Search Results (5)

Shanxi Province, a key energy base and water source in China, has long borne the responsibility of supplying external resources. Ensuring the security of its water–energy–food (WEF) resilience has remained a persistent challenge for local authorities. Conventional WEF nexus optimization policies often overlook the heterogeneity of influencing factors arising from geographic variability, leading to generalized approaches that lack precision and efficiency in resource governance. To address these limitations, this study employed the Moran’s I index, exploratory regression analysis, and the geographically weighted regression (GWR) model to investigate the spatial patterns of factors influencing WEF resilience across 11 cities in Shanxi Province from 2014 to 2023. Based on these analyses, the study proposes targeted policy recommendations that account for regional heterogeneity and prioritize differentiated strategies, thereby avoiding the pitfalls of a one-size-fits-all framework. This tailored approach aims to support Shanxi in managing the enduring pressures of external resource supply. The main findings are as follows: (1) WEF resilience in Shanxi exhibited significant spatial autocorrelation, with Moran’s I values ranging from 0.013 to 0.043, confirming the influence of spatial geographic factors on the studied variables and supporting the applicability of the GWR model; (2) key factors influencing WEF resilience included population density, technological innovation, industrial structure, and resource mismatch, with effect sizes ranging from −0.90 to −0.48, 0.68 to 1.01, 0.43 to 0.79, and −0.45 to −0.22, respectively; (3) drawing on the spatially variable impact of these factors, the study offers optimization strategies that emphasize regional specificity and multi-policy prioritization to enhance WEF resilience across Shanxi Province. Full article

This article presents a Blockchain-based solution for the management of multipolicies in insurance companies, introducing a standardized policy model to facilitate streamlined operations and enhance collaboration between entities. The model ensures uniform policy management, providing scalability and flexibility to adapt to new market demands. The solution leverages Merkle trees for secure data management, with each policy represented by an independent Merkle tree, enabling updates and additions without altering existing policies. The architecture, implemented on a private Ethereum network using Hyperledger Besu and Tessera, ensures secure and transparent transactions, robust dispute resolution, and fraud prevention mechanisms. The validation phase demonstrated the model’s efficiency in reducing data redundancy and ensuring the consistency and integrity of policy information. Additionally, the system’s technical management has been simplified, operational redundancies have been eliminated, and privacy is enhanced. Full article

Forests are the most important part of terrestrial ecosystems. In the context of China’s industrialization and urbanization, mining activities have caused huge damage to the forest ecology. In the Ulan Mulun River Basin (Ordos, China), afforestation is standard method for reclamation of coal mine degraded land. In order to understand, manage and utilize forests, it is necessary to collect local mining area’s tree information. This paper proposed an improved Faster R-CNN model to identify individual trees. There were three major improved parts in this model. First, the model applied supervised multi-policy data augmentation (DA) to address the unmanned aerial vehicle (UAV) sample label size imbalance phenomenon. Second, we proposed Dense Enhance Feature Pyramid Network (DE-FPN) to improve the detection accuracy of small sample. Third, we modified the state-of-the-art Alpha Intersection over Union (Alpha-IoU) loss function. In the regression stage, this part effectively improved the bounding box accuracy. Compared with the original model, the improved model had the faster effect and higher accuracy. The result shows that the data augmentation strategy increased AP by 1.26%, DE-FPN increased AP by 2.82%, and the improved Alpha-IoU increased AP by 2.60%. Compared with popular target detection algorithms, our improved Faster R-CNN algorithm had the highest accuracy for tree detection in mining areas. AP was 89.89%. It also had a good generalization, and it can accurately identify trees in a complex background. Our algorithm detected correct trees accounted for 91.61%. In the surrounding area of coal mines, the higher the stand density is, the smaller the remote sensing index value is. Remote sensing indices included Green Leaf Index (GLI), Red Green Blue Vegetation Index (RGBVI), Visible Atmospheric Resistance Index (VARI), and Normalized Green Red Difference Index (NGRDI). In the drone zone, the western area of Bulianta Coal Mine (Area A) had the highest stand density, which was 203.95 trees ha⁻¹. GLI mean value was 0.09, RGBVI mean value was 0.17, VARI mean value was 0.04, and NGRDI mean value was 0.04. The southern area of Bulianta Coal Mine (Area D) was 105.09 trees ha⁻¹ of stand density. Four remote sensing indices were all the highest. GLI mean value was 0.15, RGBVI mean value was 0.43, VARI mean value was 0.12, and NGRDI mean value was 0.09. This study provided a sustainable development theoretical guidance for the Ulan Mulun River Basin. It is crucial information for local ecological environment and economic development. Full article

An edge computing system is a distributed computing framework that provides execution resources such as computation and storage for applications involving networking close to the end nodes. An unmanned aerial vehicle (UAV)-aided edge computing system can provide a flexible configuration for mobile ground nodes (MGN). However, edge computing systems still require higher guaranteed reliability for computational task completion and more efficient energy management before their widespread usage. To solve these problems, we propose an energy efficient UAV-based edge computing system with energy harvesting capability. In this system, the MGN makes requests for computing service from multiple UAVs, and geographically proximate UAVs determine whether or not to conduct the data processing in a distributed manner. To minimize the energy consumption of UAVs while maintaining a guaranteed level of reliability for task completion, we propose a stochastic game model with constraints for our proposed system. We apply a best response algorithm to obtain a multi-policy constrained Nash equilibrium. The results show that our system can achieve an improved life cycle compared to the individual computing scheme while maintaining a sufficient successful complete computation probability. Full article

As one of the emerging research fields of sustainability management, Organizational Citizenship Behavior (OCB), especially its influence on project performance, has been drawing increased attention both in the academic and industrial areas. Nevertheless, existing studies mainly examine the static relationship between OCB and project performance but fail to explore the dynamic characteristic of the relationship as a project may evolve and proceed over the time. Therefore, this paper aims to evaluate the dynamic impacts of OCB on the performance of megaprojects with the assistance of a system dynamic model. Four causal feedback loops and a stock-flow diagram were developed to illustrate the dynamic influencing mechanism, and three distinct policies quantitatively simulated the possible impacts arising from the changes of OCB on the whole system and, specifically, on the performance megaproject. The results show that an increase in the AIRPP (actual increasing rate of potential promotion) exerts significant influence on the improvement in OCB and the performance of megaprojects. The higher the AIRPP in the multi-policy scenario, the higher the OCB and the performance. One major contribution is that this study is one of the first studies to explore the potential use of system dynamics to model megaproject organizational behavior and its performance with implications in both the practical and cultural promotion of OCB. Full article