Land use as for human-circumstance interaction is as we all know changed the global land surface sharply and continuously. Farmland abandonment is the phenomenon of going extreme of marginal of land use, which exert positive and negative impacts on our living circumstances. In order to map the extent of farmland abandonment of Zhejiang Province, we try to use the geo-big data analysis platform to perform the massive data preprocessing and map the extent of farmland abandonment of the study area based on multi-source land use and land cover data. Then we execute landscape pattern analysis using landscape pattern analysis software and spatial auto-correlation (Moran's I) analysis based on ArcGIS and Fragstats software. We found that the area of farmland is about 16.32% on account of all land use types, which is 1.89104 km2. While the whole area of FA is 1.72 × 108 m2, and the farmland abandonment ratio is 1.65%. AF's area is about 1.95 × 109 m2, and the continuous cultivation ratio is 18.69%. The landscape fragmentation, landscape aggregation and landscape diversity of FA, AF and FL are different. At the same time, the spatial auto-correlation of FA and AF are dominant high congregation and low discrete. At last, we compared our calculated results with the existed research results which demonstrate our research does scientific convincible. We also make futural prospects prediction and show the research deficiency as well as bring out some policy implications based on our research, which means build proper land use management regulation and decrease the farmland abandonment on account of the premise of suitable land use policies.

One crucial metric for estimating a reservoirs and dam’s lifespan is sedimentation. It is dependent upon sediment output, which in turn is dependent upon soil erosion. The study area, the Aguat Wuha Dam, was located in Simada woreda, of northwestern parts of Ethiopia. And the study's goal was to use Arc GIS and RUSLE adjusted to Ethiopian conditions to assess potential soil erosion and sediment output from the watershed and identify hotspot locations for appropriate planning for erosion and sedimentation problem management techniques to make the outputs of the dam project more productive and effective for the proposed and suggested purpose of the dam. To predict the geographical patterns of soil erosion in the watershed, the Geographic Information System (GIS) was combined with the revised universal soil loss equation (RUSLE). A soil erosion map was produced using ArcGIS by utilizing all of the model's parameters, including Erosivity, erodibility, steepness, land use, land cover, and supportive practice factors. The watershed's yearly soil loss varies from 0 to 413.86 tons/ha. In order to determine the erosion hotspot area, the average annual soil loss value was discovered to be 9.24 tons/ha/year and was categorized into six erosion severity classes: low, moderate, high, very high, severe, and very severe. These findings indicated that 162.57 ha and 699.17 ha of the watershed were considered to be extremely and severely vulnerable to soil erosion, respectively. It was discovered that the anticipated sediment yield supplied to the outlet varied from 0 to 104.94 tons/ha/year. By standing from the implications of the assessments of the geological, geotechnical, topographical, and socioenvironmental considerations Watershed management is the most effective way to reduce the amount of sediment produced and the amount that enters the reservoir among the several reservoir sedimentation control options that are available.

Heat transfer fluids (HTFs) are critical in numerous industrial processes (e.g., the chemical industry, oil and gas, and renewable energy), enabling efficient heat exchange and precise temperature control. HTF degradation, primarily due to thermal cracking and oxidation, negatively impacts system performance, reduces fluid lifespan, and increases operational costs associated with correcting resulting issues. Regular monitoring and testing of fluid properties can help mitigate these effects and provide insights into the health of both the fluid and the system. To date, there is no extensive literature published on this topic, and the current narrative review was designed to address this gap. This review outlines the typical operating temperature ranges for industrial heat transfer fluids (i.e., steam, organic, synthetic, and molten salts) and then focuses specifically on organic and synthetic fluids used in industrial applications. It also outlines the mechanisms of fluid degradation and the impact of fluid type and condition. Other topics covered include the importance of fluid sampling and analysis, the parameters used to assess the extent of thermal degradation, and the management strategies that can be considered to help sustain fluid and system health. Operating temperature, system design, and fluid health play a significant role in the extent of thermal degradation, and regular monitoring of fluid properties, such as viscosity, acidity, and flash point, is crucial in detecting changes in condition (both early and ongoing) and providing a basis for decisions and interventions needed to mitigate or even reverse these effects. This includes, for example, selecting the right HTF for the specific application and operating temperature. This article concludes that by understanding the mechanisms of thermal degradation and implementing appropriate management strategies, it is possible to sustain the lifespan of thermal fluids and systems, ensure safe operation, and help minimise operational expenditure.

With the wide application of the Internet and smart systems, data centers (DCs) have become a hot spot of global concern. The energy saving for data centers is at the core of the related works. The thermal performance of a data center directly affects its total energy consumption, as cooling consumption accounts for nearly 50% of total energy consumption. Superior power distribution is a reliable method to improve the thermal performance of DCs. Therefore, analyzing the effects of different power distribution on thermal performance is a challenge for DCs. This paper analyzes the thermal performance numerically and experimentally in DCs with different power distribution. First, it uses Fluent simulate the temperature distribution and flow field distribution in the room, taking the cloud computing room as the research object. Then, it summarizes a formula based on the computing power distribution in a certain range by the numerical and experimental analysis. Finally, it calculates an optimal cooling power by analyzing the cooling power distribution. The results shows that it reduces the maximum temperature difference between the highest temperature of the cabinet from 5-7k to within 1.2k. In addition, the cooling energy consumption is reduced by more than 5%.

The sense of belonging in any organization is vital to generate a work motivation with the objective of a good organizational performance, because of this, companies usually take this point into account, ensuring that this leads to greater performance. For this reason, the objective of this article is to determine the relationship between the sense of belonging and the work motivation in the workers of a small Peruvian research company. For this purpose, a quantitative methodology was used, with a cross-sectional descriptive design. The instrument used was a survey consisting of 10 items, which were interpreted using the Likert scale. The survey was conducted and delivered to 24 workers, who were selected by non-probabilistic convenience sampling. After verifying the validity of the instrument and the study variables by means of Cronbach's Alpha statistic, we proceeded to determine the existence of correlation between the variables, which, using Spearman's Rho coefficient, obtained a 70.2% which demonstrates a moderate positive correlation, therefore it indicates that employees feel highly motivated as they feel an indispensable part of the company, therefore they feel job satisfaction by being part of the organization.

Small and medium-sized enterprises (SMEs) play a critical role in achieving environmental sustainability, particularly in developing economies where regulatory enforcement and resource constraints remain significant challenges. Drawing on Institutional Theory, this study examines how green leadership influences environmental performance in Ghanaian SMEs, with digital innovation as a mediating variable and environmental culture as a moderating variable. Institutional Theory provides the conceptual foundation for explaining how normative pressures embedded in leadership values and organizational culture, alongside mimetic pressures associated with digital innovation adoption, shape firms’ environmental outcomes. Using survey data collected from SMEs in Ghana and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results revealed that green leadership has a significant positive effect on both digital innovation and environmental performance. Digital innovation also significantly enhances environmental performance and partially mediates the relationship between green leadership and environmental performance. Notably, the findings demonstrated that environmental culture significantly moderates the relationship between digital innovation and environmental performance, with the effect stronger in organizations with a well-developed environmental culture. This indicates that internalized environmental values amplify the effectiveness of digital innovation initiatives. The study contributes to the sustainability and organizational literature by extending Institutional Theory to the SME context in a developing economy and by clarifying the conditional role of environmental culture in translating digital innovation into superior environmental performance. Practically, the findings suggest that SME leaders and policymakers should promote environmentally oriented leadership, invest in digital innovation, and cultivate strong environmental cultures to enhance sustainability outcomes.