Search Results (1,700)

Tourist congestion and load imbalance during peak periods pose critical challenges to the safe operation and experience assurance of large scenic areas. To address the limitations of traditional management approaches in capturing the dynamic and stochastic nature of tourist flows, this study develops a dynamic visitor guidance modeling and analysis framework based on a Timed Petri Net. The proposed model provides a formal representation of tourist movements, scenic spot load evolution, and guidance decision mechanisms within a scenic area. Under unified parameter settings and controlled random conditions, multiple visitor guidance strategies with different information coverage scopes are designed, and minute-level simulation experiments are conducted using the Huangshan Scenic Area as a case study. The simulation results show that, compared with unguided tourist flows, the proposed strategies significantly reduce average load levels, alleviate spatial load imbalance, and enhance TS. Using mean–standard deviation analysis, distributional analysis, and dynamic evolution analysis, differences among guidance strategies in terms of load control, visitor experience, and operational stability are systematically evaluated. Furthermore, a quantitative relationship model between tourist satisfaction and scenic area load is constructed, revealing a consistent inverted-U pattern. Robustness tests under multiple random seeds indicate that the main conclusions are not sensitive to specific stochastic realizations. Overall, the simulation results suggest that dynamic visitor guidance may improve load control, visitor experience, and system stability by optimizing the spatiotemporal distribution of tourist flows, thereby providing simulation-based quantitative insights for peak-period management in large scenic areas. Full article

In quantum time (QT) schemes, time is promoted to a degree of freedom, allowing Lorentz covariance to be made explicit for single particles. We ask whether this can be lifted to QFT so that Lorentz covariance becomes manifest at the Hilbert-space level, rather than being hidden as in the standard canonical formulation. We address this question by proposing a second-quantized approach in which the elementary particle is the QT particle itself, leading naturally to the notion of spacetime field algebras and of quantum action. We show, however, that a naive many-body construction runs into inconsistencies. To pinpoint their origin we introduce a classical counterpart of the second-quantized formalism, spacetime classical mechanics (SCM), and prove a no-go theorem: Dirac quantization of SCM collapses back to standard QFT and therefore hides covariance. We circumvent this problem by presenting a quantum-action-based quantization that yields a spacetime version of quantum mechanics (SQM), making covariance manifest for (interacting) QFTs. Finally, we show that this resolution is tied to a genuine spacetime generalization of the notion of a quantum state, required by causality and closely connected to recent “states over time” proposals and, in dS/CFT–motivated settings, to microscopic notions of timelike entanglement and emergent time. Full article

Background/Objectives: Children and adolescents on the autism spectrum often experience delays in both gross and fine motor skills, which can limit their participation in physical activity and everyday tasks. Methods: This narrative review synthesizes evidence from 88 peer-reviewed studies examining fundamental motor skills, broader motor competence, and perceived motor competence in individuals aged 3–18 years with a formal diagnosis of autism. Results: Across the literature, children with autism consistently demonstrate lower proficiency in locomotor and object control skills compared with their typically developing peers, while perceived competence emerges as an important factor influencing motivation and engagement. Intervention studies—most commonly school-based or structured physical activity programs—generally report short-term improvements in motor performance, although outcomes vary depending on study design, dosage, and assessment tools. The review also highlights substantial methodological heterogeneity and a notable lack of evidence concerning adolescents, underscoring the need for longitudinal and developmentally sensitive research. Conclusions: Practical implications are discussed for creating supportive movement environments in educational and adapted physical activity settings. This review follows a narrative synthesis approach informed by a structured search strategy. Full article

The deep integration of the Internet of Things (IoT) and blockchain technology enables emerging applications in multi-party collaboration and trusted data sharing. However, the scalability constraints of blockchain networks remain a major bottleneck when handling high-frequency interactions in IoT–blockchain systems. Sharding addresses this challenge by partitioning the blockchain network into parallel sub-networks. Nevertheless, it introduces significant coordination overhead for cross-shard transactions. Among mitigation strategies, Broker-based mechanisms (e.g., BrokerChain) have attracted increasing attention for their efficiency in handling cross-shard communication by reducing verification overhead and communication latency. Despite these advantages, existing research typically treats the Broker group as a fixed configuration, neglecting the impact of Broker selection on system performance. To bridge this gap, this paper proposes the Accumulative Activity–Temporal Liveness Broker Selection Strategy (AT-BSS) to optimize cross-shard transaction processing in sharded IoT–blockchains. Specifically, we formally characterize the Accumulative Activity and Temporal Liveness of accounts in the account–transaction network and use these two metrics to identify accounts that maximize transaction-aggregation efficiency. We implement AT-BSS on the BlockEmulator platform and evaluate it against two baselines, namely, ABChain and BrokerChain. Under different settings of the number of Brokers (BrokerNum), number of shards (ShardNum), transaction arrival rate (InjectSpeed), and maximum block size (MaxBlockSize), AT-BSS consistently outperforms both baselines in terms of Transactions Per Second (TPS), Transaction Confirmation Latency (TCL), and Cross-shard Transaction Ratio (CTX). Compared with ABChain, AT-BSS achieves up to 15.5% higher TPS and reduces TCL and CTX by up to 80.2% and 28.7%, respectively. AT-BSS yields more pronounced results over BrokerChain, with TPS improvements of up to 229% and reductions of up to 97.7% in TCL and 80.5% in CTX. Full article

This paper analyzes “prompt engineering” through the economic lens of self-insurance against the risk of errors from noisy AI systems. To formalize this approach, we model an agent under cognitive load, allocating effort between working unassisted and prompting an AI assistant. The theoretical model demonstrates that an agent’s optimal prompting effort is driven by the agent’s attitude toward risk. Specifically, the model proves that risk-averse agents rationally “over-invest” in prompting effort, while risk-seeking agents “under-invest” relative to the risk-neutral benchmark. This outcome stems from the covariance between the marginal utility of performance and the marginal product of prompting. This alignment is positive for risk-averse agents, effectively boosting the AI’s perceived productivity. The novel implication is that prompting effort is an economically meaningful behavior that can be informative about an individual’s underlying attitude toward downside AI risk. These results offer a new perspective for understanding heterogeneity in AI adoption and oversight. They also suggest that, under comparable task conditions and controlling for prompting ability, observed prompting effort may be informative about attitudes toward downside AI risk. The framework therefore provides a risk-management perspective for understanding heterogeneity in AI governance in high-stakes settings such as healthcare and finance. Full article

Substance use disorder (SUD) undermines social connection, identity, and well-being. While art therapy is formally incorporated into clinical treatment, far less is known about how informal, group-based creative activities contribute to recovery. This qualitative study examines whether and how participation in a creative arts group fosters social support and human flourishing among individuals with SUD. We conducted semi-structured, individual interviews of eight adults enrolled in SUD outpatient treatment at the Johns Hopkins Broadway Center for Addiction who voluntarily participated in a creative arts class. Recordings were transcribed and analyzed using an iterative, thematic approach. Analysis revealed four themes: (1) Social connectedness and support—artmaking fostered camaraderie, accountability, and peer encouragement; (2) Holistic and supportive environment—the group offered a safe, nonjudgmental space that affirmed participants beyond their addiction; (3) Emotional renewal through art—creative engagement reduced anxiety, promoted joy, and provided a constructive outlet for emotions; and (4) Reclaiming agency through artistic expression—participants experienced autonomy, skill development, and identity building, which fostered hope and personal growth. Overall, participants viewed artmaking as a catalyst for relational and personal transformation. These exploratory findings generate hypotheses for future research on the role of informal creative arts groups within recovery-oriented care settings. Full article

Experience-based co-design emphasizes understanding service-users’ experiences to inform service improvement, yet little research has explored domestic abuse survivors’ perspectives within this framework. This study examined survivors’ accounts of their interactions with the police and organizations that support domestic abuse survivors. We aimed to identify aspects of practice experienced as either helpful or in need of improvement. Semi-structured interviews with six survivors in one area of England were analyzed using reflexive thematic analysis. Survivors described obstructive and supportive responses from formal services. Four interrelated themes were developed: The Importance of Being Understood, Believed, and Cared For; It Is Important That There Is Good Communication Between the Survivor and Formal Services; Survivors Want a Victim-Centered, Rapid, and Meaningful Response; and Specific Circumstances Sometimes Influence Opportunities for Help-Seeking. Survivors described being dismissed and disbelieved, which contributed to negative help-seeking experiences and heightened feelings of vulnerability. In contrast, empathic and timely responses validated survivors’ experiences and supported their sense of safety. The findings highlighted the importance of practice that recognizes the different forms abuse can take, provides timely, victim-centered support, and responds equitably to survivors in diverse circumstances. This study demonstrates the valuable insights gained through applying an experience-based co-design approach in this setting. Full article

During the Northern Song period, the gifting of Buddhist artifacts frequently appeared in Sino–Japanese exchanges. Although Japan had established a self-centered order with its emperor at its core and tended toward isolation, the Heian imperial court, led by the Fujiwara regents, actively dispatched monks to Song China and requested Buddhist artifacts. Although these monks were not official envoys, they reflected a trend toward diversified diplomacy in Japan. Recognizing the close ties between these monks and the Japanese rulers, the Song court used the bestowal of Buddhist artifacts to encourage them to convey messages to the Japanese court, urging Japan to send formal tribute missions and thereby incorporating this into its broader diplomatic strategy. Under the “Chanyuan Treaty System”, Buddhism served as a shared cultural foundation for transregional interaction in East Asia. By collecting and bestowing Buddhist artifacts, the Song Dynasty proclaimed its orthodox status within the Buddhist world and enhanced its diplomatic influence. However, the Heian court, upon receiving these artifacts, repurposed them to construct their own divine authority and vision of a “Land of Buddha’s Kingdom”. Thus, the very same set of Buddhist artifacts carried vastly different symbolic meanings and functions in the Northern Song–Heian diplomatic interactions. Full article

This study aims to automate the generation of execution plans for university projects by transforming BPMN-based process models into hierarchical planning representations that can be executed by HTN planners. Effective implementation of university extension projects requires explicit management of objectives, dependencies, and operational constraints, yet this process is often carried out manually and without formal planning support. To address this problem, the paper proposes PlanProjU, a web-based platform that captures project knowledge through BPMN and translates it into HDDL domain and problem files for execution with SHOP2 and PyHOP. The system was evaluated through real university project cases and a comparative analysis of alternative generated plans. The results show that BPMN-based project knowledge can be operationalized into executable hierarchical planning structures and that different planners may produce distinct plan alternatives depending on project characteristics. The originality of the study lies in the design of a traceable BPMN-to-HDDL workflow for university project planning, implemented in an integrated platform that connects business process modeling with HTN automated planning the originality of the study lies in the design of a traceable BPMN-to-HDDL workflow for university project planning, implemented in an integrated platform that connects business process modeling with HTN automated planning in a domain that has received limited attention in prior research. In this sense, the proposal serves both as an innovative research contribution and as a practical alternative for structuring implementation decisions in institutional settings. Full article

Background: Occupational exposure to cytotoxic drugs remains a major concern for pharmacy personnel, due to their well-established, carcinogenic, mutagenic and organ-specific effects. Despite the existence of robust international guidelines, evidence suggests substantial variability in compliance, training quality and operational conditions across healthcare settings. Objective: This study aimed to characterise current handling practices, assess working conditions, training, safety procedures, exposure patterns, and perceived risk factors among pharmacy technicians involved in the preparation of cytotoxic drugs in Portugal. Methods: A cross-sectional descriptive study was conducted using a structured questionnaire grounded in international standards (ISOPP, NIOSH, ASHP, USP <800>). The instrument was developed through literature review, expert panel validation (n = 42), and pre-testing. Data were collected electronically between April and May 2025 from pharmacy technicians actively handling cytotoxic drugs in Portugal. Results: A total of 124 valid responses were analysed. Most participants were female (78%) and under 50 years, with nearly one-third having less than one year of experience. Prolonged daily exposure (31.5% participants worked ≥ 5 h/day) extended uninterrupted handling periods (28.2% worked > 120 min), and high preparation workloads were common. While adherence to core protective measures—such as reinforced gowns, double gloves, and Class II B2 biological safety cabinets—was high, important gaps were identified, including incomplete use of closed system transfer devices, inconsistent respiratory and foot protection, limited automation, and insufficient environmental monitoring. Structured competency assessment, periodic training, and formal documentation were frequently absent. Institutional policies on reproductive risk showed strong protection for women but less clarity for male workers. Conclusions: Cytotoxic drug handling practices in Portugal demonstrate satisfactory adherence to fundamental protective measures but reveal significant structural and organisational gaps related to workload management, environmental monitoring, and continuous training. The absence of unified national guidance contributes to variability across institutions. These findings highlight the need for greater standardisation of occupational safety practices. Full article

Deep learning systems deployed in regulated settings require explanations that are accurate and stable under nuisance transformations, yet classical post hoc transition matrices rely on fidelity-only fitting that fails to guarantee consistent explanations under spatial rotations or other group actions. In this work, we propose Equivariant Transition Matrices, a post hoc approach that augments transition matrices with Lie-group-aware structural constraints to bridge this research gap. Our method estimates infinitesimal generators in the formal and mental feature spaces, enforces an approximate intertwining relation at the Lie algebra level, and solves the resulting convex Least-Squares problem via singular value decomposition for small networks or implicit operators for large systems. We introduce diagnostics for symmetry validation and an unsupervised strategy for regularization weight selection. On a controlled synthetic benchmark, our approach reduces the symmetry defect from 13,100 to 0.0425 while increasing the mean squared error marginally from 0.00367 to 0.00524. On the MNIST dataset, the symmetry defect decreases by 72.6 percent (141.19 to 38.65) with changes in structural similarity and peak signal-to-noise ratio below 0.03 percent and 0.06 percent, respectively. These results demonstrate that explanation-level equivariance can be reliably imposed post-training, providing geometrically consistent interpretations for fixed deep models. Full article

This paper develops a rigorous algebraic framework for quasi-substructures in Sheffer-based Nelson algebras, extending the landscape of fuzzy algebraic theory. By systematically introducing $(\in ,\in \vee q)$-bipolar fuzzy quasi-subalgebras and ideals, we analyze their structural properties through generalized belongingness and quasi-coincidence relations. We formalise invariant threshold symmetry as the condition $g^{+}\left(\chi \right)+\left|g^{-}\left(\chi \right)\right|=c$ for a constant $c\in [0,2]$ and every $\chi \in \Omega$ (Definition 10) and prove its structural preservation within $(\in ,\in \vee q)$-bipolar fuzzy quasi-subalgebras (Theorem 4, supported by Theorems 3, 15 and 16). This enables a balanced dual evaluation of positive and negative information. Characterization theorems are established via level subsets, revealing how quasi-substructure properties are governed by bounds at critical membership values. Equivalence results unify classical and bipolar fuzzy perspectives, demonstrating that algebraic constraints preserve structural coherence across crisp and fuzzy environments. Algorithmic verification procedures are provided for practical validation in finite systems, and illustrative examples highlight applications in uncertainty modeling and decision support. Overall, the proposed theory formalizes bipolar fuzzy structures in Sheffer-based Nelson algebras, utilizing invariant threshold symmetry, level-set decomposition, and crisp equivalence to evaluate dual information. Full article

Creative tourism is increasingly discussed as a pathway for tourism development in rural and peripheral destinations, yet empirical evidence remains uneven and is still drawn mainly from contexts where it is already explicitly labelled and institutionally supported. This article examines whether and how creative tourism-aligned practices are present in Kupiškis District, a peripheral rural municipality in north-eastern Lithuania where creative tourism has not been formally institutionalised as a tourism development category. The study adopts a qualitative single-case design combining a multi-stakeholder focus group and semi-structured interviews with municipal, intermediary, and private-sector actors. The findings reveal a meaningful but weakly integrated experiential base shaped by educational activities, water-based leisure, symbolic narratives, routes, and micro-entrepreneurial initiatives. Although these practices are rarely named locally as creative tourism, they display several of its defining characteristics, including participatory learning, host involvement, small-scale interaction, and local embeddedness. The study suggests that the main development challenge lies not in the absence of creative resources, but in limited coordination, weak articulation, and the difficulty of translating dispersed practices into coherent and consistently bookable visitor experiences. The article conceptualises this condition as a latent experiential portfolio and, in doing so, makes three contributions: it offers a sensitising concept for describing pre-consolidation stages of creative tourism where relevant practices exist but remain only partly articulated; it supports a practice-based rather than label-based identification of creative tourism in weakly institutionalised settings; and it extends the empirical scope of creative tourism research to a peripheral rural case in the Baltic region. Full article

Background/Objectives: Stuttering is a neurodevelopmental disorder of speech fluency. It emerges most commonly between 2 and 5 years old, often causing social exclusion and stigma. In Latin America, cultural misconceptions regarding its causes exacerbate these psychosocial challenges. This study validated a culturally adapted instrument for Chile to measure public attitudes toward stuttering. The instrument provides a psychometrically sound method to assess and address stigma within educational and community settings. Methods: A total of 756 Chilean adults (mean age = 36.7 years, SD = 15.8; 64% women, 36% men) were recruited using stratified probability sampling to reflect the national demographics. Ethical approval and informed consent were obtained. The subsection underwent rigorous cross-cultural adaptation (translation, expert review, cognitive debriefing n = 30, pre-testing n = 50). Analysis employed polychoric matrices, EFA, CFA with WLSMV, and multiple reliability/validity indices. Results: Joint analysis showed poor fit (CFI = 0.72, RMSEA = 0.12), confirming independence. Beliefs (14 items): three-factor CFA fit excellent (CFI = 0.993, RMSEA = 0.034); factors: competence/normality (α = 0.85), psychological causes (α = 0.78), and help/support (α = 0.72). Reactions (11 items): four-factor fit adequate (CFI = 0.97, RMSEA = 0.043); factors: distant concern (α = 0.82), personal concern (α = 0.79), media sources (α = 0.75), and formal sources (α = 0.77). Validity was supported; bifactor models favored multidimensionality. Conclusions: The adapted subsection is psychometrically robust and effectively captures Chilean-specific attitudes toward childhood stuttering. It provides a reliable tool for quantifying public stigma and misconceptions, particularly in educational and school contexts, thereby supporting the design of targeted school-based policies and interventions to reduce bullying, promote inclusion, and safeguard the psychosocial well-being of children and adolescents who stutter. Full article

Structural Equation Modeling (SEM) is a key framework for analyzing complex economic relationships involving latent variables, mediation effects, and endogeneity, yet the choice between frequentist and Bayesian estimation remains theoretically and practically contested, especially in settings with non-stationary data and small samples. This study provides a formal comparison of the two approaches by formulating SEM as a probabilistic graphical model and deriving the corresponding estimation procedures, identifiability conditions, and uncertainty measures. We examine asymptotic properties of frequentist estimators and posterior consistency in Bayesian SEM, with particular attention to integrated time-series SEM applications such as shadow economy estimation. The analysis shows that while both approaches converge under large-sample conditions, important differences arise in finite samples. Bayesian methods exhibit more stable point estimates through coherent uncertainty quantification, particularly when prior information regularizes an otherwise ill-conditioned likelihood. Under model misspecification, Bayesian posteriors concentrate around the pseudo-true parameter defined by the Kullback-Leibler projection, providing a probabilistic representation of misspecification uncertainty through posterior spread—an advantage over frequentist inference, which typically conditions on the maintained model as exact. These findings carry direct implications for empirical economic modeling under realistic data constraints. In settings where sample sizes are small, identification is weak, and model uncertainty is substantial, conditions that routinely characterize macroeconomic research, the choice of inferential framework is not a matter of philosophical preference but a determinant of whether policy-relevant conclusions can be credibly defended. Bayesian SEM offers a principled and transparent path forward in precisely these conditions. Full article