Search Results (10,092)

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

Developing a deep understanding of the evolutionary driving mechanisms of university–industry collaborative innovation networks among Chinese cities is of great significance for advancing sustainable urban development. Based on university–industry collaborative patent data from 275 prefecture-level and above cities in China during the period 2004–2020, this study constructs an intercity university–industry collaborative innovation network and employs the temporal exponential random graph model to analyze its evolutionary driving mechanisms. The results indicate that the network structure has become increasingly complex over time and exhibits pronounced small-world characteristics in the later stages. Network formation is distinctly non-random and is jointly shaped by endogenous structural effects and exogenous factors. Diffusion, connectivity, and closure effects are all significant, while intercity collaborative ties are influenced by multidimensional proximity, including economic, geographic, and organizational proximity. Moreover, the network structure demonstrates strong temporal stability. In the context of high-intensity collaboration, cities place greater emphasis on economic and organizational proximity, and cities with higher levels of economic development and prior experience in high-intensity collaboration are more likely to establish collaborative ties. Furthermore, eastern cities tend to collaborate with partners at similar levels of economic development, whereas cities in central and western regions display a more pronounced core–periphery pattern. Overall, from the perspective of intercity university–industry collaborative innovation networks, this study provides new empirical evidence and insights for promoting coordinated regional innovation capacity and sustainable urban development. Full article

This study aims to explore the relationship between a company manager’s activities and their impact on business performance. Networking is considered a worthy factor in professional and organizational success, providing access to important research, industry insights and future partnerships. Through the analysis of the data used in the study, this paper adopts a methodological approach to examine how managerial networking influences business results, with a particular focus on French small and medium-sized enterprises (SMEs). The findings indicate a strong and positive correlation between the manager’s ability to build and maintain professional relationships and the entire performance of their business. In fact, managers who actively engage in networking often gain access to better business opportunities, funding sources and strategic collaborations that increase growth and competitiveness. Additionally, strong networks facilitate the exchange of knowledge, best practices and innovative ideas, thereby improving decision making and operational efficiency. The review further highlights that networking is not just about expanding contacts, but also about attending meaningful and beneficial affairs that contribute to long-term success. These results underline its importance as a strategic tool for business leaders, sustaining the idea that well-connected managers are better equipped to navigate challenges, catch opportunities and drive sustainable business prosperity in an increasingly competitive market. Full article

Service-learning has emerged as a promising pedagogical approach to address social challenges while fostering students’ academic, socioemotional, and civic development. Despite the growing body of literature, there is a lack of systematic reviews evaluating its effectiveness in secondary education beyond the United States. Therefore, this systematic review aimed to synthesize the available empirical research on service-learning interventions implemented with secondary education students (grades 7–10) outside United States. Following The Campbell Collaboration guidelines, a comprehensive search was conducted across Web of Science and ProQuest, supplemented by other resources (general web search, hand searches, ongoing research, open access and relevant institutions and networks). Inclusion criteria required quantitative empirical studies (randomized controlled trials, quasi-experimental designs, or pretest–posttest designs) published from 2008 to June 2025 that measured academic, cognitive, socio-emotional, civic, and community outcomes using quantitative procedures. After screening, 10 studies met the inclusion criteria. The findings indicate that service-learning programs can generate positive outcomes on academic performance and non-cognitive skills. Nevertheless, methodological weaknesses and heterogeneity across studies prevent drawing robust conclusions. The review highlights the need for more rigorous research to strengthen the evidence base for service-learning among adolescents in systems worldwide. Full article

Reducing dependency on chemical pesticides is a core ambition of the European Green Deal, yet adoption of low-input practices remains uneven. This systematic review synthesizes evidence on the behavioural determinants of European farmers’ knowledge, attitudes, and practices (KAP) regarding sustainable pesticide use and evaluates the role of digital tools in facilitating Integrated Pest Management (IPM). Following PRISMA 2020 guidelines, we analysed 65 peer-reviewed articles published between 2011 and 2025, which were identified through Scopus and Web of Science. The synthesis reveals that while pro-environmental attitudes drive the intention to change, actual behaviour is frequently inhibited by loss aversion, ‘clean field’ social norms, and perceived economic risks. Digital tools—specifically Decision Support Systems (DSSs) and precision technologies—demonstrate technical potential to reduce pesticide loads but are constrained by the same behavioural barriers: a lack of trust in models, perceived complexity, and costs. Consequently, we propose a Psycho-Digital Integration Framework which posits that digital innovation acts as a catalyst only when embedded in systemic enablers—specifically green insurance schemes and independent advisory networks. These mechanisms are critical to redistribute perceived agricultural risk and bridge the gap between technical potential and behavioral adoption. Full article

Pedestrian trajectory prediction plays a vital role in autonomous driving and intelligent surveillance systems. Graph neural networks (GNNs) have shown remarkable effectiveness in this task by explicitly modeling social interactions among pedestrians. However, existing methods suffer from two key limitations. First, they face difficulty in balancing the reduction in redundant connections with the preservation of critical interaction relationships in spatial graph construction. Second, higher-order graph convolution methods lack adaptability to varying crowd densities. To address these limitations, we propose a pedestrian trajectory prediction method based on Delaunay triangulation and density-adaptive higher-order graph convolution. First, we leverage Delaunay triangulation to construct a sparse, geometrically principled adjacency structure for spatial interaction graphs, which effectively eliminates redundant connections while preserving essential proximity relationships. Second, we design a density-adaptive order selection mechanism that dynamically adjusts the graph convolution order according to pedestrian density. Experiments on the ETH/UCY datasets show that our method achieves 5.6% and 9.4% reductions in average displacement error (ADE) and final displacement error (FDE), respectively, compared with the recent graph convolution-based method DSTIGCN, demonstrating the effectiveness of the proposed approach. Full article

Social sustainability has become a central concern in development-induced resettlement, yet little is known about how social integration and community relations are sustained over long time horizons. Drawing on a retrospective longitudinal ethnographic reconstruction spanning 21 years (2004–2025) of Three Gorges Dam resettlers relocated to rural Anhui, China, this paper examines the co-evolution of group boundaries, interaction strategies, and social networks between migrants and local residents. Using group boundary theory, we identify three sequential phases of interaction: initial boundary demarcation and social distancing, subsequent bridge-building through economic cooperation and relational ingratiation, and a later stage of pragmatic, transactional engagement. We show that the gradual erosion of migrant–local boundaries is driven by economic interdependence, cultural adaptation, individualization, and rural out-migration. Rather than resulting in deep social fusion, long-term integration stabilizes in a form of “thin integration,” characterized by low-density but sustainable social ties, institutionalized conflict resolution, and routine coexistence. This study conceptualizes social integration as a dynamic process of social sustainability, demonstrating how resettled communities maintain social order and functional cohesion amid structural change. The findings contribute to debates on sustainable rural development, forced migration, and the long-term governance of resettlement communities. Full article

Research often emphasises dysfunctional Social Networking Site (SNS) usage. In contrast, the current research examined a more positive element of human functioning, specifically how motivations to use SNSs may be associated with meaning in life, which can help give purpose and direction to people’s lives. A sample of 384 undergraduate students (aged 18 to 50; M = 20.95; SD = 4.95; 81.5% females) completed questionnaire-based measures of motivations to use SNSs, self-reported time spent on SNSs, and meaning in life (coherence, purpose, and mattering). Multiple regressions showed that models for coherence, purpose, and mattering explained 5.8–8.8% of the variance (R² = 0.058–0.088). Self-expression was positively associated with coherence (β = 0.128), purpose (β = 0.16), and mattering (β = 0.137). Following/monitoring others predicted higher coherence (β = 0.158), and using SNSs to find information predicted higher purpose (β = 0.12). Academic purposes were positively related to mattering (β = 0.12). By contrast, using SNSs for new friendships predicted lower coherence (β = −0.197) and mattering (β = −0.154), entertainment predicted lower coherence (β = −0.178), and greater time on SNSs predicted lower purpose (β = −0.186). Overall, different motivations for using SNSs are associated with different facets of meaning in life. Full article

Background: Chronic nonbacterial prostatitis (CNP), the major subset of chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS), imposes a substantial global burden yet lacks satisfactory therapies. Maizibizi Wan (MZBZ) has long been used clinically for prostatitis, but its pharmacodynamic substance basis and mechanisms remain unclear. Methods: Ultra-high-performance liquid chromatography–Q-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) coupled with Global Natural Products Social Molecular Networking (GNPS) molecular networking profiled MZBZ constituents and rat plasma–exposed prototype components and metabolites was used. Based on blood-absorbable components, network pharmacology predicted core targets/pathways; representative interactions were validated by molecular docking. A λ-carrageenan–induced CNBP rat model underwent histopathology (H&E), serum cytokine assays (TNF-α, IL-1β, IL-6/IL-17), immunohistochemistry (COX-2, TNF-α, MMP-9), and Western blotting (P-p65/p65, p-AKT/AKT, COX-2, TGF-β1, BCL2). Results: A total of 188 chemical constituents were identified in MZBZ (79 flavonoids, 38 organic acids, 30 alkaloids, 15 phenylpropanoids, 7 steroids, 4 phenylethanoid glycosides, 15 others). A total of 35 blood-absorbable components (18 prototype components, 17 metabolites) were identified, mainly involving Phase I oxidation and Phase II glucuronidation/sulfation. Network analysis yielded 54 core targets enriched in NF-κB and PI3K/AKT signaling and apoptosis. Docking indicated stable binding of key flavonoids to COX-2, NFKB1, TNF, IL-6, and BCL2. In vivo, MZBZ ameliorated prostatic inflammation, reduced serum TNF-α/IL-1β/IL-6/IL-17 (p < 0.05 or p < 0.01); decreased P-p65/p65, p-AKT/AKT, COX-2, and TGF-β1; and increased BCL2 in prostate tissue. Conclusions: MZBZ exerts anti-CNBP effects via multi-component synergy (prototypes + metabolites) that suppresses inflammatory cytokines, modulates apoptosis, and inhibits NF-κB and PI3K/AKT pathways. These findings provide a mechanistic basis and quality control cues for the rational clinical use of MZBZ. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impairments in social interaction and communication, along with atypical behavioral patterns. Affected individuals often seem isolated in their inner world and exhibit particular sensory reactions. The World Health Organization has indicated a persistent increase in the global prevalence of autism, with approximately 1 in 127 persons affected worldwide. This study contributes to the growing research effort by presenting a comprehensive analysis of functional connectivity patterns for ASD prediction using rs-fMRI datasets. A novel approach was used for ASD identification using the ABIDE II dataset, based on functional networks derived from BOLD signals. The sparse functional brain connectome (Lean-NET) model is employed to construct subject-specific connectomes, from which local graph metrics are extracted to quantify regional network properties. Statistically significant features are selected using Welch’s t-test, then subjected to False Discovery Rate (FDR) correction and classified using a Support Vector Machine (SVM). Our experimental results demonstrate that locally derived graph metrics effectively discriminate ASD from typically developing (TD) subjects and achieve accuracy ranging from 70% up to 91%, highlighting the potential of graph learning approaches for functional connectivity analysis and ASD characterization. Full article

Informal settlements are widely present and important urban spaces, providing valuable living spaces for many migrant populations, low-income groups, and indigenous peoples. However, urbanization faces a common challenge: the transformation of informal settlements often destroys social structures and belongingness. Despite its importance, few studies have examined how redevelopment is correlated with original residents’ belongingness. To address this gap, this study proposes a research framework of belongingness structured along the logical chain of “network–node–subject”. Social network analysis (SNA) is employed to identify the existing outdoor activity space network and its key nodes. Exploratory factor analysis (EFA) is then conducted to determine the key environmental features of outdoor activity spaces that influence original residents’ belongingness. Furthermore, K-means clustering is applied to explore the correlation mechanism between space and belongingness across different age groups. This study identifies differentiated and universal elements by analyzing the clustered conflict factors, in order to provide precise policy insights. The findings provide actionable insights for enhancing residents’ belongingness during the redevelopment of informal settlements in cities. Full article

This study investigates how emotionally structured online interaction networks shape consumer perception of new energy vehicle (NEV) technology. Drawing on discussion forum data from two leading NEV brands, Brand_T and Brand_B, we focus on how users respond to brand technological narratives and how these responses translate into distinct patterns of peer-to-peer interaction. Using a behavioral network analysis framework, we integrate sentiment analysis, topic modeling, and Exponential Random Graph Modeling (ERGM) to uncover the psychological and structural mechanisms underlying consumer engagement. Three main findings emerge. First, users display brand-specific emotional-cognitive profiles: Brand_T communities show broader technological engagement but more heterogeneous emotional responses, whereas Brand_B communities exhibit more emotionally aligned discussions. Second, emotional homophily is a robust driver of interaction ties, particularly in Brand_B forums, where positive sentiment clusters into dense and supportive discussion subnetworks. Third, perceived technological benefits, rather than risk sensitivity, are consistently associated with higher interaction intensity, underscoring the motivational salience of anticipated gains over cautionary concerns in shaping engagement behavior. The study contributes to behavioral science and transportation behavior research by linking consumer sentiment, cognition, and social interaction dynamics in digital environments, offering an integrated theoretical account that bridges the Elaboration Likelihood Model, social identity processes, and behavioral network formation. This advances the understanding of technology perception from static individual evaluations to dynamic, group-structured outcomes. It highlights how emotionally patterned interaction networks can reinforce or recalibrate technology-related perceptions, offering practical implications for NEV manufacturers and policymakers seeking to design psychologically informed communication strategies that support sustainable technology adoption. Full article

Digital identity operates as the connective infrastructure of the digital age, linking individuals, organisations, and devices into networks through which services, rights, and responsibilities are transacted. Despite this centrality, the field remains fragmented, with technical solutions, disciplinary perspectives, and regulatory approaches often developing in parallel without interoperability. This paper presents a systematic survey of digital identity research, drawing on a Scopus-indexed baseline corpus of 2551 publications spanning full years 2005–2024, complemented by a recent stratum of 1241 publications (2023–2025) used to surface contemporary thematic structure and inform the ontology-oriented synthesis. The survey contributes in three ways. First, it provides an integrated overview of the digital identity landscape, tracing influential and widely cited works, historical developments, and recent scholarship across technical, legal, organisational, and cultural domains. Second, it applies natural language processing and subject metadata to identify thematic patterns, disciplinary emphases, and influential authors, exposing trends and cross-field connections difficult to capture through manual review. Third, it consolidates recurring concepts and relationships into ontological fragments (illustrative concept maps and subgraphs) that surface candidate entities, processes, and contexts as signals for future formalisation and alignment of fragmented approaches. By clarifying how digital identity has been conceptualised and where gaps remain, the study provides a foundation for progress toward a universal digital identity that is coherent, interoperable, and socially inclusive. Full article

The Ming Dynasty (1368–1644) was a transformative era for Baojuan (寶卷, “precious scrolls”), a traditional genre of Chinese folk religious literature, which evolved from its Yuan origins to achieve widespread prominence. Luo Qing’s Wubu liuce (五部六冊, “Five Books in Six Volumes”) during the Zhengde reign (1506–1521) marked a pivotal moment, enabling the systematic dissemination of his teachings among diverse social strata and profoundly shaping popular religious beliefs. The Ming Baojuan texts, bridging the developments between the Yuan and Qing periods, offer rich and dispersed data suitable for digital visualization. Employing digital humanities tools such as 3D radar charts and GIS visualization, this study maps the spatial distribution and influence of Baojuan in Ming China. The findings reveal that transportation networks and regional economic prosperity played a crucial role in driving its dissemination, with southern regions–particularly the Wu-Yue region (referring to the historical cultural area encompassing southern Jiangsu and northern Zhejiang, core parts of Ming Jiangnan)–showing high density, reflecting the economic and cultural vitality of Ming Jiangnan. The research further demonstrates that the flourishing of Baojuan publication and dissemination during the Ming period was sustained not only by economic and cultural forces but also by the ruling elite’s patronage, a form of discursive strategies that functioned as a mechanism of sectarian legitimation, thereby underscoring the interdependence of regional prosperity, elite patronage, and religious transmission. Full article

Information diffusion models developed for Twitter, Reddit, and Facebook assume network contagion and competition for shared attention. Telegram operates differently. It is built around channels rather than social graphs, and users receive posts directly from subscribed channels without algorithmic mediation. We analyze over 5000 forwarding cascades from the Pushshift Telegram dataset to examine whether existing diffusion models generalize to this broadcast environment. Our findings reveal fundamental structural differences. Telegram forwarding produces perfect star topologies with zero multi-hop propagation. Every forward connects directly to the original message, creating trees with maximum depth of exactly 1. This contrasts sharply with Twitter retweet chains that routinely reach depths of 5 or more hops. Forwarding delays follow heavy-tailed Weibull or lognormal distributions with median delays measured in days rather than hours. Approximately 15 to 20 percent of cascades exhibit administrative bulk reposting rather than organic user-driven growth. Most strikingly, early-stage competitive overtaking is absent. Six of 30 pairs exhibit crossings, but these occur late (median 79 days) via administrative bursts rather than organic competitive acceleration during peak growth. We develop a delay-driven star diffusion model that treats forwarding as independent draws from a delay distribution. The model achieves median prediction errors below 10 percent for organic cascades. These findings demonstrate that platform architecture fundamentally shapes diffusion dynamics. Comparison with prior studies on Twitter, Weibo, and Reddit reveals that Telegram’s broadcast structure produces categorically different patterns—including perfect star topology and asynchronous delays—requiring platform-specific modeling approaches rather than network-based frameworks developed for other platforms. Full article