Search results

The article examines the process of formation of the russian model of state-confessional relations, which develops in conditions of equality of all traditional religions before the law. Its formation is based on an understanding of the importance of building constructive relations between the state and religious associations in Russian society, where the demand for the preservation of traditional values dominates.According to the author, currently the Russian model of state-confessional relations is still at the stage of formation, but it is already possible to identify trends and contours of its development. The specificity of this model lies in the fact that the current legal norm of separation of the state and religious associations is not considered as a barrier excluding any contacts between them. The importance of establishing partnerships between authorities and religious associations is determined by the need to ensure stability in a multi-confessional and multi-ethnic Russian society.During the period of the Special Military Operation in Ukraine and the confrontation with the bloc of western countries, criticism of the emerging state-confessional relations from the preachers of radical Islam living on the territory of Ukraine, Turkey and a number of European countries is increasing. The North Caucasian muftiats working in the Russian legal space are mainly the object of information pressure from abroad.

© 2019, Emerald Publishing Limited. Purpose: Consumption volatility is a key source of economic growth volatility; thus, it is an important factor in designing macroeconomic policy. The purpose of this paper is to investigate the factors that determine household consumption volatility, using urban household survey (UHS) data over the period 2002–2009 in 18 provinces in China. Design/methodology/approach: Both a traditional variance decomposition method and an advanced variance decomposition method are used. Findings: The traditional variance decomposition method suggests that heterogeneity of consumption goods is the key to analyze consumption volatility in China. Consumption of transportation makes the highest aggregate contribution and per-unit volatility in consumption volatility, whereas consumption of food makes the second highest aggregate contribution and the lowest per-unit volatility. Further investigation with the advanced variance decomposition method, which allows the authors to capture intertemporal dynamics and cross-household differences simultaneously, finds that the main factor determining the consumption volatility in China is intertemporal dynamics, rather than cross-household differences. Research limitations/implications: Future research could fruitfully explore four issues. First, consumption upgrading has increased the volatility of China's household consumption. How much will this affect economic growth in China under its "new normal" conditions, and how should the Chinese government respond? Second, differences between UHS data and aggregate data in the calculations of consumption risk sharing need to be investigated. Third, it is important to investigate the channels through which the Chinese government can enhance its ability to spread consumption risks and thus reduce consumer consumption volatility. Finally, further study could extend the current 18 provinces to a nation-wide sample and update the data beyond 2009 to estimate the impact of the global financial crisis. Practical implications: The results suggest that when policy makers design macroeconomic policies to smooth consumption volatility, they should consider heterogeneity in household consumption goods, regional disparity and intertemporal dynamics simultaneously. Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world. Social implications: Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world. Originality/value: This paper fills this gap by using China's UHS data to assess consumption volatility from the perspectives of heterogeneity in household consumption goods, cross-household differences and intertemporal dynamics. We make three contributions to the literature. The first contribution of this paper consists of demonstrating the contributions of heterogeneity in household consumption goods to consumption volatility. The second contribution consists of using the advanced variance decomposition method proposed by Crucini and Telmer (2012). This decomposition methodology allows the authors to examine whether household consumption volatility is due to cross-household differences or intertemporal dynamics. The third contribution is that this paper takes Chinese residents' consumption fluctuations as the starting point to analyze the impact of consumption fluctuations on the future trend of China's economy.

At present the land subsidence has been the main geological disaster in the plain area of China, and became one of the most serious disaster that restrict the social and economic sustainable development, it also is an important content in the project of national geographic conditions monitoring. With the development of economy and society, Beijing as the capital of China has experienced significant population growth in the last few decades which led to over-exploitation of the ground water to meet the water demand of more than 20 million inhabitants, especially in the urban region with high population density. However, the rainfall and surface runoff can't satisfy the need of aquifer recharge that product the land subsidence. As China's political center and a metropolis, there are a lot of large constructions, underground traffic projects and complicated municipal pipeline network, and Beijing is also an important traffic hub for national railway and highway network, all of them would be threatened by the land subsidence disaster. In this article the author used twenty ENVISAT Synthetic Aperture Radar (SAR) images acquired in 2008 June–2010 August and ten TerraSAR images acquired in 2011 June–2012 September were processed with Small Baseline Subset SAR Interferometry (SBAS-InSAR) techniques, to investigate spatial and temporal patterns of land subsidence in the urban area of Beijing.

At present the land subsidence has been the main geological disaster in the plain area of China, and became one of the most serious disaster that restrict the social and economic sustainable development, it also is an important content in the project of national geographic conditions monitoring. With the development of economy and society, Beijing as the capital of China has experienced significant population growth in the last few decades which led to over-exploitation of the ground water to meet the water demand of more than 20 million inhabitants, especially in the urban region with high population density. However, the rainfall and surface runoff can't satisfy the need of aquifer recharge that product the land subsidence. As China's political center and a metropolis, there are a lot of large constructions, underground traffic projects and complicated municipal pipeline network, and Beijing is also an important traffic hub for national railway and highway network, all of them would be threatened by the land subsidence disaster. In this article the author used twenty ENVISAT Synthetic Aperture Radar (SAR) images acquired in 2008 June–2010 August and ten TerraSAR images acquired in 2011 June–2012 September were processed with Small Baseline Subset SAR Interferometry (SBAS-InSAR) techniques, to investigate spatial and temporal patterns of land subsidence in the urban area of Beijing.

Surface faults related to land subsidence have been observed in coastal cities, such as Nantong, Yancheng, and Lian Yungang, in Jiangsu Province (CAJS) since the early 1970s. Nowadays, increases flooding and rising sea levels are attributed to subsidence caused by groundwater pumping. In this work we present a brief description of land subsidence in CAJS, we examine the mechanisms of land subsidence induced mainly by groundwater pumping and its evolution and economic implications as well as the implemented measures by the local government to prevent new damage.

© 2016 by the authors. This study analyzes the economic system dynamics of investment in real estate from mainly four participants in China. Local governments limit the supply of commercial and residential land to raise fiscal revenue, and expand debts by land mortgage to develop industrial zones and parks. Led by local government, banks and real estate development enterprises forge a coalition on real estate investment and facilitate real estate price appreciation. The above theoretical model is empirically evidenced with VAR (Vector Auto Regression) methodology. A panel VAR model shows that land leasing and real estate price appreciation positively affect local government general fiscal revenue. Additional VAR models find that bank credit in addition to private and foreign funds respectively have strong positive dynamic effects on housing prices. Housing prices also have a strong positive impact on speculation from private funds and hot money.

Major depressive disorder (MDD) is a critical cause of morbidity and disability with an economic cost of hundreds of billions of dollars each year, necessitating more effective treatment strategies and novel approaches to translational research. A notable barrier in addressing this public health threat involves reliable identification of the disorder, as many affected individuals remain undiagnosed or misdiagnosed. An objective blood-based diagnostic test using transcript levels of a panel of markers would provide an invaluable tool for MDD as the infrastructure—including equipment, trained personnel, billing, and governmental approval—for similar tests is well established in clinics worldwide. Here we present a supervised classification model utilizing support vector machines (SVMs) for the analysis of transcriptomic data readily obtained from a peripheral blood specimen. The model was trained on data from subjects with MDD (n=32) and age- and gender-matched controls (n=32). This SVM model provides a cross-validated sensitivity and specificity of 90.6% for the diagnosis of MDD using a panel of 10 transcripts. We applied a logistic equation on the SVM model and quantified a likelihood of depression score. This score gives the probability of a MDD diagnosis and allows the tuning of specificity and sensitivity for individual patients to bring personalized medicine closer in psychiatry.

Surface faults related to land subsidence have been observed in coastal cities, such as Nantong, Yancheng, and Lian Yungang, in Jiangsu Province (CAJS) since the early 1970s. Nowadays, increases flooding and rising sea levels are attributed to subsidence caused by groundwater pumping. In this work we present a brief description of land subsidence in CAJS, we examine the mechanisms of land subsidence induced mainly by groundwater pumping and its evolution and economic implications as well as the implemented measures by the local government to prevent new damage.