines that can lead to enhanced presence assessments and personalized VR experiences. Full article

Social media platforms have been established as relevant sources of real-time information for urban traffic analysis. This study proposes an intelligent framework for the classification and spatiotemporal analysis of traffic incidents based on semi-synthetic data streams constructed from historical geolocated seeds for controlled validation, utilizing real reports from platforms such as X and Telegram. The approach integrates adaptive machine learning and incremental density-based clustering. An Adaptive Random Forest (ARF) incremental classifier is used to identify the type of incident, allowing for continuous updating of the model in response to changes in traffic flow and concept drift. The classified events are then processed using DenStream, a clustering algorithm that incorporates a temporal decay mechanism designed to identify dynamic spatial patterns and discard older information. The evaluation is performed in a controlled streaming simulation environment that replicates the dynamics of cities such as Panama and Guayaquil. The proposed framework demonstrated robust quantitative performance, achieving a prequential accuracy of up to 86.4% and a weighted F1-score of 0.864 in the Panama scenario, maintaining high stability against semantic noise. The results suggest that this hybrid architecture is a highly viable approach for urban traffic monitoring, providing useful information for Intelligent Transportation Systems (ITS) by processing authentic social signals. Full article

A review of morphing actuation systems in relation to rotary-wing aerial platforms is presented. The research highlights an inadequate maturation of rotary actuation systems, characterised by a scarcity of (1) comprehensive full-scale experimental research relative to non-rotary (fixed-wing) systems, (2) techniques used for rotary actuation systems and (3) implementation of full-chord morphing systems, with existing research only utilising partial-chord actuation techniques. Additionally, another notable shortcoming is presented to be the lack of comprehensive proportional investigation in the proposed five-step development process for rotary actuation designs. A comprehensive critical review is offered, covering the following challenges of progressing through this development process for rotary actuation systems from conceptual design to production: (1) numerical and computational studies, (2) small-scale wind-tunnel testing, (3) full-scale wind-tunnel testing, (4) demonstrator, and ultimately (5) fabrication for industrial implementation. The review examines several existing rotary actuation systems, including (but not limited to) leading-edge, trailing-edge and Gurney flaps; active twist; chord extension; variable span and camber systems. Comparisons are made between rotary morphing actuation systems and their non-morphing counterparts, highlighting the distinct difficulties encountered by rotary-wing systems due to the more complex and challenging operational conditions found in rotorcraft. The review reveals that a significant portion of existing research on rotary-wing systems has focused only on early-stage development, including computational modelling and sub-scale wind-tunnel experiments, underscoring the necessity for more comprehensive full-scale testing and prototype evaluation given that only a small number of studies have progressed to full-scale wind-tunnel testing or actual prototype evaluation, with only one example identified as having been tested on a production helicopter. In addition, a comparative Technology Readiness Level (TRL) assessment is presented for both rotary-wing and fixed-wing morphing actuation systems, enabling a structured evaluation of relative technology maturity, experimental validation depth, and proximity to operational implementation. Building upon this assessment, a morphing Actuation Concept-Transfer Feasibility (ACTF) study is also provided, examining the potential for adapting mature fixed-wing morphing actuation technologies for application in rotary-wing environments, while identifying the key structural, aerodynamic, and operational constraints that currently limit direct technology transfer. This study addresses and proposes opportunities for a novel rotary actuation system design and concludes by suggesting the potential for future research on more effectual systems to include full-chord configuration over larger spanwise blade footprints with innovative actuation mechanisms that could be utilised and progressed through all development stages from numerical studies to full-scale fabrication. Full article

(1) Research Highlights: This study provides the first integrated assessment of Scots pine (Pinus sylvestris L.) growing in the urban forests of Karaganda, Kazakhstan, a city consistently ranked among the most air-polluted cities globally. We examined the adaptive phyto-chemical response of needles to extreme technogenic stress and evaluated their dual potential as biological filters and renewable sources of bioactive compounds. (2) Background and Objectives: Urban forests are critical for mitigating air pollution; however, the biochemical responses of trees in heavily industrialized environments remain poorly understood. Karaganda faces severe atmospheric pollution from mining, metallurgy, and energy sectors, with particulate matter (PM) levels exceeding permissible limits by up to 20-fold. This study aimed to evaluate the state of Pinus sylvestris, a key component of local protective plantations, by studying heavy metal accumulation, anatomical localization of secondary metabolites, and the phytochemical profile and biological activity of needle extracts obtained using different extraction techniques. (3) Materials and Methods: Needles were collected from 15 trees across three sites in Karaganda’s industrial green zones. Heavy metal content (Pb, Cd, As, and Hg) was determined using atomic absorption spectroscopy and voltammetry. Anatomical–histochemical analysis localizes major metabolite classes. Liquid extracts were prepared using four methods, percolation (PER), vortex-assisted (VAE), microwave-assisted (MAE), and ultrasound-assisted (UAE) extraction, and analyzed by GC-MS. Antimicrobial activity was tested against S. aureus, B. subtilis, E. coli, and C. albicans using the disk diffusion method. The antioxidant capacity (water- and fat-soluble) was measured amperometrically. Statistical analysis was performed using one-way ANOVA with Tukey’s HSD test (p < 0.05). Results: Despite extreme ambient pollution, heavy metal concentrations remained below pharmacopoeial limits (Pb < 0.1, Cd < 0.05, As < 0.01, Hg < 0.001 mg/kg), indicating effective biofiltration without toxic accumulation. Histochemistry confirmed the active synthesis of protective phenolics, flavonoids, and essential oils in the mesophyll, epidermis, and schizogenic cavities. GC-MS identified 72 compounds in the PER extract, 70 (the VAE), 72 in (MAE), and 46 in (UAE). The PER extract exhibited the highest relative abundance of bioactive terpenoids: α-cadinol (5.24%), α-muurolene (4.32%), and caryo-phyllene (2.20%). UAE extracts exhibited elevated 5-hydroxymethylfurfural (6.90%), indicating degradation. Antimicrobial testing revealed that PER produced the largest inhibition zone against S. aureus (15.0 ± 1.0 mm), significantly exceeding that of the other methods (p < 0.001). PER extract also demonstrated the highest water-soluble antioxidant capacity (3600 ± 0.40 mg quercetin equiv./dm³) and substantial fat-soluble activity (1633 ± 0.23 mg gallic acid equiv./dm³). (4) Conclusions: Pinus sylvestris in Karaganda exhibits remarkable adaptive resilience, maintaining safe heavy metal levels while accumulating a rich repertoire of stress-induced secondary metabolites. Classical percolation optimally preserves this native phytocomplex, yielding extracts with superior antimicrobial and antioxidant properties. These findings support a dual-use model wherein urban pine plantations simultaneously serve as living biofilters and renewable sources of standardized bioactive extracts, a concept with direct implications for circular bioeconomy strategies in industrial regions worldwide. This supports the strategic importance of coniferous plantations for bioremediation and sustainable resource use in industrial regions. Full article

Background/Objectives: Despite growing recognition of empathy as a cornerstone of high-quality care, its role within interprofessional collaboration remains underexplored. While the Interprofessional Education Collaborative explicitly references empathy only under the Values and Ethics domain, emerging evidence suggests its potential relevance across all four core competencies. This study aimed to explore the influence of empathy on each of the Interprofessional Education Collaborative core competencies and to highlight its role in the contemporary interprofessional healthcare environment. Methods: A narrative literature review was conducted to identify articles published in English between 2014 and 2025, through searches of PubMed and Scopus. The sub-competency statements of the Interprofessional Education Collaborative framework were used to guide keyword selection and map concepts that empathy may influence. Results: Seventy-two articles were included in this narrative review. According to the literature, evidence suggests that empathy may support humanitarian values and ethical decision making (Values and Ethics), but the mechanisms underlying this remain to be considered. Empathy has also been discussed in relation to therapeutic and team communication (Communication), as well as to processes such as conflict resolution, supportive leadership, team cohesion, and staff well-being (Teams and Teamwork). The evidence regarding the Roles and Responsibilities domain remains relatively limited, preventing definitive conclusions about the potential influence of empathy in this domain. A clear distinction emerges between clinical and interprofessional empathy, with evidence suggesting that both are essential for collaborative practice. Conclusions: Empathy appears to be linked with several domains of interprofessional collaboration and may represent an important relational component in collaborative healthcare practice. However, the influence of empathy may depend on structural and organizational conditions and may vary across different interprofessional healthcare contexts. These findings offer a conceptual bridge between empathy and interprofessional collaboration, providing actionable insights for educators, leaders, and policymakers involved in healthcare training. Full article

Virtual reality (VR)-based evacuation training provides a safe and immersive environment for participants to experience disaster scenarios. However, existing systems often prioritize the experience itself, leaving the critical stage of reflection—essential for refining and stabilizing evacuation knowledge—under-supported. This study presents a qualitative pilot investigation into an extended reflection support function for a VR-based evacuation training system. Unlike traditional replay functions that only visualize avatar movements, our system synchronizes spatialized environmental sounds and recorded verbal utterances, i.e., voices of the user and non-player characters (NPCs), with the visual replay. A preliminary experiment involving eight university students was conducted to evaluate how these auditory clues influence the reflection-on-action process. Qualitative results indicate that audio clues help participants recall their internal decision-making processes and provide essential context for understanding the actions of others (NPCs). The findings suggest that the integration of auditory information facilitates evacuation knowledge refinement, i.e., the transition from mere experience to the formulation of concrete survival concepts. Although limited by a small sample size, this study highlights the potential of multi-modal reflection support in VR-based evacuation training. Full article

When high-altitude aircraft operate in a low-density environment, the flow instability within their internal ducts poses a severe challenge to aerodynamic design and operational safety. Especially in the intake system of the tandem dual-fan configuration, the asymmetric flow caused by rotating machinery coupled with the low-density effect exacerbates flow distortion, momentum dissipation, and efficiency loss and may even trigger system instability risks such as rotational stall or surge. To address these challenges, this paper establishes a high-fidelity dynamic model of the internal flow field of the aircraft, based on the Reynolds-averaged Navier–Stokes equations and the SST k-ω turbulence model, combined with dynamic mesh technology. It reveals the unstable mechanism caused by angular momentum accumulation under co-rotation conditions and its intrinsic correlation with the degradation of aerodynamic performance. Inspired by the concept of micro-flow regulation, an active flow control strategy integrating discrete auxiliary injection and local geometric shape optimization is proposed. Numerical results show that by reasonably arranging auxiliary injection holes in the intake duct and optimizing local geometric fillets, the uniformity of intake flow can be effectively improved, and the formation of large-scale vortex structures can be suppressed. This method increases the system’s flow capacity by approximately 47.4%, significantly improves the total pressure recovery coefficient and fan aerodynamic efficiency, and reduces the amplitude of low-frequency pressure fluctuations by approximately 23.1%. Research shows that in high-altitude low-Reynolds-number conditions, micro-flow regulation combined with geometric reconstruction can effectively suppress flow instability induced by rotating machinery. This achievement provides a theoretical basis and feasible engineering path for aerodynamic stability design and optimization of key components, such as the aircraft intake and exhaust systems and thermal management systems, and is of significant value for improving the overall performance and reliability of high-altitude long-endurance aircraft. Full article

Background/Objectives: To identify and prioritize adolescents’ motivations for alcohol consumption using a participatory qualitative approach. Methods: We conducted a concept mapping study with 39 adolescents aged 15–16 years from a public secondary school in Santiago de Compostela, Spain. Participants generated statements in response to a focal question about reasons for drinking, grouped them into categories, and then rated each statement according to perceived frequency and importance using a five-point Likert scale. Results: A total of 41 statements were generated and organized into eight clusters: peer approval, influence, enjoyment, experimentation, fun, disinhibition, social pressure, and coping. Motivations related to fun, peer dynamics, and disinhibition received the highest ratings for both frequency and importance. In contrast, motivations linked to advertising, social media, and influencers were rated lowest. A strong positive association was observed between perceived importance and reported frequency across statements. Conclusions: Adolescents identified enjoyment and peer dynamics as the primary motivations for alcohol use, emphasising the significance of social influences in adolescent drinking behaviours. Despite the necessity for cautious interpretation of findings due to the context-specific nature of the sample, the results suggest that prevention efforts may benefit from the promotion of alcohol-free social environments, the strengthening of social-emotional skills, and the involvement of adolescents in preventive initiatives. Full article

Falls represent a major health risk for older adults living independently, motivating the development of unobtrusive and privacy-preserving monitoring solutions. This study investigates whether Bluetooth Low Energy (BLE) 6.0 Channel Sounding (CS) can support device-free fall detection using low-complexity signal representations suitable for residential deployment. The proposed system employs two BLE nodes performing periodic channel sounding, from which only scalar distance estimates are extracted. Time-domain and temporal-dynamic features are computed from sliding windows of the distance signal and used for supervised classification. Three widely used classifiers—Support Vector Machine with radial basis function kernel, Random Forest, and gradient-boosted decision trees (XGBoost)—are evaluated under both a default operating point and a sensitivity-first regime achieved through validation-based decision threshold adjustment, reflecting the higher cost of missed fall detections in assisted living scenarios. Experiments conducted in a furnished indoor environment with six participants performing realistic fall and non-fall scenarios demonstrate strong window-level sensitivity under subject-independent evaluation, with XGBoost providing the most favorable sensitivity–specificity balance. Under sensitivity-first operation, very high recall is achieved at the expense of increased false alarms. Given the limited dataset and single-environment setting, the reported results should be interpreted as a proof-of-concept demonstration of feasibility rather than definitive large-scale performance. The findings suggest that BLE CS captures motion-relevant signal variations that may support practical fall detection while maintaining low deployment complexity and privacy preservation. Full article