Search Results (2,578)

Industry 4.0 and 5.0 technologies have made industrial environments data-rich, yet a persistent cognitive gap remains: operators face substantial difficulty interpreting and acting on this data in unstructured, time-critical situations. This paper presents an architecture that integrates the Asset Administration Shell (AAS), OPC UA, and a Large Language Model (LLM)-based agentic AI within a mandatory Human-in-the-Loop (HITL) framework. The AAS acts as a semantic grounding layer through Retrieval-Augmented Generation (RAG), supplying the LLM agent with ECLASS-referenced technical parameters that reduce the risk of hallucination. OPC UA Methods form a deterministic execution layer that keeps agent actions within PLC-validated safety boundaries. The HITL mechanism enforces a cryptographic approval gate so that no physical machine action can occur without documented human authorization. This requirement was motivated by an industrial survey ($n=117$), in which 47% of employees stated that human oversight is irreplaceable, combined with enterprise safety and accountability requirements and broader governance considerations for AI-driven actuation in safety-critical cyber-physical systems. Two proof-of-concept case studies evaluate the architecture under controlled laboratory conditions. Proof-of-concept results indicate system processing latencies of 1.7 s (maintenance) and ∼15 s (scheduling), with end-to-end latencies (including mandatory human approval) of 14.9 s and 62 s, respectively, representing estimated improvements of approximately 97% and 96% over expert-estimated manual baselines (∼8 min and 25–40 min). All figures derive from single scripted runs under controlled laboratory conditions and should be read as indicating architectural feasibility at Technology Readiness Level 4, not as statistically validated performance benchmarks: variability bounds and confidence intervals are unavailable, the manual baselines are expert estimates rather than instrumented measurements, and operator deliberation times derive from a single response per scenario. A structured comparison with related work shows that, to the authors’ knowledge, no published approach in the surveyed literature combines AAS semantic grounding, OPC UA deterministic execution, and mandatory cryptographic HITL within a single empirically grounded framework. Full article

Digital gamification may function as motivational scaffolding within situated course designs when it helps learners perceive progress, participate actively, and connect course activities with meaningful professional goals. This article examines how motivational scaffolds were designed and refined through digital gamification in a fourth-year science course in early childhood teacher education. Using a two-cycle design-based research approach, the study analyzed an initial FantasyClass-supported implementation and a subsequent redesigned version. In Cycle 1, broad affective outcomes, feature ratings, and open responses were associated with more favorable recent learning experiences, somewhat more favorable current views of science and its relevance, and higher perceived science-teaching capability and preparedness. Feature-level evidence identified progression, collaborative work, and narrative coherence as central motivational supports. These findings informed Cycle 2, which recalibrated selected mechanics and strengthened the narrative structure. Post-course Intrinsic Motivation Inventory results were descriptively consistent with above-midpoint enjoyment, perceived competence, and perceived choice, with enjoyment positively associated with competence and choice. Qualitative evidence highlighted active participation, progress awareness, and perceived relevance for future teaching. The findings suggest that, under the design conditions examined here, digital gamification may support motivationally meaningful course design when treated as motivational scaffolding rather than as an isolated reward system. Full article

Studentpreneurship has gained prominence in South Africa as universities are increasingly expected to foster innovation, job creation, and youth participation in the economy. However, despite the establishment of incubators, entrepreneurship centres, mentorship programmes, and EDHE-aligned initiatives, support for studentpreneurs remains unevenly implemented, poorly integrated, and inconsistently accessible, particularly within a historically disadvantaged university. This study examines how university support mechanisms shape the experiences, challenges, and business development trajectories of studentpreneurs in a South African university. Guided by Entrepreneurial Ecosystem Theory, the study adopts a qualitative research design involving in-depth interviews with 15 studentpreneurs. Thematic analysis reveals significant gaps in awareness, accessibility, and continuity of institutional support. While students valued motivational workshops, pitching opportunities, and limited mentorship, these interventions lacked sustained follow-up, sector-specific guidance, and financial or infrastructural resources necessary for business growth. The study contributes to South African entrepreneurship scholarship by highlighting the lived realities of studentpreneurs at a historically disadvantaged university and by proposing institutional reforms to build more coherent, equitable, and sustainable studentpreneurship ecosystems. Full article

This study examines communal and motivational mechanisms associated with well-being and ill-being among teacher education students during wartime. Drawing on self-determination theory and resilience frameworks, it focuses on environments that support autonomy, competence, and relatedness, as well as communal resilience. Participants included 332 Jewish and Arab-Bedouin students (Mean age = 26.24, SD = 6.38; 93.7% female), who completed an online questionnaire. Jewish students reported higher well-being indicators (autonomous motivation, resilience, hope, and engagement) and lower ill-being indicators (anxiety, depression, and PTSD) than Arab-Bedouin students. Structural equation modeling was used with a mediation model in which community resilience was associated with need satisfaction and need frustration, which, in turn, were associated with well-being and ill-being. Community resilience was positively associated with need satisfaction, which, in turn, was linked to resilience, hope, engagement, and autonomous motivation in both groups, and to lower ill-being among Arab-Bedouin students. It was also negatively associated with need frustration, which was linked to lower resilience among Jewish students and higher ill-being in both groups. These findings highlight SDT as a resilience theory characterized by cultural specificity during wartime and the role of communal resilience as a resource associated with well-being and ill-being among students. They emphasize educational settings as environments that promote resilience. Full article

Background and Objectives: Williams syndrome (WS) is a rare neurodevelopmental genetic condition traditionally described as being associated with a highly sociable behavioral profile. However, growing evidence indicates that this characterization may oversimplify the socio-cognitive phenotype, as some individuals with WS exhibit socio-communicative and pragmatic difficulties that may overlap with ASD-related features, although these difficulties should not be interpreted as autism-specific. The present systematic review aimed to investigate the presence of autistic traits in WS, to synthesize evidence on pragmatic and socio-communicative difficulties, and to explore their association with adaptive functioning and, indirectly, adaptive and functional outcomes. Materials and Methods: This study follows a systematic search and selection process in accordance with PRISMA 2020 guidelines and employs a systematic review with structured narrative synthesis. A systematic search of PubMed, Scopus, and Web of Science was performed up to December 2022, supplemented by grey literature sources. Nine studies met the predefined inclusion criteria. Due to substantial methodological heterogeneity, findings were synthesized using a structured narrative approach. Study quality was evaluated using adapted criteria addressing research design, sample characteristics, measurement tools, and risk of bias. Results: The findings suggest that autistic traits may constitute a potentially clinically relevant, though not universal, aspect of the WS phenotype. Pragmatic language difficulties were consistently reported, particularly in relation to conversational management, social reciprocity, and context-appropriate language use. These difficulties appear to function as a key mechanism linking socio-cognitive characteristics with functional outcomes. Patterns of adaptive functioning showed both distinctions from and overlaps with autism spectrum disorder (ASD), especially in communication domains. Available genetic and molecular evidence points to a possible contribution of additional modifying factors for phenotypic variability, with possible phenotypic overlap between WS and ASD, particularly in pragmatic language and adaptive communication. Conclusions: The evidence supports a multidimensional and spectrum-based conceptualization of socio-communicative functioning in Williams syndrome. Despite strong social motivation, individuals with WS may experience meaningful pragmatic and adaptive challenges, with implications for assessment and intervention. These findings highlight the importance of multidimensional and individualized clinical approaches. Full article

Hybrid quantum-classical learning pipelines combine conventional accelerators, quantum runtimes, and quantum processing units (QPUs), creating scheduling, memory, isolation, encoding, and deployment challenges that are not captured by application-level quantum machine learning surveys alone. This paper presents a systematic review of runtime and systems mechanisms for hybrid quantum-classical workloads, with medical imaging used as a translation lens rather than as an exclusive inclusion boundary. Following a PRISMA-aligned review process, we screened 364 records and synthesized 40 studies published between 2020 and 2025. Each study was coded by systems layer, application grounding, noisy-label relevance, and evaluation maturity. The coding shows that the corpus combines direct medical evidence with broader transferable systems evidence: 8 studies directly evaluated medical data, 12 were medically motivated, and 20 were generic systems studies. Across the corpus, the strongest support concerns hybrid orchestration, qubit/resource allocation, classical–quantum data movement, and container-based reproducibility, whereas evidence remains limited for realistic clinical operation, end-to-end remote-QPU workflows, multi-tenant isolation, and noisy-label retraining loops. We contribute an evidence map, a direct/indirect/interpretive evidence distinction, and cross-layer design guidelines for future hybrid quantum-classical imaging pipelines in regulated settings. Full article

Perceived overqualification has attracted widespread scholarly attention; however, its impact on employees’ innovative behavior remains inconclusive, particularly from a sustainability perspective. Drawing on person–job fit theory, self-determination theory, and social identity theory, this study develops an integrated framework to examine the mechanisms and conditions under which perceived overqualification inhibits innovative behavior, with a focus on the sustainable utilization of human capital. This study proposes that perceived overqualification undermines employees’ sense of job meaningfulness, thereby reducing intrinsic motivation and limiting sustained engagement in innovative activities. Professional identity is introduced as a key boundary condition that buffers this negative process. Based on a three-wave time-lagged dataset collected from employees in high-tech and knowledge-intensive organizations, the findings reveal that perceived overqualification is negatively associated with innovative behavior. Job meaningfulness mediates this relationship, while professional identity weakens the negative effect of overqualification on job meaningfulness and further attenuates its indirect negative impact on innovative behavior. Overall, the findings suggest that the consequences of perceived overqualification depend on employees’ ability to maintain meaning and professional identity under conditions of misfit. This study highlights the importance of activating underutilized human capital and provides important implications, from a sustainable human resource management perspective, for enhancing resource utilization efficiency and fostering sustainable innovation. Full article

Amidst the protracted socio-political volatility of Thailand’s southern border provinces, youth have emerged as pivotal agents of social architecture rather than mere passive observers of conflict. This study investigates Emotional Intelligence (EQ) not merely as a personal trait, but also as a critical psychosocial infrastructure for peace. Adopting a qualitative lens through in-depth interviews and focus groups with youth leaders, the research elucidates how EQ functions as a strategic mechanism for identity negotiation and intergroup reconciliation. The findings delineate five cornerstone competencies: acute self-awareness within structural constraints; emotional regulation as a safety stratagem; collective resilience-driven motivation; multicultural empathy as a catalyst for prejudice reduction; and non-violent communication. These attributes empower youth to undergo a profound transformation from victims of circumstance to proactive peacemakers. By bridging the internal emotional landscape with external social stability, the study argues that fostering emotional maturity is fundamental to communal resilience. From an educational standpoint, the paper advocates for the systemic integration of Social and Emotional Learning (SEL) to cultivate collective emotional capital. Such a pedagogical shift—moving toward human security-centered curricula—is essential for fostering sustainable coexistence in multicultural, high-pressure environments. This study situates Emotional Intelligence within the framework of peace education, conceptualizing it as a psychosocial foundation for fostering relational peace, emotional resilience, and sustainable coexistence in conflict-affected contexts. Full article

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder worldwide, and its early diagnosis remains a major challenge due to reliance on subjective clinical assessments. This study proposes a bio-inspired computational framework for automatic PD detection that draws explicit architectural inspiration from two biological systems: the hierarchical tonotopic organization of the human auditory cortex, which motivates the design of a 1D Convolutional Neural Network (CNN) for vocal biomarker analysis, and the basal ganglia–cerebellar motor control circuit, which motivates the selection and design of features extracted from Archimedean spiral drawing tasks. Unlike previous studies that apply standard machine learning techniques without grounding architectural choices in biological mechanisms, the proposed framework establishes a direct mapping between neural processing pathways and model design decisions. A Support Vector Machine (SVM) classifier evaluated on the Kaggle vocal dataset achieved 87% test accuracy with no overfitting, outperforming AdaBoost, Random Forest, KNN, XGBoost, and Decision Trees in terms of generalization. The 1D CNN applied to UCI spiral drawing data achieved 85% test accuracy, with overfitting behavior addressed through architectural regularization strategies including early stopping. A conceptual multimodal fusion architecture integrating both modalities is proposed as a direction for future experimental validation; it was not implemented or experimentally validated within the present study. The primary novelty of the framework resides in this explicit biomimetic grounding, which distinguishes it from existing performance-driven approaches. Results confirm that biologically grounded computational models constitute promising objective decision-support tools for early PD diagnosis. Full article

Given that stress is a significant risk factor for problematic social media use, understanding the underlying psychological mechanisms is essential. We introduce the Stress-Induced Digital Escapism (SIDE) framework, which posits that negative internal emotional responses to external stressors may increase reliance on maladaptive emotion regulation strategies that fail to alleviate distress. These processes may, in turn, strengthen escapism motives that lead to seeking emotional relief through compulsive social media use. Using structural equation modeling (N = 238), we examined three integrated psychological pathways—negative stress reactions, maladaptive emotion regulation strategies, and escapism motives—as sequential mediators linking external demands to problematic social media use. Consistent with the proposed framework, external demands showed significant indirect associations with problematic social media use through negative emotional responses, maladaptive interpersonal emotion regulation strategies (venting, reassurance-seeking), and escapism motives as sequential mediators. Sensitivity analysis supported the robustness of the serial mediation model over alternative models with reversed pathways. These findings support the SIDE framework as a unified account of the psychological mechanisms underlying stress-related problematic social media use. Full article

Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism in cross-border e-commerce rather than merely a reverse logistics function. Drawing on UTAUT2, perceived risk theory, and trust theory, we develop and test a research model using survey data from South Korean consumers with prior experience of digital local return services (LRS). Structural equation modeling (SEM) is used to test the proposed relationships, and artificial neural networks (ANN) are employed to capture nonlinear effects and compare the relative importance of key predictors. Qualitative interview evidence is further incorporated to enrich the interpretation of the findings. The results show that performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation significantly reduce perceived risk. Perceived risk, in turn, exerts a strong negative effect on purchase intention and weakens consumer trust. Additional ANN results indicate that hedonic motivation and facilitating conditions are particularly influential in lowering perceived risk, while perceived risk is more important than trust in predicting purchase intention. These findings show that digital return service design shapes consumer decisions primarily through risk reduction rather than trust enhancement alone. The study contributes to digital commerce research by explaining how return service design functions as a customer-facing platform assurance mechanism that improves conversion in cross-border online retailing. Full article

The clean and low-carbon transition of new-type power systems imposes increasingly stringent demands on green technology innovation among enterprises along the power industry chain. Identifying the drivers and potential remedies for green innovation bubble can offer China-originated solutions to the sustainable development of the global power sector. This paper focuses on Chinese power industry chain enterprises over the period 2016–2023. Drawing on the AMO framework, a three-dimensional analytical framework encompassing ability, motivation, and opportunity is developed. Double machine learning (DDML) is employed to perform benchmark regression and causal identification. Subsequently, gradient boosting trees (GBT) combined with SHAP interpretability analysis are applied to uncover nonlinear relationships and heterogeneous transmission pathways among key variables. The results indicate that energy-saving policies and green financial policies significantly inhibit the formation of the green innovation bubble in power industry chain enterprises. Specifically, these policies curb the green innovation bubble via three channels: an innovation incentive management mechanism, a peer imitation and convergence mechanism, and an industrial chain technology spillover mechanism. Upstream enterprises exhibit greater sensitivity to direct regulatory measures and backward technology spillovers from energy-saving and green finance policies, whereas midstream enterprises are more reliant on peer carbon emission pressure. The findings are validated through cross-verification among DDML, mechanism analysis, and interpretable analysis. The results provide empirical evidence and policy implications for optimizing energy-saving and green finance policies and for precisely deflating the green innovation bubble. Full article

The rapid expansion of artificial intelligence and cloud computing is straining terrestrial data center infrastructure, motivating exploration of space-based data centers (SBDCs) as a scalable and energy-efficient alternative. While orbital platforms offer unique advantages, including continuous solar energy, radiative cooling, and global coverage, their practical deployment is constrained by unresolved reliability challenges across the mission lifecycle. This study presents a lifecycle-oriented reliability and risk assessment for SBDCs spanning launch, orbital operation, maintenance, and end-of-life phases, using a structured systems-level analysis of failure modes and operational dependencies. This paper focuses on compute-centric SBDC architectures, treating storage solely as a supporting resource. We identify and classify space-environment-specific risks, including launch-induced mechanical stress, radiation-driven degradation, thermal extremes, and single points of failure in power and communication subsystems. By integrating engineering constraints with economic considerations, we develop a unified risk-chain framework that shows how reliability limitations propagate from component design to system cost and operational viability. The analysis reveals a critical trade-off: achieving terrestrial-grade reliability in orbit requires substantial redundancy and radiation hardening, increasing mass and cost and reducing economic feasibility, whereas lower-reliability designs introduce operational and financial risks that challenge sustainability. These findings establish reliability as the central determinant of SBDC viability, providing an applied foundation for fault-tolerant, modular, and lifecycle-aware design strategies essential for transitioning orbital cloud infrastructure from concept to scalable reality. Full article

The corrosion behavior and time-dependent mechanism of 22MnB5 steel featuring a thinned Al-Si coating (60 g/m²) were systematically investigated in a chloride ion wet–dry cyclic environment, motivated by the demand for thinning and toughening development of aluminum-silicon coatings. A periodic immersion accelerated corrosion test using 3.5% NaCl solution was conducted, together with macro/microscopic morphology observation (SEM/EDS), phase analysis (XRD, FTIR), and electrochemical measurements (polarization curves, EIS). The Al-Si coated steel was studied over corrosion periods of 1, 8, 10, and 20 days to elucidate its corrosion behavior, interfacial evolution, and failure mechanism. The results indicated that the corrosion process exhibited a three-stage evolution: stable protection, rapid failure, and dynamic equilibrium. At the initial stage (1 day), a dense Al₂O₃ passive film formed on the coating surface, providing excellent substrate protection, with a corrosion current density of only 1.77 µA/cm² and a maximum charge-transfer resistance (R₂) of 652 Ω·cm². In the middle stage (8 days), Cl⁻ permeated through the cracked film, triggering selective dissolution of Al, while Si was enriched in situ to form a porous residual layer; the corrosion current density (I_corr) sharply increased to 13.25 µA/cm², and R₂ dropped to its minimum of 156.6 Ω·cm². Corrosion products at this stage were mainly Al₂O₃ and SiO₂, accompanied by small amounts of iron oxyhydroxides and hydroxides, and local coating failure began to appear. During the later stage (10–20 days), the corrosion products evolved into γ-FeOOH, α-FeOOH, and Fe₂O₃, which, together with an amorphous SiO₂ gel network enriched at the interface, formed a dual-layer composite rust layer. R2 consequently recovered from 156.6 Ω·cm² at 8 days to 424 Ω·cm² at 20 days, indicating a reduced corrosion rate and entry into a stable inhibition stage. The critical failure mechanism is that Cl⁻ preferentially penetrates the surface of the Al₂O₃ passive film, disrupting the metastable state of the coating and thereby creating pathways for corrosive media intrusion. The findings of this study can provide technical support for the safe application of such as-received coatings in non-load-bearing components with heat and corrosion resistance requirements. Full article

The digital transformation of agriculture is a critical pathway for promoting sustainable rural livelihoods in transition economies. This study examines the determinants of mobile agricultural application adoption among 327 smallholder farmers in Tajikistan, integrating the Technology Acceptance Model (TAM) with New Institutional Economics (NIE). We develop a formative Institutional Support Index (ISI) comprising cooperative membership, extension access, and regulatory familiarity. Using binary logistic regression and multi-model robustness checks (probit, LPM, IV-probit), we identify three core findings. First, perceived usefulness (PU) is the dominant positive driver (AME = +12.2 pp; p < 0.001). Second, perceived risk (PR) constitutes a significant psychological barrier (AME = −7.6 pp; p < 0.01), while perceived trust (PT) partially offsets this deterrent effect (AME = +6.4 pp; p < 0.01). Third, we document a “land ownership puzzle,” where land ownership exerts a robust negative conditional effect on adoption (AME = −14.2 pp; p < 0.01). This finding suggests a property-rights-based “conservatism bias” unique to transition contexts, where asset-protection motives increase the adoption threshold for landowners compared to tenants. Exploratory analysis indicates a tentative “Sensitization Effect,” in which institutional support may increase risk awareness in the absence of financial risk-sharing mechanisms. These results broaden the applicability of the TAM to post-Soviet transition environments and suggest that digital extension initiatives must incorporate risk-management tools to effectively assist smallholder farmers. Full article