Search Results (23,283)

Electrochemical energy storage systems are increasingly utilized across a wide range of applications, from small-scale consumer electronics to large-scale utility systems providing grid services. Among these, lithium-ion batteries have emerged as a preferred solution because of their high efficiency and power density. However, accurately modeling the behavior of Li-ion cells remains a critical and complex task. It is particularly important to determine the open-circuit voltage (OCV), which is an essential component of most battery models. This paper presents the results of an experimental comparison of three common methods for measuring and estimating the OCV of lithium-ion cells with nickel–manganese–cobalt cathodes. Each method is described in detail, with particular attention given to the testing procedures and influence of the experimental parameters on the accuracy of the resulting OCV curves. The outcomes are then analyzed and compared to highlight the strengths, limitations, and practical considerations associated with each approach. The findings of this work will assist researchers and practitioners in selecting the most appropriate OCV measurement techniques for various applications, especially where time constraints or experimental limitations must be considered. Full article

As population aging accelerates, the mounting burden on informal family caregivers in areas lacking formal care systems threatens the sustainability of elder care. This study aims at evaluating how the rural living environment and external connectivity jointly alleviate caregiver burden and exploring whether regional accessibility serves as a substitute for local infrastructure deficits. Guided by Ecological Systems Theory, we analyzed a cross-sectional dataset of 327 matched caregiver-recipient dyads from rural China using multivariate regression and mediation models. Results indicate that a favorable local environment reduces burden both directly and indirectly through improved recipient health. Crucially, county-level accessibility moderates this relationship via a substitution effect, where the marginal relief from local environmental improvements is most potent in isolated areas but diminishes where external access is convenient. Dimension-specific analyses show that developmental and physical strains are particularly sensitive to these factors. We conclude that sustaining informal care requires a dual-pathway strategy: prioritizing local “soft” assets like community safety and cultural activities while enhancing regional connectivity to service hubs. Ultimately, this research provides empirical evidence and a theoretical framework for enhancing rural informal care sustainability through environmental optimization, thereby advancing Sustainable Development Goals regarding health, reduced inequalities, and sustainable communities. Full article

With the increasing prominence of sustainable consumption and the rising influence of Generation Z in the fashion market, secondhand fashion e-commerce platforms have become essential carriers of green fashion. Although AI-assisted recommendation mechanisms are widely embedded in these platforms, their psychological and behavioral effects on users’ continuous use and social engagement remain insufficiently examined. To address this gap, this study incorporates the Stimulus–Organism–Response (SOR) framework to investigate the psychological reaction pathways and behavioral intentions of Generation Z users within Human-AI Collaboration-enabled green e-commerce environments. Three AI-driven service stimuli—Human-AI Collaborative Recommendation Perception, AI Interaction Transparency, and Perceived Personalization—were conceptualized as stimulus variables; Psychological Immersion, Emotional Triggering, Cognitive Engagement, and Platform Trust were modeled as organism variables; and Continuous Use Intention and Social Sharing Intention served as behavioral response variables. Based on 498 valid samples analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results demonstrate strong empirical support for all proposed hypotheses. Specifically, AI-driven stimuli significantly and positively influence psychological responses, which subsequently strengthen users’ continuous usage and social sharing intentions. This research provides theoretical insights for developing Human-AI Collaboration-enabled service systems that balance efficiency and emotional resonance on green e-commerce platforms, and offers practical implications for promoting sustainable fashion values among younger consumers. Full article

Existing research highlights that Lesbian, Gay, Bisexual, Transgender and Queer (LGBTQ+) teachers are often exposed to additional stressors in schools which adversely affect their mental health. Some mitigate the effects of these stressors by separating their personal and professional identities while others choose to integrate their identities so that they can be authentic, advance social justice in school contexts or be visible and vocal role models. Less is known about the experiences of pre-service teachers who are undertaking teacher preparation programmes. This systematic literature review presents the results of 20 published papers which represent the global experiences of both pre-service teachers and serving teachers. The findings highlight identity management, experiences of discrimination, agency and lack of confidence of teacher educators. Two new frameworks are presented that lay the foundations for embedding LGBTQ+ inclusion and proposed mandatory elements of curricula for initial teacher training. This systematic literature review has been informed by the following research questions RQ1. What are the experiences of LGBTQ+ pre-service teachers? RQ2. How do LGBTQ+ pre-service teachers negotiate their identities? RQ3. How do LGBTQ+ pre-service teachers disrupt hetero/cis-normative cultures in schools? RQ4: How well does the teacher education programme prepare pre-service teachers for teaching LGBTQ+ inclusive education? Full article

End–edge–cloud collaboration enables significant improvements in system resource utilization by integrating heterogeneous resources while ensuring application-level quality of service (QoS). However, achieving efficient collaborative decision-making in such architectures poses critical challenges within dynamic and complex computing network environments, including dynamic resource allocation, incentive alignment between cloud and edge entities, and multi-objective optimization. To address these issues, this paper proposes a dynamic resource optimization framework for complex cloud–edge collaborative networks, decomposing the problem into two hierarchical decision schemes: cloud-level coordination and edge-side coordination, thereby achieving adaptive resource orchestration across the End–edge–cloud continuum. Furthermore, leveraging differential game theory, we model the dynamic resource allocation and cooperation incentives between cloud and edge nodes, and derive a feedback Nash equilibrium to maximize the overall system utility, effectively resolving the inherent conflicts of interest in cloud–edge collaboration. Additionally, we formulate a joint optimization model for energy consumption and latency, and propose an Improved Discrete Artificial Hummingbird Algorithm (IDAHA) to achieve an optimal trade-off between these competing objectives, addressing the challenge of multi-objective coordination from the user perspective. Extensive simulation results demonstrate that the proposed methods exhibit superior performance in multi-objective optimization, incentive alignment, and dynamic resource decision-making, significantly enhancing the adaptability and collaborative efficiency of complex cloud–edge networks. Full article

Background: Neurogenic bowel dysfunction (NBD) is a major chronic sequela of spinal cord injury (SCI) with substantial implications for rehabilitation and long-term management. However, population-level evidence describing how gastrointestinal (GI) diagnostic codes are used following SCI, particularly within administrative healthcare systems, remains limited. Methods: We conducted a nationwide retrospective cohort study using administrative claims data from the Korean National Health Insurance Service (NHIS). A total of 584,266 adults with trauma-related SCI encounters between 2009 and 2019 were identified. GI diagnostic codes—paralytic ileus (K56), irritable bowel syndrome (K58), and functional bowel disorders (K59)—were evaluated as administrative proxies for bowel dysfunction. Demographic characteristics, disability status, regional factors, and health behaviors were analyzed using multivariable logistic regression. Results: GI diagnostic codes were frequently recorded after SCI, most commonly irritable bowel syndrome (approximately 30%) and functional bowel disorders (approximately 37%), whereas paralytic ileus was uncommon. Greater disability severity, female sex, older age, and rural residence were consistently associated with higher odds of GI diagnostic coding. Physical activity showed robust inverse associations across all models. Inverse associations observed with smoking and alcohol consumption were interpreted as reflecting residual confounding or health-related selection, rather than biological protective effects. Conclusions: Patterns of GI diagnostic coding after SCI likely reflect the clinical burden and management needs of neurogenic bowel dysfunction within healthcare systems, rather than the development of new gastrointestinal diseases. These findings underscore the importance of individualized bowel management, incorporation of structured physical activity into rehabilitation programs, and equitable access to SCI rehabilitation services, particularly for individuals with greater disability or those living in rural areas. Full article

Drastic cropland expansion and its internal structural changes have had an obvious impact on agricultural landscapes and ecosystem services. However, a prolonged investigation of this effect is still lacking in China’s grain-producing bases, such as Sanjiang Plain. To address this issue, half a century of study on the ‘land trajectory migration–landscape evolution–ecological effect,’ covering the period 1970–2020, was elucidated using the synergistic methodology of spatial analysis technology, the reclamation rate algorithm, the landscape indicator, and the newly established ecosystem service improvement model. Satellite observation results indicate that the cropland area exhibited a substantial expansion trend from 23,672.69 km² to 42,856.17 km² from 1970 to 2020, representing a net change of +19,183.48 km² and a huge growth rate of 81.04%, which led to an obvious improvement in the level of agricultural cultivation. Concurrently, the internal structure of the cropland underwent dramatic restructuring, with rice fields increasing from 6.46% to 53.54%, while upland fields decreased from 93.54% to 46.46%. In different regions, spatially heterogeneous improvements of 2.64–52.47% in agricultural cultivation levels across all cities were observed. From 1970 to 2020, the tracked cropland center of gravity trajectories exhibited a distinct biphasic pattern, initially shifting westward and then followed by a southward transition, accumulating a displacement of 19.39 km². As for the evolved agricultural landscapes, their integrity has improved (SHDI = −0.08%), accompanied by increased connectivity (CON = +8.82%) and patch edge integrity (LSI = −15.71%) but also by reduced fragmentation (PD = −48.14%). Another important discovery was that the evaluated ecosystem services continuously decreased from 2337.84 × 10⁸ CNY in 1970 to 1654.01 × 10⁸ CNY in 2020, a net loss of −683.84 × 10⁸ CNY and a huge loss rate of 33.65%, accompanied by a center–periphery gradient pattern whereby degradation propagated from the low-value central croplands to the high-value surrounding natural covers. These discoveries will play a significant role in guiding farmland structure reformation, landscape optimization, and ecosystem service improvement. Full article

The current debate on digital education is at a crossroads between the need for technological innovation and the growing concern about the impact of passive screen use. In this context, identifying sustainable pedagogical models that integrate Information and Communication Technologies (ICT) in a meaningful and inclusive way is an urgent need. This article presents a case study of the Amara Berri System (ABS), aiming to analyze how inclusive and sustainable digital innovation is operationalized within the system and whether teachers’ length of service is associated with the implementation and perceived impact of inclusive ICT practices. The investigation is based on a mixed-methods sequential design. A questionnaire was administered to a sample of 292 teachers to collect data on their practices and perceptions. Subsequently, a focus group with eight teachers was conducted to further explore the meaning of their practices. Quantitative results show that the implementation and positive evaluation of inclusive ICT practices correlate significantly with teachers’ seniority within the system, which suggests that the model is formative in itself. Qualitative analysis shows that ICTs are not an end in themselves within the ABS, but an empowering tool for the students. The “Audiovisual Media Room”, managed by students, functions as a space for social and creative production that gives technology a pedagogical purpose. The study concludes that the sustainability of digital innovation requires coherence with the pedagogical project. Findings offer valuable implications for the design of teacher training contexts that foster the integration of technology within a framework of truly inclusive education. Full article

Large language models (LLMs) show limited capability in processing low-resource historical languages due to insufficient training data and domain-specific linguistic structures. Korean Literary Sinitic (KLS), the principal written medium of the Joseon dynasty, remains particularly under-resourced despite its lexical overlap with modern Korean and shared script with classical Chinese. To enable systematic evaluation in this domain, we introduce KLSBench, a comprehensive benchmark for assessing LLM performance on KLS. KLSBench contains 7871 instances sourced from Joseon dynasty civil service examination archives and parallel corpora of the Four Books, and encompasses five task categories: classification, retrieval, punctuation restoration, natural language inference, and translation. Our evaluation suggests KLSBench could work as an effective diagnostic tool that distinguishes lexical recall from deeper linguistic comprehension in low-resource historical languages. Beyond establishing evaluation baselines, KLSBench provides practical frameworks for deploying LLM-based tools in digital humanities contexts, including automated annotation systems and intelligent search interfaces for classical text repositories. Full article

Empirical approaches alone have significant limitations for accurate estimation of the fracture toughness of welds in gas line pipes being considered for repurposing to hydrogen service. These problems arise because most samples machined from ex-service welds contain a range of microstructures. The different microstructural zones have different properties and even when compact tension samples with side grooves are utilized, it is unlikely that plane strain conditions are achieved during laboratory testing. Thus, the measured toughness may not be directly relevant to assessing in-service performance. The present research has been undertaken as part of an integrated series of projects seeking to define a robust protocol for assessing the damage tolerance of piping used for the transmission of hydrogen, especially when considering repurposing existing infrastructure. The key work described in this paper involved establishing heat treatments which produced microstructures relevant to the constituents found in ex-service welds of X46 type steel. Following comprehensive microstructural characterization, these heat treatments were applied to steel sections which allowed for the fabrication of standard compact tension specimens, which were subsequently tested in hydrogen to measure fracture toughness. The results obtained showed that the fracture behavior varied for different microstructures. To identify the influence that hydrogen gas has on the performance of pipeline steels, it is important to assess microstructures relevant to the welds present, as testing only on base metal may not provide conservative information. However, the results from well-planned and carefully executed programs can be used to identify the relative performance in hydrogen. The data can also be used as critical input to models which form part of an integrated approach to structural integrity assessment. Full article

Although pre-service teachers play a crucial role in promoting safe mobility among children, there are no validated instruments to assess their civic competencies, knowledge, and behaviors in road safety education. Existing questionnaires primarily target the general population or college students, and thus it remains unclear whether future teachers are adequately prepared to deliver road safety education. This study aims to design and validate a tool to assess pre-service teachers’ behavior in situations related to traffic safety and their knowledge of road safety education.. The designed tool is a questionnaire made up of 32 items distributed across five dimensions. The questionnaire’s content was validated through the judgment of eight experts, who ensured the relevance and adequacy of its items. The confirmatory factor analysis of data obtained from a pilot sample was used to examine the questionnaire’s structure, and reliability was assessed using Cronbach’s alpha coefficient. After analyzing the responses of 388 participants, the results suggest that the questionnaire’s overall structure is adequate and satisfactory reliability coefficients were obtained. The confirmatory factor analysis supported the proposed four-factor structure, indicating good model fit. These findings suggest that a valid and reliable diagnostic tool can identify the road safety training needs of future teachers and inform curriculum design and targeted educational interventions to enhance road safety competencies in schools. Full article

Wood flooring manufacturers face complex challenges in dynamically allocating resources across multi-channel markets, characterized by channel conflicts, demand uncertainty, and long-term cumulative effects of decisions. Traditional static optimization or myopic approaches struggle to address these intertwined factors, particularly when critical market states like brand reputation and customer base cannot be precisely observed. This paper establishes a systematic and theoretically grounded online decision framework to tackle this problem. We first model the problem as a Partially Observable Stochastic Dynamic Game. The core innovation lies in introducing an unobservable market position vector as the central system state, whose evolution is jointly influenced by firm investments, inter-channel competition, and macroeconomic randomness. The model further captures production lead times, physical inventory dynamics, and saturation/cross-channel effects of marketing investments, constructing a high-fidelity dynamic system. To solve this complex model, we propose a hierarchical online learning and control algorithm named L-BAP (Lyapunov-based Bayesian Approximate Planning), which innovatively integrates three core modules. It employs particle filters for Bayesian inference to nonparametrically estimate latent market states online. Simultaneously, the algorithm constructs a Lyapunov optimization framework that transforms long-term discounted reward objectives into tractable single-period optimization problems through virtual debt queues, while ensuring stability of physical systems like inventory. Finally, the algorithm embeds a game-theoretic module to predict and respond to rational strategic reactions from each channel. We provide theoretical performance analysis, rigorously proving the mean-square boundedness of system queues and deriving the performance gap between long-term rewards and optimal policies under complete information. This bound clearly quantifies the trade-off between estimation accuracy (determined by particle count) and optimization parameters. Extensive simulations demonstrate that our L-BAP algorithm significantly outperforms several strong baselines—including myopic learning and decentralized reinforcement learning methods—across multiple dimensions: long-term profitability, inventory risk control, and customer service levels. Full article

This work studies the formation control problem of general linear multi-agent systems (MASs) under hybrid attacks that include man-in-the-middle attacks (MITM) and denial-of-service attacks (DoS). First, an improved Diffie–Hellman key exchange (DHKE)-based encryption–decryption mechanism is proposed. This mechanism combines the challenge–response mechanism and hash function, which can achieve identity authentication, detect MITM attacks and ensure the confidentiality and integrity of information. Second, considering that DoS attacks on different channels are independent, a division model for distributed DoS attacks is established, which can classify attacks into different patterns. Third, an edge-based event-triggered (ET) formation control scheme is proposed. This control method only relies on the information of neighbor agents, which not only saves communication resources but also resists distributed DoS attacks. Finally, sufficient conditions for the implementation of formation control for MASs under hybrid attacks are provided, and the effectiveness and advantages of the proposed strategy are verified by simulation. Full article

Ants act as keystone species in terrestrial ecosystems, providing important ecosystem services. The large-scale production and application of GO constitute a predominant contributor to its inevitable environmental dispersion. Most GO toxicity studies have focused on plants, animals, and microorganisms, with limited research on ground-dwelling ants. In the study, we used Camponotus japonicus as a model to investigate the toxic effects of GO on ants by integrating physiological characteristics, gut microbiota and transcriptome profiling. Results showed that GO exposure induced mitochondrial dysfunction, as evidenced by mitochondrial ROS accumulation and elevated mitochondrial membrane permeability. Physiological assessments revealed that GO exposure induced oxidative stress. Specifically, GO treatment significantly suppressed superoxide dismutase (SOD) and catalase (CAT) activities, while enhancing peroxidase (POD) and carboxylesterase (CarE) activities and increasing the levels of malondialdehyde (MDA) and trehalose. Gut microbiota analyses showed that GO remarkably reduced the relative abundance of beneficial bacterial symbionts (e.g., Candidatus Blochmannia) and destabilized the whole community structure. Furthermore, transcriptome profiling revealed 680 differentially expressed genes (DEGs) in the ants after GO exposure, most of which were significantly enriched in pathways associated with oxidative phosphorylation. This study suggests that GO may compromise ant-mediated ecosystem function and provides a reference for understanding the environmental risks of GO. Our findings also offer new insights for protecting the ecosystem services of ants. Full article

This paper presents a comprehensive techno-economic assessment of a community battery energy storage system (BESS) participating concurrently in energy arbitrage and frequency control ancillary services (FCAS) markets, while also providing customer savings through coordinated demand management. The proposed framework employs a mixed-integer linear programming (MILP) model to co-optimize the charging, discharging, and reserve scheduling of the battery under dynamic market conditions. The model explicitly incorporates key operational and economic factors such as round-trip efficiency, degradation cost, market-participation constraints, and revenue from multiple value streams. By formulating the optimization problem within this MILP structure, both the operational feasibility and the economic profitability of the system are evaluated over annual market cycles. Simulation results demonstrate that integrating FCAS participation with conventional energy arbitrage substantially enhances total revenue potential and improves asset utilization, compared with single-service operation. Furthermore, the coordinated management of community demand contributes to additional cost savings and supports local grid reliability. The findings highlight the critical role of co-optimized control and multi-market participation strategies in improving the financial viability and grid-support capabilities of community-scale BESS deployments. Full article