Industrialization Promotes Global Common Development

World history shows that industrialization has been an effective driver of economic growth through its creation of job opportunities,promotion of technological innovation,and raising of national income.

Pattern of Opening Up,Integration and Reshaping Economic Geography——A New Economic Geography Analysis of the Belt and Road Initiative and the Yangtze River Economic Belt

Since the 18 th National Congress of the Communist Party of China,the central government has implemented several regional development plans,including the Belt and Road Initiative and the Yangtze River Economic Belt,aiming to reshape the economic geography of China.This paper is based on the Belt and Road Initiative and the Yangtze River Economic Belt and outlines the pattern of opening up.To analyze the impact of the pattern of opening up on the regional integration of China's economic geography,this paper has developed a new economic geography model comprised of four regions and two countries.From this,it draws some conclusions.First,the change of pattern of opening up will lead to shifting centripetal and centrifugal forces from the international market.The greater the scale of neighboring markets,the stronger the agglomeration force will be; the more product varieties made in neighboring countries,the more potent its dispersion force.Second,developing an inland international trade corridor will decentralize industry distribution and reduce the impact of external market integration on home countries.Third,the inland international trade corridor could alter the effect of domestic market integration on the economic geography.When domestic integration occurs prior to international integration,further integration of a domestic market leads to greater industrial distribution along a bell-shaped curve,which describes economic activities from dispersion to agglomeration to decentralization.Therefore,developing an integrated market system of major countries and opening a corridor between China and Europe is not only the key to reshaping China's economic geography but also the path to solving the problems of the Heihe-Tengchong Line.

Covariance Estimation Using High-Frequency Data： An Analysis of Nord Pool Electricity Forward Data

The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM （Capital Asset Pricing Model betas）, derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution （both distributional properties and temporal dependencies） of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.

Deep reinforcement learning for the optimized operation of large amounts of distributed renewable energy assets

This study utilizes machine learning and,more specifically,reinforcement learning(RL)to allow for an optimized,real-time operation of large numbers of decentral flexible assets on private household scale in the electricity domain.The potential and current obstacles of RL are demonstrated and a guide for interested practitioners is provided on how to tackle similar tasks without advanced skills in neural network programming.For the application in the energy domain it is demonstrated that state-of-the-art RL algorithms can be trained to control potentially millions of small-scale assets in private households.In detail,the applied RL algorithm outperforms common heuristic algorithms and only falls slightly short of the results provided by linear optimization,but at less than a thousandth of the simulation time.Thus,RL paves the way for aggregators of flexible energy assets to optimize profit over multiple use cases in a smart energy grid and thus also provide valuable grid services and a more sustainable operation of private energy assets.

Eddy Current Losses in Solid Pole Shoes in a Two-Pole Permanent Magnet Motor

The aim of this paper is to present the eddy current losses in solid pole shoes in a permanent magnet two-pole electric motor. In the presented paper, the authors have chosen to work with three different analytical models, Carter’s theory, Gibb’s theory and Lawrenson’s theory, each with different degree of accuracy and simplifications. The results from the analytical models all present relatively low eddy current losses, giving the designer valuable arguments to utilize solid pole shoes, as a rotor with solid poles is from a construction point of view a more suitable choice, increasing the mechanical stability and reducing the production cost, compared to the laminated design.