China’s Healthcare Reform And Resources Redistribution: Lessons For Emerging Nations

Following China’s recent economic growth and healthcare reform, medical services quickly merged into the market economy. The burden of healthcare expense on the Chinese people has become a serious political issue. This research project reviews the changes in health expenditures made during the last two decades. This paper explores the cause of this rapid change in the healthcare sector and analyzes the corresponding statistics during the entire economic reform period. In addition, the paper articulates that the lack of healthcare coverage existed even before the healthcare reform formally started. As a direct result of this reform, medical resources were quickly concentrated in urban hospitals and the individual out-of¬pocket expense as the share of total health expenditures sharply increased. Recommendations are made for further healthcare reform.Healthcare, Economic transition, Redistribution, China

Study of the export control tendency in the United States and the European Union and the response strategy of S company

The study of the export control tendency in the United States and the European Union and the response strategy of a company is an important issue that has gained increasing attention in recent years. The export control system in the United States and Europe is based on strict regulations, and the implementation of these regulations is crucial for the protection of national security and economic interests. This study aimed to analyze the export control tendency in the United States and Europe and the response strategy of S company. Through a comprehensive analysis of the export control regulations in these regions, we found that the export control system in the United States and Europe is highly regulated, and the implementation of these regulations is crucial for multilateral cooperation, international coordination and trade balance. The export control tendency in the United States and Europe has been affected by various factors, such as economic and political events, technological advancements, Geopolitical Tensions, Innovation and Collaboration. Therefore, the response strategy of a company should take these factors into account when designing its export policy. Overall, this study provides valuable insights into the export control tendency in the United States and Europe and the response strategy of S company, which can be useful for companies operating in these regions and for policymakers and regulatory bodies.O estudo da tendência de controle de exportação nos Estados Unidos e na União Europeia e a estratégia de resposta de uma empresa é um assunto importante que tem ganho atenção crescente nos últimos anos. O sistema de controle de exportação nos Estados Unidos e na Europa é baseado em regulamentos rígidos, e a implementação desses regulamentos é crucial para a proteção da segurança nacional e dos interesses económicos. Este estudo teve como objetivo analisar a tendência de controle de exportação nos Estados Unidos e na Europa e a estratégia de resposta da empresa S. Por meio de uma análise abrangente dos regulamentos de controle de exportação nessas regiões, descobrimos que o sistema de controle de exportação nos Estados Unidos e na Europa é altamente regulamentado e a implementação desses regulamentos é crucial para a cooperação multilateral, coordenação internacional e equilíbrio comercial. A tendência de controle de exportação nos Estados Unidos e na Europa foi afetada por vários fatores, como eventos económicos e políticos, avanços tecnológicos, tensões geopolíticas, inovação e colaboração. Portanto, a estratégia de resposta de uma empresa deve levar em conta esses fatores ao traçar sua política de exportação. No geral, este estudo fornece informações valiosas sobre a tendência de controle de exportação nos Estados Unidos e na Europa e a estratégia de resposta da empresa S, que pode ser útil para empresas que operam nessas regiões e para formuladores de políticas e órgãos reguladores

The Application of Improved Bacteria Foraging Algorithm to the Optimization of Aviation Equipment Maintenance Scheduling

Taking the aviation equipment scheduled maintenance as a prototype, this paper improves a bionic global random search algorithm - bacteria foraging optimization algorithm to solve the task-scheduling problem. Inspired by gene mutation, the activity of bacteria is dynamically adjusted to make good bacteria more capable of action. In addition, a bacterial quorum sensing mechanism is established, which allows bacteria to guide their swimming routes by using their peer experience and enhance their global search capability. Its application to the engineering practice can optimize the scheduling of the maintenance process. It is of great application value in increasing the aviation equipment maintenance efficiency and the level of command automation. In addition, it can improve the resource utilization ratio to reduce the maintenance support cost

Assessing biogeochemical effects and best management practice for a wheat–maize cropping system using the DNDC model

Contemporary agriculture is shifting from a single-goal to a multi-goal strategy, which in turn requires choosing best management practice (BMP) based on an assessment of the biogeochemical effects of management alternatives. The bottleneck is the capacity of predicting the simultaneous effects of different management practice scenarios on multiple goals and choosing BMP among scenarios. The denitrification–decomposition (DNDC) model may provide an opportunity to solve this problem. We validated the DNDC model (version 95) using the observations of soil moisture and temperature, crop yields, aboveground biomass and fluxes of net ecosystem exchange of carbon dioxide, methane, nitrous oxide (N2O), nitric oxide (NO) and ammonia (NH3) from a wheat–maize cropping site in northern China. The model performed well for these variables. Then we used this model to simulate the effects of management practices on the goal variables of crop yields, NO emission, nitrate leaching, NH3 volatilization and net emission of greenhouse gases in the ecosystem (NEGE). Results showed that no-till and straw-incorporated practices had beneficial effects on crop yields and NEGE. Use of nitrification inhibitors decreased nitrate leaching and N2O and NO emissions, but they significantly increased NH3 volatilization. Irrigation based on crop demand significantly increased crop yield and decreased nitrate leaching and NH3 volatilization. Crop yields were hardly decreased if nitrogen dose was reduced by 15% or irrigation water amount was reduced by 25%. Two methods were used to identify BMP and resulted in the same BMP, which adopted the current crop cultivar, field operation schedules and full straw incorporation and applied nitrogen and irrigation water at 15 and 25% lower rates, respectively, than the current use. Our study indicates that the DNDC model can be used as a tool to assess biogeochemical effects of management alternatives and identify BMP

Building Detection using Aerial Images and Digital Surface Models

In this paper a method for building detection in aerial images based on variational inference of logistic regression is proposed. It consists of three steps. In order to characterize the appearances of buildings in aerial images, an effective bag-of-Words (BoW) method is applied for feature extraction in the first step. In the second step, a classifier of logistic regression is learned using these local features. The logistic regression can be trained using different methods. In this paper we adopt a fully Bayesian treatment for learning the classifier, which has a number of obvious advantages over other learning methods. Due to the presence of hyper prior in the probabilistic model of logistic regression, approximate inference methods have to be applied for prediction. In order to speed up the inference, a variational inference method based on mean field instead of stochastic approximation such as Markov Chain Monte Carlo is applied. After the prediction, a probabilistic map is obtained. In the third step, a fully connected conditional random field model is formulated and the probabilistic map is used as the data term in the model. A mean field inference is utilized in order to obtain a binary building mask. A benchmark data set consisting of aerial images and digital surfaced model (DSM) released by ISPRS for 2D semantic labeling is used for performance evaluation. The results demonstrate the effectiveness of the proposed method