Search Results (713)

Money laundering remains a persistent challenge to financial integrity and effective economic and institutional governance, while its concealed nature and heterogeneous measurement methods limit precise estimates of its scale. This study examines money laundering and anti-money-laundering (AML) governance through a structured integrative review and comparative policy analysis of the United States and the European Union. The review synthesizes peer-reviewed research, legal and regulatory materials, official statistics, institutional assessments, enforcement evidence, and selected specialist evidence, prioritizing official and peer-reviewed sources for quantitative and institutional claims. The comparison distinguishes formal regulatory development from operational effectiveness and applies six common analytical dimensions: supervision and regulatory implementation, financial-intelligence capacity and use, investigation and enforcement, confiscation and asset recovery, beneficial-ownership transparency, and domestic and cross-border institutional coordination. The findings show substantial overlap in the principal laundering vulnerabilities affecting both systems, including financial intermediation, beneficial-ownership opacity, trade-based money laundering, real estate, professional facilitation, and virtual assets. The principal comparative difference lies in governance architecture: the United States operates through a predominantly federal AML system, whereas the European Union combines supranational rules and institutions with national supervisory, financial-intelligence, law-enforcement, and judicial authorities, creating an additional multi-level coordination challenge. Available indicators do not support a simple quantitative ranking of the two systems because reporting, enforcement, and asset-recovery measures differ in definition, institutional meaning, and comparability. Instead, the evidence identifies a recurrent divergence between the extensive development of formal AML frameworks and the more uneven evidence available concerning operational outcomes. The study concludes that AML effectiveness should be assessed through the capacity to translate regulation, ownership information, and financial intelligence into coordinated supervision, investigation, enforcement, and asset-recovery outcomes. Priority areas are beneficial-ownership transparency and information quality, the intelligence-to-enforcement and asset-recovery chain, and cross-border and cross-sector institutional coordination. Full article

With the availability of a large amount of renewable energy, the need for flexibility in power grid operation is much higher than that of the conventional power grid, and virtual power plants (VPPs) have become an important key structure. This paper reviews the developments of VPPs in key technologies, scheduling and market design. In the case of infrastructure, cloud-edge computing and distributed communication are used to exchange data between various devices. These techniques underpin rapid sensing, low-order modeling and resource pooling. To schedule and control, multi-timescale mechanisms soak up generation and load variations. Moreover, grid-forming (GFM) control and digital twins provide local voltage and frequency control, enhancing dynamic grid stability. VPPs have in the market dimension incorporated combined trading in electricity, carbon and green certificate markets. Effective entry into the market presupposes open profit-sharing systems among the participants. Immediate transformation of environmental qualities into revenue supports long-term business. The future digital technologies will transform VPPs out of simple resource pooling to multi-market revenue generation. Full article

Understanding how pedestrians perceive roadway conditions and vehicle-state communication is important for examining pedestrian interactions with automated vehicles (AVs). This study used an immersive virtual reality experiment to examine three trial-level perception outcomes—perceived crash likelihood, perceived environmental safety, and perceived collision severity—across urban local-street crossing scenarios. The primary analysis included 949 trial-level observations from 104 participants across scenarios varying in site context, roadway-design configuration, vehicle speed, and vehicle condition. The three vehicle conditions represented a conventional vehicle, an AV without an external human–machine interface (eHMI), and an eHMI-equipped AV. Linear mixed-effects models were used to account for repeated observations within participants. Curbside buffer presence was associated with lower perceived crash likelihood and perceived collision severity and higher perceived environmental safety. Relative to the conventional-vehicle condition, the eHMI-equipped AV condition was associated with more favorable ratings across all three outcomes, whereas no statistically significant differences were detected between the AV-without-eHMI and conventional-vehicle conditions. Direct comparison of the two AV conditions showed lower perceived crash likelihood and perceived collision severity for the eHMI-equipped AV. The 50-km/h vehicle-speed condition was associated with higher perceived crash likelihood and perceived collision severity but not with perceived environmental safety. Overall, the findings highlight the importance of distinguishing multiple dimensions of pedestrian safety perception and support the use of immersive VR as a controlled platform for examining perceptual responses to roadway and vehicle conditions. Full article

Background/Objectives: Compassion fatigue can affect nursing professionals exposed to demanding clinical environments and may be influenced by individual and work-related factors. The objective of this study was to analyze the factors associated with the compassion and fatigue/exhaustion dimensions of compassion fatigue (CF) among nursing professionals in Peru. Methods: This was an observational, analytical, and cross-sectional study in 374 nursing professionals from Peru, with data on the study variables collected at a single point in time through a virtual survey. Primary analyses used the two original EFat-Com subscales and complete-case multiple linear regression without automated selection (n = 339), with HC3 robust 95% confidence intervals (CIs). Sensitivity analyses examined age, resilience, continuous life satisfaction, workplace grouping, and an exploratory 11-item version; stepwise models underwent bootstrap validation. Results: The sample was predominantly female (88.2%) and had a mean age of 39.77 years (SD = 9.11). Empathy was associated with compassion (b = 0.312; 95% CI 0.237 to 0.387); adjusted R² was 0.216. Experience exceeding ten years (b = −0.201; 95% CI −0.396 to −0.006) and neutral job satisfaction (b = 0.226; 95% CI 0.057 to 0.395) were associated with fatigue/exhaustion scores; adjusted R² was 0.080. Several associations varied across sensitivity analyses, whereas the empathy–compassion association persisted. Conclusions: The dimensions showed different association patterns, but the fatigue/exhaustion model had limited explanatory capacity, suggesting that other relevant factors not assessed in this study may also contribute to this dimension. Measurement uncertainty, missing data, and model instability warrant cautious interpretation. Full article

Digital humans are emerging as a form of mediated communication, appearing as virtual influencers, virtual agents, avatars, VTubers, AI companions, and other humanlike digital entities across social media, entertainment, commerce, and online communities. Research on how users perceive and respond to these entities remains fragmented across disciplines. This scoping review synthesizes evidence on users’ perceptions of and responses to digital humans. Following established scoping review guidance and PRISMA-ScR reporting principles, we searched Scopus, Web of Science, and EBSCO for English-language, peer-reviewed studies published between 2016 and 2025. Fifty-one studies met the inclusion criteria and were synthesized descriptively and thematically. The synthesis identified three recurring dimensions of user perception (i.e., perceived agency, perceived embodiment, and perceived social role) and three broad response domains: psychological, relational, and behavioral. These findings suggest that users’ responses to digital humans are shaped by more than human-likeness alone, with capability, embodied presence, and social role also emerging as important interpretive dimensions. The evidence base was concentrated in marketing and commerce, with limited attention to broader media contexts, long-term interaction, cultural diversity, and negative or ambivalent responses. Overall, this review provides an evidence-organizing framework for understanding how users interpret, relate to, and act toward digital humans. Full article

Fire evacuation training is essential for reducing casualties during building emergencies, yet conventional approaches such as drills and instructional materials are often limited in realism, scalability, and their ability to capture human behavior. Serious games (SGs), particularly those using immersive virtual environments, have emerged as promising alternatives for interactive fire safety training. This study systematically reviews 31 peer-reviewed SG-based fire evacuation training studies identified through Scopus and Google Scholar, with searches completed on April 18, 2026. Eligible studies addressed game-based approaches to fire or general building evacuation and reported primary research involving system development, implementation, application, or evaluation. The studies were analyzed across five dimensions: simulation and environment design, interaction and game mechanics, behavioral representation, performance evaluation, and social and collaborative aspects. The review identifies three recurring limitations: simplified representations of occupant decision-making, fragmented evaluation approaches, and limited integration of social dynamics and adaptive training. Given the heterogeneity of study designs and outcomes, the overall effectiveness of SG-based fire evacuation training cannot yet be determined consistently. Based on these findings, the study proposes a roadmap for next-generation SG-based fire evacuation training systems and introduces the Behavior-Aware, Adaptive, and Socially Responsive (BAS) framework. The proposed roadmap and framework provide a conceptual foundation for designing more realistic, personalized, and behavior-aware fire evacuation training systems by integrating behavioral modeling, social interactions, multidimensional assessment, and AI-enabled adaptive learning. The review is limited by English-language inclusion, database coverage, and single-reviewer screening and coding. Full article

Antioxidant peptides from marine proteins are promising bioactive compounds, yet efficient discovery and multilevel validation remain challenging. Here, we established a proteome-scale workflow integrating virtual enzymatic hydrolysis, dual-model antioxidant prediction, consensus ranking, toxicity screening, sequence-diversity-informed selection, experimental validation, and molecular simulation to identify antioxidant short peptides from Apostichopus japonicus. Five newly identified antioxidant short peptides (DHE, HDHE, DDHN, EHED, and QHDE) were synthesized for experimental validation. All showed DPPH and ABTS radical-scavenging activity, good cytocompatibility, and protection against D-galactose-induced loss of HepG2 cell viability. HDHE showed the highest DPPH activity and QHDE showed the highest ABTS activity at higher concentrations, whereas EHED produced the greatest recovery of cell viability. Molecular docking and 100 ns molecular dynamics simulations indicated sequence-dependent Keap1 interaction patterns and preserved global receptor stability, but these computational features did not parallel cytoprotection. Western blotting further showed differential regulation of Keap1, Nrf2, and HO-1, with DDHN, EHED, and QHDE significantly increasing HO-1 expression. Across the workflow, predicted activity, chemical radical scavenging, Keap1 interaction characteristics, and cellular protection did not converge on the same peptide. These findings establish a proteome-scale discovery strategy and show that multilevel validation is essential because computational, chemical, molecular-interaction, and cellular readouts represent complementary rather than interchangeable dimensions of antioxidant peptide performance. Full article

Passive sit-to-stand (STS) assistive devices provide an affordable and reliable alternative to powered rehabilitation systems; however, their effectiveness depends on the kinematic compatibility between the mechanism and the user. Existing studies primarily focus on specific mechanism implementations, whereas systematic methodologies that translate human morphology and motion into conceptual mechanism designs remain limited. This paper proposes an integrated framework combining Human Kinematic Modeling (HKM) and Anthropometry-informed Mechanism Design (AMeD) for the conceptual design of passive STS assistive mechanisms. The HKM reconstructs the STS motion from user anthropometric dimensions using a simplified sagittal-plane kinematic model to derive hip trajectories, center-of-mass progression, and critical assistance phases. These motion descriptors are transformed into engineering requirements through motion abstraction and hierarchical engineering mapping, enabling the generation of alternative linkage concepts, virtual mechanism instantiation, motion compatibility assessment, and preliminary mechanism specification. For the illustrative reference case, based on a stature-derived anthropometric parameterization ($H=1.73$ m), the reconstructed hip trajectory exhibits horizontal and vertical excursions of approximately $0.422$ m and $0.461$ m, respectively, defining the target motion envelope for the virtual mechanism. The proposed HKM-AMeD framework establishes a traceable methodology that transforms user anthropometry and human motion into engineering design knowledge, providing a reproducible foundation for the early-stage development and evaluation of passive assistive mechanisms before detailed optimization and physical prototyping. Full article

High penetration of renewable energy imposes greater demands on the scheduling flexibility of demand-side resources in virtual power plant (VPP) dispatch. Nevertheless, heterogeneous resources exhibit remarkable differences in response reliability, and electric vehicles (EVs) in particular show distinct execution performance between orderly charging and vehicle-to-grid (V2G) modes. To tackle this issue, this paper proposes a two-stage optimal scheduling strategy for multi-agent VPPs incorporating scheduling success probability. A quantitative model for the effective dispatch contribution coefficient is constructed from two dimensions, i.e., relative capacity weight and dispatch execution reliability, with differentiated parameters tailored for EV charging and V2G modes. The two-stage leader–follower game problem is decoupled via backward induction, and the optimal dispatch price is rigorously derived through Karush–Kuhn–Tucker conditions. A 24 h case study covering wind power, photovoltaics, energy storage, EVs, and air-conditioning loads validates the proposed method. Results indicate that the strategy boosts total VPP revenue by 7.43% compared with independent operation, lifts the renewable energy accommodation rate from 88.3% to 94.6%, and reduces the average operating cost by 19 CNY/MWh. Through dual-mode differentiated scheduling, EVs achieve 5.10% revenue growth and serve as a key flexible resource for VPP economic operation. Full article

Virtual cities in video games have emerged as significant sites for the production and reinterpretation of contemporary urban imaginaries. By translating the complexity of real-world urban life into interactive and emotionally engaging environments, they offer new ways of experiencing and understanding cities. Despite their growing importance, research on virtual urbanism remains fragmented across disciplines and lacks a coherent conceptual foundation. Consequently, there is an urgent need for an integrative conceptual framework that explains how virtual cities mediate the production and transformation of urban knowledge. Drawing on an interdisciplinary synthesis of the literature from urban theory, media studies, and game design, this study identifies three key analytical dimensions (representation, abstraction, and spatial cognition) through which virtual urban experience is mediated, alongside urban rearticulation as a distinct process through which virtual urban experiences may be reinterpreted in relation to real urban thought and practice. These insights are integrated into the Virtual Urbanism Feedback Model (VUFM), a cyclical framework composed of three interconnected domains: Real to Virtual Inputs, Ludic Urban Transformations, and Virtual to Real Outputs. The model conceptualizes virtual cities as dynamic epistemic systems in which real and digital urban processes continuously interact through cycles of translation, reinterpretation, and feedback. The study contributes a unified conceptual framework for understanding digital urban mediation and highlights its implications for urban planning, urban design education, participatory planning, and the study of spatial experience in increasingly hybrid urban environments. Full article

Digital twins (DTs) are increasingly studied together with vehicular communications, but the literature spans different twinned entities, synchronization assumptions, computing placements, and levels of experimental evidence, which makes results difficult to compare. This survey provides a communication-centric review of DT-enabled vehicular systems. We first introduce an operational definition for a vehicular DT and distinguish a synchronized DT from a static simulator or digital model. We then organize the field according to twin granularity, physical–virtual synchronization, vehicle–edge–cloud placement, enabling V2X technologies, and measurable evaluation dimensions. The standardization discussion is updated from DSRC and IEEE 802.11p through 5G-Advanced and ongoing 3GPP work toward 6G, together with recent digital-twin and network-digital-twin standards. Rather than treating reported benefits as established outcomes, we compare the assumptions, metrics, evidence, limitations, deployment constraints, and safety and security implications of representative studies. Finally, we identify research priorities involving synchronization staleness, twin placement and migration, communication–computation–fidelity tradeoffs, validation and uncertainty, interoperable data models, lifecycle management, and safety-aware closed-loop operation. The survey is intended to provide researchers and practitioners with a structured basis for deciding when DT techniques are appropriate for vehicular communication systems and how such systems should be evaluated. Full article

Background: Automated assessment of relational competencies by large language models (LLMs) is gaining traction in medical education, yet its empirical reliability remains poorly documented. Methods: We evaluated ATENA, a GPT-3.5-Turbo virtual-patient simulator deployed at the Faculty of Medicine of Nice (France), in two sequential components. First, 21 university hospital professors rated seven dimensions of realism on 7-point Likert scales. Second, across 129 student simulations of a single diagnostic disclosure scenario, expert human scores based on the empathic communication coding system (ECCS) were compared with ATENA’s automated scores using agreement metrics, Bland–Altman analysis, confusion matrix, and qualitative subcorpus analysis. Results: Realism was rated high on six of seven dimensions. Evaluative agreement was poor (ICC = 0.146), with a systematic overscoring bias (+0.80 points) and wide limits of agreement [−1.57; +3.16]. Three bias patterns emerged—score compression (76% of scores within 4.2–4.3), overscoring of weak performance, and underscoring of exemplary performance—indicating that ATENA responds to formal markers of empathy present in nearly every transcript. Conclusions: In this first-generation version of ATENA, the system distinguishes stronger from weaker interviews without being able to place them at the level assigned by expert human raters. These patterns preclude any certificatory use and support a critical, formative-only deployment grounded in instructor algorithmic literacy. The audit protocol applies to any LLM evaluator scored against human coding on a validated instrument. Full article

Neurosymbolic AI (NeSy AI) seeks to integrate the strengths of symbolic reasoning with computational learning methods, addressing fundamental challenges of each paradigm in isolation. Existing surveys have primarily organized this growing body of research by architecture. The systematic evaluation of NeSy systems against the foundational questions about knowledge–learning interaction raised in the literature has received far less attention. This paper introduces a multi-axis analytical framework that combines the six-type taxonomy proposed by Kautz with four foundational dimensions derived from the open questions raised by van Harmelen: the mode of integration between symbolic and computational learning components, the use of symbolic priors for learning, the enforcement of symbolic constraints for safety and bias prevention, and the production of symbolic knowledge from learning. Complemented by a systematic reasoning categorization (deductive, inductive, abductive), this framework is applied to categorize and analyze 70 NeSy papers. The analysis reveals that while symbolic priors for learning are widely adopted in the surveyed corpus, symbolic constraints for safety and fairness remain significantly underexplored despite being among the most frequently cited motivations for NeSy research. Task-level abductive reasoning is virtually absent, appearing in only three of the 70 systems, all but one from 2026. Fully integrated architectures (Kautz Type 6) remain scarce and largely theoretical, and bidirectional knowledge–learning interaction is rare. Six concrete gaps are identified, providing specific directions for future research in neurosymbolic AI. Full article

The digital transformation of manufacturing requires training approaches that build operational competence in human-centered production systems. This study develops and experimentally applies a multidimensional framework to characterize operational learning and compare alternative operator training strategies. Experiments were conducted in a Lean Learning Factory using three strategies, conventional workstation training, digitally assisted workstation training, and virtual reality-based training, followed by practical validation. Operational learning was assessed across five dimensions—accuracy, continuity, efficiency, convergence, and retention—using statistical analysis, regression modeling, convergence indicators, and maturity-stage assessment. The results show that the three strategies yield distinct learning trajectories. Digital assistance was associated with faster development and stabilization of operational performance, whereas virtual reality training was associated with higher initial performance during subsequent practical validation. The proposed OLM–OLAM–OLMM framework integrates these dimensions into a common methodology for describing, comparing, and assessing the maturity of operational learning. The approach extends traditional learning-curve analysis by incorporating performance convergence, retention, and maturity assessment, providing a structured basis for evaluating operator training strategies in human-centered Industry 5.0 manufacturing systems. Full article

Job satisfaction has become a significant factor in organizational performance, particularly in operational sectors such as port activities, where efficiency, coordination, and safety are essential. Port operations provide a theoretically relevant setting because technical work is safety-sensitive, operationally interdependent, and strongly dependent on coordination, communication, and compliance with procedures. This study aimed to analyze the relationship between job satisfaction and perceived productivity among technical workers at port companies in Guayaquil, Ecuador, from a social sustainability and Happiness Management perspective. A mixed-methods approach with a convergent design was employed, integrating ordinal data obtained through an online survey with qualitative data from virtual semi-structured interviews. The survey, based on a 7-point Likert scale, was administered online to 54 port technicians, while the qualitative component consisted of virtual semi-structured interviews with five industry experts. Descriptive statistics, preliminary construct validity assessment, sensitivity analysis, power analysis, and Spearman’s correlation coefficient were used to analyze the ordinal data, while the qualitative information was analyzed using thematic analysis. The findings showed that 59.3% of participants were classified in the high job satisfaction category and 85.2% in the high revised perceived productivity category, according to predefined Likert-scale classification criteria. Furthermore, a strong, statistically significant positive association was identified between job satisfaction and the revised perceived productivity score, excluding the item that directly embedded the satisfaction–performance relationship ($\rho$ = 0.781, $p<0.001$, $N=54$; 95% bootstrap CI = [0.633–0.881]). A stricter sensitivity analysis excluding both Items 22 and 23 also showed a strong association ($\rho$ = 0.789, $p<0.001$). Qualitative results provided contextual insights into how experts perceived satisfaction-related dimensions, such as recognition, organizational climate, communication, coordination, and labor well-being, as being associated with perceived productivity in port operations. The study concludes that higher job satisfaction composite average scores are significantly associated with higher revised perceived productivity composite average scores, although the cross-sectional design does not allow causal conclusions. The findings contribute to the social sustainability and Happiness Management literature by showing how job satisfaction, recognition, motivation, organizational climate, and labor well-being are associated with perceived productivity in a highly demanding port context. Rather than treating job satisfaction only as an isolated employee attitude, the study interprets it as a workplace well-being dimension connected with Happiness Management and sustainable port operations. Full article