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To overcome the shortcoming of the Fuzzy C-means algorithm (FCM)—that it is easy to fall into local optima due to the dependence of sub-spatial clustering on initialization—a Multi-Strategy Tuna Swarm Optimization-Fuzzy C-means (MSTSO-FCM) algorithm is proposed. Firstly, a chaotic local search strategy and an offset distribution estimation strategy algorithm are proposed to improve the performance, enhance the population diversity of the Tuna Swarm Optimization (TSO) algorithm, and avoid falling into local optima. Secondly, the search and development characteristics of the MSTSO algorithm are introduced into the fuzzy matrix of Fuzzy C-means (FCM), which overcomes the defects of poor global searchability and sensitive initialization. Not only has the searchability of the Multi-Strategy Tuna Swarm Optimization algorithm been employed, but the fuzzy mathematical ideas of FCM have been retained, to improve the clustering accuracy, stability, and accuracy of the FCM algorithm. Finally, two sets of artificial datasets and multiple sets of the University of California Irvine (UCI) datasets are used to do the testing, and four indicators are introduced for evaluation. The results show that the MSTSO-FCM algorithm has better convergence speed than the Tuna Swarm Optimization Fuzzy C-means (TSO-FCM) algorithm, and its accuracies in the heart, liver, and iris datasets are 89.46%, 63.58%, 98.67%, respectively, which is an outstanding improvement. [ABSTRACT FROM AUTHOR]

Abstract A comprehensive understanding of the relationships between environmental regulations and green growth of economy is essential for policy design and decision-making. This paper combines hybrid measure with Global Malmquist Luenberger index to estimate national green growth level. A panel threshold regression technique is then employed to observe the non-linear impacts of both the formal and informal environmental regulations on green growth in Group 20 countries during 2001–2015. Results from empirical tests reveal that, for the formal environmental regulations represented by Environmental Policy Stringency (EPS), the market-based EPS is only significant at high-level phase while this is not the case in the low-level counterpart; non-market based EPS witnessed significant signs across the three phases, but in varied coefficients and significance levels. By comparison, the informal environmental regulations represented by environmental-related technologies and education levels show positive and significant impact on green growth, except for the case when countries have higher level of technologies. In addition, income per capita and gross Research & Development (R&D) expenditures present significant positive impacts on the dependent while share of service sector to the economy and investment on transport infrastructure witnessed negative effects across the models. Policy implications are proposed thereafter, although both the formal and informal environmental regulations are important to promote green growth, but they show different impacts at different phases. Graphical abstract Unlabelled Image Highlights • A global Malmquist Luenberger index has been employed to measure green growth. • Non-linear regulation-growth nexus has been examined by panel threshold model. • Environmental Policy Stringency show significant positive effects on green growth. • Education exerts larger impact on green growth than environmental-related technologies. [ABSTRACT FROM AUTHOR]

Abstract Particles with a diameter of <2.5 μm (PM 2.5) have serious adverse-effects on human health, which have caused widespread public concern in recent decades. Currently, most of the existing research on PM 2.5 have used linear regression analysis; very few studies on the subject have been conducted using non-linear models. This study adopts a panel threshold model, which is seldom used in environmental studies, to examine the non-linear effects of environmental regulation and economic growth on PM 2.5 in 30 OECD countries, and we also explore the key driving socio-economic factors for PM 2.5 emissions. The results of our analysis show that, along with an increase in environmental policy stringency, PM 2.5 emissions first rise and then show no significant correlations, and thus a reduction in emissions can be expected if current trends continue. As for GDP per capita, significant and negative correlations are found across the three phases divided by the panel threshold model, indicating a promoting effect for PM 2.5 mitigation. In addition, public expenditure on the air sector correlated positively with PM 2.5 concentrations, expanding the share of service economy reward to reduce air pollution, and urban population ratio exhibits an inverted U-shaped pattern. Future studies may shed more light on the regulation-PM 2.5 nexus, and more studies are needed to confirm the existence of bi-directional correlations between economic development and air pollution. Graphical abstract Unlabelled Image Highlights • Environmental regulation show different impacts on PM 2.5 at high-, mid- and low-level phases; • GDP per capita is negatively correlated with PM 2.5 at 1% level; • Expansion of service industry reduces pollution; • An inverted U-shaped relationship exist between urbanization and pollution. [ABSTRACT FROM AUTHOR]

The two essential terms in environmental sciences - dematerialization and decoupling - have always been controversial. This study aims to trace the evolution path on the methodologies, the evidences and the policies, and to reflect on the implications of the development. We specifically present several classical definitions so as to summarize the similarities and differences thereinafter. Several commonly used methodologies, which are employed for evaluating the levels of dematerialization and decoupling, are discussed. As expected, the empirical evidences rarely support the absolute dematerialization and decoupling, which challenge the relevant policies implemented worldwide. In this context, the rebound effect, which is regarded as the main obstacle, is necessary to be examined in the various sectors and areas. However, the results of the rebound levels are far from unanimous. This article has a further discussion on the possible direction for the inconclusive debate in a broader perspective. [ABSTRACT FROM AUTHOR]

High Efficiency Video Coding (HEVC), as a novel video coding standard, has shown a better coding efficiency than all existing standards, such as H.264/AVC. It adopts a lot of new efficient coding tools, the most important one is the new hierarchical structures which include the coding unit (CU), prediction unit (PU) and transform unit (TU). However, the rate-distortion (RD) optimization process for all CUs, PUs, and TUs cause large computational costs. In this paper, a fast Inter-frame encoding scheme using the edge information and the spatiotemporal encoding parameters is proposed to reduce the encoder complexity of HEVC, which consists of a fast all 2 N × 2 N modes decision method, a fast CU depth level decision method and a fast PU mode decision method. This scheme uses edge information to express the structure complexity and uses the difference of edge information between current CU and its spatiotemporal CUs to express the edge similarity (ES) in one frame and the edge movement (EM) between two adjacent frames. And then, utilizes ES and EM as assistant parameters cooperate with CU depth levels and PU mode RD costs of spatiotemporal CUs to accomplish the early termination of CU split and the PU mode selection. The experimental results show that the proposed fast inter-frame encoding method can significantly reduce the computational costs with negligible RD loss. There are 53.7 and 54.9% encoding time savings on average, but only with average 1.5 and 1.8% Bjøntegaard difference bitrate (BDBR) losses for various test sequences under random access and low delay conditions, respectively. [ABSTRACT FROM AUTHOR]

Few studies have discussed marine industrial upgrading and its association with marine economic growth and technological innovation. This study uses a vector error correction model (VECM) to explore the short-term and long-term relationship between marine economic growth, technological innovation, and industrial upgrading in China from 2006 to 2016. Results reveal the existence of two co-integration relationships between the three variables: specifically, in the long term, marine economic growth positively affects marine technological innovation, and vice versa; however, neither promote industrial upgrading and neither are promoted thereby. These findings indicate that marine economic growth and technological innovation are mutually promoting in the long term, but the mutual driving mechanism between the upgrading of marine industry and the other two variables has not yet formed. The study also reveals that the shift from secondary industry toward tertiary industry is not conducive to improving marine technological innovation, which is especially alarming given the current service-oriented tendency of China's marine industry. Key policy implications include the need to expand the relative size of the marine economy, prioritize developing marine secondary industry, develop marine technology, and train high-level marine professionals. Image 1 • Relations of marine growth, innovation and industrial upgrading in China are studied. • A vector error correction model has been used. • Marine growth and innovation are mutually promoted in the long-term. • Neither affects or is affected by marine industrial upgrading in the long-term. • Shifting toward marine tertiary industry inhibits innovation and economic growth. [ABSTRACT FROM AUTHOR]

Arable land resources are essential for food security and sustainable agricultural development, and an objective and comprehensive evaluation of overseas arable land resources is indispensable to the decision-making of various Chinese enterprises. However, overseas arable land resources and factors influencing China's investment therein have rarely been investigated. In the present study, the authors select eight indexes related to the quantity and quality of arable land and utilize the entropy weighting method and technique for order preference by similarity to ideal solution (TOPSIS) method to comprehensively evaluate arable resources in 48 "Belt and Road" countries for the period 2008–2016. Renewable internal freshwater resources and irrigated farmland area are found to be the primary factors affecting the wealth of arable land resources. Based on this evaluation, the authors conduct empirical tests concerning the main factors affecting the scale of China's investment in foreign arable land using a panel Tobit model. The results show that Chinese companies tend to invest in countries with high levels of arable land resources and low corruption risk. Based on these findings, this study concludes that Chinese enterprises should engage in joint development with host countries and support the sustainability of long-term investment in cultivated land. [ABSTRACT FROM AUTHOR]

The evaluation of urban comprehensive carrying capacity (UCC) is of great importance in maintaining urban socio-economic sustainable development. However, UCC is still in its nascent period with limited applications and a lack of credible assessment methods. To enrich this field, this study constructed an objective scientific index to evaluate the UCC of the Yangtze River Delta (YRD) region from a four-dimensional perspective, examining economy, society, environmental, and transportation subsystems. The improved entropy method based on 18 weighted indicators was used to measure the UCC of the 26 cities of the YRD for the period 1990–2018. Results indicate that nine cities were overloaded in 2018, meaning comprehensive carrying capacity demand exceeds supply, and the other seventeen were in loadable condition, meaning such demand did not exceed supply; the social and transportation subsystems are the most important because their index weights and UCC levels are higher than the other two subsystems; the overall UCC for all cities in the YRD is at a medium level, and there are large disparities between the various cities. The empirical results imply that the government should take effective measures to improve UCC in these cities, combining cities' specific advantages to enhance the efficiency of resource allocation and utilization and improve carrying capacities, and changing the mode of economic development. Based on UCC levels, it is also important to improve environmental conditions and coordination and integration in the development of urbanization. Policy implications on improving UCC have been highlighted in the final section. [ABSTRACT FROM AUTHOR]