Optimal coordination strategy of regional vertical emission abatement collaboration in a low-carbon environment

This study introduces a time factor into a low-carbon context, and supposes the contamination control state of local government and the ability of polluting enterprise to abate emissions as linear increasing functions in a regional low-carbon emission abatement cooperation chain. The local government effectuates and upholds the low-carbon development within the jurisdiction that is primarily seeking to transform regional economic development modes, while the polluting enterprise abates the amounts of emitted carbon in the entire period of product through simplifying production, facilitating decontamination, and adopting production technology, thus leading to less contamination. On that basis, we infer that the coordinated joint carbon reduction model and two decentralization contracts expound the dynamic coordination strategy for a regional cooperation chain in terms of vertical carbon abatement. Furthermore, feedback equilibrium strategies that are concerned with several diverse conditions are compared and analyzed. The main results show that a collaborative centralized contract is able to promote the regional low-carbon cooperation chain in order to achieve a win–win situation in both economic and environmental performance. Additionally, the optimal profits of the entire regional low-carbon cooperation channel under an integration scenario evidently outstrip that of two non-collaborative decentralization schemes. Eventually, the validity of the conclusions is verified with a case description and numerical simulation, and the sensitivity of the relevant parameters is analyzed in order to lay a theoretical foundation and thus facilitate the sustainable development of a regional low-carbon environment

Theoretical Guidance on Evacuation Decisions after a Big Nuclear Accident under the Assumption That Evacuation Is Desirable

The development of nuclear power is a major measure for implementing energy-saving and emission reduction strategies all over the world. For a long time, the hazards of nuclear accidents have been obstacles to the development of nuclear power. Temporary evacuation is the fastest and most effective emergency measure to ensure the safety of residents in a short period of time after a nuclear accident. Numerous nuclear accident emergency management personnel make judgments based on personal work experience and subjective awareness when formulating a nuclear accident emergency evacuation plan. How to make a scientific and reasonable decision on the emergency evacuation of nuclear accidents in the shortest time is a common problem faced by many emergency departments when a nuclear accident occurs. In a complex and ever-changing radiation environment, how to maximize the use of limited information and make decisions quickly in an uncertain environment is a core issue that effectively reduces the risk of nuclear accidents. This paper constructs a set of assessment system of nuclear accident emergency evacuation plan selection based on the characteristics of nuclear accident emergencies under uncertain environmental conditions. It uses triangular fuzzy language to describe nuclear accident emergency evacuation decision plans and the weighting of relevant factors. Additionally, the K-means clustering method is used to calculate the weight of experts, which reduces the influence of subjective factors considered by decision makers. Finally, a decision model for emergency evacuation of nuclear accidents is constructed based on the TOPSIS decision model

Research on Image Denoising in Edge Detection Based on Wavelet Transform

Photographing images is used as a common detection tool during the process of bridge maintenance. The edges in an image can provide a lot of valuable information, but the detection and extraction of edge details are often affected by the image noise. This study proposes an algorithm for wavelet transform to denoise the image before edge detection, which can improve the signal-to-noise ratio of the image and retain as much edge information as possible. In this study, four wavelet functions and four decomposition levels are used to decompose the image, filter the coefficients and reconstruct the image. The PSNR and MSE of the denoised images were compared, and the results showed that the sym5 wavelet function with three-level decomposition has the best overall denoising performance, in which the PSNR and MSE of the denoised images were 23.48 dB and 299.49, respectively. In this study, the canny algorithm was used to detect the edges of the images, and the detection results visually demonstrate the difference between before and after denoising. In order to further evaluate the denoising performance, this study also performed edge detection on images processed by both wavelet transform and the current widely used Gaussian filter, and it calculated the Pratt quality factor of the edge detection results, which were 0.53 and 0.47, respectively. This indicates that the use of wavelet transform to remove noise is more beneficial to the improvement of the subsequent edge detection results

Analysis of the Spatial Effect of Fiscal Decentralization and Environmental Decentralization on Carbon Emissions under the Pressure of Officials' Promotion

Using panel data of 30 provinces and regions in Mainland China (excluding Tibet) from 2006 to 2016, the Spatial Durbin Model was employed for the empirical research, and the spatial impact of fiscal decentralization and environmental decentralization on regional carbon emissions were analyzed from the perspective of promotion pressure of officials. The empirical study concludes: ; Fiscal decentralization, both within the region and in its neighborhood, will contribute to carbon emissions in the region; Environmental decentralization will help reduce carbon emissions, while environmental decentralization in neighboring regions will increase carbon emissions in the region; The promotion pressure of officials plays a positive role in moderating the impact of fiscal decentralization on carbon emissions, and at the same time weakens the suppression of carbon emissions by environmental decentralization; From a regional point of view, there is a positive relationship between fiscal decentralization and carbon emissions in various regions; but environmental decentralization has obvious spatial heterogeneity. The research suggests that reducing the degree of local fiscal decentralization, investment in major infrastructure projects involving high carbon emissions should be relatively centralized; appropriately increase the environmental management authority of local environmental protection agencies, fully use the advantages of local environmental protection departments to protect the environment according to local conditions; gradually improve the assessment system for local officials, moderately reduce the proportion of fiscal revenue and GDP assessment in areas with fragile ecological environment, and increase incentives for ecological performance assessment, put the development of low-carbon economy into practice

Research on Image Denoising in Edge Detection Based on Wavelet Transform

Photographing images is used as a common detection tool during the process of bridge maintenance. The edges in an image can provide a lot of valuable information, but the detection and extraction of edge details are often affected by the image noise. This study proposes an algorithm for wavelet transform to denoise the image before edge detection, which can improve the signal-to-noise ratio of the image and retain as much edge information as possible. In this study, four wavelet functions and four decomposition levels are used to decompose the image, filter the coefficients and reconstruct the image. The PSNR and MSE of the denoised images were compared, and the results showed that the sym5 wavelet function with three-level decomposition has the best overall denoising performance, in which the PSNR and MSE of the denoised images were 23.48 dB and 299.49, respectively. In this study, the canny algorithm was used to detect the edges of the images, and the detection results visually demonstrate the difference between before and after denoising. In order to further evaluate the denoising performance, this study also performed edge detection on images processed by both wavelet transform and the current widely used Gaussian filter, and it calculated the Pratt quality factor of the edge detection results, which were 0.53 and 0.47, respectively. This indicates that the use of wavelet transform to remove noise is more beneficial to the improvement of the subsequent edge detection results

Effects of rural medical insurance on chronically III patients’ choice of the same hospital again in rural Northern China

The emergence of rural health insurance plays a crucial role in alleviating the pressure on rural medical expenditure. Under the current medical system in northern China, rural medical insurance may reduce the free referral of patients with chronic diseases among hospitals. This study was carried out based on the results of an investigation of rural chronically-ill patients in eight county hospitals in northern China, as well as through the comparison and analysis of patients with chronic diseases, considering whether they were with or without rural health insurance. The main results showed that both age (χ2 = 22.9, p < 0.000) and income level (χ2 = 18.5, p < 0.000) had considerable impact on the rural peoples’ willingness to buy health insurance. Meanwhile, both the quality of the hospital’s treatment (B = 0.555, p < 0.000), and service quality (B = 0.168, p < 0.000) had a significant positive correlation with the likelihood of a given patient choosing the same hospital on the next visit, but the medical costs had a significant negative correlation (B = −0.137, p < 0.000). Eventually, it was found that the provision of rural health insurance had weakened the three relationships upon which the aforementioned correlations were based