Search

The implementation of rural entrepreneurship emerges as a pivotal pathway for fostering rural economic growth. However, unsustainable entrepreneurial endeavors have posed notable ecological threats and environmental degradation. Drawing upon the triple bottom line framework, this research devised a comprehensive evaluation system for sustainable rural entrepreneurship, spanning four dimensions: entrepreneurs, economic, social, and environmental aspects. Employing the fuzzy Decision-Making Trial and Evaluation Laboratory (DANP) approach, we delineated the intricate causal relationships among influencing factors and identified key determinants along with their respective weights. Our findings underscore the prominence of economic dimensions in fostering sustainable rural entrepreneurship. Specifically, entrepreneurial motivation, type of entrepreneurship, financial backing, economic value, favorable policy frameworks, and a conducive business environment emerged as pivotal indicators. Notably, the type of entrepreneurship, financial support, economic value, and favorable policies emerged as propelling factors driving sustainable rural entrepreneurial progress. Conversely, entrepreneurial motivation and the business environment manifested as dependent factors within this causal nexus. This study offers valuable managerial implications for entrepreneurial teams and pertinent government agencies, enabling decision-makers to formulate evidence-based strategies aimed at realizing sustainable rural entrepreneurship. [ABSTRACT FROM AUTHOR]

The burgeoning field of fog computing introduces a transformative computing paradigm with extensive applications across diverse sectors. At the heart of this paradigm lies the pivotal role of edge servers, which are entrusted with critical computing and storage functions. The optimization of these servers' storage capacities emerges as a crucial factor in augmenting the efficacy of fog computing infrastructures. This paper presents a novel storage optimization algorithm, dubbed LIRU (Low Interference Recently Used), which synthesizes the strengths of the LIRS (Low Interference Recency Set) and LRU (Least Recently Used) replacement algorithms. Set against the backdrop of constrained storage resources, this research endeavours to formulate an algorithm that optimizes storage space utilization, elevates data access efficiency, and diminishes access latencies. The investigation initiates a comprehensive analysis of the storage resources available on edge servers, pinpointing the essential considerations for optimization algorithms: storage resource utilization and data access frequency. The study then constructs an optimization model that harmonizes data frequency with cache capacity, employing optimization theory to discern the optimal solution for storage maximization. Subsequent experimental validations of the LIRU algorithm underscore its superiority over conventional replacement algorithms, showcasing significant improvements in storage utilization, data access efficiency, and reduced access delays. Notably, the LIRU algorithm registers a 5% increment in one-hop hit ratio relative to the LFU algorithm, a 66% enhancement over the LRU algorithm, and a 14% elevation in system hit ratio against the LRU algorithm. Moreover, it curtails the average system response time by 2.4% and 16.5% compared to the LRU and LFU algorithms, respectively, particularly in scenarios involving large cache sizes. This research not only sheds light on the intricacies of edge server storage optimization but also significantly propels the performance and efficiency of the broader fog computing ecosystem. Through these insights, the study contributes a valuable framework for enhancing data management strategies within fog computing architectures, marking a noteworthy advancement in the field. [ABSTRACT FROM AUTHOR]

New diabatic potential energy surfaces (PESs) for the KH2 system, related to both ground and first excited states, were constructed using only adiabatic electronic energies. The elements of the diabatic potential energy matrix were determined using neural network (NN) method. Prior to calculation, the symmetry constraints of the coupling term were incorporated into the NN code. A comprehensive comparison was undertaken between the topographic characteristics of the newly constructed diabatic PESs and those previously developed using the molecular properties method. To validate the accuracy of the new diabatic PESs, the dynamics calculations of K(4p2P) + H2 (v0 = 1, j0 = 0) reaction were performed based on both new and old diabatic PESs with same parameters. The results indicate that the values based on the new diabatic PESs generally agree well with those from the old ones. In addition, compared with the previous diabatic PESs, the new diabatic PESs can accurately describe the geometric phase effect. [ABSTRACT FROM AUTHOR]

With the rapid development of e-commerce, the backlog of distribution orders, insufficient logistics capacity and other issues are becoming more and more serious. It is very significant for e-commerce platforms and logistics enterprises to clarify the demand of logistics. To meet this need, a forecasting indicator system of Guangdong logistics demand was constructed from the perspective of e-commerce. The GM (1, 1) model and Back Propagation (BP) neural network model were used to simulate and forecast the logistics demand of Guangdong province from 2000 to 2019. The results show that the Guangdong logistics demand forecasting indicator system has good applicability. Compared with the GM (1, 1) model, the BP neural network model has smaller prediction error and more stable prediction results. Based on the results of the study, it is the recommendation of the authors that e-commerce platforms and logistics enterprises should pay attention to the prediction of regional logistics demand, choose scientific forecasting methods, and encourage the implementation of new distribution modes. [ABSTRACT FROM AUTHOR]

Acetaminophen (APAP), commonly used in clinical prescription, has time- and dose-dependent side effects. Thus, further animal study warrants to be investigated to assess possible adverse effect of APAP application. Here, we conducted pre-clinical research to elucidate the molecular mechanism regarding APAP-mediated toxicological action. Our data showed that serous/urinary and hepatic/renal APAP concentrations were significantly increased when compared with normal control, which the liver tissue showed the highest level. As an acute liver damage model induced by APAP, absolute liver weight, serum enzyme (ALT), urine protein content were notably elevated. Representatively, APAP-damaged liver resulted in increased pro-apoptotic Bax and compensatory Ki-67 positive cells, while the number of anti-apoptotic Bcl2 positive cells was reduced. In addition, the immunoactivity markers for NF-κB, TRL4, TNF-α in the kidney were increased, respectively. Furthermore, intracellular TRL4 and TNF-α mRNAs in the liver and kidney showed significant up-regulation. In summary, our current findings demonstrate that APAP-mediated the specific cytotoxicity is linked to the molecular mechanisms of facilitating apoptosis and inflammatory stress in the liver and kidney.