Trend Of Convergence Research Articles

Does vertical environmental protection pressure promote convergence of urban air pollution?

Recent research shows that the annual average concentration and winter average concentration of PM2.5 in Chinese cities have exhibited a convergence trend since 2013. However, the urban air situation in China remains far from ideal. For an authoritative government, vertical environmental protection pressure (VEPP) may be an important mechanism to motivate cities with high PM2.5 concentration levels to reduce haze pollution more rapidly compared to cities with low PM2.5 concentrations. Thus, VEPP could be considered an institutional advantage in China's vertical air pollution allocation strategy. To investigate the impact of the VEPP of Chinese local governments on the convergence of PM2.5 concentrations, this study uses the counterfactual distribution dynamics analysis framework, which combines parametric regression analysis with the nonparametric distribution dynamics technique. The results show that the Chinese government can promote the convergence of air pollution in local cities to a “favorable” level by increasing the pressure of environmental protection. However, merely increasing VEPP will not completely solve the problem of air pollution in Chinese cities during winter months. Compared with the central and western regions, the VEPP of local governments in the eastern region can promote the convergence of the average annual and winter PM2.5 concentrations.

Economic Convergence in Sumatra Island: Stochastic Approach

Purpose: convergence occurs when regions with poor economies tend to grow faster than regions with rich economies, so poorer regions tend to catch up with rich regions in terms of GRDP or per capita products. The concept of convergence is dividedinto3 (three) namely sigma convergence, absolute convergence, and conditional convergence. This study focuses on analyzing the trend of convergence based on the approach to the concept of convergence with a concern for analysis, namely stochastic convergence.Methods: the analysis of convergence using a stochastic approach and a sigma and beta convergence approach for each province on the island ofSumatraduringthe2011–2020 periods. This research data uses secondary data with a combination of time-series data and cross-sectional data obtained from the Central Statistics Agency, the Ministry of Finance, and the Investment Coordinating Board. Calculation of beta convergence is based on the equation model developed by Barro and Sala-I-Martin (1990) and stochastic convergence based on the measurement model by Ludlow and Enders (2000).Results: the finding from this study shows that there is a stochastic convergence in all provinces on the island of Sumatra which is described based on the Sumatra. The economy has proven Beta convergence which explains the convergence with a relatively low rate of convergence, but the addition of determinant variables such as Domestic Investment and government spending has an impact on increasing the rate of convergence in the island of Sumatra.Conclusions and Relevance: the recommendation for further research emphasizes the spatial interaction between regions because the stochastic stocked test has not been able to see the interdependence between regions that causes convergence.

Makroregionální divergenční a konvergenční trendy světové ekonomiky

Current global trends belong to important branches of economic research. This article discusses changes among different parts of the world: do these changes increase or decrease over time? Are convergent trends more important within the global system than the divergent ones or vice versa? Changes are examined on the base of so-called world's macro-regions over the period 1970-2018, when the bipolar world has changed into a unipolar one and is currently moving towards multipolarity. The study aims to determine which global processes show divergent/convergent trends using different methodological approaches. It also discusses and explains the changing character of trends over time. The authors reach conclusions that exclude one-sidedness of the observed development trends, which derive from the multiplicity of factors influencing them.

Research on carbon productivity and its spatial convergence of steel industry in China.

The Global-Malmquist-Luenberger (GML) index was applied to analyze the carbon productivity in steel industry (SICP) of 29 provinces in China from 2006 to 2019, and then, the SICP was decomposed into technical efficiency change index (TC) and technical progress index (EC). On this basis, the spatial effect is introduced into the traditional convergence model to investigate the spatial convergence of SICP. The empirical results show that: (1) the overall carbon productivity of China's steel industry is at a relatively low level, showing a slow growth trend. (2) The average value of the GML index of SICP is higher than 1, showing obvious inter-provincial and regional heterogeneity. Compared with TC, EC is the leading factor that promotes the increase of SICP. (3) The spatial absolute and condition β convergence of SICP exist in the whole country and the three major regions, but the σ convergence feature is not significant. The addition of spatial factors speeds up the convergence trend, and the speed of spatial absolute β convergence is about 3 times that of the classical convergence model. At the same time, the conditional convergence rate is significantly faster than the absolute convergence, which is closely related to the differences in influencing factors such as the industrial structure, economic development level, human capital, energy consumption intensity, and R&D investment among regions. There is still much room for improvement in carbon productivity in China's steel industry, and investment in scientific research must be increased in order to achieve the upgrading of the industrial structure and technological innovation. The existence of spatial convergence requires strengthening the joint reorganization of steel enterprises between provinces and regions, making full use of the spatial spillover effects of production technology, and realizing regional green and coordinated development.

Spatial–Temporal Differentiation and the Driving Mechanism of Rural Transformation Development in the Yangtze River Economic Belt

Rural transformation development is an important part of rural revitalization, and the study of spatial–temporal differentiation characteristics and the driving mechanism of rural transformation development can provide a decision-making reference for formulating rural revitalization programs according to local conditions. Taking the Yangtze River Economic Belt as the research case, we constructed an evaluation system of rural transformation development in the dimension of “population, land and industry”, and the entropy TOPSIS method, spatial autocorrelation model and geographic detector model were used to reveal spatial-temporal differentiation and the driving mechanism of rural transformation development in the Yangtze River Economic Belt from 1978 to 2018. The results showed that (1) rural transformation development has been significantly unbalanced in the Yangtze River Economic Belt, and rural transformation development showed a weak distribution. Moreover, in terms of dimensions, the land use transformation level > population development transformation level > industrial development transformation level. (2) On the global, rural transformation development presented a spatial distribution trend of club convergence. On the local, the H(High)–H(High) type was mainly distributed in Shanghai City and the southern part of Jiangsu Province, and it evolved to Hangzhou-Shaoxing-Ningbo and Wanjiang City Belt; the L(Low)–L(Low) type was mainly concentrated in the western part of Sichuan Province and in the southwest of Yunnan Province. (3) Natural conditions, economic social development, traffic accessibility, policies and systems were the leading factors affecting rural transformation development in the Yangtze River Economic Belt. The influences of economic social development and traffic accessibility on rural transformation development were increasing, and policy factors had an important guiding effect on rural transformation development, and the influence of natural conditions on rural transformation development has weakened. This study can provide a practical reference for rural transformation and rural revitalization in the Yangtze River Economic Belt.

Convergent and Divergent Legal Trends in Addressing the CORONAVIRUS Pandemic at the EU Level

The greatest humanitarian crisis of the 21st century, triggered by the pandemic emergence and spread of the Covid-19 coronavirus, has caused all European Union States to identify and apply rapid solutions to limit and stop this humanitarian disaster. The ways approached by each Member State in achieving this desideratum were different depending on the potential of assistance and endowment of the hospitals but also on the legal and legislative measures applied. The different percentages of the level of vaccination of the population that vary from state to state show how important is the unitary approach of information measures, strategic organization but also the convergent legislative correlation at the European Union level in stopping this scourge. The percentage of vaccination has proved to be closely linked to saving lives, a conclusion which leads to the need to address a convergent strategy across EU Member States on the measures needed to achieve the highest possible percentage of vaccination at the level of all EU Member States to stop this virus and return to normality.

Adaptive cost-sensitive learning: Improving the convergence of intelligent diagnosis models under imbalanced data

The natural distribution of industrial data is imbalanced, which deteriorates the performance of intelligent fault diagnostic models. Although cost-sensitive learning is an effective method for solving the data imbalance problem, it suffers from the difficulty of setting optimal costs. Therefore, this paper proposes a strategy that considers the number distribution of samples, the convergence trend of classes, and the convergence trend of samples to calculate sample costs adaptively. Using costs to weigh the sample losses and applying them to different models and different loss functions, the diagnostic results under different sample sets show that the weighted losses can significantly improve the model’s performance when using imbalanced data. By further analysing the training loss of the modified model, the angles between deep features, and the angles between deep features and classification weight vectors, it can be found that the dominance of majority classes in imbalanced data is suppressed in training, which is attributed to the loss of each class being coordinated by the proposed strategy. The comparison with various imbalanced learning methods demonstrates the advantages of the proposed method under conditions of large imbalance ratios and complex tasks.

A hybrid multifactorial evolutionary algorithm and firefly algorithm for the clustered minimum routing cost tree problem

The clustered minimum routing cost tree (CluMRCT) problem is a recent problem with a wide range of real-life applications, especially in designing computer networks with peer-to-peer architecture. Many multifactorial evolutionary algorithms have been proposed to solve multiple CluMRCT problems simultaneously. However, these algorithms only function effectively on complete graphs with small-and-medium sizes. Moreover, the blindness and randomness in the transfer of genetic materials cause a reduction in the exploitation ability and make these algorithms ineffective to solve low-similarity tasks. This paper proposes a hybrid multitasking algorithm named multifactorial firefly algorithm, which integrates the firefly algorithm’s strong exploitation ability to enhance the self-evolution of each task when facing low-similarity tasks while improving inter-task knowledge transfers by delivering higher-quality solutions. Also, the proposed algorithm is equipped with new encoding and decoding to focus more on potential search areas on both complete and sparse graphs. The experiments and Wilcoxon signed-rank tests were conducted on various instances to verify our proposal with several state-of-the-art methods. The results portrayed that the proposed encoding scheme helped multitasking algorithms improve solution quality by 32% on average. Besides, the statistical test values proved the superiority of the proposed hybrid algorithm in terms of solution quality and convergence trend.

Indoor Emergency Path Planning Based on the Q-Learning Optimization Algorithm

The internal structure of buildings is becoming increasingly complex. Providing a scientific and reasonable evacuation route for trapped persons in a complex indoor environment is important for reducing casualties and property losses. In emergency and disaster relief environments, indoor path planning has great uncertainty and higher safety requirements. Q-learning is a value-based reinforcement learning algorithm that can complete path planning tasks through autonomous learning without establishing mathematical models and environmental maps. Therefore, we propose an indoor emergency path planning method based on the Q-learning optimization algorithm. First, a grid environment model is established. The discount rate of the exploration factor is used to optimize the Q-learning algorithm, and the exploration factor in the ε-greedy strategy is dynamically adjusted before selecting random actions to accelerate the convergence of the Q-learning algorithm in a large-scale grid environment. An indoor emergency path planning experiment based on the Q-learning optimization algorithm was carried out using simulated data and real indoor environment data. The proposed Q-learning optimization algorithm basically converges after 500 iterative learning rounds, which is nearly 2000 rounds higher than the convergence rate of the Q-learning algorithm. The SASRA algorithm has no obvious convergence trend in 5000 iterations of learning. The results show that the proposed Q-learning optimization algorithm is superior to the SARSA algorithm and the classic Q-learning algorithm in terms of solving time and convergence speed when planning the shortest path in a grid environment. The convergence speed of the proposed Q- learning optimization algorithm is approximately five times faster than that of the classic Q- learning algorithm. The proposed Q-learning optimization algorithm in the grid environment can successfully plan the shortest path to avoid obstacle areas in a short time.

Capital structure of non-financial companies in EU countries – macroeconomic view

Abstract This article examines the macroeconomic aspects of capital structure of companies in EU countries in the international context during the period 2011–2020. It aims at evaluating the capital structure of European non-financial companies in general, followed by the application of market timing theory and convergence tendencies in the companies within the EU countries. Our results suggest that the equity ratio of examined companies has grown over the last decade at the expense of credit sources of financing. Although our research could not confirm the possibility of market timing theory application, this was due to the limitations of our analysis caused also by an inappropriate data structure. The general result of the examination of convergence suggests that the historical capital structure has a strong impact on the current structure. Analysis of the capital structure of companies in individual European countries also shows that there are still significant differences between these countries, which have been reduced only partially in the medium term, and thus convergence trends are insignificant.

基于三生空间质量的哈长城市群城市脆弱性时空演变格局及驱动力研究

PDF HTML阅读 XML下载 导出引用 引用提醒 基于三生空间质量的哈长城市群城市脆弱性时空演变格局及驱动力研究 DOI: 10.5846/stxb202106221662 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 黑龙江省自然科学基金项目(LH2019D008)；黑龙江省哲学社会科学研究规划项目(21JLE323)；国家自然科学基金项目(42171191,41771172) Patterns and Driving Forces of the Temporal-Spatial Evolution of Urban Vulnerability in Harbin-Changchun Urban Agglomeration based on the production-living-ecological Spatial Quality Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:高质量的三生空间是城市高品质空间布局、高效率功能体现的重要保障与载体。城市群作为城市三生空间矛盾的集中地,降低其城市脆弱性,是区域可持续发展的关键。因此,基于三生空间质量的哈长城市群城市脆弱性研究对国土空间协调与稳定发展具有重要意义。以哈长城市群11个地市为研究区域,基于生产空间质量、生活空间质量、生态空间质量构建城市脆弱性评价指标体系,运用熵权-TOPSIS评价模型、ArcGIS空间分析工具以及地理探测器对2010-2018年哈长城市群城市脆弱性的时空格局演变与驱动力进行分析。研究结果表明:①在时间变化上:整体来看,2010-2018年哈长城市群城市脆弱性呈下降的趋势,城市脆弱性空间上呈"先增强后减弱"的态势。城市脆弱性高等级地区数量呈现"先增强后减弱"的趋势,而城市脆弱性指数相似地区集中分布呈现"先减弱后增强"态势。②在空间布局上:形成了II、I级区"点状零散",V、IV级区的"边缘式"的空间分布格局。空间分布呈现"随机化",无明显集聚性。从其演化趋势类型特征上看,呈发散趋势的城市多于呈收敛趋势的城市,说明哈长城市群城市脆弱性空间差异呈逐渐增大态势。③基于三生空间质量哈长城市群城市脆弱性的空间分异主要是由城市生活空间质量脆弱性的差异引起,其次是城市生产空间质量脆弱性。其中,经济增长水平不高是城市生产空间质量脆弱性的首要因素;交通设施水平不完善、燃气资源供给力度不够、城乡差距偏大、教育水平程度偏低、信息化水平低下是城市生活空间质量脆弱性的关键因素;污水处理强度、城市绿化水平和生活垃圾无害化处理强度是影响哈长城市群城市生态空间质量脆弱性的基础要素。 Abstract:High-quality production-living-ecological space is an important guarantee and carrier for high-quality urban spatial layouts and high-efficiency functions. Urban Agglomerations are the concentrated areas of urban production-living-ecological spatial conflicts. Reducing the urban vulnerability of Urban Agglomerations has become the key to regional sustainable development. Therefore, the research on the urban vulnerability of Harbin-Changchun Urban Agglomeration based on the production-living-ecological Spatial Quality is of great significance to the coordinated and stable development of territorial space. Taking 11 cities in the Harbin-Changchun Urban Agglomeration as the research area, the urban vulnerability evaluation index system was constructed based on the quality of production space, the quality of living space and the quality of ecological space. The entropy weight-TOPSIS evaluation model, ArcGIS spatial analysis tools and geographic detectors were used to analyze the patterns and driving forces of the spatial and temporal evolution of urban vulnerability in the Harbin-Changchun Urban Agglomeration from 2010 to 2018. The research results show that: (1) The urban vulnerability of the Harbin-Changchun Urban Agglomeration presented a downward trend from 2010 to 2018, and the urban vulnerability spatially showed a trend of increasing first and then weakening. The number of high-level areas of urban vulnerability showed a trend of strengthening first and then weakening, while the concentrated distribution of areas with similar urban vulnerability indexes showed a trend of weakening first and then increasing. (2) The II and I level areas were mainly distributed in the core area, which were distributed in spots and scattered. The V and IV level areas were mainly distributed in the peripheral areas, showing a spatial pattern of widely distributed on the edge. The spatial distribution was randomized and there was no obvious agglomeration. Judging from the characteristics of the types of evolution trends, there were more cities showing a divergent trend than a convergence trend, which indicated that the spatial differences in urban vulnerability of the Harbin-Changchun Urban Agglomeration were gradually increasing. (3) Based on the production-living-ecological Spatial Quality, the spatial differentiation of the urban vulnerability of Harbin-Changchun Urban Agglomeration was mainly caused by the difference in the vulnerability of urban living space quality, followed by the difference in the vulnerability of urban production space quality. Among them, the low level of economic growth was the primary factor for the vulnerability of urban production space quality; The imperfect transportation facilities, insufficient gas supply, large gap between urban and rural areas, low education level and low level of information were the key factors for the vulnerability of urban living space quality; The intensity of sewage treatment, the level of urban greening and the intensity of harmless treatment of domestic waste were the basic elements that affected the vulnerability of the urban ecological space quality of the Harbin-Changchun Urban Agglomeration. 参考文献 相似文献 引证文献

The Development of Broadcasting and Hosting from the Perspective of Media Intelligence-The Case of AI Anchors for Beijing 2022 Winter Olympics

With the continuous progress of media technology, the media communication environment has undergone profound changes, and media intelligence has become a new trend of media convergence. As an innovative product of the combination of artificial intelligence technology and media communication, AI anchors have been applied to information communication in the Olympic Winter Games Beijing 2022, which has attracted widespread attention from the public. According to the current development of AI anchors, this paper uses embodied cognition theory to investigate the development trend of the broadcasting and hosting industry under the influence of intelligent media. On this basis, the paper takes AI anchors of the Winter Olympics as the research object, analyzes their application reasons and communication characteristics, and then explores the irreplaceability of human broadcasters and hosts by comparing them with AI anchors. The study of this paper will provide a feasible path for the development direction of human-machine symbiosis and a new case for the study of AI anchors.

КОНВЕРГЕНЦІЯ NBICS-ТЕХНОЛОГІЙ ТА ПРОБЛЕМИ РОЗВИТКУ ГЛОБАЛЬНОЇ ЕКОНОМІКИ

The dynamic development of the modern global economy is determined by its close relationship with trends in modern technology, the state of the natural and social environment, the level of development of science. Given this circumstance, business representatives, national governments, the scientific community, the public are constantly looking for ways to integrate scientific and technological progress, innovation, areas of intellectual activity and social issues in a single cluster. Since the studied problem is a relatively new interdisciplinary field of knowledge, hence its insufficient coverage in the domestic economic literature. The lack of tradition of interdisciplinary research, especially in technical, natural, philosophical and economic sciences, is a deterrent to attracting a wide range of domestic economists to the study relationship between the convergence of NBICS technologies and the development of the global economy. However, this problem has received some attention from foreign researchers. Given this, the chosen topic of the article has theoretical, scientific and applied and ideological significance. In the process of realization of the formulated goal of the research the essence, content of convergence of NBICS technologies as a complex multidimensional process is determined and the problems of global economy development in the context of technology convergence are characterized. The scientific novelty of the study is to substantiate, based on a critical analysis of scientific publications of foreign and domestic scientists, trends in technology convergence, highlights differences in American and European approaches to interpreting the role and importance of convergence of nano-, bio-, info-, cogno- and social technologies, of disclosing their interdisciplinary nature and identifying problems of global economic development that are the result of the deployment of convergence of these technologies, which are a consequence of the deployment of convergence of these technologies. A generalization is made about the inadmissibility of the dominance of the technocratic approach to the interpretation of the essence of the convergence of NBICS technologies; of necessity to understand the cyclical nature of the convergence of NBICS technologies as a process that occurs as a result of their integration and under the influence of synergies and divergence; of developing the necessary of an appropriate scientific apparatus to describe trends in this process. The priority directions of further scientific research on this problem are outlined.

Temporal Trend and Regional Disparity of Agricultural Green Total Factor Productivity in China: Data Envelopment Analysis with Biennial Environmental Technology

This paper investigates the temporal trend and regional disparity of China’s agricultural green total factor productivity (AGTFP) during 1997‐2016. Combined with the green Luenberger productivity indicator, two different data envelopment analysis models with the biennial environmental technology are constructed for robust checks. Compared with the existing literature, more agricultural carbon emissions are used as the undesirable outputs in the models. It is found that AGTFP in the whole of China and all of its sub‐regions (the east, the middle, and the west) showed an overall increase, with the drive of high technical progress. The east had the largest AGTFP, and the middle experienced the largest AGTFP growth. More specifically, with respect to AGTFP, the total difference and the gross difference among the three regions as well as the specific difference within regions widened during these periods. There was an absolute convergence trend of AGTFP in the whole of China as well as the middle and the west. The speed of convergence was highest in the west.

Regional Differences and Convergence of Urban-Rural Integration Development from the Perspective of Factor Flow.

Based on the panel data of thirty-one provinces in China from 2003 to 2020, we constructed an evaluation index system of urban-rural integration development level from the perspective of factor flow. The combined weighting model of GI and CRITIC were used to evaluate the regional urban-rural integration development. The coefficient of variation and panel fixed effect model was used to explore convergence, absolute convergence, and conditional convergence. The impact of capital, labor, and technology factor flow on the convergence of urban-rural integration development level was further investigated. In addition, the difference analysis in time scale and impulse response function analysis was performed to explore the regular pattern of factor flow on the convergence of urban-rural integration development. The main conclusions were as follows: first, the growth of urban-rural integration development had an absolute convergence trend and tended to conditional convergence faster. Second, the capital flow positively affected the convergence of urban-rural integration development, while labor and technology flow had a slowing effect on the convergence of urban-rural integration development at this stage. Third, the impact of factor flow on the convergence of urban-rural integration development was dissimilar during different phases. The convergence rate of urban-rural integration development after 2012 was drastically slower than before.

Structures and Settlement Control of Yujingshan High-Speed Railway Tunnel Crossing Massive Rockfill in a Giant Karst Cave

The Yujingshan high-speed railway tunnel crosses a giant cavern system with a 108 × 104 m3 volume chamber and an 18 km long underground river. The massive project, which lasted three years, was eventually awarded the “Overcoming the Challenges” award by the International Tunneling and Underground Space Association (ITA) in 2020. However, since the cave chamber was filled with large-scale rockfill, structural settlement is a non-negligible problem. This paper presents the unique structures of a bridge supporting railway tracks wrapped by tunnel lining and the settlement control of the Yujingshan tunnel crossing massive rockfill in the giant cave. The geological characteristics and design considerations are systematically introduced. A three-dimensional coupling discrete element method (DEM) and finite difference method (FDM) numerical model and 13 months of long-term settlement monitoring were conducted to evaluate the settlement behavior. The results indicate that the morphology of cavern and internal deposits caused the whole rockfill to migrate to the lower left. The tunnel structure consequently developed a significant inclined settlement. The continuous construction load would increase the settlement value by 31.4%. The bottom reinforcement of steel-pipe pile with grouting could effectively inhibit settlement and differential settlement. Considering the simulation results, the tunnel bottom had greater settlement than the limit standard for high-speed railway embankment, which means this special structure form is reasonable for operation. Meanwhile, the monitoring results show that the tunnel bottom settlement in D3K279+891~D3K279+947 had not performed an apparent convergence trend after 13 months. Further structural monitoring and compensation grouting should be actively considered for operation maintenance.

Characteristics and causes of crest cracking on a high core-wall rockfill dam: A case study

Avoiding and controlling dam crest cracking is one of the most difficult problems facing high core rockfill dams of more than 100 m. However, few studies have been conducted on the characteristics and causes of dam crest cracking based on long-term measurement data. In this study, a real case of a dam suffering cracking at the crest was studied. The dam has a maximum height of 186 m and has been in service for 10 years. The spatiotemporal characteristics of the dam crest cracking were determined based on monitoring data obtained using crack monitoring instruments, radar detection, seismic refraction tomography, and pit exploration. The causes of dam cracking were analyzed based on the deformation inclination and strain index. The factors controlling the cracking (such as the dam structure, geological structure, and materials' properties) were investigated. The results show the following. 1) The cracks mainly occurred at the interface between the core wall and the downstream dam shell. 2) The cracks mainly developed during the impoundment and operation periods with high water levels, and there was no convergence trend within the 10 years of operation. 3) Uneven settlement and uneven horizontal displacement were the main reasons for the crack formation. 4) The factors influencing the cracking include dam zoning, the geological structure, wetting, and the rheological properties of the rockfill materials, and the reservoir level. The results of this study provide an important engineering reference for the prevention and control of dam crest cracking in high rockfill dams.

The dynamics of industrial geographic distribution: evidence from Brazil (2002-2014)

ABSTRACT The geographical distribution of Brazilian industries changed between 2002 and 2014, and it was more significant for some industries. Based on Dumais et al. (2002), we explore the dynamics of these changes by a decomposition of the employment variation and concentration index for manufacturing industries grouped by technological intensity, and we identify the direction of the locational movements of the firms among microregions. In general., the results indicate that between 2002 and 2014, there was a trend of convergence among the microregions’ participation in industrial employment, contributing to industrial deconcentration in the country, with the exception of the group of high-technology industries, which became more concentrated. Components of the life cycle of industries, especially the growth of employment generated by new industries in non-metropolitan microregions, are identified as main propelling of this evidence. In general., the results are consistent with the importance of agglomeration economies over historic accidents to explain the industrial concentration in Brazil between 2002 and 2014.

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. The present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework [Yaghoobi et al., npj Comput. Mater., 7, 38 (2021)] to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

Research on Industry Difference and Convergence of Green Innovation Efficiency of Manufacturing Industry in China Based on Super-SBM and Convergence Models

To accurately grasp the current situation of green innovation efficiency in the manufacturing industry in China, this paper analyzes the differences and convergence characteristics of green innovation efficiency in various industries. Based on the panel data of 29 manufacturing industries in China from 2010 to 2019, the super-slack-based measure (Super-SBM) model measures the green innovation efficiency of manufacturing industries whose evolution characteristics are classified and analyzed from the perspective of technical demand. The Dagum Gini coefficient decomposition method indicates the source of industry differences in green innovation efficiency of the manufacturing industry in China with its convergence characteristics analyzed from the time dimension by constructing σ and β convergence models. The results reveal the improvement of green innovation efficiency of the Chinese manufacturing industry with obvious distinctions among different sectors and the industries with high green innovation efficiency, mostly high-end technology ones. The narrowing overall difference of green innovation efficiency in the manufacturing industry is accompanied by the lowest contribution rate of super-variable density, with the disparities between groups being the main source. It also shows the fluctuation of the intermittent σ convergence characteristics of the national manufacturing industry as a whole and low-end and high-end technology industry groups. However, the entire manufacturing industry and the three groups witness the absolute β convergence trend, with an ununiform convergence rate. The research will provide a reference for further upgrading the efficiency of green innovation in the industry and help to achieve the goals of carbon emission reduction and neutrality with the policy implications for promoting high-quality development of the manufacturing industry.