As an important ecosystem type in the coastal zone, mangroves have important ecological functions, such as maintaining coastal biodiversity, preventing wind and consolidating the coast, promoting silt and building land. It is of great significance to understand the protected status of mangroves in the context of climate change and rapid urbanization. Based on the mangrove classification data from remote sensing interpretation, through vacancy analysis, the in-situ protection status of mangroves in China is analyzed. The results show that the total area of mangroves distributed in China is 264 km2 (excluding the statistical data of Hong Kong, Macao and Taiwan), of which 61.4% are protected in natural reserves. In terms of the main provinces where mangroves are distributed, the mangrove area distributed in Hainan Province is small but the protection proportion is high, while the mangrove area distributed in Guangxi and Guangdong Province is large but the proportion of protected areas is relatively low. Among the three mangrove types, Rhizophora apiculate-Xylocarpus granatum and Rhizophora stylosa-Bruguiera gymnorrhiza had high proportions (>90%) covered by reserves, but relatively small areas. In contrast, Kandelia candel-Aegiceras corniculatum-Avicennia marina had relatively low reserve coverage (52.6%), but a large area. The study puts forward the key areas of mangrove distribution outside the nature reserve, and suggests that they should be protected by delimiting ecological protection red lines.
With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.
This study provides an empirical examination of the design and modification of China’s urban social security programme. In doing so, this study complements the popular assumption regarding the correlation between economic growth and social security development. Focusing on the economic and political motivations behind the ruling party’s decision to implement social security, this study first discusses the modification of urban social security and welfare in China. It then empirically demonstrates the mechanisms behind the system’s operation. This study proposes the following hypothesis: in a country like China, a change in the doctrine of the ruling party will affect government alliances, negating the positive impact of economic growth on the development of social security. In demonstrating this hypothesis, this study identifies a political precondition impacting the explanatory power of popular conceptions of social security development.
Management education in health service industry is essential to enhance systems performance and should offer a broad curriculum that contain the context of practice, research awareness and skills of critical appraisal, a grounding in a range of disciplines and a reflective approach towards general management skill. With the improvement of living standard and significant growth of aging population, there is an obvious gap between health service coverage and the demand in China, especially the shortage of workforce with professional health service management knowledge. The objective of this essay is to compare the element of health service management education in China and British.
Chinese multinational enterprises (MNEs) have increasingly engaged in outward foreign direct investment in recent years, and particularly into the infrastructure sector of developing economies. This has been prompted by the infrastructure-led economic integration plan of China’s Belt and Road Initiative. However, such collaboration faces many challenges. Infrastructure projects are often undertaken in industries, countries, and regions posing particular and difficult challenges, and with divergent, often conflicting interests, with the ensuing conclusion that the MNE is simply exploiting the project and not delivering value to the host country. Overall, not only does the infrastructure project have to be well-functioning with expected returns (or savings) realized, but these projects face close scrutiny from local communities, labor, opposition parties, neighboring countries, and various international bodies and nonprofits, requiring delicate handling of the principals involved. The unfolding of these issues and their management by the multinational are examined through an in-depth longitudinal case study. The data are drawn from major participants and stakeholders around a leading Chinese MNE and the mega project of the construction of a major hydropower plant in Pakistan.
Copyright © by EnPress Publisher. All rights reserved.