Search Results (2,470)

The regulation of reproductive division of labor in eusocial insects is pivotal for the evolution and maintenance of social organization. In Bombus terrestris, dominance hierarchies emerge among orphan workers through repeated agonistic interactions, forming distinct behavioral ranks. To explore the neural basis of this process, we combined behavioral assays with single-nucleus RNA sequencing to profile brain-wide gene expression across α-, β-, and γ-bumblebee workers. Our analyses revealed pronounced transcriptional divergence among Kenyon cells, which exhibited enrichment in synaptic, insulin, and MAPK signaling pathways. Among the neuropeptides examined, Neuroparsin-A was markedly upregulated in the Kenyon cells and glial cells of dominant workers, while its receptor, OR1, showed strong expression within Kenyon populations, suggesting a conserved neuropeptide–receptor axis in social Hymenoptera. Gene regulatory network inference further identified ecdysone-responsive transcription factors, including br, Eip74EF, Hr38, Hr3 and Hr4, as key regulators linked to neural plasticity and behavioral differentiation. Together, our findings uncover a neuroendocrine mechanism in which Neuroparsin-A signaling coordinates brain transcriptional programs associated with dominance hierarchy formation in queenless bumblebee societies, offering new insights into the molecular underpinnings of eusocial behavior. Full article

Artificial intelligence (AI) is transforming accounting by automating cognitive tasks and redefining mechanisms of governance and risk control. This study examines how AI operates as an intelligent control system—one that substitutes manual accounting procedures while enhancing transparency, internal control, and fraud detection. Integrating the Technology Acceptance Model (TAM) with Organizational Information Processing Theory (OIPT), the research develops a behavioral–organizational framework linking perceived usefulness, ease of use, AI literacy, technology readiness, social influence, and facilitating conditions to AI adoption and perceived substitution benefits. A structured survey was administered to accounting students and practitioners in Northern Italy (n = 185) and analyzed through reliability tests and partial least squares structural equation modeling (PLS-SEM). The results show that AI literacy, facilitating conditions, and social influence significantly drive adoption intention, while perceived substitution benefits fully mediate the relationship between adoption and governance outcomes. The findings demonstrate that AI adoption enhances governance and risk management effectiveness by functioning as an intelligent control mechanism. The study introduces the AI-to-Control (A2C) Blueprint to guide responsible integration of AI into accounting systems, reframing AI adoption as a structural evolution in corporate governance rather than a mere technological upgrade. Full article

This study investigates the spatiotemporal evolution and key obstacle factors of urban flood resilience in the Shenyang Metropolitan Area, aiming to inform regional flood resilience planning and management. A comprehensive assessment indicator system was established, integrating natural, economic, social, and infrastructure dimensions to capture the multifaceted nature of flood resilience. The long short-term memory (LSTM) network with an attention mechanism, combined with the obstacle degree model, was employed to analyze resilience trends and diagnose limiting factors from 2001 to 2023. The findings reveal a sustained increase in the regional flood resilience index, rising from 0.255 in 2001 to 0.574 in 2023. Spatially, the resilience pattern evolved from a monocentric core diffusion to a dual-core leadership and multi-city collaborative structure, driven by basin-wide management and differentiated development between mountainous and plain areas. Disparities in resilience levels across cities narrowed over time. At the criterion level, infrastructure was the primary obstacle before 2010, while social factors became increasingly significant thereafter. At the indicator level, the main limiting factors varied among cities and shifted over time, reflecting local development dynamics. These results provide a theoretical basis and practical guidance for enhancing urban flood resilience in the Shenyang Metropolitan Area and offer insights applicable to other rapidly urbanizing regions. Full article

Intangible cultural heritage (ICH) is deeply embedded in everyday social life, yet its officially recognized spatial distribution reflects both the independent influences of cultural traditions, development trajectories, and governance practices, and the complex interactions among them. Focusing on 494 national-level ICH items across ten categories in Jiangsu(J), Zhejiang(Z), and Shanghai(H), this study adopts a social-geographical perspective to examine both the spatio-temporal evolution and the driving mechanisms of ICH recognition in one of China’s most developed regions. After rigorous verification of point-based ICH locations, we combine kernel density estimation and the average nearest neighbor index to trace changes across five batches of national designation, and then employ the univariate and interaction detectors of the Geodetector model to assess the effects of 28 natural, socioeconomic, and cultural-institutional variables. The results show, first, that ICH exhibits significant clustering along river corridors and historical cultural belts, with a persistent high-density core in the Shanghai–southern Jiangsu–northern Zhejiang zone and a clear shift over time from highly concentrated to more dispersed and territorially balanced recognition. Second, human-environment factors—especially factors such as urban and rural income and consumption; residents’ education and cultural expenditures; and public education and cultural facilities—have far greater explanatory power than natural conditions, while different ICH categories embed distinctively in urban and rural socio-economic contexts. Third, bivariate interactions reveal that natural and macroeconomic “background” variables are strongly amplified when combined with demographic and cultural factors, whereas interactions among strong human variables show bivariate enhancement with diminishing marginal returns. In summary, these findings enrich international debates on the geography of ICH by clarifying how recognition processes align with regional development and social equity agendas, and they provide a quantitative basis for category-sensitive, place-based strategies that coordinate income policies, public cultural services, and the joint safeguarding of tangible and intangible heritage in both urban renewal and rural revitalization planning. Full article

Background: Survival among children and adolescents and young adults (AYA) with cancer has improved substantially over recent decades; however, dominant survivorship models remain reactive—activated post-treatment and anchored to static exposure- and organ-based screening. This design underuses the anticipatory window at diagnosis and overlooks environmental and social determinants that modulate outcomes across the life course. Methods: We narratively reviewed international frameworks including the Children’s Oncology Group (COG), the International Late Effects of Childhood Cancer Guideline Harmonization Group (IGHG), the Pan-European Network for Care of Survivors after Childhood and Adolescent Cancer (PanCare) and the National Comprehensive Cancer Network (NCCN), and synthesized evidence on environmental determinants, exposomics, toxicogenomics, and implementation. Building on two decades of real-world practice, we describe the evolution from the Pediatric Environmental History (PEHis) to the Ambiomic Health Compass (AHC), integrating genomic, exposomic, geospatial, clinical, and biomonitoring layers into routine care. In this framework, survivorship is conceptualized as beginning at the time of cancer diagnosis (“day 0”). Results: PEHis operationalizes guideline-based care with structured environmental and social assessment, personalized plans, and community integration, contributing to improved survival, healthier behaviors, reduced treatment-related mortality and stronger oncology–primary-care coordination. AHC extends PEHis with dynamic risk recalibration, contextual alerts, targeted biomonitoring, and toxicogenomic interpretation, enabling anticipatory decisions from day 0. The manuscript summarizes the paradigm shift (current vs. Ambiomic models), the domain-specific expansion over existing guidelines, the core clinical/system tools, and time-bound metrics (12, 24, 60 months) to support implementation and evaluation. Conclusions: Survivorship should move upstream—from late surveillance to ambiomic, exposure-aware care beginning at diagnosis. Integrating advanced exposomics, mutational epidemiology, and explainable analytics can reduce preventable events and chronicity, enhance equity, and align pediatric oncology with planetary health. The PEHis–AHC continuum offers a scalable blueprint for next-generation survivorship programs in Europe and beyond. Ambiomic medicine does not replace precision medicine—it completes and extends it by integrating exposomics, social context, and anticipatory analytics from day 0. Full article

Balancing tourism industry (TI) growth and ecological protection is critical for sustainable development in the Yellow River Basin (YRB), China’s vital ecological security barrier and economic belt. However, existing research lacks a spatial perspective on the coordinated development between TI and inclusive green growth (IGG), with limited understanding of cross-regional spillover mechanisms. Based on panel data from 75 cities in the YRB (2011–2023), this study constructs a comprehensive evaluation system encompassing the scale, structure, and potential dimensions of the TI and the economic, social, livelihood, and environmental dimensions of IGG. The study employs the coupling coordination degree (CCD) model, exploratory spatial data analysis (ESDA), and the Spatial Durbin Model (SDM) to examine spatiotemporal evolution and spillover effects. The results reveal an upward yet fluctuating coordination trend with pronounced spatial heterogeneity, characterized by a “downstream–midstream–upstream” gradient pattern, dual-core radiation centered on the Jinan–Qingdao and Xi’an–Zhengzhou agglomerations, and persistent High–High clusters in the Shandong Peninsula contrasted with Low–Low clusters in the upstream Qinghai–Gansu–Ningxia region. Critically, new-quality productive forces exert significant positive direct and spillover effects, while industrial structure and government intervention have inhibitory spatial effects on adjacent cities. Regional heterogeneity analysis confirms factor-endowment-driven differentiation across upstream, midstream, and downstream areas. These findings advance spatial spillover theory in river basin contexts and provide evidence-based pathways for balancing economic growth with ecological protection in ecologically sensitive regions worldwide, directly supporting multiple UN Sustainable Development Goals. Full article

The figure of Íñigo Ibáñez de Arteita exemplifies military and social advancement during the transition from the 15th to the 16th century. Drawing upon archival materials from Lequeitio, notarial records from Valencia and Barcelona, and royal sources such as the Registro General del Sello and the proceedings of the Royal Chancery, this study examines his multifaceted profile. It introduces his family roots in the Basque town of Lequeitio and traces his trajectory—from his roles as merchant, transporter, and pirate in the Mediterranean and Atlantic, to his service as captain in the Catholic Monarchs’ fleet stationed in the Strait of Gibraltar, and as second-in-command in the 1495 expedition to Italy. His paradigmatic evolution enables an analysis of the rise of an extraordinary figure from one of the leading bourgeois families of Biscay, who—thanks to substantial real estate holdings, influential social and political networks, and remarkable nautical expertise—came to command one of the earliest permanent war fleets of his time. Full article

Climate change has intensified the frequency, scale, and interconnection of disasters, challenging the resilience of urban social–ecological systems. Progress remains fragmented because studies on climate adaptation, disaster risk, and resilience often evolve in isolation. Using an integrated methodological approach that combines bibliometric and knowledge mapping analyses of 2396 climate change, 1228 disaster risk, and 989 climate-related disaster risk publications (1994–2024) from the Web of Science Core Collection, this study explores global trends, collaboration networks, and thematic evolution. Results show that (1) disaster risk research remains centered on emergency management; (2) climate change resilience emphasizes adaptive governance and nature-based transformation; and (3) climate-related disaster studies increasingly address compound hazards and cross-sectoral feedback. Synthesizing these strands, this study develops a Dynamic Resilience Framework integrating multi-level feedbacks, governance coordination, and spatiotemporal coupling across robustness, redundancy, transformability, and learnability. The framework identifies future research priorities in multi-risk governance, urban transformability, and justice-oriented adaptation. Full article

Integrating environmental, social, and governance (ESG) reporting with the Sustainable Development Goals (SDGs) is important for achieving corporate sustainability. The rapid evolution of regulations like the Corporate Sustainability Reporting Directive (CSRD), and the fragmented research landscape create uncertainty for strategic planning. This paper addresses the critical gap related to the lack of predictive data into future research trends at the ESG-SDG nexus. The research begins with a bibliometric analysis using two software programs R-Biblioshiny 5.2.0 and VOSviewer 1.6.20, to process data extracted from the Web of Science (Clarivate). Selected key terms regarding sustainability reporting concepts and reporting standards, as well as the engagements of auditors were used to filter the database information. Starting from the bibliometric analysis of 361 publications completed during January 2015–September 2025, the study performs further a quantitative measurement bibliometrics using RStudio 4.5.2 and provides a novel ensemble forecasting model (AutoRegressive Integrated Moving Average, Error, Trend, Seasonal Components, and Linear regression with SDG factors) that cartograph the alignment of the current research field and forecast its evolution. The results reveal that terms regarding reporting “CSRD” and sustainability assurance, “ISSA 5000” are the most dominant research fronts, strongly aligned with SDG 12, 13 and 17. The forecasting model predicts sustained growth in this area. The study contributes by providing a forward-thinking strategic map for researchers, policymakers and businesses, transforming sustainability integration from a compliance task into systematic, data-driven approach for priority setting strategy. Full article

Achieving the Sustainable Development Goals (SDGs) hinges critically on extensive international cooperation. However, the extent and evolution of such cooperation at the global level, along with the relative synergy contributions of different country groups, remain insufficiently studied and inadequately quantified. This study aims to assess the level of global cooperation in advancing the SDGs from 2001 to 2023. It further examines the synergy contributions of countries across different income groups and geographic regions. To this end, a synergy-based statistical framework is employed for the analysis. Our results indicate that global cooperation has shown a steady upward trend during this period, yet substantial disparities persist across different goals and indicators. High-income countries contributed most to economic SDGs, whereas low-income countries contributed most to environmental and social SDGs. Regionally, North America and Europe contributed most to economic synergy. Asia, Africa, Latin America, and the Caribbean made more substantial contributions to social and environmental progress. This study enhances the understanding of global cooperation dynamics related to the SDGs. It also provides evidence-based insights to support the design and timely adjustment of more effective international cooperation strategies. Full article

In recent years, financial statement fraud schemes have evolved to become markedly more sophisticated and concealed, thereby posing severe threats to both social stability and economic health. Traditional detection methods, which rely primarily on fragmented corporate data, exhibit significant limitations in capturing the dynamic evolution and spatial diffusion characteristics of fraudulent behaviors over time and space. To address this issue, in this study, we undertake a thorough analysis of the intrinsic nature of fraud risk from a sociotechnical systems perspective and construct a multi-level indicator system to comprehensively quantify risk elements. Furthermore, recognizing the dynamic evolution nature and propagating characteristics of fraud risk, we propose a novel financial statement fraud detection framework to capture behavior patterns in temporal and spatial dimensions. Experiments on A-share-listed companies of high-risk industries in China demonstrate that the proposed framework significantly outperforms other mainstream machine learning and deep learning techniques. In addition, we open the “black box” of the detection framework and empirically validate fraud risk patterns with respect to social–technical elements by leveraging explainable AI techniques. Practically, the proposed framework and interpretable analysis are capable of providing precise early warnings and supervision. Full article

This study presents a sociotechnical framework for mitigating ethnic violent conflicts by integrating information and communication technologies (ICTs) with community-based social capital. Drawing on longitudinal case studies from three conflict-prone regions in Kenya, Mt. Elgon, Muhoroni, and the Turkana–West Pokot borderlands, the research examines how ICT-enabled peace networks, particularly the Early Warning and Early Response System (EWERS), mobilize bonding, bridging, and linking social capital to reduce violence. The study employs a multi-phase qualitative design, combining retrospective analysis, key informant interviews, focus group discussions, action participation, and thematic coding of EWERS data collected between 2009 and 2021. This approach enabled the reconstruction of system evolution, stakeholder dynamics, and community responses across diverse socio-political contexts. Findings demonstrate that embedding ICTs within trusted social structures fosters inter-ethnic collaboration, inclusive decision-making, and trust-building. EWERS facilitated confidential reporting, timely alerts, and coordinated interventions, leading to reductions in livestock theft, improved leadership accountability, emergence of inter-ethnic business networks, and enhanced visibility and response to gender-based violence. The system’s effectiveness was amplified by faith-based legitimacy, local governance integration, and adaptive training strategies. The study argues that ICTs can become effective enablers of peace when sensitively contextualized within local norms, relationships, and community trust. Operationalizing social capital through digital infrastructure strengthens community resilience and supports inclusive, sustainale peacebuilding. These insights offer a scalable model for ICT-integrated violence mitigation in low- and middle-income countries. This is among the first studies to operationalize bonding, bridging, and linking social capital within ICT-enabled peace networks in rural African contexts. By embedding digital infrastructure into trusted community relationships, the framework offers an analytical approach that can inform inclusive violence mitigation strategies across low- and middle-income settings. While the framework demonstrates potential for scalability, its outcomes depend on contextual adaptation and cannot be assumed to replicate uniformly across all environments. Full article

Effective post-disaster management requires continuous and reliable monitoring of the evolving disaster situation. While remote sensing provides objective measurements of ground deformation, social media data offer dynamic insights into public perception and disaster progression. However, integrating these complementary data sources to achieve sustained monitoring of disaster remains a challenge. To address this, we propose a novel framework that combines Sentinel-1 SAR data with Sina Weibo posts to improve dynamic earthquake impact assessment. Physical damage was quantified using D-InSAR-derived deformation. Disaster-related locations were identified using a fine-tuned pre-trained language model, and public sentiment was inferred through prompt-based few-shot learning with a large language model. Spatiotemporal analysis was performed to examine the relationship between sentiment dynamics and varying levels of physical damage, followed by an analysis of topic transitions within regional semantic networks to compare discussion patterns across areas. A case study of the 2023 Jishishan earthquake demonstrates the framework’s capability to continuously track disaster evolution: regions experiencing severe physical damage exhibit clear concentrations of negative sentiment, whereas increases in positive sentiment coincide with areas where rescue operations are effectively underway. These findings indicate that integrating the two data sources improves continuous disaster monitoring and situational awareness, thereby supporting emergency response. Full article

Urban inefficient land redevelopment (UILR) is crucial for sustainable urban development, yet its progress is driven by the interplay of multiple factors. To systematically uncover the driving mechanisms and dynamic patterns of these factors, an integrated analytical approach combining Structural Equation Modeling (SEM) and Fuzzy Cognitive Map (FCM) is developed in this study. Based on 222 valid survey responses from professionals across eight cities in China’s Yangtze River Delta region, five key factors are identified within the “drivers–pressure–enablers” conceptual framework: economic incentives, environmental objectives, social needs, policy guidance, and implementation conditions. SEM is first employed to examine static causal relationships, and the quantified pathway effects are subsequently incorporated into an FCM model to simulate the long-term evolution. The results reveal the following: (i) All five factors exert significant direct effects, with economic incentives, environmental objectives, and policy guidance also demonstrating notable indirect effects. (ii) The factors exhibit distinct temporal characteristics: policy guidance acts as a “fast variable” enabling short-term breakthroughs; economic incentives serve as a “strong variable” driving medium-term progress; and social needs function as a “slow variable” with long-term benefits. (iii) Policy guidance is essential, as its absence leads to persistently low effectiveness, while its synergy with implementation conditions can achieve satisfactory performance even without economic incentives. The combined SEM–FCM approach validates static hypotheses and simulates dynamic scenarios, offering a new perspective for analyzing complex driving mechanisms of UILR and providing practical insights for targeted redevelopment strategy design. Full article

This article examines the evolution of heraldic memory and genealogical consciousness within the Czerny family from the Middle Ages to the 20th century. Focusing on this single lineage makes it possible to trace, in a longue durée perspective, how heraldic narratives emerged, were transformed, and became embedded in family identity. The study employs a mixed methodology combining historical and genealogical analysis of municipal and noble registers, heraldic artefacts, epitaphs, and family archives with critical interpretation of early modern panegyrics and oral traditions. This approach enables reconstruction of both material and symbolic aspects of heraldic memory and its adaptation to changing political and social contexts. The findings reveal three major patterns. First, in the 15th and 16th centuries, the Czerny (Szwarc/Czarny) family consolidated its noble status by linking the Nowina coat of arms to heroic myths, especially after the death of Mikołaj Czerny at Pskov. Second, in the 17th century, Michał Czerny introduced the “Szwarcenberg” element to the surname, signifying aspirations to aristocratic prestige rather than actual heraldic adoption. Third, these narratives persisted in epitaphs, literary texts, and oral tradition into the modern period. The case illustrates how heraldic memory operated as a dynamic instrument of symbolic self-legitimation among the Polish nobility. Full article