Search Results (2,654)

Prevention of crossing collisions between cyclists and vehicles at nonsignalized intersections on community roads where walls and hedges limit visibility is required in Japan. Because available observation information in real-time is limited on community roads, the use of statistical information that represents the typical movement characteristics of cyclists is effective to compensate for the lack of observation information. From such a background, in our previous study, we proposed a method to construct “location-dependent statistical information” (LDSI) and a method to utilize it as “virtual observation” (VO) and “virtual control input” (VCI) in stochastic position estimation. Here, although LDSI was constructed for multiple clusters of cyclists, the classification method of the cyclists observed in real-time was not considered. In the real world, the limitation of the observation information causes classification uncertainty. Thus, in this study, we propose a position estimation method that utilizes soft classification results and considers classification uncertainty by integrating VO and VCI derived from LDSI of each cluster. To evaluate the proposed method in this study, we conduct a simulation and an experiment in the real world. Through the comparison with conventional methods, we confirm that our proposed method in this study improves the performance of the position estimation. The proposed method will contribute to a cooperative safety system. Full article

The burden of disability is rising rapidly in Africa, where a severe shortage of rehabilitation professionals and limited infrastructure create a major treatment gap. Immersive virtual reality and serious games have shown promise for upper limb rehabilitation, but current extended reality (XR) solutions lack personalization, cultural adaptability, real-time feedback, and scalability. This perspective paper proposes a conceptual AI-enhanced XR framework tailored to African low- and middle-income countries. We identify how generative AI, large language models, multiagent systems, and explainable AI can address specific rehabilitation barriers. The framework integrates these four pillars into a three-layer architecture covering content creation, interaction, and decision support. We analyze implementation considerations specific to African contexts—infrastructure, capacity building, cultural adaptation, ethics, and financing—and outline a detailed research agenda with near, medium, and longer term priorities. Realizing this vision requires co-design with African communities, investment in local capacity, adaptation to infrastructure constraints, and development of ethical frameworks. AI-enhanced XR has the potential to democratize access to quality rehabilitation across Africa, but this potential must be validated through rigorous, context-sensitive research. Full article

Simulation technologies are widely used in the construction industry to analyze complex operations and evaluate project performance before physical construction begins. However, interpreting simulation outputs remains challenging due to the dynamic nature of construction activities and the difficulty of representing spatial and temporal changes using traditional numerical or textual outputs. To address these limitations, researchers increasingly integrate visualization technologies with construction simulation models to improve understanding, communication, and decision-making. Using the PRISMA methodology, this paper presents a systematic literature review of visualization technology applications in construction simulation during the building phase. A total of 118 relevant publications published between 2000 and 2023 are reviewed and analyzed. The findings reveal a strong relationship between visualization technologies and Building Information Modeling (BIM), Virtual Reality (VR), and game engine technologies. Autodesk Navisworks and Unity are identified as the most frequently used visualization platforms, with game engines showing increasing adoption in recent years due to their support for immersive and interactive environments. The reviewed studies are further categorized into six primary use cases: scheduling and planning, education and training, equipment management, safety management, workspace planning, and simulation validation and verification. The results also demonstrate increasing research interest in real-time visualization, AR/VR integration, and interactive simulation environments. Overall, the findings highlight the growing role of visualization technologies in improving construction project planning, communication, training, safety, and decision-making, while also identifying important future research directions related to interoperability, real-time interaction, and extensible visualization platforms. Full article

The representation of the sexuality of people with disabilities in contemporary media is often characterized by stereotypes, omissions, and heteronormative narratives that deny the complexity and richness of their emotional experiences. This essay explores the potential of photovoice-based methodology as a tool of visual empowerment to foster processes of authentic and self-aware self-representation through the immersive dynamic that this methodology can activate. Through an interdisciplinary theoretical approach that combines special pedagogy with recent research on digital media and immersive technologies, the study seeks to understand whether virtual spaces can be configured as protected environments in which people with disabilities have the opportunity to explore and communicate their sexual identity. Photovoice thus becomes a tool of narrative resistance that overcomes barriers and counters mediatized representations, often conveyed through dynamics of ableist cyberbullying and online discrimination. The contribution highlights how the combination of participatory visual storytelling and immersive environments can generate new forms of inclusive media literacy, promoting a Visual Education that recognizes and values the diversity of human experiences. Particular attention is devoted to the educational potential of these tools in the training of educators and social workers, as well as in raising awareness within the broader community. The paper proposes a theoretical and methodological framework for the implementation of visual self-representation projects capable of transforming social perceptions of disability and promoting a culture of authentic and respectful inclusion. Full article

The object of the research is the information interaction processes between the components of a simulation model of a PID controller based on Digital Twin technology. The problem addressed lies in the need to extend the functionality of various models when they are integrated into real control systems. The aim of the study is to develop a simulation model of a PID controller for electric-drive frequency-based control systems using Digital Twin technology. A concept for constructing a simulation model using unified hardware–software tools from Simatic S7 and Digital Twin technology is proposed. In this approach, virtual components of the simulation model are configured, parameterized, and programmed within the same engineering environment as the real ones. Projects developed based on simulation results of PID controllers provide the foundation for their implementation on real Simatic S7 hardware. The simulation model provides for integration and interaction of fully virtual components, including PLC, frequency converter, electric drive, SCADA, and communication environment. Procedures for parameterizing monitoring tools and for the automatic tuning of PID controller parameters according to the chosen strategy were implemented, which enabled a clear graphical evaluation of transient processes under different operating modes of the simulation model. The response of the PID controller to periodic and random disturbance signals within up to100% of the control range was tested. Full article

With the proliferation of digital platforms, virtual brand communities have become important contexts for examining how individual perceptions shape discretionary behaviors in online environments. However, the mechanisms through which user experience translates into value co-creation behaviors remain underexplored. Drawing on relationship marketing theory and a behavioral perspective, this study develops and tests a theoretical model linking user experience to value co-creation citizenship behaviors through distinct dimensions of quality of relationship-satisfaction, trust, and commitment. Using a two-wave survey with 549 matched responses, we employ multiple regressions and bootstrapping analyses to assess mediation and moderation effects. The findings indicate that different dimensions of user experience have differential impacts on satisfaction, trust, and commitment, which in turn promote value co-creation citizenship behaviors, supporting their roles as central psychological mechanisms. Specifically, affective and behavioral experiences exert significant positive impacts on value co-creation citizenship behaviors, mediated by all three dimensions (satisfaction, trust, and commitment), whereas the influences of sensory and intellectual experiences are only mediated by two dimensions (satisfaction and trust) of the quality of relationship. In addition, perceived community support strengthens the relationship between satisfaction and value co-creation citizenship behaviors, while it exerts no significant moderating effects on the impact of trust or commitment on value co-creation citizenship behaviors. By situating value co-creation within a behavioral framework, this study contributes to the literature by exploring the mechanism through which user experience influences voluntary, citizenship-like behaviors in digital communities from a relational perspective, and by identifying boundary conditions under which these effects are amplified. Full article

Sports non-fungible tokens (NFTs) have rapidly emerged as tradable digital goods within platform-mediated marketplaces, reshaping how sports organizations, athletes, and brands design fan experiences and monetize digital assets. To consolidate fragmented scholarship and clarify the concept space, this study conducts a systematic quantitative literature review combined with thematic analysis, following PRISMA 2020 and a SPIDER-guided review logic. Searches across six major databases (Web of Science, Scopus, ScienceDirect, PubMed, IEEE Xplore, ProQuest) plus Google Scholar (2017–March 2025) yielded 40 peer-reviewed studies that met predefined inclusion criteria and passed quality appraisal. Results show a sharp growth of sports-NFT research from 2021 to 2024, with strong inter-disciplinary convergence spanning sports marketing, information systems, computer science, and law. Integrating findings through a consumer-value lens, we inductively propose a five-type taxonomy—collectible, empowerment, identity/authentication, physical-asset linked, and virtual-interaction NFTs—each associated with distinct value mechanisms and e-commerce functionalities. The thematic synthesis further identifies four dominant research streams (industry digitalization, consumer psychology/behavior, legal–regulatory issues, and digital marketing), while revealing gaps in theory operationalization, method diversity (e.g., limited experiments/longitudinal designs), cross-context generalizability, and governance/sustainability. The study contributes to marketing and management scholarship by positioning sports NFTs as emerging technologies that reorganize customer engagement, brand-community building, and governance in platform-mediated sport markets, and it offers a research agenda for measuring consumer, brand, and organizational effects. Full article

The hot-pressing process for reconstituted bamboo suffers from issues such as insufficient process monitoring, scattered quality data, difficulties in quality traceability, and a lack of intuitive on-site management. This paper designs and implements a digital twin quality monitoring system tailored for the hot-pressing process of reconstituted bamboo. The system adopts an overall architecture combining a data acquisition layer, a business logic layer, and a display and interaction layer. It collects key data—such as on-site hot-pressing temperature, pressure, displacement, and equipment operating status—via PLCs and industrial communication interfaces. Based on Spring Boot and MySQL, the system handles data reception, storage, processing, and interface publishing. It integrates web pages and Unity 3D interfaces to enable basic information management, quality traceability, hot-pressing temperature monitoring, retrieval of prediction results, equipment status display, and operational data visualization. The system was deployed and validated at the enterprise’s hot-pressing production site. Test results indicate that the system continuously recorded hot-pressing process data for 2040s; the average synchronization delay between the physical end and the virtual model was 520 ms, with a maximum synchronization delay of 1360 ms and a 95th percentile synchronization delay of 910 ms, meeting the requirements for second-level monitoring and visual display of the hot-pressing process. Field application results demonstrate that the system can stably support data acquisition, quality information management, retrieval of predictive results, and digital visualization for the hot-pressing process of reconstituted bamboo, providing systematic support for quality monitoring, process traceability, and digital management of the hot-pressing process. Full article

Telemedicine has become a routine component of healthcare delivery, creating a need for dedicated undergraduate training in teleconsultation-specific competencies. Although artificial intelligence (AI)-assisted educational systems have been proposed as scalable tools to support teleconsultation training, the evidence remains fragmented, and their educational role is not yet clearly defined. Objective: To map and critically synthesize empirical evidence on AI-assisted teleconsultation training systems used in undergraduate medical education, with attention to skill domains, system capabilities, and implementation considerations. Methods: A structured narrative review with transparent search and study selection procedures was conducted. Literature published between January 2019 and December 2025 was identified through searches of major bibliographic databases and supplementary semantic and citation-based sources. Studies involving undergraduate medical students and evaluating AI-assisted interventions targeting teleconsultation-related skills were included. Results: Eight empirical full-text studies met the final eligibility criteria and were included in the structured narrative synthesis. Across the included studies, AI-assisted systems tended to show favorable patterns in structured domains such as verbal communication, history-taking, and selected aspects of early clinical reasoning during virtual consultations. Evidence regarding nonverbal communication and empathic or relational skills was more limited and methodologically heterogeneous, and human-based simulation remained important in these domains. Students generally reported favorable perceptions of usability, accessibility, and psychological safety, although satisfaction and perceived realism were not uniformly superior to human-based approaches. AI-assisted systems also appeared scalable and potentially cost-efficient, particularly as preparatory or supplementary training modalities. Conclusions: Current evidence suggests that AI-assisted teleconsultation training systems may be useful as preparatory and supportive tools in undergraduate medical education, particularly for structured and repeatable components of remote consultation practice. However, the evidence base remains limited and heterogeneous, and these systems do not replace human-led training for relational, nonverbal, and context-sensitive competencies. Their educational value appears greatest within blended training models that align platform capabilities with specific teleconsultation skills. Full article

Very High Frequency (VHF) radio communication systems face significant challenges in modern electromagnetic environments, including spectrum congestion, dynamic interference, and varying channel conditions. Existing adaptive approaches rely on static rule-based switching or single-cycle optimization, which cannot accumulate operational experience across decision cycles. This paper proposes a digital twin-enabled online learning framework (DT-MAB) for adaptive waveform selection in tactical VHF communication. The framework employs a contextual multi-armed bandit algorithm (Lin-UCB) that continuously learns the mapping from channel conditions to optimal configurations, with the digital twin serving as a virtual exploration sandbox that screens candidate configurations before physical deployment—preventing link disruptions during exploratory actions. An expanded configuration space of 63 candidates (7 waveforms × 3 MAC protocols × 3 power levels) is constructed, and a hierarchical performance evaluation model combining voice quality, bit error rate, communication delay, and transmission range is developed using the Analytic Hierarchy Process (AHP) as the reward function for online learning. Experimental results across 10 random seeds demonstrate that DT-MAB achieves the lowest mean cumulative regret, reducing regret by 29% relative to MAB without a digital twin and by 16.5% relative to PSO-based optimization on average. Ablation experiments confirm that removing virtual exploration increases performance drop events by 49% (from 250 ± 79 to 373 ± 6), demonstrating that the digital twin is a functionally indispensable component of the online learning architecture. Full article

A distinct typing interface using surface electromyography (sEMG) can facilitate silent, hands-free typing by interpreting muscle activity in relation to specific keystrokes. Character-level recognition poses greater challenges than coarse gesture recognition because it is sensitive to subtle temporal variations and overlapping muscle dynamics. Temporal features are essential for typing recognition because keypresses may differ in duration, force, and accompanying hand movements across users. This paper proposes TransTCNet, a two-stage deep neural network architecture with a causal convolutional layer for learning local features and a transformer-based component for learning long-range temporal interactions. We evaluated our network on a publicly available 26-class typing sEMG dataset acquired from 19 individuals. The model achieved a validation accuracy of 96.53%, exceeding the baseline models. Our study revealed generalization among participants, and the AUC values were also high (>0.994) across all classes. The model was highly reliable and exhibited high prediction confidence (>0.9), enabling us to achieve a high training accuracy (97.86%) for real-time filtering decisions. TransTCNet could be suitable for wearable and edge devices due to its efficient architecture and low inference cost. The model’s ability to consistently decode fine-grained neuromuscular signals across users makes it well-suited for real-time applications such as adaptive user interfaces, virtual and augmented reality, prosthetic control, and communication systems. Full article

Background/Objectives: Liver diseases cause more than 2 million annual deaths globally, accounting for 4% of the total global mortality rate. Hepatic fibrosis (HF) acts as an indispensable pathological mediator in the progressive deterioration of chronic liver diseases. Thus, the identification of effective anti-fibrotic targets and rational development of corresponding therapeutic agents are expected to deliver profound clinical value for patients suffering from chronic liver disorders. Methods: An in vivo HF model was established to detect Kupffer cell (KC) polarization and periostin (POSTN) protein expression. In vitro, the CCK-8 (Cell Counting Kit-8) assay was applied to evaluate the regulatory effects of Postn-knockdown macrophages on LX-2 cell activity. Conditional knockout mice with Postn were constructed in vivo, and liver tissue samples were used for single-cell sequencing. Functional enrichment and cell differentiation prediction analyses were performed. CellChat was further utilized to characterize alterations in intercellular communication between Postn-deficient KCs and adjacent liver cells. Finally, POSTN-targeted inhibitors were screened and validated via virtual drug screening and experiments. Results: In the HF model, the M2 polarization of KCs was associated with the upregulated expression of POSTN. In contrast, in vitro Postn knockdown correlated with significantly suppressed LX-2 cell activation. Single-cell profiling suggests that Postn deficiency in Kupffer cells is linked to remodeling of the hepatic microenvironment. In drug repurposing, Rhodiosin exhibited binding affinity to POSTN and was observed to inhibit macrophage M2 polarization. Conclusions: POSTN may contribute to KC M2 polarization and be associated with remodeling of the intercellular interaction network among liver cells. Rhodiosin, as a POSTN-binding compound, shows potential for anti-hepatic fibrotic effects. Full article

Virtual patients (VPs) and artificial intelligence (AI) are being implemented in pharmacy education across various countries in order to learn different techniques to improve communication skills, identify drug-related problems, assess the pharmacist’s role in the self-medication process or assess students’ knowledge acquisition. The objective of this study was to assess the benefits of integrating VPs and AI in pharmacy education, particularly their impact on pharmacy students’ knowledge and skills in self-medication counselling. A literature search was conducted across PubMed, Scopus and Web of Science databases. Studies focused on the integration of VPs and AI tools in pharmacy education and their impact on students’ knowledge, counselling and communication skills related to self-medication, were evaluated. Eligible studies were full-text, peer-reviewed research articles published in English. No restrictions were applied regarding publication year. A total of 857 articles were identified through electronic databases and 9 met the inclusion criteria. Six studies were conducted in the USA and one each in Portugal, Sweden and Indonesia. Most studies employed a pre–post-study design. Six studies utilized VP simulations, while the remaining three implemented AI-based tools. Key outcomes covered in analyzed articles included improvements in knowledge score, communication, and consultation skills, along with positive perceptions, including increased student satisfaction and confidence levels. Using VP simulations and AI tools in pharmacy education could positively impact students by enhancing their knowledge as well as their confidence and counselling skills. Full article

Aquatic macroinvertebrates inhabit virtually all freshwater ecosystems, yet communities in extreme saline environments remain largely undescribed, particularly in the Tropical Andes. This study characterizes the taxonomic diversity of aquatic macroinvertebrates in a travertine-fed saline stream (salinity: 12.5 ± 0.2 g/L; 2520 m a.s.l., southern Ecuador) and compares it with an adjacent freshwater stream. Macroinvertebrates were sampled on four occasions (n = 4 events per stream) using a multi-habitat D-net technique; physicochemical variables were compared with Mann–Whitney U exact tests, and diversity metrics with exact permutation tests (C(8,4) = 70 permutations) supplemented with Cliff’s delta as effect-size estimator. Community composition was assessed with ANOSIM and non-metric multidimensional scaling (NMDS). A total of 919 individuals were collected. The freshwater stream harbored significantly greater richness (49 genera, 28 families), abundance, and Shannon diversity than the saline stream (14 genera, 8 families; all p = 0.029, Cliff’s δ = 1.00), while Pielou’s evenness did not differ between stream types. Community composition was fully separated (ANOSIM R = 1.00, p = 0.028), with salinity (R² = 0.95, p < 0.01) and water temperature (R² = 0.79, p = 0.03) as the primary environmental drivers. The saline stream was dominated by halotolerant Diptera (Ceratopogonidae, Stratiomyidae) and water mites (Hydrachnidae), with virtually no EPT (Ephemeroptera–Plecoptera–Trichoptera) representation. These findings establish the first macroinvertebrate diversity baseline for a travertine-associated saline stream in the Tropical Andes, highlighting salinity and temperature as key environmental filters of aquatic biodiversity in extreme Andean lotic ecosystems. Full article

As the core repository of historical memory, the revitalisation and utilisation of cultural heritage (CH) are paramount to cultural transmission. Currently, virtual reality (VR) has become a mainstream method for public engagement with cultural heritage, but existing research mainly focuses on knowledge transfer efficiency while neglecting emotional factors’ key role in heritage identification and dissemination. This study examines the VR-based CH experience for Tianjin Marco Polo Square via multi-stakeholder collaboration, exploring how emotional design affects users’ CH learning and identity formation. Findings show emotionally driven VR games enhance immersion, engagement, resonance and learning outcomes through multisensory immersion, goal-oriented interaction and narrative connections. Theoretically, a three-tier “instinct–behaviour–reflection” emotional design framework integrated with constructivist learning theory is built to tackle emotional deficiency in CH communication. Practically, it verifies that affective VR games upgrade CH transmission from unidirectional dissemination to dynamic inheritance, establishing a new participatory culture paradigm. Full article