Search Results (381)

While the inclusiveness of digital finance is widely acknowledged, existing research predominantly focuses on its developmental level, with limited attention to its spatial correlation network and structural characteristics. A city’s centrality within this network governs the flow and allocation of digital financial resources, thereby influencing interregional and urban-rural efficiency in resource allocation and income distribution, which ultimately shapes the trajectory of common prosperity. Based on panel data from 280 Chinese cities (2011–2021), this study employs social network analysis to measure urban centrality in the digital financial spatial correlation network and empirically investigates its impact and mechanisms on common prosperity. The main findings are as follows: (1) Benchmark regressions confirm that overall network centrality and its three dimensions—degree, betweenness, and closeness centrality—significantly promote common prosperity, specifically by enhancing the “wealth” dimension and reducing regional development disparities, with the growth effect currently surpassing the inclusion effect. (2) Robustness checks, including instrumental variable approaches addressing endogeneity, affirm the reliability of the core findings. (3) Heterogeneity analysis reveals that the positive effect is more pronounced in cities that are less developed or have weaker financial foundations, such as those in Western China, non-financial centers, cities with no presence of formal financial institutions in antiquity, fifth-tier cities, and small and medium-sized cities, suggesting that network centrality serves as a catalytic tool for urban catch-up strategies. (4) Mechanism analysis identifies that fostering entrepreneurship, particularly among self-employed individuals and wholesale/retail enterprises characterized by decentralized operations and abundant transaction data, is the primary channel through which centrality advances common prosperity. This study provides insights into promoting balanced regional development and common prosperity by optimizing the spatial structure of digital finance. Full article

The world is far from meeting the goals of the Paris Agreement of limiting the rise of global temperature to below 1.5 °C, with dire consequences for Small Island Developing States (SIDS) in particular. If SIDS are to address their climate vulnerabilities through policy-induced resilience building, they need to have a robust governance framework in place that coherently addresses climate change adaptation and disaster risk reduction. What would such a governance framework look like? To address this question, we carried out a systematic literature review of papers published between 1992 and 2023. Our review reveals that the governance around climate change adaptation and disaster risk reduction is relatively weak in SIDS. However, the analysis of barriers and enablers unveils the contours of a proposed three-tiered governance framework, the application of which needs to be contextualised: Tier 1 comprises three key pillars: Policy Planning, Institutional Arrangements, and Laws and Regulations; Tier 2 identifies the principles of transparency, accountability, equity, legitimacy, and subsidiarity; the core pillars and the principles are nested within a broader Tier 3 comprising democratic processes (rule of law), religious and cultural values, and political commitment. In order for SIDS to fight the existential threat of climate change, the proposed framework will allow SIDS to better understand their climate governance framework and deliver low-carbon, climate resilient development within the broader ambit of sustainable development. This framework also addresses the weakness in previous studies, which consider dimensions, principles, and enabling an environment of good governance on equal footing. We illustrate this framework using the analogy of the lotus flower. Full article

This study explored the psychological characteristics of homeroom teachers’ reflective practice with a focus on student mental health, addressing a gap in empirical research. This study conducted semi-structured interviews with seventeen Chinese homeroom teachers and applied thematic analysis to examine how reflective practice supported mental health education. It also evaluated this practice from the perspective of multi-tiered systems of support (MTSS). The findings reveal the cognitive, emotional, motivational, and behavioral characteristics of homeroom teachers’ reflective practice. Cognitive characteristics centered on three aspects—the focus of reflection, the thinking process, and the formation or transformation of cognition—with student mental health being a primary concern. Emotional elements were less explicitly mentioned but were embedded in teachers’ narratives. Motivational characteristics comprised autonomy and physical–mental states, supporting or impeding reflection. Behaviorally, homeroom teachers engaged in silent, written, and dialogic forms of reflection, with silent reflection being common yet often undervalued. The study also indicated that homeroom teachers’ work in mental health education mainly involves MTSS Tier 1 and Tier 2, with insufficient collaboration with other professionals and characteristics distinct from traditional MTSS practices. Overall, the study highlights the multifaceted nature of reflective practice and its implications for enhancing school-based mental health education. Full article

Background/Objectives: Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare disease, in which multiple genetic and environmental factors may contribute. This study aimed to identify potential genetic determinants in patients with CTEPH and to compare their occurrence to a control group, which included patients with pulmonary embolism who had not developed CTEPH. Methods: Tier 1 and 2 genes related to coagulation, fibrinolysis and platelet disorders—as recommended by the International Society on Thrombosis and Haemostasis—and genes associated with vascular conditions were analyzed in n = 15 patients with CTEPH and n = 17 controls using next-generation sequencing. Non-synonymous, rare variants were collected and interpreted. Results: As expected, no single gene or variant was consistently present among CTEPH patients. Instead, individuals carried different mutations and combinations of variants. We identified several variants that were not found in the control group. Candidate variants were detected in F12, F13A1, F13B, F5, KNG1, SERPIND1, THBD, ADAMTS13, VWF, STIM1, ETV6, THPO, MPL, SERPINA1, ENG, RASA1, ACVRL1, GDF2, NFE2, SOX17 and RNF213. We did not detect exclusive variants in FGA, CPB2, and BMPR2 although they were suggested as candidates in previous studies. Elevated factor VIII and von Willebrand factor in CTEPH could not be explained by mutations in VWF and F8. Conclusions: Our study supports the hypothesis of heterogeneous genetic background in CTEPH, involving multiple pathways such as coagulation, altered fibrinolysis and impaired angiogenesis. These results provide a basis for more detailed investigations into specific genes and variants potentially associated with CTEPH in larger cohorts. Full article

Enhancing climate resilience is imperative for cities to mitigate the effects of global warming and the rising frequency of extreme weather events. This paper develops an evaluation index system for urban climate resilience in Hebei Province, based on data from 11 cities within the province. It evaluates the levels of climate resilience and identifies their limiting factors using the entropy weight method, an urban climate resilience assessment model, and an obstacle degree model, with a focus on four dimensions: ecological resilience, economic resilience, social resilience, and infrastructure resilience. The results indicate that (1) spatial variations in climate resilience across cities in Hebei Province are minimal, with the majority of cities exhibiting climate resilience levels within the moderate resilience category. (2) The majority of regions display low ecological and infrastructure resilience (0.1–0.3), while economic resilience is distributed across three tiers, with regional variations; social resilience remains moderately resilient (above 0.3). (3) Among the social resilience factors, C₃ and C₈ exhibit the highest obstruction levels, emerging as key barriers. (4) In order to effectively respond to climate change risks and challenges in a scientific manner, differentiated implementation of climate response strategies, the core of which lies in identifying the dominant vulnerability dimensions of different cities and accurately applying policies, such as Shijiazhuang, Baoding, Xingtai, Handan, and other cities with fragile ecological resilience, should comprehensively deepen the construction of sponge cities to alleviate urban flooding and the heat island effect. Full article

The Yangtze River Basin serves as the socioeconomic core of China, and rapid development in recent years has intensified the conflict in the area between economic growth and ecological conservation. This study evaluated the spatiotemporal evolution of the land ecological security (LES) across 11 provinces and municipalities in the Yangtze River Basin from 2008 to 2023 by using the framework of the drivers, pressures, state, impact, and response model of intervention. We forecasted the trends of LES (2024–2033) by using a grey prediction model and identified the key obstacles to it through an obstacle degree model. The findings revealed the following: (1) Economic density (D3) and per capita water resources (S4) had significantly high weights, disproportionately impacting LES. Shanghai scored highest for Drivers, Impact, and Response subsystems, while Tibet led in Pressures and State. (2) Basin-wide LES scores improved from “less safe” to “critical safe” but saw no fundamental breakthrough. LES exhibited a three-tier spatial pattern: higher in the middle-lower reaches (e.g., Shanghai, Jiangsu) and lower in the upper reaches (e.g., Qinghai). Tibet remained “critical safe” with minor fluctuations; other regions improved gradually yet mostly remained “less safe” or “critical safe”. (3) Forecasts (2024–2033) indicate continued overall LES improvement. Shanghai and Jiangsu are projected to reach “safe” status, Qinghai will remain “unsafe”, while most others persist as “critical safe”. Basin LES remains fragile, requiring intervention. (4) The Drivers (D) and State (S) subsystems were the primary constraints on LES. Critical obstacle indicators included economic pressure (per capita GDP (D2), D3), resource availability (S4, ratio of effectively irrigated area (I1)), land productivity (agricultural/forestry output per unit area (I3)), and forest coverage rate (R6). Enhancing LES necessitates implementing regionally tailored policies addressing spatial variations, prioritizing urban economic optimization, strengthening water resource management, and ensuring effective cross-regional governance. Full article

In recent years, China has faced the dual challenge of achieving high-quality economic development (HQED) alongside carbon emission reduction (CER), with new-quality productivity (NQP) emerging as a key driver integrating both agendas. Research on the coordinated development of these three dimensions remains limited but is critical for effective policy-making. Based on panel data from 30 Chinese provinces (2014–2023), this study constructs the NQP-CER-HQED evaluation indicator system; calculates the composite index using the entropy weight method and composite index calculation model; computes the coupling coordination degree (CCD) of the three components via the CCD model; analyzes the temporal evolution and future trends of CCD using kernel density and GM(1,1) models; examines the spatial evolution of CCD through Moran’s I index; employs traditional Markov chains and spatial Markov chains to investigate the spatial-temporal evolution patterns of CCD; and applies the geographic detector method to analyze the influencing factors of CCD among NQP, CER and HQED. The findings reveal that (1) the CCD of China’s NQP-CER-HQED has undergone six levels, showing an overall upward trend; (2) temporally, CCD levels improve annually, with all provinces expected to achieve coordinated development by 2026; (3) spatially, the CCD exhibits a “high-east, low-west” tiered distribution; (4) spatially/temporally, the transition of the CCD levels is primarily gradual rather than leapfrogging; and (5) the level of opening up and new-quality labor resources are identified as dominant influencing factors, with the interaction between new-quality labor resources and government support showing the strongest explanatory power. This study provides an analytical framework for understanding the NQP-CER-HQED synergy and offers a scientific basis for sustainable policy formulation. Full article

This study presents an integrated framework for spatiotemporal mapping of carbon stocks in rubber plantations in Rayong Province, Eastern Thailand—an area undergoing rapid agricultural transformation and rubber expansion. Unlike most existing assessments that rely on Tier 1 IPCC defaults or coarse plantation age classes, our framework combines annual plantation age derived from Landsat time series, age-specific allometric growth models, and Tier 2 soil organic carbon (SOC) accounting. This enables fine-scale, age- and site-sensitive estimation of both tree and soil carbon. Results show that tree biomass dominates the carbon pool, with mean tree carbon stocks of 66.94 ± 13.1% t C ha⁻¹, broadly consistent with national field studies. SOC stocks averaged 45.20 ± 0.043% t C ha⁻¹, but were overwhelmingly inherited from pre-conversion land use (43.7 ± 0.042% t C ha⁻¹). Modeled SOC changes ($\mathsf{\Delta }\mathrm{SOC}$) were modest, with small gains (2.06 t C ha⁻¹) and localized losses (−9.96 t C ha⁻¹), producing a net mean increase of only 1.44 t C ha⁻¹. These values are substantially lower than field-based estimates (5–15 t C ha⁻¹), reflecting structural limitations of the global empirical ΔSOC model and reliance on generalized default parameters. Uncertainties also arise from allometric assumptions, generalized soil factors, and Landsat resolution constraints in smallholder landscapes. Beyond carbon, ecological trade-offs of rubber expansion—including biodiversity loss, soil fertility decline, and hydrological impacts—must be considered. By integrating methodological innovation with explicit acknowledgment of uncertainties, this framework provides a conservative but policy-relevant basis for carbon accounting, subnational GHG reporting, and sustainable land-use planning in tropical agroecosystems. Full article

Digital technology transfer plays a pivotal role in reshaping innovation landscapes and fueling the growth of the digital economy. To investigate this phenomenon, this study draws on data on digital technology transfers from the China National Intellectual Property Administration (CNIPA). Using tools such as Gephi 0.10.1 and ArcGIS 10.8, we construct an inter-city digital technology transfer network and develop a quantitative model to analyse the mechanisms by which it impacts urban digital innovation across multiple geographic scales. The main findings are as follows: (1) The inter-city digital technology transfer network in China forms a “diamond-shaped” spatial structure centred on Beijing, Shanghai, Guangzhou, and Shenzhen, with several regional hubs sustaining its connectivity and organisation. (2) Despite a decline in the proportion of intra-city transfers, the number of participating cities continues to rise, revealing a spatial pattern of diffusion from core cities toward inland provincial capitals. (3) Benchmark regression results show that both inter- and intra-city transfers significantly enhance urban digital innovation capacity, with inter-city transfers exhibiting a more substantial effect than their intra-city counterparts. This finding holds after a series of robustness tests. (4) Heterogeneity analysis, based on categorising cities into higher-tier (municipalities, sub-provincial cities, and provincial capitals) and lower-tier groups, indicates that the effect of digital technology transfer on innovation is more pronounced in lower-tier cities. Full article

This entry explains how China’s e-CNY, the retail form of its Central Bank Digital Currency, translates three design choices into improved access, affordability, and reliability: (1) enabling wallet-to-wallet payments on the CBDC ledger with settlement upon payment (SUP); (2) ensuring seamless integration at checkout with existing QR-code systems and popular payment apps; and (3) providing users with practical control through credentials stored on their devices and managed by licensed operators. With payment finality clarified in law and a two-tier structure in place, offline payments can shift to a hybrid architecture. It blends account- and token-based functionality across online and offline settings, incorporates tiered identity verification, and supports low-cost solutions. In essence, e-CNY demonstrates that strategic decisions regarding settlement, interoperability, and user control can expand financial inclusion while maintaining robust regulatory safeguards. Full article

This research evaluates the performance of the Final Run remote sensing precipitation products from the Integrated Multi-satellite Retrievals for GPM (IMERG-F) in complex terrain river basins (2014–2023). Utilizing decade-long daily precipitation data from 2415 manned national-level ground stations, the evaluation employs eight statistical metrics—probability of detection, false alarm ratio, accuracy, critical success index, Pearson correlation coefficient (PCC), root mean square difference, mean difference, and relative difference—to analyze detection accuracy, correlation, and bias on daily, monthly, and annual scales. The main findings include the following: (1) IMERG-F’s daily precipitation detection capability follows a three-tier spatial pattern (northwest to southeast), aligning with the stepped terrain of China. (2) Stronger correlations (PCC = 0.7–0.9) with gauge data emerge in southeastern regions despite higher biases, while northwestern areas show weaker correlations but fewer deviations. (3) IMERG-F overestimates annual rainy days, but slightly underestimates precipitation intensity compared with ground observations. (4) Annual precipitation estimates exceed gauge measurements, particularly in the Songhua and Liao River Basins (18–20% overestimation). Monthly analysis shows fewer errors during rainy seasons versus winter dry periods, with pronounced seasonal variations in northwestern basins. These findings emphasize the need for terrain-aware calibration to improve satellite precipitation monitoring in hydrologically diverse basins, particularly addressing seasonal and spatial error patterns in water resource management applications in northern China. Full article

Addressing Artificial Intelligence (AI) faculty deficiencies in higher education, this paper develops the AI+ Dual-qualified Teacher Capability Ecology Model (AI-DTCEM) based on Capability Ecology Theory. The model is developed after a thorough analysis of the current state of new engineering talent cultivation in universities and the innovative practical abilities required in the AI+ environment. This paper proposes an implementation framework characterized by “three-dimensional collaboration, four-tier progression, and five-element drive.” Additionally, it uses the collaborative education project involving Hangzhou Normal University, Zhejiang University, and Hangzhou Ruishu Technology Co., Ltd. as a backdrop to introduce a deep collaborative education model, showcasing the theoretical and practical achievements of this project. Using NetLogo as the simulation platform, this paper designs a 96-month system dynamics experiment to compare and analyze the outcomes of four scenarios: the baseline experiment, the AI-enhanced experiment, the policy-driven experiment, and the comprehensive optimization experiment. This study reveals the following findings: (1) Policy-driven initiatives are crucial for the successful construction of dual-qualified teacher teams, with the policy-driven scenario achieving the highest overall skill level (9.332). (2) The application of AI technology significantly enhances teacher skill development, resulting in AI skill improvements ranging from 116.6% to 163.4%. (3) The comprehensive optimization scenario (utilizing a collaborative mechanism) achieves systemic advantages, realizing a 100% dual-qualified teacher ratio. However, this comes with diminishing marginal returns on investment. This research provides a theoretical foundation, quantitative analysis, and practical pathways for developing dual-qualified teacher teams in the AI+ era. Full article

This study explores how digitalization by focal firms affects carbon performance across the entire supply chain, advancing the literature by adopting a holistic supply chain perspective rather than a single-firm lens. We further draw on dynamic capability theory to explain the mechanisms through which digitalization enhances supply chain carbon performance. Based on an unbalanced panel dataset of Chinese listed firms from 2008 to 2022, we construct a three-tier supply chain panel linking upstream, focal, and downstream firms. The benchmark regression results show that focal firm digitalization significantly enhances overall supply chain carbon performance. Mechanism analyses identify two critical transmission channels: (1) optimizing supply chain resource allocation efficiency, through improved inventory turnover and strengthened supply chain finance; and (2) enabling collaborative technological upgrading, by enhancing the total factor productivity of upstream and downstream partners. Further heterogeneity analysis reveals that the effect of digitalization on improving carbon performance is more pronounced in regions with stronger environmental regulation and in non-regulated industries. In addition, we analyze the moderating role of the Supply-Chain Pilot-Cities Program. The findings provide practical insights for firm managers globally seeking to leverage digitalization for supply chain decarbonization and for policymakers across jurisdictions aiming to design supportive mechanisms that facilitate digital and green integration. Full article

Background: Contralateral lymph node metastasis (CLNM) in oral squamous cell carcinoma (OSCC) represents a major clinical challenge, in patients with a clinically contralateral node-negative neck. Individualized risk stratification is crucial to guide decisions on elective contralateral neck dissection. This study aimed to synthesize existing evidence and apply Bayesian Monte Carlo Simulation (MCS) to estimate CLNM probability across various clinic-pathological scenarios. Methods: A systematic search of PubMed, PubMed Central, and Embase (2000–2024) identified 26 eligible studies. Effect sizes for seven key risk factors—midline-crossing tumours, extranodal extension (ENE), ≥2 ipsilateral lymph nodes, depth of invasion (DOI) >10 mm, perineural invasion and lymphovascular invasion (PNI-LVI), poor differentiation, and floor of mouth subsite—were computed and incorporated into a Bayesian logistic model. Using the No-U-Turn Sampler (NUTS) in RStan, 100,000 virtual patient profiles were simulated to generate posterior probabilities of CLNM. Results: The baseline CLNM risk for lateralized tumours without additional risk factors was 4.2%. Single risk factors increased probability substantially: midline-crossing tumours (31.7%), ENE (27.4%), and ≥2 ipsilateral nodes (24.9%). Combinations of risk factors amplified the risk non-linearly: the presence of a midline-crossing tumour, ENE, and ≥2 ipsilateral nodes yielded a 76.8% CLNM probability, and the presence of all seven risk factors increased it to 93.7%. Risk tiers were classified from minimal (<20%) to very high (>50%) to guide clinical decision-making. Conclusions: This MCS-based model reveals that CLNM risk increases multiplicatively with the presence of various high-risk features. The simulation supports bilateral neck management in high-risk patients and observation in low-risk cases. Prospective validation is needed to integrate this model into routine clinical practice and to guide patient-specific surgical planning. Full article

Urban park green spaces (UPGSs) play a critical role in enhancing residents’ quality of life, particularly for older adults. However, inequities in accessibility and resource distribution remain persistent challenges in aging urban areas. To address this issue, this study takes Gulou District, Nanjing City, as an example and proposes a comprehensive framework to evaluate the overall quality of UPGSs. Furthermore, an enhanced Gaussian two-step floating catchment area (2SFCA) method is introduced that incorporates (1) a multidimensional park quality score derived from an objective evaluation system encompassing ecological conditions, service quality, age-friendly facilities, and basic infrastructure; and (2) a Gaussian distance decay function calibrated to reflect the walking and public transit mobility patterns of the older adults in the study area. The improved method calculates the accessibility values of UPGSs for older adults living in residential communities under the walking and public transportation scenarios. Finally, factors influencing the social equity of UPGSs are analyzed using Pearson correlation coefficients. The experimental results demonstrate that (1) high-accessibility service areas exhibit clustered distributions, with significant differences in accessibility levels across the transportation modes and clear spatial gradient disparities. Specifically, traditional residential neighborhoods often present accessibility blind spots under the walking scenario, accounting for 50.8%, which leads to insufficient accessibility to public green spaces. (2) Structural imbalance and inequities in public service provision have resulted in barriers to UPGS utilization for older adults in certain communities. On this basis, targeted improvement strategies based on accessibility characteristics under different transportation modes are proposed, including the establishment of multi-tiered networked UPGSs and the upgrading of slow-moving transportation infrastructure. The research findings can enhance service efficiency through evidence-based spatial resource reallocation, offering actionable insights for optimizing the spatial layout of UPGSs and advancing the equitable distribution of public services in urban core areas. Full article