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Nowadays, the process of urbanization is accelerating, and the density of buildings is increasing rapidly. Natural ventlation is an energy-saving way of building ventilation and to solve the issue of building overheating. The buildings are all considered as cubes and their arrays are evenly distributed. The results from nearly 100 cases show density is the main factor in uniform arrays and not much difference between the staggered and normal arrangements if consider a year. The method can reflect the ventilation capacity of the buildings, which is somewhat inverse to the air age but different meaning. It can be used to guide the layout and planning in early design stage.

As the backbone of the national innovation system, enterprises are the key drivers of economic development and environmental sustainability. However, at the microlevel, research in this area is lacking, as attention is paid on the comprehensive capabilities of top managers, industrial heterogeneity, and heterogeneous green innovation (GI), including inventive innovation and utility innovation. Based on Upper Echelons Theory, this paper constructs a research framework to explore and empirically analyze the specific impact of managerial capacity (MA) of top managers, as "gatekeepers" of enterprise decision‐making, on the heterogeneous enterprise GI, as well as its potential mechanism. Our results shows that (1), overall, MA can significantly promote GI of enterprises. Interestingly, compared with green strategic innovation, managerial capacity has a greater effect on green inventive innovation; (2) based on industrial heterogeneity, in heavy‐polluting industries, managerial capacity is more likely to promote green strategic innovation rather than green inventive innovation; (3) further analysis shows that enterprise value, internal control quality, and financing constraints are important mechanisms; and (4) the moderating effect of external environment shows that to some extent either the regional marketization level or management capabilities can drive GI. This paper has practical implications for policymakers and corporate managers adopting the management heterogeneity perspective and suggests areas for future studies in this field to promote green low‐carbon transition. [ABSTRACT FROM AUTHOR]

Variable Elimination (VE) is the most basic one of many Bayesian network inference algorithms. The speed and complexity of reasoning mainly depend on the order of elimination. Finding the optimal elimination order is a Nondeterministic Polynomial Hard (NP-Hard) problem, which is often solved by heuristic search in practice. In order to improve the speed of reasoning of the variable elimination method, the minimum, maximum potential, minimum missing edge and minimum added complexity search methods are studied. The Asian network is taken as an example to analyze and calculate the complexity and elimination of the above search method. Meta-order, through MATLAB R2018a, the above different search methods were constructed and reasoned separately. Finally, the performance of the four search methods was compared by inference time analysis. The experimental results show that the minimum increase complexity search method is better than other search methods, and the average time consuming is at least 0.012s, which can speed up the reasoning process of Bayesian network.

Carbon emissions have become a global issue of increasing concern due to their detrimental impact on the environment. Efforts to combat rising emissions have been taken globally. Despite China's commitment to globalization, policymakers have faced challenges in adequately addressing this pressing issue. This paper aims to fill this gap by exploring a specific aspect of international trade, namely service trade. We theoretically analyzed the impact of service trade on carbon emissions and then empirically examined the impact using panel data from 2009 to 2019 of 30 provincial regions in China. Specifically, a non-linear model was used to capture the direct effect, particularly the potential non-linear relationship; a mediating effect model was applied to investigate the indirect effects; and a panel quantile model was adopted to examine the heterogeneity of the impact across different levels of carbon emissions. The research revealed: (1) The impact of service trade on carbon emissions exhibits a non-linear characteristic with a significant inverted U-shaped relationship being evident, indicating that the development of service trade can ultimately contribute to carbon reduction; (2) service trade can directly impact carbon emissions through its scale effect, while mechanism analysis showed that service trade can indirectly affect carbon emissions through its technological and structural effects, with carbon emission reduction also relying on these mechanisms; (3) There is significant heterogeneity in the impact of service trade on carbon emissions across geographic regions and at different levels of carbon emissions in China. [ABSTRACT FROM AUTHOR]

The precision of numerical overland flow models is limited by their computational cost. A GPU-accelerated 2D shallow flow model is developed to overcome this challenge in this study. The model employs a Godunov-type finite volume method (FVM) to solve shallow water equations (SWEs) with unstructured grids, while also considering rainfall, infiltration, bottom slope, and friction source terms. The numerical simulation demonstrates that this model has well-balanced and robust properties. In an experiment of urban rain-runoff and flood, the accuracy and stability of the model are further demonstrated. The model is programmed with CUDA, and each numerical computation term is processed in parallel to adopt multi-thread GPU acceleration technology. With the GPU computation framework, this model can achieve a speeding up ration around 75 to single-thread CPU in the dam-break flow for a large-scale application. [ABSTRACT FROM AUTHOR]