Reduction of carbon dioxide (CO₂) emissions is one of the biggest challenges for global sustainable development, in which economic growth characterized by industrialization plays a formidable role. We innovatively adopted the input and output (I-O) table of 41 countries released by World I-O Database to determine the industrial structure change and analyze its impact on CO₂ emission evolution by developing a cross-country panel model. The empirical results show that industrial structure change has a significantly negative effect on CO₂ emissions; to be specific, 0.1 unit increase in the linkage of manufacturing sector and service sector will lead to a decrease of 0.94 metric tons per capita CO₂ emissions, indicating that upgrading industrial structure contributes to carbon mitigation and sustainable development. Further, urbanization, technology and trade openness have significantly negative impact on CO₂ emissions, while economy growth and energy use take positive impacts. In particular, a 1% increase in per capita income will contribute to an increase of 8.6 metric tons per capita CO₂ emissions. However, the effect of industrial structure on environment degradation is moderated by technology level. These findings fill the gaps of previous literature and provide valuable references for effective policies to mitigate CO₂ emissions and achieve sustainable development.

Our article discusses a class of Jump-diffusion stochastic differential system under Markovian switching (JD-SDS-MS). This model is generated by introducing Poisson process and Markovian switching based on a normal stochastic differential equation. Our work dedicates to analytical properties of solutions to this model. First, we give some properties of the solution, including existence, uniqueness, non-negative and global nature. Next, boundedness of first moment of the solution to this model is considered. Third, properties about coefficients of JD-SDS-MS is proved by using a right continuous markov chain. Last, we study the convergence of Euler-Maruyama numerical solutions and apply it to pricing bonds.

This paper seeks to position the third-party transaction (TPT) in the macrostructure of Chinese market in terms of Concentration Ratio and Herfindahl-Hirschman Index. By extending both Cournot oligopolistic and Stackelberg oligopolistic competition models, a new oligopolistic competition model is established for China's TPT market. Based on multidimensional game, a pricing game model is theorized accordingly to elucidate the TPT platform. The influence of various factors on the price of the TPT platform is verified with numerical simulation. The formation of monopoly is an inevitable consequence of the "one superpower and multi powers" market structure given the unregulated development of TPT enterprises as the prerequisite. In addition, through the studies on telecom payment market, such unregulated development can also cause the "big-three" domination for the TPT enterprises in the "multi powers" market structure. Based on our modelizations, this paper serves to provide prospect recommendations for policy-making of state supervision authorities.

We employ the static and dynamic copula models to investigate whether technical indicators provide information on volatility in the next trading day, where the volatility is measured by daily realized volatility. Our empirical results, based on long samples of 8 well-known stock indexes, suggest that a significant and asymmetric tail dependence between the technical indicators based on moving average and the next day volatility. The level of dependence change over time in a persistent manner. And the dependence structure presents some distinct differences between emerging market indexes and developed market indexes. These results indicate that the technical indicators can provide information on the next day volatility at extremes, and are less informative at normal market.

According to the philosophy of self-cultivation that "one should refine his personal virtue when in poverty, and help save the world when in success", a new type of evolutionary strategy, PoorCompetition-Rich-Cooperation (PCRC), is proposed. To discuss its superiority and inferiority, based on a multi-player iterated Prisoner's Dilemma game, PCRC and other six kinds of strategies are played by using the roulette method in three different populations (a uniformly distributed population, a cooperation-preference population, a defection-preference population). The payoff characteristics for each strategy under different temptation coefficients and noise values are also analyzed. Simulation results indicate that PCRC has a sufficient robustness and its payoff presents a basically monotonic increasing tendency with the increment of noise. The superiority of PCRC becomes more obvious when the temptation coefficient becomes larger. Furthermore, a higher population preference for defection yields a more obvious advantage for PCRC.

In this paper, we propose and analyze a cooperation model with harvesting and statedependent delay, which is assumed to be an increasing function of the population density with lower and upper bound. The main purpose of this article is to obtain the dynamics of our model analytically by controlling the harvesting. We present results on positivity and boundedness of all populations. Criteria for the existence of all equilibria and uniqueness of a positive equilibrium are given by controlling the harvesting. Finally, the global exponentially asymptotical stability criteria of model is obtained by the improved Hanalay inequality.

This paper mainly studies whether and how stock prices fluctuate around their intrinsic values. Based on data from 10 stock markets for the period between 2000 and 2018, we demonstrate that the relative price fluctuates around and approaches the intrinsic value in the long term. For the ten markets, the relative price crosses the intrinsic value on average once in 3~4 years. Profitability growth is a key factor in rising stock prices, but the level of valuations in the market has a regulatory effect to the growth of price in the future: For every 1 % increase in valuation, the price tends to decline by 0.26% in the next year, 0.74% in the next 3 years.

Understanding the satisfaction impact factors of China-Eurasia Expo is important to hold and improve the Expo. This paper divides the impact factors of satisfaction into local residents and exhibitors' aspects. Firstly, this paper constructs a five-dimension conceptual model to measure the local residents' satisfaction which consists of the degree of promoting economic development, environmental protection, cultural quality, urban convenience and urban brand image of the China-Eurasia Expo. 898 valid questionnaires were collected and structural equation model (SEM) was used to validate the constructed model and the proposed hypotheses were proved; the path coefficients of cultural quality, urban convenience and urban brand image to locals' satisfaction are all greater than 0.90, indicating that they have high impacts on local residents' satisfaction, while the path coefficient of the degree of promoting economic development to residents' satisfaction is 0.695, indicating a relatively low impact. Secondly, this paper constructs a five-dimension conceptual model of exhibitors' satisfaction which includes infrastructure, management level, service quality, organizing effect, and advancement. 708 valid questionnaires were collected and SEM was used to valid the constructed model and the proposed hypotheses. The results show that the five path coefficients to exhibitors' satisfaction are higher than 0.7, all hypotheses were proved.

The Beijing-Tianjin-Hebei region is one of the regions with the most dynamic economies, highest degrees of openness, strongest innovation capacities and largest populations, as well as an important engine driving China's economic development. Currently, the development of the BeijingTianjin-Hebei region faces many difficulties, including an inefficient distribution of regional functions, imbalance in industrial structure, low sophistication, and serious overburdening of resources and the environment. Promoting the overall coordinated development of the region has become an urgent challenge. In this paper, according to the conventions of industrial structure optimization, the three core indicators of regional industrial structure rationalization, sophistication and ecologicalization are constructed. With the help of the grey dynamic correlation model, the three indicators are coupled with the economic growth rate, and the industrial structure optimization index of the Beijing-Tianjin-Hebei region is comprehensively measured. The study shows that rationalization of the industrial structure in the Beijing-Tianjin-Hebei region is increasing but that this trend is not obvious; sophistication of the industrial structure is relatively high and has also been operating at a high level; however, the overall ecological level of the industrial structure in the Beijing-Tianjin-Hebei region is not high and presents the characteristics of high in the middle and low at both ends. In terms of the relationship between industrial structure and economic growth in the Beijing-Tianjin-Hebei region, ecologicalization of the industrial structure has the greatest influence on economic growth, followed by sophistication of the industrial structure, and rationalization of the industrial structure has the weakest influence.

The entrepreneurship has positive and significant connection with economic growth. Competition would be increased by new entrants in the market; then, social welfare would be improved. Thus, positive entrepreneurship policies are often linked to increased social welfare by authorities. In this paper, we focus on a certain case where potential entrepreneurs are employees of existing firms to test the above ideas. The purpose of our research is to assess the variation of social welfare in the context of employer-restricted separation. Therefore, the model of Cournot competition where employees constitute the only entry threat was used in this paper. The results demonstrate that social welfare would not always be improved even in a good entrepreneurial context. If the deterring strategy is present, the relationship between positive entrepreneurship policies and increased social welfare might not hold, or would depend on the different strategies adopted by the incumbent. Therefore, the sustainability of a positive entrepreneurship policy would be impaired by incumbent firms.

A parameter estimation method, called PMCMC in this paper, is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps. There is a closed form solution to term structure of interest rates under Markov regime. However, the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM) in the case of adding jumps. Although the difficulty of parameter estimation greatly prevents from researching models, we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility. The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR. Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.

Material incentive is the main motivation for solvers to attend crowdsourcing tasks. So raising the bidding success rate is benefit to inspire the solvers attendance' and increase the answering quality. This paper analyzes the effect of participation experience, task-fit capability, participation strategy and task attribute on the solvers bidding success by the solvers attending the series tasks of Tripadvisor. The results show that: 1) Participation times enrich the participation experiences and promote the bidding success, while bidding success times and last performances lower the bidding success because of the cognitive fixation; 2) The chance of bidding success will be increase when the solver own high task-fit capability; 3) The relationship between task submit sequence and bidding success is the type of reverse U shape, and the optimal submit sequence rate on the top of the reverse U shape; 4) Higher task difficulty lower bidding success, while higher task density easier bidding success.

Single image dehazing algorithm based on the dark channel prior may cause block effect and color distortion. To improve these limitations, this paper proposes a single image dehazing algorithm based on the V-transform and the dark channel prior, in which a hazy RGB image is converted into the HSI color space, and each component H, I and S is processed separately. The hue component H remains unchanged, the saturation component S is stretched after being denoised by a median filter. In the procession of intensity component, a quad-tree algorithm is presented to estimate the atmospheric light, the dark channel prior and the V-transform are used to estimate the transmission map. To reduce the computational complexity, the intensity component I is decomposed by the V-transform first, coarse transmission map is then estimated by applying the dark channel prior on the low frequency reconstruction image, and the guided filter is finally employed to refine the coarse transmission map. For images with sky regions, the haze removal effectiveness can be greatly improved by just increasing the minimum value of the transmission map. The proposed algorithm has low time complexity and performs well on a wide variety of images. The recovered images have more nature color and less color distortion compared with some state-of-the-art methods.

Linear and mixed integer programming are very popular and important methods to make efficient scientific management decision. With large size of real application data, the use of linear-mixed integer programming is facing problems with more complexity; therefore, preprocessing techniques become very important. Preprocessing aims to check and delete redundant information from the problem formulation. It is a collection of techniques that reduce the size of the problem and try to strengthen the formulation. Fast and effective preprocessing techniques are very important and essential for solving linear or mixed integer programming instances. In this paper, we demonstrate a set of techniques to presolve linear and mixed integer programming problems. Experiment results showed that when preprocessing is well done, then it becomes easier for the solver; we implemented interior-point algorithm for computational experiment. However, preprocessing is not enough to reduce the size and total nonzero elements from the constraints matrix. Moreover, we also demonstrate the impact of minimum degree reordering on the speed and storage requirements of a matrix operation. All techniques mentioned above are presented in a multifunctional software to facilitate users.

With the boom of web technology, Internet concerns (IC) have become emerging drivers of crude oil price. This paper makes the first attempt to measure the frequency-varying co-movements between crude oil price and IC in five domains (i.e., fundamentals, supply-demand, crisis, war and weather) by using the frequency causality test method. Based on the monthly Brent spot price and search volumes (SVs) captured by Google Trends from January 2004 to September 2019, new and complementary insights regarding the co-movements between crude oil price and IC are obtained. 1) The co-movements between crude oil price and the IC of supply-demand, war, and weather support a neutral hypothesis at all frequencies due to the characteristics (low value or volatility) of these IC data. 2) There is a unidirectional causal relationship between crude oil price and the IC of fundamentals, running from the latter to the former at low frequencies (long-term). 3) There is a feedback relationship between crude oil price and the IC of crisis, with the IC of crisis driving crude oil price at medium and low frequencies (mid- and long-term) and crude oil price causing the IC of crisis to change permanently. The conclusions of this paper provide important implications for both oil market economists and investors.

In this paper, M-Copula is used to analyze the correlation between Shanghai Composite Index and Shanghai Fund Index. By analyzing the characteristics of the logarithmic yields sequence of two samples, the marginal distribution model is established by using EGARCH-M-GED model. According to the correlation between two logarithmic yields sequence, the M-Copula model is selected to model its correlation structure, and its parameters are estimated by EM algorithm. Because MCopula combines characteristics of different Copulas, it has more flexible distribution forms and more prominent ability to describe the fat tails and correlation characteristics of data, and more importantly, the effect is better than single Copula.

Truck and trailer routing problem (TTRP) is one of the most frequently encountered problem in city distribution, particularly in populated and intensive downtown. This paper addresses this problem and designs a novel backtracking search algorithm (BSA) based meta-heuristics to solve it. The initial population is created by T-sweep heuristic and then based on the framework of backtracking search algorithm, four types of route improvement strategies are used as building blocks to improve the solutions of BSA in the process of mutation and crossover. The computational experiments and results indicate that the proposed BSA algorithm can provide an effective approach to generate high-quality solutions within the satisfactory computational time.

An M/M/1 constant retrial queue with balking customers and set-up time is considered. Once the system becomes empty, the server will be turned down to reduce operating costs, and it will be activated only when there is a customers arrives. In this paper, the almost unobservable case is studied, in which the information of the queue length is unavailable, whereas the state of the server can be obtained. Firstly, the steady state solutions are derived and the individual equilibrium strategies are analyzed. In addition, social optimization problems, including cost analysis and social welfare maximization are investigated by using the PSO algorithm. Finally, by appropriate numerical examples, the sensitivity of some main system parameters is shown.

Assessment of brand competitiveness which influences consumer trends and company's sales performance contributes to business development. This paper elaborates the theories and the main investigations of brand competitiveness, and formulates a comprehensive hierarchical structure integrating multi-attribute indexes, i.e., social, technical, managerial, environmental and cultural criteria. An integrated multi-criterion decision-making (MCDM) model combining with analytic hierarchy process (AHP), grey relational analysis (GRA) and VIKOR is presented to determine the weights of influence criteria and to evaluate brand competitiveness. The utilized integrated methodology has been proved to be valid and practical by the empirical application on three enterprises. The results provide an accurate and effective tool for MCDM problem and also a new guideline for the enterprise development.

Online media have brought tremendous changes to civic life, public opinions, and government administration. Compared with traditional media, online media not only allow individuals to browse news and express their views more freely, but also accelerate the transmission of opinions and expand influence. As public opinions may arouse societal unrest, it is worth detecting the primary topics and uncovering the evolution trends of public opinions for societal administration. Various algorithms are developed to deal with the huge volume of unstructured online media data. In this study, dynamic topic model is employed to explore topic content evolution and prevalence evolution using the original posts published from 2013 to 2017 on the Tianya Zatan Board of Tianya Club, which is one of the most popular BBS in China. Based on semantic similarities, topics are grouped into three themes: Family life, societal affairs, and government administration. The evolution of topic prevalence and content are affected by emergent incidents. Topics on family life become popular, while themes "societal affairs" and "government administration" with bigger standard deviations are more likely to be influenced by emergent hot events. Content evolution represented by monthly pairwise distance matrix is very easy to find change points of topic content.

Spatio-temporal model and event analysis were integrated in this paper, with 156 prefecture level cities' housing transaction data and 167 items policies proposed by 10 central cities between January, 2010 and December, 2018 as samples. This paper studied the regional and cross-regional spillover effects of central cities' urban housing regulation policies to the peripheral cities in the scope of urban agglomerations, as well as the policy-driven interactions of different regional real estate markets. The results indicated that: China's regional housing market has obvious characteristics of policy orientation, of which the regulation measures on some central cities can affect the residential market and produce certain spillover interference on the market fluctuations of peripheral cities in time and space dimension. When geographical factor was considered, the 10 central cities had different degree of policy spillover effects caused by distinct policy types in their respective urban agglomerations. When ignoring spatial factors, restrictive policies in Beijing, Shanghai, Zhengzhou, Xi'an, Wuhan and Shenzhen had significant cross-regional spillover effects and drove the surrounding housing markets to have geared interactions, which to a certain extent revealed the flowing way of population and wealth in China's regional economy during the past dozen years.

Recent empirical studies show that an underlying asset price process may have the property of long memory. In this paper, it is introduced the bifractional Brownian motion to capture the underlying asset of European options. Moreover, a bifractional Black-Scholes partial differential equation formulation for valuing European options based on Delta hedging strategy is proposed. Using the final condition and the method of variable substitution, the pricing formulas for the European options are derived. Furthermore, applying to risk-neutral principle, we obtain the pricing formulas for the compound options. Finally, the numerical experiments show that the parameter HK has a significant impact on the option value.

Carpooling as a transportation demand management (TDM) tool is currently being prevalent in major Chinese cities and producing much diminishment in the frequency of solo-driving trips. Meanwhile, much disputes relating to carpooling is arising. To better understand the acceptance and the influence factors of carpooling, this paper investigates travelers' willingness to provide and accept carpooling services. Firstly, a questionnaire survey was conducted. Secondly, we proposed a theoretical model, both car-owners and non-car-owners were sampled as respondents, and a multi-variable regression method was employed to analyze the survey data. Finally, we found that the higher acceptance, the more positive reactions to carpooling. The results indicate that it is necessary to improve the public's acceptance of carpooling, because lower acceptance will lead to more negative reactions towards the carpooling, which may weaken its effectiveness.

In this paper we consider a discrete-time Geo/G/1 queue with delayed Min(N, D)-policy. Using renewal process theory, total probability decomposition technique and z-transform, we study the transient and equilibrium properties of the queue length from an arbitrary initial state, and obtain both the recursive expressions of the transient state queue length distribution and the steady state queue length distribution at arbitrary time epoch n⁺. Furthermore, we derive the important relations between equilibrium queue length distributions at different time epochs n^-, n and n⁺. Finally, we give some numerical examples about capacity decision in queueing systems to demonstrate the application of the analytical results reported in this paper.

Government investment plays an important role in promoting and guiding the economic and social development in China. Xinjiang is the core province of the Belt and Road and its economic growth is mainly driven by investment. This paper decomposes the determinants of government investment effect into economic structure change, technological change and investment structure change, using the non-competitive input-output table of Xinjiang province in 2007, 2012 and 2015 and structural decomposition analyses. The results show that, the government investment effect in Xinjiang shows a slight decline trend. During the period, the change of economic structure and investment structure have the negative impact on government investment effect, while the change of technology has the positive impact on government investment effect. In addition, these impacts have strong sectoral heterogeneity.

This paper investigates the frequency connectedness among economic policy uncertainties of G20 countries using the novel frequency connectedness proposed by Barunik and Krehlik (2018) which can depict the dynamic connectedness not only over time but also across different frequencies. The empirical results obtained in this paper demonstrate that, firstly, the connectedness among economic policy uncertainties is significant, and the spillover effects during the financial crisis and the postfinancial crisis period are stronger than the pre-financial crisis period. Secondly, the United States, France, and Australia are the main net-transmitters of the economic policy uncertainty spillovers while Brazil, Italy, Mexico, and Russia act as the main net-recipients of the spillovers. Thirdly, the major international events may significantly enhance the spillover transmissions of economic policy uncertainty among different countries, thus increasing the magnitude of the total connectedness. Finally, the economic policy uncertainty spillovers are mainly transmitted in the short term, i.e., 1~4 months instead of longer time horizons in terms of the magnitude of the frequency connectedness measures. The findings of this paper not only have profound theoretical and practical significance but also provide several significant implications for the policymakers, supervision agents, international traders, and various investors.

In this work, neutral stochastic functional differential equations with infinite delay (NSFDEwID) have been addressed. By using the Euler-Maruyama scheme and a localization argument, the existence and uniqueness of solutions to NSFDEwID at the state space C_r under the local weak monotone condition, the weak coercivity condition and the global condition on the neutral term have been investigated. In addition, the $ {\cal{L}}^2$ and exponential estimates of NSFDEwID have been studied.

The optimization investment policy decision of SCM-supply chain management-implementation has been analysed under symmetric and asymmetric information conditions. For both conditions, SCM implementation optional decision optimizing models have been developed. In these models, both clients and vendors try to pursue their own benefits. Based upon the principal-agent theory, the models show to what extent a principal (a client) needs to pay more to an agent (a vendor) in a context of asymmetric information. For the client it is important to understand the extra costs to be able to adopt effective strategies to stimulate a vendor to perform an optimal implementation of a SCM system. The results of a simulation experiment regarding SCM implementation options illustrate and verify the theoretical findings and confirm the general notion that the less informed party is obliged to pay information rent to the better-informed party.

This paper aims to propose a new trend in research which integrates the online customer relationship management through the perspectives of perceived value, satisfaction, and e-trust regarding the online restaurant in Chinese e-CRM business backgrounds. This study constructs a structural equation model to analyze the online restaurant marketing with the research perspective of the relationships among perceived value, satisfaction and e-Trust, corresponding to the cognitive belief, affective experiences and cognitive behavior of e-CRM. This model proposes six hypotheses concerning the relationships among perceived value, satisfaction and e-trust, aiming to demonstrate the predominant factors affecting the online restaurant sales and further to have a better understanding of the customers' preferences on placing orders and purchases in the online context. The results show that there is a series of connections among perceived value, satisfaction and e-trust, and most of them are important. First, the perceived value has an incentive effect on satisfaction, e-trust, and customers' commitment to a relationship. Second, satisfaction has a positive impact on e-trust and leads to the commitment to a relationship. Third, e-trust positively affects the consumer commitment to a relationship. In addition, production quality, service quality and price fairness have a significant impact on the perceived value.

Based on image segmentation and the dark channel prior, this paper proposes a fog removal algorithm in the HSI color space. Usually, the dark channel prior based defogging methods easily produce color distortion and halo effect when applied on images with a large sky area, because the sky region does not meet the prior assumption. For this reason, our method presents a new threshold sky region segmentation algorithm using the initial transmission map of the intensity component Ⅰ. Based on the segmentation result, the initial transmission map is modified in turn, and finally refined by the guided filter. The saturation components S is reconstructed using the low frequencies of the V-transform to reduce noise, and stretched by multiplying a constant related to the initial transmission map. Experimental results show that the proposed algorithm has low time complexity and compelling fog removal result in both visual effect and quantitative measurement.

Although China has made great achievements in economic scale, the model of high-quality economic developments is still in the exploratory stage. A series problems, such as unreasonable industrial structure and low production efficiency, need to be resolved urgently. The transformation and upgrading of industrial structure is the inevitable choice. The analysis of industrial relations is an important method to reveal the internal mechanism of industrial structure change. Therefore, based on the concepts of sensitivity and influence coefficient, this paper proposed the concepts of driven and driving coefficient, and constructed the industrial complex networks of China from 1999 to 2013 according to the EORA input-output table. From the perspectives of the interaction power, industrial linkages and community structure, this paper systematically analyzes the evolution of China's industrial structure. Results show that China's industrial structure is undergoing a transformation from industry-oriented to industry-service-oriented. The interaction linkages between industries has formed a robust association structure. The traditional sectors such as infrastructure construction and industries are still the largest consumer group driving the development of other industries. Besides, light industry, infrastructure construction and finance have become increasingly important hub industries in the industrial system. However, some unbalanced community structures are formed in the economic system, which has resulted in a waste of resources and low production efficiency to a certain extent. Effectively grasping the relationship between China's industrial structure evolution and its association is conducive to formulating economic restructuring policies, promoting the upgrading of China's economic and, realizing the leap from quantitative change to qualitative change.

China's grain science and technology policies have played an important role in the development of China's food industry. This paper aims to examine the effects of China's grain science and technology policies on food security. It quantitatively assesses China's food security by analyzing the main contents and development trends of China's food science technology policies through the text metrology method, and then investigates the effects of grain science and technology policies on food security by employing a provincial dynamic panel model. The results show that food security in China is all-round developed, and that the release frequency and cumulative effect of grain science and technology policies play a significant role in promoting food security. Powerful grain science and technology policies can effectively guarantee China's food security.

In this paper, we investigate the multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant trapezoid fuzzy information. Firstly, inspired by the idea of hesitant fuzzy sets and trapezoid fuzzy numbers, the definition of hesitant trapezoid fuzzy set and some operational laws of hesitant trapezoid fuzzy elements are proposed. Then some hesitant trapezoid fuzzy aggregation operators based on Hamacher operation are developed, such as the hesitant trapezoid fuzzy Hamacher weighted average (HTrFHWA) operator, the hesitant trapezoid fuzzy Hamacher weighted geometric (HTrFHWG) operator, the hesitant trapezoid fuzzy Hamacher Choquet average (HTrFHCA), the hesitant trapezoid fuzzy Hamacher Choquet geometric (HTrFHCG), etc. Furthermore, an approach based on the hesitant trapezoid fuzzy Hamacher weighted average (HTrFHWA) operator and the hesitant trapezoid fuzzy Hamacher weighted geometric (HTrFHWG) operator is proposed for MADM problems under hesitant trapezoid fuzzy environment. Finally, a numerical example for supplier selection is given to illustrate the application of the proposed approach.

Detecting differential expression of genes in genom research (e.g., 2019-nCoV) is not uncommon, due to the cost only small sample is employed to estimate a large number of variances (or their inverse) of variables simultaneously. However, the commonly used approaches perform unreliable. Borrowing information across different variables or priori information of variables, shrinkage estimation approaches are proposed and some optimal shrinkage estimators are obtained in the sense of asymptotic. In this paper, we focus on the setting of small sample and a likelihood-unbiased estimator for power of variances is given under the assumption that the variances are chi-squared distribution. Simulation reports show that the likelihood-unbiased estimators for variances and their inverse perform very well. In addition, application comparison and real data analysis indicate that the proposed estimator also works well.

We propose a two-echelon remanufacturing model in the context of two periods in which the factor of patent protection of the original manufacturer is considered. Through the analysis of the Stackelberg game among the supplier, the original manufacturer and the remanufacturer we obtain the equilibrium solutions of the unit patent licensing fee of the original manufacturer, the recycling effort degree of the remanufacturer, the wholesale price of new and remanufactured core components and the retail price of new and remanufactured products in the second period which are all dependent on the retail price of new products in the first period in cases with patent protection and without patent protection. In the numerical study we analyze the impacts of the remanufacturing rate of used products and the retail price of new products in the first period on the equilibrium results of the second period, and make a comparison between the case with patent protection and the case without patent protection.

With the rapid development of cloud computing and other related services, higher requirements are put forward for network transmission and delay. Due to the inherent distributed characteristics of traditional networks, machine learning technology is difficult to be applied and deployed in network control. The emergence of SDN technology provides new opportunities and challenges for the application of machine learning technology in network management. A load balancing algorithm of Internet of things controller based on data center SDN architecture is proposed. The Bayesian network is used to predict the degree of load congestion, combining reinforcement learning algorithm to make optimal action decision, self-adjusting parameter weight to adjust the controller load congestion, to achieve load balance, improve network security and stability.