Search Results (3,058)

This study selects Chinese A-listed non-financial and non-insurance enterprises covering the period from 2009 to 2023 as the research sample. Utilizing the green credit interest subsidy policy (GCISP) as a quasi-natural experiment, it employs a multi-period difference-in-differences (DID) model to examine the policy effect and micro-level mechanisms through which GCISP—by coordinating fiscal subsidies with green finance—impacts corporate green innovation. The findings reveal that GCISP significantly promotes corporate green innovation. This enhancing effect is achieved through two pathways: alleviating financing constraints and reducing agency costs. The conclusions of this study provide valuable insights for refining green economic policies that harmonize green finance with fiscal subsidies, and offer reliable empirical evidence and policy implications to support corporate green transformation. Full article

Aiming at the challenge of balancing the accuracy and cost of the initial state calibration of traditional MEMS inertial navigation systems, as well as the current situation of the lack of high-precision three-axis turntables in engineering practice, this paper proposes a practical and innovative systematic error calibration and compensation scheme, which effectively suppresses the deterministic errors of MEMS-INS and enhances its applicability in high-precision and long-duration tasks. By analyzing the coordinate transformation characteristics of the MEMS-INS solution process under small-angle disturbances, a deterministic error model based on the device’s zero bias, scale factor, and cross-coupling errors is constructed. A twelve-position dual-axis calibration method, combined with a high-precision orthogonal fixture, is designed to excite errors on a dual-axis turntable, converting originally unobservable error terms into observable periodic signals. Experimental results show that the installation error calibration accuracy reaches 0.03°, an improvement of about 25% compared to the traditional dual-axis method, breaking through the limitations of dual-axis turntables in cross-coupling error calibration, achieving an initial error ≤ 1 μrad, and reducing the navigation error by 90% within one hour. This method eliminates reliance on expensive three-axis turntables while enabling multi-error calibration, addressing the cost–accuracy trade-off in engineering applications. Full article

The application of orchard inspection robots has become increasingly widespread. How-ever, achieving autonomous navigation in unstructured environments continues to pre-sent significant challenges. This study investigates the Simultaneous Localization and Mapping (SLAM) navigation system of an orchard inspection robot and evaluates its performance using Light Detection and Ranging (LiDAR) technology. A mobile robot that integrates tightly coupled multi-sensors is developed and implemented. The integration of LiDAR and Inertial Measurement Units (IMUs) enables the perception of environmental information. Moreover, the robot’s kinematic model is established, and coordinate transformations are performed based on the Unified Robotics Description Format (URDF). The URDF facilitates the visualization of robot features within the Robot Operating System (ROS). ROS navigation nodes are configured for path planning, where an improved A* algorithm, combined with the Dynamic Window Approach (DWA), is introduced to achieve efficient global and local path planning. The comparison of the simulation results with classical algorithms demonstrated the implemented algorithm exhibits superior search efficiency and smoothness. The robot’s navigation performance is rigorously tested, focusing on navigation accuracy and obstacle avoidance capability. Results demonstrated that, during temporary stops at waypoints, the robot exhibits an average lateral deviation of 0.163 m and a longitudinal deviation of 0.282 m from the target point. The average braking time and startup time of the robot at the four waypoints are 0.46 s and 0.64 s, respectively. In obstacle avoidance tests, optimal performance is observed with an expansion radius of 0.4 m across various obstacle sizes. The proposed combined method achieves efficient and stable global and local path planning, serving as a reference for future applications of mobile inspection robots in autonomous navigation. Full article

Amid the rapid evolution of the digital economy reshaping global competitiveness, China has advanced regional coordination through the Digital China initiative and the “Data Elements ×” Three-Year Action Plan (2024–2026). To further integrate digital transformation with high-quality growth in the urban agglomerations of the middle and lower Yellow River, this study aims to strengthen regional competitiveness, expand digital industries, foster new productivity, refine the development pathway, and safeguard balanced economic, social, and ecological progress. Taking the Yellow River urban clusters as the research object, a comprehensive assessment framework encompassing seven subsystems is established. By employing a mixed-weighting approach, entropy-based TOPSIS, hotspot analysis, coupling coordination models, spatial gravity shift techniques, and grey relational methods, this study investigates the spatiotemporal dynamics between the digital economy and high-quality development. The findings reveal that: (1) temporally, the coupling–coordination process evolves through three distinct phases—initial fluctuation and divergence (1990–2005), synergy consolidation (2005–2015), and high-level stabilization (2015–2022)—with the average coordination index rising from 0.21 to 0.41; (2) spatially, a persistent “core–periphery” structure emerges, while subsystem coupling consistently surpasses coordination levels, reflecting a pattern of “high coupling but insufficient coordination”; (3) hot–cold spot analysis identifies sharp east–west contrasts, with the gravity center shift and ellipse trajectory showing weaker directional stability but greater dispersion; and (4) grey correlation results indicate that key drivers have transitioned from economic scale and infrastructure inputs to green innovation performance and data resource allocation. Overall, this study interprets the empirical results in both temporal and spatial dimensions, offering insights for policymakers seeking to narrow the digital divide and advance sustainable, high-quality development in the Yellow River region. Full article

Education for sustainable development (ESD) plays a pivotal role in facilitating a sustainable transformation. A prerequisite for the successful implementation of ESD is the coordinated cooperation of stakeholders from different levels of the education system. The present study explores the perceptions of key stakeholders in education in Germany concerning (a) the conceptual framework of ESD, (b) the present status of ESD implementation, and (c) the ideal governance of ESD implementation. An exploratory, qualitative approach was selected as the study design. A total of eleven interviews were conducted with stakeholders representing various levels of the German education system, including representatives from ministries, state institutes, associations, and school practice. The findings indicate that the stakeholders have a shared understanding of ESD, with varying degrees of elaboration and areas of emphasis. All acknowledge the advancement in the implementation of ESD, concurrently recognizing the necessity for substantial enhancement. This study’s main contributions are a better understanding of stakeholders’ perceptions on ESD implementation and an ideal governance model that allocates specified responsibilities across all relevant system levels and actors. A combined bottom-up and top-down approach is proposed as essential in the pursuit of fostering sustainability within and through education, encompassing professionalism, profoundness, and persistence. Full article

Although existing models and theories have explained systemic behaviors such as demand amplification and disruption propagation, practical challenges in Modular Construction Supply Chains (MCSC) remain unresolved due to production heterogeneity, geographic dispersion, and conflicting stakeholder interests. In addition, the lack of digital infrastructure and process-level data integration continues to hinder the development of automation and intelligent decision-making. To address these issues, this study develops an MCSC coordination system informed by industrial input. The system features a novel dual-engine architecture that integrates blockchain-enabled smart contracts and Robotic Process Automation (RPA). It also incorporates a practice-oriented approach to MCSC Supply Batch (MSB)-based management, using industrial insights to define the MSB as the fundamental coordination unit in process execution. The automatic triggering mechanism enabled by MSBs and dual-engine enables task-to-task transitions while maintaining traceability and operational clarity across supply chain nodes. A real-world case study validates the effectiveness of the proposed system in enhancing traceability, automation, and stakeholder collaboration within MCSC environments. Full article

The building sector represents a major frontier in the global response to climate change, accounting for approximately one-third of global energy consumption and a comparable share of energy-related carbon dioxide emissions. This review conducts a PRISMA-ScR–based scoping synthesis of technological, behavioural, and policy pathways to achieve energy efficiency and deep decarbonization in buildings. It systematically examines passive design principles, high-performance envelopes, efficient HVAC and lighting systems, renewable energy integration, building energy modelling, and retrofit strategies. The study also addresses the role of regulatory instruments, energy codes, and certification schemes in accelerating sectoral transformation. The synthesis identifies three cross-cutting drivers of decarbonization: integrated design across building systems, digitalization enabling predictive and adaptive operation, and robust policy frameworks ensuring large-scale implementation. The review concludes that while most technologies required to reach zero-emission buildings are already available, their potential remains underutilized due to fragmented policies, limited retrofit rates, and behavioural barriers. Coordinated implementation across technology, governance, and user engagement is essential to realise a net-zero building sector. Full article

Background/Objective: Healthcare accessibility remains a critical challenge in medically underserved regions, particularly for specialized care such as trauma treatment and hyperbaric oxygen therapy (HBOT). This study aims to develop and empirically evaluate the Dr. LINK platform, a remote collaborative care system designed to bridge healthcare gaps in geographically isolated or resource-limited areas through real-time interdisciplinary medical collaboration. Methods: Dr. LINK platform employs a SaaS-based infrastructure with Zero Trust security architecture, supporting structured data exchange, automated notifications, and dynamic consultation transfer. Patients completed a modified Telehealth Usability Questionnaire on a 7-point Likert scale, evaluating usefulness, ease of use, interface quality, interaction quality, reliability, and overall satisfaction. Results: Dr. LINK successfully facilitated real-time collaborative consultations for emergency medicine and HBOT, supporting multiple concurrent consultations while maintaining data security and system performance. Overall usability scores were high (mean 6.71–6.83/7), with HBOT patients consistently reporting higher satisfaction across all domains. The platform enabled timely, structured, and coordinated care, reducing unnecessary patient transfers and enhancing multidisciplinary decision-making. Conclusions: Dr. LINK represents a significant advancement in addressing healthcare disparities by enabling structured, secure, and scalable remote collaborative care. The platform effectively overcomes geographic and infrastructural barriers, providing a practical framework for future telemedicine implementations in specialized care domains. Continued refinement and evaluation will be essential to fully realize its potential in transforming healthcare delivery models toward greater equity and accessibility. Full article

Cultural ecosystem services (CES) represent fundamental expressions of human-environment interactions. A comprehensive assessment of CES supply and demand offers a robust scientific foundation for optimizing the transformation of ecosystem service values to improve human well-being. This study integrates multi-source datasets and employs Maximum Entropy (MaxEnt) modeling with the ArcGIS platform to analyze the spatial distribution of CES supply and demand in Hunan Province, a typical mountain tourism regions in China. Furthermore, geographical detector methods were used to identify and quantify the driving factors influencing these spatial patterns. The findings reveal that: (1) Both CES supply and demand demonstrate pronounced spatial heterogeneity. High-demand areas are predominantly concentrated around prominent scenic locations, forming a “multi-core, clustered” pattern, whereas high-supply areas are primarily located in urban centers, water systems, and mountainous regions, exhibiting a gradient decline along transportation corridors and river networks. (2) According to the CES supply-demand pattern, Hunan Province can be classified into demand, coordination, and enhancement zones. Coordination zones dominate (45–70%), followed by demand zones (20–30%), while enhancement zones account for the smallest proportion (5–20%). (3) Urbanization intensity and land use emerged as the primary drivers of CES supply-demand alignment, followed by vegetation cover, distance to water bodies, and population density. (4) The explanatory power of two-factor interactions across all eight CES categories surpasses that of any individual factor, highlighting the critical role of synergistic multi-factorial influences in shaping the spatial pattern of CES. This study provides a systematic analysis of the categories and driving factors underlying the spatial alignment between CES supply and demand in Hunan Province. The findings offer a scientific foundation for the preservation of ecological and cultural values and the optimization of spatial patterns in mountain tourist areas, while also serving as a valuable reference for the large-scale quantitative assessment of cultural ecosystem services. Full article

In the aspect of water purification, a photoactive hybrid material based on reduced graphite oxide (RGO) with covalently, coordinatively, and through van der Waals interactions bonded zirconium(IV) phthalocyanine (PcZr) is proposed. In the material, the phthalocyanine complex plays the role of photosensitizer, while RGO is considered a carrier, ensuring high surface area and supporting PcZr activation. The central metal atom of PcZr directly interacts with lateral active oxygen-containing surface groups of graphite oxide, mainly –OH and –COOH. Thus, the proposed method of synthesis under solvothermal conditions allowed obtaining a relatively high concentration of the dye (0.2 wt.%) in the system based on a partially reduced and exfoliated graphite oxide. Optical studies confirmed the presence of PcZr through absorption and luminescence spectra. Additionally, effective generation of reactive oxygen species was demonstrated by testing the transformation of a dye indicator (diphenylisobenzofuran). Photocatalytic activity of the system was confirmed by photooxidizing selected organic dyes (methylene blue, Rhodamine B, Brilliant Green, and Eriochrome Black T) in a water medium, tested in slightly acidic conditions under red light. The greatest overall decrease in absorption during the photodegradation test was observed for Brilliant Green, reaching 88% after 3 h of irradiation. Full article

Enhancing fuel efficiency in public transportation requires the integration of complex multimodal data into interpretable, decision-relevant insights. However, traditional analytics and visualization methods often yield fragmented outputs that demand extensive human interpretation, limiting scalability and consistency. This study presents a multi-agent framework that leverages multimodal large language models (LLMs) to automate data narration and energy insight generation. The framework coordinates three specialized agents, including a data narration agent, an LLM-as-a-judge agent, and an optional human-in-the-loop evaluator, to iteratively transform analytical artifacts into coherent, stakeholder-oriented reports. The system is validated through a real-world case study on public bus transportation in Northern Jutland, Denmark, where fuel efficiency data from 4006 trips are analyzed using Gaussian Mixture Model clustering. Comparative experiments across five state-of-the-art LLMs and three prompting paradigms identify GPT-4.1 mini with Chain-of-Thought prompting as the optimal configuration, achieving 97.3% narrative accuracy while balancing interpretability and computational cost. The findings demonstrate that multi-agent orchestration significantly enhances factual precision, coherence, and scalability in LLM-based reporting. The proposed framework establishes a replicable and domain-adaptive methodology for AI-driven narrative generation and decision support in energy informatics. Full article

Against the backdrop of global sustainable development goals, the resilience of manufacturing enterprises has become a critical topic. It serves as an important benchmark for assessing ability to coordinate environmental responsibilities and economic benefits. It also plays a pivotal role in driving the green transformation of industries and sustainable social development. To examine the relationship between environmental, social, and governance (ESG) performance and corporate resilience, as well as their underlying mechanisms, this study develops a research model incorporating moderating and mediating effects. Using a sample of manufacturing listed companies in China’s Shanghai and Shenzhen A-share markets covering the period 2011–2023, the study systematically investigates the impact of ESG performance on corporate resilience. The results indicate that ESG performance significantly enhances corporate resilience, and this conclusion remains valid under various robustness tests. Further mechanism analysis reveals that ESG performance effectively promotes corporate resilience by improving resource allocation efficiency, with analyst attention exerting a positive moderating effect in this process. Heterogeneity analysis reveals that the promoting effect of ESG performance on corporate resilience is more significant in technology-intensive and labor-intensive industries, high environmental sensitivity industries, markets with intense competition, and firms with low resource slack. This study not only expands the theoretical explanatory framework in the fields of corporate sustainable development and organizational resilience but also provides policy and management implications for manufacturing firms to achieve green transformation and sustainable competitiveness through ESG practices in an uncertain environment. Full article

Studying the coordination between urban economic resilience (ER) and high-quality tourism development (HQTD) is crucial to understanding tourism’s role in responding to economic shifts and driving urban economic transformation. Using 2010–2023 panel data from the Yangtze River Economic Belt (YREB) and a “measurement—evolution—disparity—diagnosis” framework, this study examines their coupling coordination via the coupling coordination degree (CCD) model, kernel density estimation, Gini coefficient decomposition, and influence coordination force index, elucidating spatiotemporal evolution, regional disparities, and drivers. The results show: (1) YREB synergies strengthened significantly, with ER and HQTD increasingly reinforcing each other; (2) Eastern coordination levels markedly exceeded central and western ones, reflecting persistent regional imbalances; (3) Coupling coordination converged toward higher levels, with inter-city gaps narrowing. Recommendations include enhancing regional coordination, balancing ecology and economy, fostering industrial innovation, and promoting social participation. This study provides empirical support for integrated, sustainable regional economic-tourism development. Full article

To address the security and stability requirements of renewable energy clusters under extreme weather conditions, this study investigates the coordinated voltage support mechanisms between grid-following and grid-forming converters. This paper proposes an emergency control strategy suitable for such scenarios. First, a reactive power-voltage control architecture for new energy units is constructed to clarify the information interaction process. A mode-based coordinated strategy is designed: during steady-state voltage support, grid-following units adopt reactive power-voltage droop control for voltage regulation, while grid-forming units achieve autonomous support based on the virtual synchronous generator algorithm. During low-voltage ride-through, both types of units are controlled to output corresponding reactive power according to the depth of voltage drop until the voltage is restored. Hardware-in-the-loop simulation verification shows that under steady-state conditions, the strategy meets the voltage control accuracy requirements, and partial grid-forming transformation can reduce voltage overshoot and accelerate stabilization. During low-voltage ride-through, grid-forming transformation can reduce voltage fluctuations, shorten adjustment time, and mitigate reactive inrush current, effectively enhancing the voltage support capability of renewable energy plants. Full article

In the context of rapid urbanization, human activities have profoundly transformed urban thermal environments. However, most existing studies have focused on single cities or relatively uniform climatic contexts, and the long-term dynamics between land surface temperature (LST) and nighttime light (NTL) across urban–rural gradients in diverse climates remain insufficiently explored. This gap limits a systematic understanding of how human activities and thermal environments co-evolve under varying regional conditions. To address this gap, we selected ten representative cities spanning multiple climate zones in China. Using MODIS LST and NTL datasets from 2000 to 2020, we developed an urban–rural gradient analysis framework to systematically assess the spatiotemporal response patterns and coupling mechanisms between LST and NTL. Our findings reveal the following: (1) From 2000 to 2020, NTL exhibited a pronounced upward trend across all climate zones, most notably in the marginal tropical humid region, while LST changes were relatively moderate. (2) LST and NTL displayed power-law distributions along urban–rural transects, marked by steep declines in monocentric cities and gradual transitions in polycentric cities, with sharper thermal gradients in northern and inland areas and more gradual transitions in southern and coastal regions. (3) The long-term increase in NTL was most evident in suburban areas (0.94 nW/cm²/sr/a), surpassing that in urban cores (0.68 nW/cm²/sr/a) and rural zones (0.60 nW/cm²/sr/a), with inland cities (0.84 nW/cm²/sr/a) outpacing their coastal counterparts. Although LST changes were modest, suburban warming (0.16 ± 0.08 °C/a) was over twice that of urban and rural areas. Notably, the synergistic escalation of light and heat was most pronounced in tropical and subtropical cities. (4) Eastern coastal cities exhibited strongly synchronized rises in NTL and LST, whereas cities in the plateau, temperate semi-arid, and mid-temperate arid regions showed clear decoupling. Along urban–rural gradients, NTL–LST correlations generally weakened from urban centers to peripheries, yet coupling coordination peaked in fringe areas (mean = 0.63), underscoring pronounced spatial heterogeneity. This study advances our understanding of the spatiotemporal coupling of urban light and heat under varying climatic and urbanization contexts, offering critical insights into managing urban thermal environments. Full article