Search Results (10,306)

As climate governance policies are steadily rolled out and scrutiny over corporate social responsibility intensifies, corporate ESG decoupling undermines the efficacy of climate governance and resource allocation. Using data on Chinese listed firms from 2012 to 2022, this study exploits the China Pilot Climate Adaptation City (CPCAC) program in 2017 as a quasi-natural experiment and employs a difference-in-differences (DID) approach to identify the impact of the CPCAC on corporate ESG decoupling. The results show that the CPCAC significantly reduces firms’ ESG decoupling, with the mitigating effect being particularly pronounced in the environmental responsibility dimension. Moreover, CPCAC alleviates corporate ESG decoupling by reducing corporate agency costs. Heterogeneity results show exerting a stronger influence on firms in regions with strong Confucian culture, firms with higher managerial myopia, non-politically connected firms and highly digitalized firms. The findings enrich the literature on corporate ESG behavior and its interaction with the institutional environment, and offer valuable insights for advancing climate adaptation governance and improving ESG regulatory frameworks. Full article

Computational thinking (CT) has become a cross-curriculum priority in many educational jurisdictions, yet a growing body of research reports uneven integration in initial teacher education (ITE), limited preservice teacher confidence, and persistent misconceptions that equate CT with coding. Concurrently, generative artificial intelligence (GenAI) has rapidly entered university programmes, offering new possibilities for modelling problem-solving, generating multiple representations, and supporting iterative design. However, while constructs such as self-efficacy, cognitive load, and affect are well established in educational psychology, their specific application to the intersection of CT and GenAI in teacher education remains under-theorised: existing research has not systematically examined how these psychological dimensions interact when preservice teachers learn CT through GenAI-mediated tasks. This thematic literature review synthesises 54 sources across three intersecting domains: CT frameworks and their pedagogical implications, CT integration in preservice teacher preparation, and GenAI in teacher education and learning design. Drawing on Bandura’s social cognitive theory, cognitive load theory, and research on technology-related affect, the review foregrounds the affective, cognitive, and cultural dimensions of preservice teachers’ engagement with CT and GenAI. The review proposes the GenAI-Enabled Computational Thinking for Preservice Teachers (GECT-P) model, which integrates CT dimensions with GenAI-supported learning cycles, psychological mediators, and teacher education outcomes. The model positions prompting as an epistemic and pedagogical practice that can make CT visible, supports cycles of decomposition, abstraction, pattern recognition, and algorithmic design, and embeds critical AI literacy, ethics, affective scaffolding, and classroom enactment. Design principles and practical pathways are offered for teacher educators seeking to prepare graduates who can develop CT with and beyond GenAI across diverse curriculum areas. Full article

Background: Undernutrition among children under five years remains a major public health challenge, particularly in low- and middle-income countries and rural communities where poverty, food insecurity, and limited access to health services persist. Maternal and caregiver perceptions play a critical role in shaping feeding practices and health-seeking behaviours that influence child nutritional outcomes. Objective: This study explored mothers’ and caregivers’ perceptions of factors contributing to undernutrition among children under five years in a rural community of Ngqeleni, Eastern Cape, South Africa. Methods: A qualitative descriptive study was conducted at a primary healthcare clinic in the Ngqeleni sub-district. Purposive sampling was used to recruit mothers and caregivers of children under five years. Data were collected through seven in-depth interviews and three focus group discussions involving a total of 25 participants. Interviews were conducted using a semi-structured guide and analyzed thematically. Results: Five major themes emerged: caregivers’ perceptions of nutrition, household food insecurity and unemployment, limited dietary diversity, culturally influenced feeding practices, and gaps in practical nutrition knowledge. Caregivers demonstrated concern for child nutrition but described constrained feeding choices shaped by poverty, reliance on social grants, environmental challenges, and limited access to diverse foods. Environmental challenges such as drought and lack of piped water further limited food production. Limited nutrition knowledge and reliance on informal information sources contributed to suboptimal feeding practices. Conclusions: Undernutrition in this rural setting is shaped by a complex interaction of economic hardship, environmental constraints, and limited caregiver knowledge. Community-based nutrition education, strengthened primary healthcare counselling, and multisectoral interventions addressing poverty, water access, and food security are essential to improve child nutrition outcomes. Full article

Regular social, economic and agricultural interactions occurred between the Horn of Africa and Southern Arabian Peninsula for millennia, raising questions about potential geo-culinary exchanges, including of the little-studied fermented flatbreads produced in these areas. A comparative analysis of Somali laxoox/canjeero, Ethiopian injera, Sudanese kisra and Yemeni/Saudi lahoh was conducted by combining a literature review and consultations with 17 local experts, then processing the data in a hierarchical cluster analysis to quantify “biocultural” diversity. In an interdisciplinary approach, technical aspects (bread appearance, ingredients, and production stages) and cultural characteristics (consumption patterns and social function) were considered to identify key descriptors of the breads. A dendrogram generated through cluster analysis of a binary (0/1) matrix, structured with the key descriptors, showed that each bread has a distinct biocultural identity, and enabled the quantification of their similarities. Somali laxoox/canjeero and Yemeni/Saudi lahoh had a 64% similarity to each other (Jaccard index); each had a 53% similarity to Ethiopian injera; while all of them were 41% similar to Sudanese kisra. Hierarchical cluster analysis, applied for the first time to flatbreads, contributes to their comprehensive characterization and comparison in this unique geographic region and lays the foundations for policies to protect their identity and quality. Full article

Against the backdrop of global sustainable development and ecological civilization construction, tourism ecological security at cultural landscape heritage sites faces both opportunities and challenges. This study constructs a cultural landscape heritage tourism ecological security (CLHTES) evaluation system based on the Driver–Pressure–State–Impact–Response (DPSIR) framework. It dynamically assesses CLHTES in the Yangtze River Delta Integrated Demonstration Zone (YRDIDZ) from 2014 to 2023 using the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and linear stretching transformation, identifies obstacle factors with the obstacle degree model, and predicts CLHTES trends for 2024–2030 using a radial basis function (RBF) neural network. Results show that: (1) The CLHTES index in the YRDIDZ presented a three-stage fluctuating upward trend during 2014–2023, with medium-clustered security levels and divergent evolution across the DPSIR criteria layers; (2) CLHTES obstacles feature a multi-level differentiated structure, with rising barriers in D and P layers, the R layer as the future core obstacle, and high-frequency barriers concentrated in cultural and social indicators; (3) Under the assumption of structural continuity in current trajectories, the conditional trend projection suggests that the CLHTES index of the YRDIDZ may sustain a general upward tendency during 2024–2030, with a possibility of approaching Level Ⅶ after 2028; however, these projections should be interpreted as exploratory and scenario-like rather than as robust forecasts, given the short annual series and the absence of exogenous disturbance variables. This study explores tourism-ecology interactions from a social-ecological complex system perspective, supporting synergistic tourism development and ecological protection of cultural landscape heritage. Full article

Emerging evidence indicates that non-coding RNAs (ncRNAs) play important regulatory roles in honeybee social behavior and development. However, the regulatory roles of ncRNAs in honeybees remain largely elusive. To systematically identify ncRNAs associated with queen-regulated ovary activation, we conducted whole-transcriptome sequencing on the heads of Apis mellifera workers from queenright and queenless colonies. Subsequent bioinformatics analyses were conducted to profile differentially expressed (DE) RNAs and construct potential regulatory networks. High-quality sequencing data provided a foundation for subsequent analyses. This transcriptome data yielded 3968 lncRNA transcripts, comprising 3146 known and 822 novel candidates, all of which exhibited typical structural features of lncRNAs. Comparative expression analyses revealed that 246 lncRNAs, 1439 mRNAs, and 10 miRNAs were differentially expressed. Comprehensive functional analyses indicated that the identified DElncRNAs potentially regulate sensory perception-related target mRNAs via cis-regulation, and coordinate metabolic and proteostatic reprogramming via trans-regulation to support the transition to reproductive activation in workers. Furthermore, a competing endogenous RNA network was constructed which integrated 74 DElncRNAs, 5 DEmiRNAs, and 36 DEmRNAs to predict their potential post-transcriptional interactions. Our findings highlight a comprehensive analysis of ncRNAs and mRNAs in worker heads, providing a foundation for functional validation of their roles in honeybee ovary development. Full article

Children with Autism Spectrum Disorder (ASD) frequently exhibit marked impairments in nonverbal communication, particularly in eye contact, which serves as a foundational element for social interaction and relational development. This study evaluated the effectiveness of an early intervention program utilizing interactive games supported by Augmented Reality (AR) technology to enhance eye contact behaviors, specifically initiation and maintenance, in children with autism. Using a multiple baseline across participants single-case experimental design, four boys (aged 5–7 years) diagnosed with ASD participated in an 8-week intervention at a specialized center in Saudi Arabia. The intervention featured tablet-based, gamified AR tasks incorporating real-time visual feedback, graduated difficulty levels, and reinforcement mechanisms designed to elicit social gaze and sustained eye contact. Eye contact duration and frequency were measured during structured social interactions via systematic direct observation. The results demonstrated significant improvements across all participants, with the mean duration of eye contact increasing from a baseline of 2.0 s to 5.8 s post-intervention. Visual analysis revealed robust treatment effects, further supported by substantial Tau-U effect sizes (range = 0.89–0.96; M = 0.93). Follow-up data collected three weeks post-intervention confirmed the maintenance of gains for three of the four participants. These findings suggest that AR-based interventions provide an effective and culturally responsive approach for enhancing specific nonverbal communication behaviors among children with autism in Middle Eastern contexts. Implications for clinical practice and directions for future research are discussed. Full article

The accelerated aging of the population in vulnerable urban contexts poses significant challenges for architecture, particularly with regard to the quality of life of older adults. Within this framework, the present study aimed to analyze the association between sensory architecture and the quality of life of older adults and to translate this empirical evidence into context-informed design criteria for the development of a comprehensive center for older adults. The study adopted a quantitative approach with a non-experimental, cross-sectional, and correlational design. A structured questionnaire on sensory architecture and quality of life was administered to family members and caregivers acting as proxy respondents, demonstrating high internal consistency (Cronbach’s $\mathit{\alpha }>0.90$). Given the ordinal nature of the data, inferential analysis was conducted using Spearman’s rho coefficient. Within the analyzed dataset, the results revealed a statistically significant and strong association between sensory architecture and the quality of life of older adults ($\rho$ > 0.80). At the dimensional level, visual and tactile stimuli exhibited the highest associations, followed by the social relationships dimension, while therapeutic environments showed a moderate association, allowing the identification of an empirical hierarchy among the analyzed dimensions within this dataset. These findings support the interpretation of sensory architecture as a construct statistically associated with indicators of quality of life, from a non-causal perspective. Based on this hierarchy, the results were articulated into an evidence-based architectural structure, serving as analytical input to inform context-specific criteria for spatial organization, materiality, comfort, orientation, and social interaction derived from the observed statistical associations. The study contributes a methodological approach that systematically connects correlational quantitative findings with architectural design considerations, particularly in urban contexts characterized by limited specialized infrastructure. However, a key limitation is the use of proxy respondents (family members and caregivers), which should be considered when interpreting the results. Full article

Against the backdrop of the accelerated development of the low-altitude economy and the structural transformation of modern logistics systems, systematically elucidating the key driving factors and their interaction structure is paramount for optimizing operational efficiency, promoting sustainable industry growth, and enhancing policy effectiveness. Integrating an extensive literature review with expert consultations, this study constructs a comprehensive indicator system of influencing factors for the coordinated development of the low-altitude economy and sustainable modern logistics. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to characterize the causal relationships and influence directions among the factors. Empowered by these findings, an Analytic Network Process (ANP) model is established to calculate refined weights, forming a hybrid DEMATEL–ANP analytical framework. The results indicate that technological factors and institutional factors constitute the primary driving layer of the system. Specifically, System Integration and Operational Technology, Flight Control and Scheduling Capability, as well as the Standardisation of Airspace Management and the Completeness of the Regulatory and Standards Framework, exert pivotal influences on the systemic evolution. Social factors and infrastructure factors primarily function as the outcome and feedback layers, with their effectiveness contingent upon the maturity of the core driving elements. Further hybrid weight analysis demonstrates that the ranking of key influencing factors exhibits high stability and robustness. The coordinated development process presents a progressive transmission characteristic from “technology–institution” to “market–application” providing targeted practical guidance for promoting the sustainable and high-quality synergy between the low-altitude economy and modern logistics. Full article

Background: Outdoor time in early childhood education and care (ECEC) settings provides important opportunities for children’s physical activity. Evidence is limited on whether different organizational outdoor conditions influence not only activity intensity but also the contextual characteristics of children’s movement. Methods: An observational study was conducted using the Observational System for Recording Physical Activity in Children—Preschool Version (OSRAC-P). The study was conducted in two public ECEC centers. Not all children were observed across all three conditions due to the field-based design. A total of 7440 observation intervals were analyzed from preschool children across three outdoor conditions (structured educator-led physical activity, outdoor free play, and outdoor free play with additional portable equipment) using a momentary time-sampling protocol (10 s observation + 50 s recording), resulting in one interval per minute. Physical activity intensity, activity type, equipment use, and social context were coded. Contextual differences were analyzed using chi-square tests with standardized residuals, and activity intensity using linear mixed-effects models. Results: No significant differences were found between outdoor conditions in physical activity intensity, sedentary behavior, and moderate-to-vigorous physical activity (all p > 0.05). About one-third of the variance in activity intensity was attributable to individual differences between children (ICC ≈ 33%). Differences were observed in contextual characteristics. Structured activity involved more locomotor activities and greater adult involvement, with 49.4% of intervals occurring in groups with an educator present. Free play with portable equipment showed more manipulative activities, greater equipment use, and mostly peer interactions without adult presence (55.5%), while free play without additional equipment involved more stationary behavior and activities without equipment (46.9%). Conclusions: Although physical activity intensity did not differ across conditions, the structure, material context, and social organization of children’s activity varied, highlighting the practical importance of intentionally combining different outdoor activity formats to support diverse movement patterns in ECEC settings. Full article

Social wasps are frequently associated with fruit injuries in agroecosystems, but the diversity of species involved and the ecological context of these interactions remain poorly synthesized in Brazil. This study aimed to compile and analyze records of social wasp interactions with fruits in Brazil, combining opportunistic field observations, iNaturalist records, and published studies. In total, 19 field observations, 87 iNaturalist records, and 11 published studies were incorporated into the dataset, resulting in 2443 records involving 51 social wasp species in 10 genera and 36 plant species. Most records involved fruits still attached to the plant (1853; 75.8%), whereas 590 records (24.2%) were associated with fallen fruits. Large-bodied wasps were disproportionately associated with fruits on the plant, while small- and medium-sized species were more frequent on fallen fruits, and this association was significant (χ² = 554.71; p < 0.001). Records also varied significantly throughout the year (χ² = 5693.28; p < 0.001), with peaks in February, March, and July. The interactions were strongly concentrated in a few genera, especially Polybia, Polistes, and Agelaia, and in a few fruit species, particularly Psidium guajava, Anacardium occidentale, and Mangifera indica. Overall, the compiled evidence indicates that fruit exploitation by social wasps in Brazil is structured by body size, resource accessibility, and seasonality. However, because the study compiles heterogeneous records rather than directly measuring economic losses, the agricultural significance of these interactions remains context-dependent and requires further evaluation. Full article

Climate change and rapid urbanization are intensifying urban pluvial flooding and threatening sustainable urban development. This study proposes a three-stage, four-dimensional framework (TSFD-UPFR) to assess urban pluvial flood resilience across resistance, response, and recovery phases that integrate natural, infrastructural, social, and economic dimensions. Using a representative urban catchment affected by a typical extreme rainfall event, we couple hydrological–hydrodynamic simulations with multi-source remote sensing and socio-economic indicators at a 100 m grid resolution to enable spatially explicit assessment. The results indicate moderate overall resilience with pronounced spatial heterogeneity. Resistance is primarily constrained by drainage capacity and impervious surfaces, response is shaped by road connectivity and public service accessibility, and recovery is determined by essential facility restoration and economic support. Low-resilience clusters are concentrated in dense built-up areas and transport hubs, revealing structural weaknesses in adaptive capacity. By linking flood processes with socio-economic recovery dynamics, the framework captures cross-stage interactions within urban systems. The findings support climate-adaptive planning, targeted infrastructure investment, and resilience-oriented governance, contributing to sustainable and equitable urban transformation in megacities facing intensifying extreme rainfall. Full article

In an era marked by rising stress-related disorders and cardiovascular morbidity, understanding how the brain and heart adapt to environmental, physiological, and social stressors has become an urgent biomedical priority. This review advances an integrative framework centered on sociostasis, defined as the dynamic regulation of physiological state through social interaction, and its intersection with hormesis, a biphasic adaptive response to controlled stress that enhances resilience. We focus on four evolutionarily conserved neuropeptides, vasopressin, oxytocin, corticotropin-releasing hormone, and the urocortins, which serve as molecular bridges linking social behavior, neuroendocrine signaling, autonomic regulation, and cardiovascular function. Operating within an organized autonomic architecture, these systems calibrate responses to acute and chronic stress. Their context-dependent synergy enables adaptive flexibility under manageable challenge but may promote maladaptive cardiovascular remodeling when chronically dysregulated. Genetic vulnerability, developmental adversity, and persistent psychosocial stress can shift neuroendocrine–autonomic set points, increasing susceptibility to hypertension, endothelial dysfunction, and stress-induced cardiomyopathy. Conditioning and preconditioning paradigms illustrate how repeated exposure to subthreshold stressors primes cardiovascular tissues for future insults, enhancing ischemic tolerance and adaptive gene expression. We propose that cardiovascular hormesis depends not only on stimulus intensity but also on the integrity of neuroautonomic regulatory mechanisms that support recovery and flexibility. Vagal efficiency, a dynamic index of cardioinhibitory regulation, is discussed as a potential translational metric of adaptive capacity. By integrating molecular, physiological, and psychosocial perspectives, this framework conceptualizes cardiovascular resilience as an emergent property of coordinated hormetic signaling, neuropeptidergic modulation, autonomic regulation, and social buffering. Translational implications include peptide-based therapies, autonomic biofeedback, and behavioral interventions designed to enhance stress adaptability. Full article

Consumer wellbeing systems are characterized by conceptual fragmentation, heterogeneous data sources, and multilevel interactions across economic, psychological, social, and environmental domains. Existing monitoring approaches remain largely unidimensional and lack integrative system architectures capable of supporting real-time, adaptive analysis. This paper proposes a Federated Digital Twin (FDT) framework for Consumer Wellbeing Systems, designed to integrate decentralized, multimodal data while preserving autonomy and privacy. The proposed architecture builds on a five-dimensional digital twin model and extends it through federated interoperability, data fusion, adaptive learning, simulation capabilities, and human-in-the-loop mechanisms. The framework enables the synchronization of observed, self-reported, contextual, and synthetic data across distributed environments, supporting system-level modeling, prediction, and optimization. As an illustrative application, the paper examines Shopping Wellbeing and Shopping–Life Balance as sub-systems within broader wellbeing ecosystems, demonstrating how federated digital twins can unify fragmented theoretical constructs into a coherent, dynamic monitoring structure. The study contributes a system-oriented conceptual architecture for modeling complex human-centric wellbeing ecosystems and outlines implications for systems design, governance, and future interdisciplinary research. Full article

In the existing research on information propagation modeling in social networks, hypergraphs have been widely applied to characterize the high-order interaction relationships involving multiple nodes. However, most models are still based on the assumption of undirected connections, which leads to certain limitations in depicting the information flow direction and the structural characteristics of propagation chains. To address the above problems, a social hypernetwork propagation model with directional constraints is constructed in this paper by introducing the directed hypergraph structure and combining it with the improved SEIR model. The strength of social relationships is measured by intimacy in the model, and a comprehensive characterization of the information propagation process is achieved by integrating the threshold mechanism of the directed hypergraphs with the attenuation function of information timeliness. In addition, the effectiveness of the proposed model is verified by taking the event of “imposing additional tariffs” as an example, and the evolutionary characteristics of propagation in different network structures, as well as the impacts of user confidence and information timeliness, are analyzed using simulation experiments. The results indicate that the model is applicable to characterizing the information propagation trends and dynamic characteristics in real social networks, and can provide theoretical references and methodological support for the prediction and regulation of network public opinion. Full article