ALBERT

Description: Various space missions, including the Russian and Chinese interplanetary exploration collaboration in 2011 and the Phobos-Grunt space project to be relaunched by the Chinese in 2025, carry a soil preparation system (SOPSYS), which is an instrument used for scientific experiments. The design and manufacture of this precision instrument require stringent manufacturing processes and workflow of the highest quality, with every process in the project carefully monitored and controlled. All processes should be completed within the deadline so that the space project can be launched at the scheduled time. The colored Petri net (CPN) modeling method can describe a variety of resource types and execution logic, and it can be formally verified. Based on these advantages, we clearly describe the complex structure of the SPOSYS unit production process. In addition, we use critical time and the 6 sigma system to evaluate the availability and reliability of workflows, and we use elimination and simplification (ECRS) methods and constraint theory to improve the manufacturing process of the SOPSYS unit. We further provide optimization theories, methods, and insights for workflow management in time-sensitive and independent manufacturing systems.

Description: This paper studies the global stability of a discrete-time pathogen dynamic model with both cell-mediated and antibody immune responses. Both latently and actively infected cells are incorporated into the model. We discretize the continuous-time model by using the nonstandard finite difference (NSFD) method. We establish that NSFD preserves the nonnegativity and boundedness of the solutions of the model. We derive four threshold parameters which govern the existence and stability of the steady states. We establish by using the Lyapunov method, the global stability of the five steady states of the model. We illustrate our theoretical results by using numerical simulations.

Description: This work is to discuss the Dirichlet boundary value problem of the difference equation with p -mean curvature operator. Under some determinate growth conditions on the nonlinear term, the existence of one solution or two nontrivial solutions is obtained via variational methods and some analysis techniques. Examples are also given to illustrate our theorems in the last section.

Description: This paper aims at the dynamic properties of the proposed globally planned economic systems named after CPE proposed by Loo-Keng Hua who is one of the worldwide famous Chinese mathematicians. First, we give new existence conditions of growth balanced solution to the model. Second, we lead into the concept of stability for balanced output and carry out a theorem that deals with some equivalent conditions for judging a solution of output starting from the fact that any initial input can whether approach the existing balanced solution or not. Third, a new dynamic price system related to interest factors is proposed here and it is demonstrated that the new price equation is a much generalized one in comparison with the original price one which is only a special case of this new price equation. Also, relationships of the balanced solutions between the price and the output equation are investigated and the stability analysis is studied as well for the new price system. Finally, two examples are employed to illustrate the technical operation of input-output method and some new contributions of this article.

Description: In this paper, we mainly study an exponential spline function space, construct a basis with local supports, and present the relationship between the function value and the first and the second derivative at the nodes. Using these relations, we construct an exponential spline-based difference scheme for solving a class of boundary value problems of second-order ordinary differential equations (ODEs) and analyze the error and the convergence of this method. The results show that the algorithm is high accurate and conditionally convergent, and an accuracy of 1/240h6 was achieved with smooth functions.

Description: Atrial fibrillation (AF) is a common abnormal heart rhythm disease. Therefore, the development of an AF detection system is of great significance to detect critical illnesses. In this paper, we proposed an automatic recognition method named CNN-LSTM to automatically detect the AF heartbeats based on deep learning. The model combines convolutional neural networks (CNN) to extract local correlation features and uses long short-term memory networks (LSTM) to capture the front-to-back dependencies of electrocardiogram (ECG) sequence data. The CNN-LSTM is feeded by processed data to automatically detect AF signals. Our study uses the MIT-BIH Atrial Fibrillation Database to verify the validity of the model. We achieved a high classification accuracy for the heartbeat data of the test set, with an overall classification accuracy rate of 97.21%, sensitivity of 97.34%, and specificity of 97.08%. The experimental results show that our model can robustly detect the onset of AF through ECG signals and achieve stable classification performance, thereby providing a suitable candidate for the automatic classification of AF.

Description: In the original manufacturing industry, upstream encroachment has become a universal commercial phenomenon. This paper considers a coopetition supply chain consisting of an upstream original design manufacturer (ODM) and a downstream original equipment manufacturer (OEM) and proposes a dynamic Cournot game under bounded rationality. To cope with a dynamic repeated game in discrete time, a gradient adjustment mechanism is adopted. Furthermore, bifurcation diagram, largest Lyapunov exponent, basin of attraction, and critical curve are introduced to investigate the dynamic behavior of this game. The results obtained show that as the firms’ policy adjustment speeds increase, the stability region of the dynamic system gradually narrows, but one special finding is that the complex behavior of the dynamic system is alleviated as the OEM’s adjustment speed greatly increases. Moreover, when the difference between the two firms’ adjustment speeds is relatively small, the dynamic adjustment strategy is beneficial to the coopetition supply chain and both firms under certain adjustment speeds, as compared to a one-shot game. In addition, a higher product substitutability has a positive impact on the system stability, pushing the “cooperation” business alliance towards a more coordinated outcome.

Description: This study applies 3-stage data envelopment (DEA) of 24 listed companies in the development zone of Hubei Province from 2012 to 2017 based on the panel data; we used the DEA-Tobit model and regression analysis method on the sample in order to measure the factors affecting the innovation efficiency of listed companies and the efficiency of corporate innovation. The results demonstrated that the innovation efficiency of listed companies in the development zone of Hubei Province is relatively low. It is necessary to improve the innovation system of the development zone and give the full initiative to the role of corporate innovation as a mainstay. The four environmental variables of the number of enterprises, government subsidies, foreign direct investment in the development zone, and fixed asset investment have a significant impact on innovation efficiency. The enterprise size, operating capacity, and state-owned shares of the company have a significant positive impact on the innovation efficiency. But the number of years of the establishment has a significant negative impact on innovation efficiency. Moreover, the quality of the workers is not significant. Therefore, we must increase government investment in innovation to expand the scale of listed companies in the development zone, improve the environment for foreign investment, further strengthen the construction of talented people of companies, and enhance the original ability of innovation.

Description: The variable connectivity index, introduced by the chemist Milan Randić in the first quarter of 1990s, for a graph G is defined as ∑vw∈EGdv+γdw+γ−1/2, where γ is a non-negative real number and dw is the degree of a vertex w in G. We call this index as the variable Randić index and denote it by Rvγ. In this paper, we show that the graph created from the star graph of order n by adding an edge has the minimum Rvγ value among all unicyclic graphs of a fixed order n, for every n≥4 and γ≥0.

Description: In this paper, global dynamical properties of rational higher-order system are explored in the interior of ℝ+3. It is explored that under certain parametric conditions, the discrete-time system has at most eight equilibria. By the method of linearization, local dynamics has been explored. It is explored that positive solution of the system is bounded, and moreover fixed point P000 is globally stable if α1/α2

Description: M.Kriesell conjectured that there existed b, h such that every 5-connected graph G with at least b vertices can be contracted to a 5-connected graph G0 such that 0

Description: Risk statistic is a critical factor not only for risk analysis but also for financial application. However, the traditional risk statistics may fail to describe the characteristics of regulator-based risk. In this paper, we consider the regulator-based risk statistics for portfolios. By further developing the properties related to regulator-based risk statistics, we are able to derive dual representation for such risk.

Description: Price competition has become a universal commercial phenomenon nowadays. This paper considers a dynamic Bertrand price game model, in which enterprises have heterogeneous expectations. By the stability theory of the dynamic behavior of the Bertrand price game model, the instability of the boundary equilibrium point and the stability condition of the internal equilibrium point are obtained. Furthermore, bifurcation diagram, basin of attraction, and critical curve are introduced to investigate the dynamic behavior of this game. Numerical analysis shows that the change of model parameters in a dynamic system has a significant impact on the stability of the system and can even lead to complex dynamic behaviors in the evolution of the entire economic system. This kind of complex dynamic behavior will cause certain damage to the stability of the whole economic system, causing the market to fall into a chaotic state, which is manifested as a kind of market disorder competition, which is very unfavorable to the stability of the economic system. Therefore, the chaotic behavior of the dynamical system is controlled by time-delay feedback control and the numerical analysis shows that the effective control of the dynamical system can be unstable behavior and the rapid recovery of the market can be stable and orderly.

Description: Sandstone is different from pure brittle rocks such as marble and granite. Its brittleness weakens and then increases with increasing confining pressure. This paper establishes a calculation model of the “brittleness-ductility” energy drop coefficient that characterizes the whole process of sandstone failure from the perspective of energy. The obtained result was compared with the result of traditional calculation model. The results show that the established model is more consistent with the experimental phenomenon and can describe the whole process of sandstone failure more precisely at a macro level. Moreover, the model is more practical since it avoids the tedious integration calculation process. The model and tests have extended the applicable range and applied rock types of the energy drop coefficient and enriched the knowledge system of elastoplastic mechanics. At the same time, they carry important significance for environmental restoration and geological disaster prevention and control in sedimentary rock mining zones, which can promote the sustainable development of related industries in the mining zones.

Description: This work analyzes the passivity for a set of Markov jumping reaction-diffusion neural networks limited by time-varying delays under Dirichlet and Neumann boundary conditions, respectively, in which Markov jumping is used to describe the variations among system parameters. To overcome some difficulties originated from partial differential terms, the Lyapunov–Krasovskii functional that introduces a new integral term is proposed and some inequality techniques are also adopted to obtain the delay-dependent stability conditions in terms of linear matrix inequalities, which ensures that the designed neural networks satisfy the specified performance of passivity. Finally, the advantages and effectiveness of the obtained results are verified via displaying two illustrated examples.

Description: In this article, we prove some weak and strong convergence theorems for mappings satisfying condition (E) using the AK iterative scheme in the setting of Banach spaces. We offer a new example of mapping with condition (E) in support of our main result. Our results extend and improve many well-known corresponding results of the current literature.

Description: Cyanobacteria in Chaohu Lake multiply rapidly and diffuse in large quantities every summer, which has a serious impact on the normal life of the surrounding residents and the local economic development. Therefore, it is urgent to control the cyanobacterial pollutants in Chaohu Lake. In this context, in order to improve the scientificalness and feasibility of control measures, it is an important prerequisite and condition to grasp the change of cyanobacterial pollutant diffusion in Chaohu Lake. For this reason, a computational model for cyanobacterial pollutant diffusion in Chaohu Lake, China, was designed based on the relevant large data. The design of the model is divided into three parts: the first part builds an area calculation model to analyze the change of cyanobacterial pollutant diffusion area; the second part builds a concentration calculation model to analyze the change of cyanobacterial pollutant concentration; and the third part combines the previous two to build a diffusion change calculation model to analyze the rule of cyanobacterial pollutant diffusion change in Chaohu Lake. In order to verify the feasibility and validity of the model, simulation experiments were carried out. The results show that, under the large data related to cyanobacteria pollution in Chaohu Lake, China, from May to August 2017, the calculation model is used to calculate the cyanobacteria pollutant diffusion change. The data obtained are basically consistent with the actual situation, which proves the feasibility and validity of the model. This provides data support for the cyanobacteria pollution control in Chaohu Lake and improves the efficiency and effect of the control.

Description: The aim of aspect-level sentiment analysis is to identify the sentiment polarity of a given target term in sentences. Existing neural network models provide a useful account of how to judge the polarity. However, context relative position information for the target terms is adversely ignored under the limitation of training datasets. Considering position features between words into the models can improve the accuracy of sentiment classification. Hence, this study proposes an improved classification model by combining multilevel interactive bidirectional Gated Recurrent Unit (GRU), attention mechanisms, and position features (MI-biGRU). Firstly, the position features of words in a sentence are initialized to enrich word embedding. Secondly, the approach extracts the features of target terms and context by using a well-constructed multilevel interactive bidirectional neural network. Thirdly, an attention mechanism is introduced so that the model can pay greater attention to those words that are important for sentiment analysis. Finally, four classic sentiment classification datasets are used to deal with aspect-level tasks. Experimental results indicate that there is a correlation between the multilevel interactive attention network and the position features. MI-biGRU can obviously improve the performance of classification.

Description: In this paper, our aim is to finding the solutions of the fractional kinetic equation related with the p,q-Mathieu-type series through the procedure of Sumudu and Laplace transforms. The outcomes of fractional kinetic equations in terms of the Mittag-Leffler function are presented.

Description: Crash severity prediction has been raised as a key problem in traffic accident studies. Thus, to progress in this area, in this study, a thorough artificial neural network combined with an improved metaheuristic algorithm was developed and tested in terms of its structure, training function, factor analysis, and comparative results. Data from I5, an interstate highway in the Washington State during the period of 2011–2015, were used for fitting and prediction, and after setting the theoretical three-layer neural network (NN), an improved Particle Swarm Optimization (PSO) method with adaptive inertial weight was offered to optimize the NN, and finally, a comparison among different adaptive strategies was conducted. The results showed that although the algorithms produced almost the same accuracy in their predictions, a backpropagation method combined with a nonlinear inertial weight setting in PSO produced fast global and accurate local optimal searching, thereby demonstrating a better understanding of the entire model explanation, which could best fit the model, and at last, the factor analysis showed that non-road-related factors, particularly vehicle-related factors, are more important than road-related variables. The method developed in this study can be applied to a big data analysis of traffic accidents and be used as a fast-useful tool for policy makers and traffic safety researchers.

Description: The sigmoid polynomials combining q-numbers and various properties of their polynomials are thoroughly presented in this paper. Based on several properties of q-numbers, we derive some identities of q-sigmoid polynomials. Also, from explicit polynomials, we can observe structures of the zeros of the sigmoid polynomials which are related to q-numbers.

Description: At present, the demand for on-demand meal delivery is increasing, and the main delivery pattern is rider delivery. However, rider delivery has certain problems in terms of timeliness and security. Due to its advantages of being fast, convenient, and safe, drone delivery can, to a certain extent, solve the problems of rider delivery. However, can drone delivery completely replace rider delivery? The paper mainly uses the prospect theory to discuss the conditions under which drone delivery is superior to rider delivery based on four factors: delivery distance, degree of rider delay, pickup time, and consumer attitudes towards drone delivery. Based on the research, it was found that when the delivery distance is more than 7 kilometres, the pickup time is within 2 minutes, or when consumers accept drone delivery, drone delivery is better than rider delivery. When the rider’s delay caused the delivery time to increase by more than 20%, the advantages of drone delivery began to stand out. Moreover, research has proven that drone delivery will help expand the scope of instant delivery, and the rational layout of drone airports and strengthening of consumer awareness and friendliness towards drone delivery will also help promote the development of drone delivery.

Description: The recommendation algorithm can break the restriction of the topological structure of social networks, enhance the communication power of information (positive or negative) on social networks, and guide the information transmission way of the news in social networks to a certain extent. In order to solve the problem of data sparsity in news recommendation for social networks, this paper proposes a deep learning-based recommendation algorithm in social network (DLRASN). First, the algorithm is used to process behavioral data in a serializable way when users in the same social network browse information. Then, global variables are introduced to optimize the encoding way of the central sequence of Skip-gram, in which way online users’ browsing behavior habits can be learned. Finally, the information that the target users’ have interests in can be calculated by the similarity formula and the information is recommended in social networks. Experimental results show that the proposed algorithm can improve the recommendation accuracy.

Description: In this paper, we have studied epidemiological models for Ebola infection using nonlinear ordinary differential equations and optimal control theory. We considered optimal control analysis of SIR and SEIR models for the deadly Ebola infection using vaccination, treatment, and educational campaign as time-dependent control functions. We have applied indirect methods to study existing deterministic optimal control epidemic models for Ebola virus disease. These methods in optimal control are based on Hamiltonian function and Pontryagin’s maximum principle to construct adjoint equations and optimality systems. The forward-backward sweep numerical scheme with the fourth-order Runge–Kutta method is used to solve the optimality system for the various control strategies. From our numerical illustrations, we can conclude that effective educational campaigns and vaccination of susceptible individuals as well as effective treatments of infected individuals can help reduce the disease transmission.

Description: Purpose. The purpose of this article is to predict the topic popularity on the social network accurately. Indicator selection model for a new definition of topic popularity with degree of grey incidence (DGI) is undertook based on an improved analytic hierarchy process (AHP). Design/Methodology/Approach. Through screening the importance of indicators by the deep learning methods such as recurrent neural networks (RNNs), long short-term memory (LSTM), and gated recurrent unit (GRU), a selection model of topic popularity indicators based on AHP is set up. Findings. The results show that when topic popularity is being built quantitatively based on the DGI method and different weights of topic indicators are obtained from the help of AHP, the average accuracy of topic popularity prediction can reach 97.66%. The training speed is higher and the prediction precision is higher. Practical Implications. The method proposed in the paper can be used to calculate the popularity of each hot topic and generate the ranking list of topics’ popularities. Moreover, its future popularity can be predicted by deep learning methods. At the same time, a new application field of deep learning technology has been further discovered and verified. Originality/Value. This can lay a theoretical foundation for the formulation of topic popularity tendency prevention measures on the social network and provide an evaluation method which is consistent with the actual situation.

Description: In this paper, we consider a class of boundary value problems of nonlinear fractional differential equation with integral boundary conditions. By applying the monotone iterative method and some inequalities associated with Green’s function, we obtain the existence of minimal and maximal positive solutions and establish two iterative sequences for approximating the solutions to the above problem. It is worth mentioning that these iterative sequences start off with zero function or linear function, which is useful and feasible for computational purpose. An example is also included to illustrate the main result of this paper.

Description: In this work, we propose a multifishing area prey-predator discrete-time model which describes the interaction between the prey and middle and top predators in various areas, which are connected by their movements to their neighbors, to provide realistic description prey effects of two predators. A grid of colored cells is presented to illustrate the entire domain; each cell may represent a subdomain or area. Next, we propose two harvesting control strategies that focus on maximizing the biomass of prey, in the targeted area, and minimizing the biomass of middle and top predators coming from the neighborhood of this targeted area to ensure sustainability and maintain a differential chain system. Theoretically, we have proved the existence of optimal controls, and we have given a characterization of controls in terms of states and adjoint functions based on a discrete version of Pontryagin’s maximum principle. To illustrate the theoretical results obtained, we propose numerical simulations for several scenarios applying the forward-backward sweep method (FBSM) to solve our optimality system in an iterative process.

Description: In this paper, we present a predator-prey system with mutual interference and distributed time delay and study its dynamical behavior. Based on the existence and universality of mutual interference among species, it is necessary to further study an impulsive food web system. By using stability theory, slight perturbation technique, and comparison theorem, we obtain some theoretical results of the system, such as boundedness and permanence. Moreover, numerical experiments are used to verify the theoretical results and to explore the dynamical behavior of the system, which exhibits rich dynamical behavior such as chaotic oscillation, periodic oscillation, symmetry-breaking bifurcations, chaotic crises, and period bifurcation. Finally, we give some practical guidelines for biological systems based on the theoretical results and numerical experiments of the system.

Description: In this paper, an alcoholism model of SEAR type with different susceptibilities due to public health education is investigated, with the form of continuous differential equations as well as discrete differential equations by applying the Mickens nonstandard finite difference (NSFD) scheme to the continuous equations. Threshold dynamics of the continuous model are performed by constructing Lyapunov functions. The analysis of a discrete model indicates that the alcohol-free equilibrium is globally asymptotically stable if the basic reproductive number , and conversely, the alcohol-present equilibrium is globally asymptotically stable if , revealing the consistency and efficiency of the discrete model to preserve the dynamical properties of the corresponding continuous model. In addition, stability preserving and the impact of the parameters related with public health education are conducted by numerical simulations.

Description: A discrete allelopathic phytoplankton model with infinite delays and feedback controls is studied in this paper. By applying the discrete comparison theorem, a set of sufficient conditions which guarantees the permanence of the system is obtained. Also, by constructing some suitable discrete Lyapunov functionals, some sufficient conditions for the extinction of the system are obtained. Our results extend and supplement some known results and show that the feedback controls and toxic substances play a crucial role on the permanence and extinction of the system.

Description: The reason for the self-similarity property of complex network is still an open issue. In this paper, we focus on the influence of degree, betweenness, and coreness on self-similarity of complex network. Some nodes are removed from the original network based on the definitions of degree, betweenness, and coreness in the ascending and descending order. And then, some new networks are obtained after removing nodes. The self-similarities of original network and new networks are compared. Moreover, two real networks are used for numerical simulation, including a network and the yeast protein interaction () network. The effects of the three statistical variables on the two real networks are considered. The results reveal that the nodes with large degree and betweenness have great effects on self-similarity, and the influence of coreness on self-similarity is small.

Description: Nowadays, deep learning has achieved remarkable results in many computer vision related tasks, among which the support of big data is essential. In this paper, we propose a full stage data augmentation framework to improve the accuracy of deep convolutional neural networks, which can also play the role of implicit model ensemble without introducing additional model training costs. Simultaneous data augmentation during training and testing stages can ensure network optimization and enhance its generalization ability. Augmentation in two stages needs to be consistent to ensure the accurate transfer of specific domain information. Furthermore, this framework is universal for any network architecture and data augmentation strategy and therefore can be applied to a variety of deep learning based tasks. Finally, experimental results about image classification on the coarse-grained dataset CIFAR-10 (93.41%) and fine-grained dataset CIFAR-100 (70.22%) demonstrate the effectiveness of the framework by comparing with state-of-the-art results.

Description: We study the local dynamics and bifurcation analysis of a discrete-time modified Nicholson–Bailey model in the closed first quadrant . It is proved that model has two boundary equilibria: , and a unique positive equilibrium under certain parametric conditions. We study the local dynamics along their topological types by imposing method of Linearization. It is proved that fold bifurcation occurs about the boundary equilibria: . It is also proved that model undergoes a Neimark–Sacker bifurcation in a small neighborhood of the unique positive equilibrium and meanwhile stable invariant closed curve appears. From the viewpoint of biology, the stable closed curve corresponds to the period or quasi-periodic oscillations between host and parasitoid populations. Some simulations are presented to verify theoretical results. Finally, bifurcation diagrams and corresponding maximum Lyapunov exponents are presented for the under consideration model.

Description: The population of Beijing has already come to its loading capacity. The China central government plans to build an ideal city named Xiong’an nearby Beijing. The city is expected to work as a carrying hub for noncapital functions of Beijing. The central government does not rush to build before a deliberated urban planning is accomplished. For sustainable development, a difficulty faced by urban planners is that the maximum number of people can be migrated from Beijing to Xiong’an with constraint on level of transport service. This paper developed a specialized bilevel programming model where the upper level is to ensure a predetermined transport service level regarding to population migration, while the lower level is feedback equilibrium between trip generation and traffic assignment. To be more specific, trip is generated by the gravity model, and traffic is assigned by the user equilibrium model. It is well known that the bilevel programming problem is tough and challenging. A try-and-error algorithm is designed for the upper-level model, and a method of successive average (MSA) is developed for the lower-level model. The effectiveness of the model and algorithm is validated by an experimental study using the current transport network between Beijing and Xiong’an. It shows that the methods can be very useful to identify the maximum population migration subject to level of transport service.

Description: This paper investigates a dual exclusive channel model in which each manufacturer distributes its goods through a single exclusive retailer, but two goods are substitute. The decision rule between two channels is Nash game in Case 1, while it is Stackelberg game in Case 2. From manufacturer Stackelberg (MS), retailer Stackelberg (RS), and Nash game (VN) theoretic perspectives, nine game models are developed to examine the effect of product substitutability and relative channel status on pricing decisions at both horizontal competition and vertical competition levels. The analysis suggests that the type of price leadership scenarios, the level of product substitutability, and the relative channel status play a significant role in decision making. For instance, in case 1, the symmetric leadership (two manufacturers or two retailers are leaders) is always the dominant strategy and equilibrium for either two manufacturers or two retailers regardless of product substitutability and relative channel status. Nevertheless, the asymmetric leadership may lead channel members to encounter a prisoner’s dilemma if the relative channel status is small. By contrast, in Case 2, the symmetric leadership is not the unique dominant strategy for either two manufacturers or two retailers. In contrast to many earlier results, we also show that whether the first-mover and the late-mover advantages exist, depending on the level of related channel status.

Description: In some queueing systems, customers are frequently asked for giving a service quality feedback for their service at their service completion instants. Based on this phenomenon, in this paper, we model this type of queueing systems as clearing queues with service quality feedback and system maintenance. Once the system receives an unsatisfied (negative) feedback from customers (i.e., a customer is unsatisfied with the service), the system undergoes an adjustment procedure, and at the same time, all the present customers are forced to leave the system. By considering the waiting cost and reward, we discuss the joining behavior of customers and, respectively, derive the corresponding equilibrium joining strategies and social optimal strategies under different levels of information (the observable and the unobservable cases). Finally, some numerical examples are provided to show the effect of several system parameters on the equilibrium and optimal balking strategies.

Description: Government subsidy promotes the development of green supply chain, and the influence of decision-makers’ behavioral preferences becomes increasingly prominent in green supply chain management. In order to further enrich the research content of green supply chain, we first use Stackelberg game theory to construct game models by taking the product green degree, wholesale price and retail price as the decision variables, then we work out the equilibrium strategies of the manufacturer and the retailer under four decision scenarios, and reveal the impact differences between the two parties’ fairness preference behaviors. Our research mainly has the following findings: Firstly, the government subsidy to the manufacturer can benefit these two parties and can have certain impact on the optimal decisions only by working with the green product market expansion efficiency. Secondly, these two parties’ fairness preference behaviors can cause serious damage to the other party’s profit and the overall profit of green supply chain, and increase the rate of their own profit in the overall profit of green supply chain, but the difference is that the retailer’s fairness preference behavior can cause a greater decline in product green degree and wholesale price, and when certain conditions are met, its own profit may rise compared to its fairness neutral, while the manufacturer’s fairness preference behavior can cause a greater damage to the overall profit of green supply chainand make its own profit always be lower than its fairness neutral. Thirdly, the government subsidy to the manufacturer and the fairness preference behaviors of both parties can cause a stack effect on the optimal solutions, which means that the subsidy government provides for the manufacturer can aggravate the negative influence caused by these two parties’ fairness preference behaviors.

Description: The study of forest fire prediction is of great environmental and scientific significance. China’s Guangxi Autonomous Region has a high incidence rate of forest fires. At present, there is little research on forest fires in this area. The application of the artificial neural network and support vector machines (SVM) in forest fire prediction in this area can provide data for forest fire prevention and control in Guangxi. In this paper, based on Guangxi’s 2010–2018 satellite monitoring hotspot data, meteorology, terrain, vegetation, infrastructure, and socioeconomic data, the researchers determined the main forest fire driving factors in Guangxi. They used feature selection and backpropagation neural networks and radial basis SVM to build forest fire prediction models. Finally, the researchers use the accuracy, precision, and area under the characteristic curve (ROC-AUC) and other indicators to evaluate the predictive performance of the two models. The results showed that the prediction accuracy of the BP neural network and SVM is 92.16% and 89.89%, respectively. As both results are over 85%, the requirements of prediction accuracy is met. These results can be used for forest fire prediction in the Guangxi Autonomous Region. Specifically, the accuracy of the BP neural network was 0.93, which was higher than that of the SVM model (0.89); the recall of the SVM model was 0.84, which was lower than the BANN model (0.92), and the AUC value of the SVM model was 0.95, which was lower than the BP neural network model. The obtained results confirm that the BP neural network model can provide more prediction accuracy than support vector machines and is therefore more suitable for forest fire prediction in Guangxi, China. This research provides the necessary theoretical basis and data support for application in the field of forestry of the Guangxi Autonomous Region, China.

Description: In this paper, we investigate an approximation of the Euler equation by the second-grade fluid equations in ℝdd=2,3. The convergence in Hm of a sequence of solutions to the second-grade fluid equations in a uniform interval is proven as both the viscosity coefficient ν and filter parameter α tend to zero with an initial velocity in Hm.

Description: Scene parsing plays a crucial role when accomplishing human-robot interaction tasks. As the “eye” of the robot, RGB-D camera is one of the most important components for collecting multiview images to construct instance-oriented 3D environment semantic maps, especially in unknown indoor scenes. Although there are plenty of studies developing accurate object-level mapping systems with different types of cameras, these methods either process the instance segmentation problem in completed mapping or suffer from a critical real-time issue due to heavy computation processing required. In this paper, we propose a novel method to incrementally build instance-oriented 3D semantic maps directly from images acquired by the RGB-D camera. To ensure an efficient reconstruction of 3D objects with semantic and instance IDs, the input RGB images are operated by a real-time deep-learned object detector. To obtain accurate point cloud cluster, we adopt the Gaussian mixture model as an optimizer after processing 2D to 3D projection. Next, we present a data association strategy to update class probabilities across the frames. Finally, a map integration strategy fuses information about their 3D shapes, locations, and instance IDs in a faster way. We evaluate our system on different indoor scenes including offices, bedrooms, and living rooms from the SceneNN dataset, and the results show that our method not only builds the instance-oriented semantic map efficiently but also enhances the accuracy of the individual instance in the scene.

Description: Due to information asymmetry, adverse selection exists largely in the multiagent market. Aiming at these problems, we develop two models: pure adverse selection model and mixed adverse selection and moral hazard model. We make the assumption that a type of agent is discrete and effort level is continuous in the models. With these models, we investigate the characters that make an optimal contract as well as the conditions under which the utility of a principal and agents can be optimized. As a result, we show that, in the pure adverse selection model, the conditions to reach the optimal utility of a principal and individual agents are that a principal needs to design different contracts for different types of agents, and an individual agent chooses the corresponding type of contracts. For the mixed model, we show that incentive constraint for agents plays a very important role. In fact, we find that whether a principal provides high-type contract or a separating equilibrium contract depends on the probability of existence of low-type agents in the market. In general, if a separating equilibrium contract is issued, then information asymmetry will cause the utility of the high-type agents to be less than that of the case in full information.

Description: We propose a mathematical model that describes the dynamics of citizens who have the right to register on the electoral lists and participate in the political process and the negative influence of abstainers, who abstain from registration on the electoral lists, on the potential electors. By using Routh–Hurwitz criteria and constructing Lyapunov functions, the local stability and the global stability of abstaining-free equilibrium and abstaining equilibrium are obtained. We also study the sensitivity analysis of the model parameters to know the parameters that have a high impact on the reproduction number . In addition, we propose an optimal strategy for an awareness program that helps politicians and officials to increase the rate of citizens registered on the electoral lists with an optimal effort. Pontryagin’s maximum principle is used to characterize the optimal controls, and the optimality system is solved by an iterative method. Finally, some numerical simulations are performed to verify the theoretical analysis using Matlab.

Description: Dengue fever is caused by dengue virus and transmitted by Aedes mosquitoes. A promising avenue to control this disease is to infect the wild Aedes population with the bacterium Wolbachia driven by cytoplasmic incompatibility (CI). To study the invasion of Wolbachia into wild mosquito population, we formulate a discrete competition model and analyze the competition between released mosquitoes and wild mosquitoes. We show the global asymptotic properties of the trivial equilibrium, boundary equilibrium, and positive equilibrium and give the conditions for the successful invasion of Wolbachia. Finally, we verify our findings by numerical simulations.

Description: This paper studies the impact of fresh-keeping effort (FKE) investment strategies from the perspective of green transportation on a fresh-product supply chain (FSC) system for the purpose of reducing the emission of harmful gases and waste of resources. A supplier–buyer structure in an FSC system is modeled under two approaches consisting of the fixed FKE model and the variable FKE model. Then the paper analyzes the effect of optimal FKE level on retailer’s profit and product freshness under two different approaches, and finds that there is space to be improved in the two approaches which were further optimized. Finally, the proposed models are approved with a dataset from a real-life case study. Under the above two approaches, not only profits can be increased in retail enterprises but also the freshness level of fresh agricultural products (FAP) can be improved and reduced the consumption of resources. The results show that there is an optimal investment level of FKE under different strategies, and the maximum profit could be obtained by keeping fresh at this level. Moreover, the fixed FKE will not increase the average freshness of fresh produce in a sales cycle, and the adjusted FKE can effectively improve the average freshness.

Description: The idea of action threshold depends on the pest density and its change rate is more general and furthermore can produce new modelling techniques related to integrated pest management (IPM) as compared with those that appeared in earlier studies, which definitely bring challenges to analytical analysis and generate new ideas to the state control measures. Keeping this in mind, using the strategies of IPM, we develop a prey-predator system with action threshold depending on the pest density and its change rate, and study its dynamical behavior. We develop new criteria guaranteeing the existence, uniqueness, local and global stability of order-1 periodic solutions. Applying the properties of Lambert function, the Poincaré map is portrayed for the exact phase set, which is helpful to provide the sufficient conditions for the existence and stability of the interior order-1 periodic solutions and boundary order-1 periodic solution, also confirmed by numerical simulations. It is studied in detail that how and under what conditions the fixed point of Poincaré map and its stability are affected by the newly introduced action threshold. The analytical methods developed in this paper will be very beneficial to study other generalized models with state-dependent feedback control.

Description: Institutional and individual investors are the two important players in the stock market. Together, they determine the price of the stock market. In this paper, an evolutionary game model that contains the two groups of players is proposed to analyze the stock price synchronicity considering the impacts of investors’ decisions on stock investment. Factors affecting investors’ decisions include the potential revenue or loss, the probability of gain or loss, and the cost of corresponding behavior. The proposed game model is analyzed by replicator dynamics equations and simulation of the evolutionary equilibrium strategy under different circumstances. The analysis shows that the operating cost of institutional investors, the cost of information collection before trading, and the expected loss that may be punished by regulators are the key factors that affect the evolutionary game system between institutional investors and individual investors. In addition, reducing the speculation in the market and increasing the information access of investors through the serious operation mode of institutional investors and the strengthening of the market information disclosure mechanism are beneficial to alleviate price synchronicity in stock market.

Description: In the present paper, we derive analytical formulas for barrier and lookback options with underlying assets exposed to multiple defaults risks which include exogenous counterparty default risk and endogenous default risk. The endogenous default risk leads the asset price drop to zero and the exogenous counterparty default risk induces a drop in the asset price, but the asset can still be traded after this default time. An original technique is developed to valuate the barrier and lookback options by first conditioning on the predefault and the afterdefault time and then obtaining the unconditional analytic formulas for their price. We also compare the pricing results of our model with the default-free option model and exogenous counterparty default risk option model.

Description: Particulate matter with a diameter less than 10 micrometers (PM10) is today an important subject of study, mainly because of its increasing concentration and its impact on environment and public health. This article summarizes the usage of convolutional neural networks (CNNs) to forecast PM10 concentrations based on atmospheric variables. In this particular case-study, the use of deep convolutional neural networks (both 1D and 2D) was explored to probe the feasibility of these techniques in prediction tasks. Furthermore, in this contribution, an ensemble method called Bagging (BEM) is used to improve the accuracy of the prediction model. Lastly, a well-known technique for PM10 forecasting, called multilayer perceptron (MLP) is used as a comparison to show the feasibility, accuracy, and robustness of the proposed model. In this contribution, it was found that the CNNs outperforms MLP, especially when they are executed using ensemble models.

Description: Considering periodic environmental changes and random disturbance, we explore the dynamical behaviors of a stochastic competitive system with impulsive and periodic parameters in this paper. Firstly, by use of extreme-value theory of quadratic function and constructing suitable functional, we study the existence of periodic Markovian process. Secondly, by comparison theory of the stochastic differential equation, we study the extinction and permanence in the mean of all species. Thirdly, applying an important lemma, we investigate the stochastic persistence of this system. Finally, some numerical simulations are given to illustrate the main results.

Description: The Turing pattern model is one of the theories used to describe organism formation patterns. Using this model, self-organized patterns emerge due to differences in the concentrations of activators and inhibitors. Here a cellular automata (CA)-like model was constructed wherein the Turing patterns emerged via the exchange of integer values between adjacent cells. In this simple hexagonal grid model, each cell state changed according to information exchanged from the six adjacent cells. The distinguishing characteristic of this model is that it presents a different pattern formation mechanism using only one kind of token, such as a chemical agent that ages via spatial diffusion. Using this CA-like model, various Turing-like patterns (spots or stripes) emerge when changing two of four parameters. This model has the ability to support Turing instability that propagates in the neighborhood space; global patterns are observed to spread from locally limited patterns. This model is not a substitute for a conventional Turing model but rather is a simplified Turing model. Using this model, it is possible to control the formation of multiple robots into such forms as circle groups or dividing a circle group into two groups, for example. In the field of information networks, the presented model could be applied to groups of Internet-of-Things devices to create macroscopic spatial structures to control data traffic.

Description: The reaction diffusion system is one of the important models to describe the objective world. It is of great guiding importance for people to understand the real world by studying the Turing patterns of the reaction diffusion system changing with the system parameters. Therefore, in this paper, we study Gierer–Meinhardt model of the Depletion type which is a representative model in the reaction diffusion system. Firstly, we investigate the stability of the equilibrium and the Hopf bifurcation of the system. The result shows that equilibrium experiences a Hopf bifurcation in certain conditions and the Hopf bifurcation of this system is supercritical. Then, we analyze the system equation with the diffusion and study the impacts of diffusion coefficients on the stability of equilibrium and the limit cycle of system. Finally, we perform the numerical simulations for the obtained results which show that the Turing patterns are either spot or stripe patterns.

Description: Agent-based modelling has been proved to be extremely useful for learning about real world societies through the analysis of simulations. Recent agent-based models usually contain a large number of parameters that capture the interactions among microheterogeneous subjects and the multistructure of the complex system. However, this can result in the “curse of dimensionality” phenomenon and decrease the robustness of the model’s output. Hence, it is still a great challenge to efficiently calibrate agent-based models to actual data. In this paper, we present a surrogate analysis method for calibration by combining supervised machine-learning and intelligent iterative sampling. Without any prior assumptions regarding the distribution of the parameter space, the proposed method can learn a surrogate model as the approximation of the original system with a relatively small number of training points, which will serve the needs of further sensitivity analysis and parameter calibration research. We take the heterogeneous asset pricing model as an example to evaluate the model’s performance using actual Chinese stock market data. The results demonstrate the good capabilities of the surrogate model at modelling the observed reality, as well as the remarkable reduction of the computational time for validating the agent-based model.

Description: This paper is devoted to a nonautonomous retarded degenerate parabolic equation. We first show the existence and uniqueness of a weak solution for the equation by using the standard Galerkin method. Then we establish the existence of pullback attractors for the equation by proving the existence of compact pullback absorbing sets and the pullback asymptotic compactness.

Description: In this paper, a class of impulsive neutral stochastic functional partial differential equations driven by Brownian motion and fractional Brownian motion is investigated. Under some suitable assumptions, the pth moment exponential stability is discussed by means of the fixed-point theorem. Our results also improve and generalize some previous studies. Moreover, one example is given to illustrate our main results.

Description: This paper investigates how the government can develop subsidies or tax policies to incent power plants to effectively carry out carbon capture to reduce carbon emissions. According to the government’s incentive model for carbon capture power plants, the regulation mechanism is developed when government controls carbon emission. When regional or national carbon emission quota is tense, significant effect can be obtained when regulators make regulations to take off low efficiency power plants. In addition, it is verified that the regulators should not blindly pursue a reduction in carbon emissions regardless of the cost. Therefore, regulators need to pay more attention to control the costs of carbon capture equipment and technology. Finally, by parametric and numerical analyses, the conditions of the power plant to maximize corporate surplus are further studied.

Description: Mean reversion is an important property when constructing efficient contrarian strategies. Researchers observe that mean reversion has multiperiodical and asymmetric nature simultaneously in real market. To better utilize mean reversion and improve the existing online portfolio selection strategies, we propose a new online strategy named multiperiodical asymmetric mean reversion (MAMR). The MAMR strategy incorporates a multipiecewise loss function with the moving average method and then imitates the passive-aggressive algorithm. We further provide a solution via convex optimization. This strategy runs in linear time and thus is suitable for large-scale trading applications. Our empirical results testing six real market datasets show that this strategy can achieve better results in bearing higher transaction cost.

Description: Considering market fluctuations and risk aversion, this paper analyzes the decisions of a dual-channel supply chain consisting of one manufacturer and one retailer and compares the differences in the centralized structure, manufacturer-dominated structure, retailer-dominated structure, and Nash equilibrium structure. This paper also analyzes the impacts of market fluctuations and risk aversion on supply chain profits. The results show that the direct selling price is not influenced by market fluctuations and risk aversion under the retailer’s risk aversion, and the manufacturer-dominated structure and the retail price, direct selling price, and wholesale price in other power structures are negatively correlated with market fluctuations and risk aversion, but the order quantity in the four power structures is positively correlated with market fluctuations and risk aversion, and the profits of supply chain are impacted differently by the market fluctuations and risk aversion.

Description: In this paper, upper bound on the probability of maximum a posteriori (MAP) decoding error for systematic binary linear codes over additive white Gaussian noise (AWGN) channels is proposed. The proposed bound on the bit error probability is derived with the framework of Gallager’s first bounding technique (GFBT), where the Gallager region is defined to be an irregular high-dimensional geometry by using a list decoding algorithm. The proposed bound on the bit error probability requires only the knowledge of weight spectra, which is helpful when the input-output weight enumerating function (IOWEF) is not available. Numerical results show that the proposed bound on the bit error probability matches well with the maximum-likelihood (ML) decoding simulation approach especially in the high signal-to-noise ratio (SNR) region, which is better than the recently proposed Ma bound.

Description: This work introduces a novel modification of classical perturbation method (PM), denominated Optimized Distribution of Boundary Conditions Perturbation Method (ODBCPM) with the purpose to improve the performance of PM in the solution of ordinary differential equations (ODES). We will see that the main proposal of ODBCPM rests above all in the redistribution and optimization of the boundary conditions of the problem to be solved among the iterations of the proposed method. The solution of a couple of heat relevant problems indicates the potentiality of ODBCPM even for the case of large values of the perturbative parameter.

Description: In this paper, by introducing a convergence comparison property of a self-mapping, we establish some new fixed point theorems for Bianchini type, Reich type, and Dass-Gupta type dualistic contractions defined on a dualistic partial metric space. Our work generalizes and extends some well known fixed point results in the literature. We also provide examples which show the usefulness of these dualistic contractions. As an application of our findings, we demonstrate the existence of the solution of an elliptic boundary value problem.

Description: The framework of outcomes-based education(OBE) has become a central issue for global university education, which is benefited to drive the education development by a series of assessments for historical teaching data, especially student course score, and employment information. The issue of how to timely update the talent training plans for computer major in a university has received considerable critical attention. It is becoming extremely difficult to ignore the requirement of fast shortened update cycle in IT area. One of the main obstacles is that the teaching inertia and the fixed awareness of a major training plan may delay the feedback of teaching problems. There is still a contradiction between the plan rationality and the real-time needs of contemporary IT enterprises. Hence, this paper puts forward a novel data-based framework to evaluate the relevance between the major courses, employment rate, and enterprise needs through the decision tree expression, thus providing reliable data support for systematic curriculum reform. On top of that, A recommendation algorithm is proposed to automatically generate the computer course group that satisfies the staff requirements of IT enterprises. Finally, teaching and employment data of Xihua University in China is applied as an example to undertake course optimization and recommendation. The consequences have an obvious positive effect on student employment and enterprise feedback.

Description: This paper reports a new bifurcation pattern observed in a Lorenz-type system. The pattern is composed of a main bifurcation route to chaos () and a sequence of sub-bifurcation routes with isolated sub-branches to chaos. When is odd, the isolated sub-branches are from a period- limit cycle, followed by twin period- limit cycles via a pitchfork bifurcation, twin chaotic attractors via period-doubling bifurcations, and a symmetric chaotic attractor via boundary crisis. When is even, the isolated sub-branches are from twin period- limit cycles, which become twin chaotic attractors via period-doubling bifurcations. The paper also shows that the main route and the sub-routes can coexist peacefully by studying basins of attraction.

Description: In this paper, an alcoholism model of SEAR type with different susceptibilities due to public health education is investigated, with the form of continuous differential equations as well as discrete differential equations by applying the Mickens nonstandard finite difference (NSFD) scheme to the continuous equations. Threshold dynamics of the continuous model are performed by constructing Lyapunov functions. The analysis of a discrete model indicates that the alcohol-free equilibrium is globally asymptotically stable if the basic reproductive number , and conversely, the alcohol-present equilibrium is globally asymptotically stable if , revealing the consistency and efficiency of the discrete model to preserve the dynamical properties of the corresponding continuous model. In addition, stability preserving and the impact of the parameters related with public health education are conducted by numerical simulations.

Description: At present, the problems of homogenization and low quality in China’s iron and steel industry are particularly prominent and the ability of the enterprises to cope with change is insufficient. Adopting product differentiation strategy and dynamic adjustment strategy can allow steel enterprises and the industry to better adapt to future changes. By introducing the product differentiation degree (substitution coefficient) and the bounded rationality strategy to simulate these two strategic means, this paper constructs an extended two-stage dynamic game model to analyse the dynamic game scenarios and steel market stability in China. As new findings, we report the following: (1) The system is more likely to fall into an unbalanced state when multiple enterprises adopt the policy of dynamic output adjustment simultaneously. (2) Enterprises with large output and small output have different output adjustment policies. When enterprises with big-scale output adopt a bit larger adjustment policies, enterprises with small output will be strongly impacted, and the available adjustment space will be sharply compressed. (3) The gradual increase in the difference between products reduces the stability of the market. (4) When product differentiation and bounded rationality strategies coexist, the steel market may fall into an unbalanced state when the degree of product difference increases excessively and the enterprise adopts more drastic output adjustment policies. Therefore, there are pros and cons to product differentiation strategy and bounded rationality adjustment strategy. When each steel oligopoly enterprise formulates a production plan, it needs to comprehensively consider the output changes of the other enterprises and carefully weigh the strategic issues.

Description: Effective railway freight transportation relies on a well-designed train service network. This paper investigates the train service network design problem at the tactical level for the Chinese railway system. It aims to determine the types of train services to be offered, how many trains of each service are to be dispatched per day (service frequency), and by which train services shipments are to be transported. An integer programming model is proposed to address this problem. The optimization model considers both through train services between nonadjacent yards, and two classes of service between two adjacent yards ( i.e., shuttle train services directly from one yard to its adjacent yard, and local train services that make at least one intermediate stop). The objective of the model is to optimize the transportation of all the shipments with minimal costs. The costs consist of accumulation costs, classification coststrain operation costs, and train travel costs. The NP-hard nature of the problem prevents an exact solution algorithm from finding the optimal solution within a reasonable time, even for small-scale cases. Therefore, an improved genetic algorithm is designed and employed here. To demonstrate the proposed model and the algorithm, a case study on a real-world sub-network in China is carried out. The computational results show that the proposed approach can obtain high-quality solutions with satisfactory speed. Moreover, comparative analysis on a case that assumes all the shuttle train services between any two adjacent yards to be provided without optimization reveals some interesting insights.

Description: Emergency vehicle (EV) plays an important role in evacuations or rescues when emergencies occur. To insure that an EV can transfer people in danger to emergency shelters or medical assistance organizations as soon as possible, EV signal preemption (EVSP) strategy is usually adopted. After EV has passed through the intersection, traffic signal has to transfer back to normal signal timing scheme. This paper focuses on the control strategy of EV signal transitioning from EVSP back to normal operation. Considering both efficiency and fairness, the maximum vehicles passing through in per unit time during the transition period and the minimum difference between the maximum and the minimum queue length after transition are selected as objectives, and a multi-objective optimization model is presented. A nondominated sorting genetic algorithm II (NSGA-II) is designed to solve the optimization model and unique encoding and decoding methods are presented. The established model and designed algorithm are verified and the control effect is analyzed. Simulation results indicate that by adopting the control strategy obtained by the presented model, the number of vehicles passing through in per unit time during the transition period is increased and the difference of vehicle length in different directions is reduced significantly, from which we can conclude that the control method proposed in this paper has good performance.

Description: Nowadays, deep learning has achieved remarkable results in many computer vision related tasks, among which the support of big data is essential. In this paper, we propose a full stage data augmentation framework to improve the accuracy of deep convolutional neural networks, which can also play the role of implicit model ensemble without introducing additional model training costs. Simultaneous data augmentation during training and testing stages can ensure network optimization and enhance its generalization ability. Augmentation in two stages needs to be consistent to ensure the accurate transfer of specific domain information. Furthermore, this framework is universal for any network architecture and data augmentation strategy and therefore can be applied to a variety of deep learning based tasks. Finally, experimental results about image classification on the coarse-grained dataset CIFAR-10 (93.41%) and fine-grained dataset CIFAR-100 (70.22%) demonstrate the effectiveness of the framework by comparing with state-of-the-art results.

Description: In this paper, we present a predator-prey system with mutual interference and distributed time delay and study its dynamical behavior. Based on the existence and universality of mutual interference among species, it is necessary to further study an impulsive food web system. By using stability theory, slight perturbation technique, and comparison theorem, we obtain some theoretical results of the system, such as boundedness and permanence. Moreover, numerical experiments are used to verify the theoretical results and to explore the dynamical behavior of the system, which exhibits rich dynamical behavior such as chaotic oscillation, periodic oscillation, symmetry-breaking bifurcations, chaotic crises, and period bifurcation. Finally, we give some practical guidelines for biological systems based on the theoretical results and numerical experiments of the system.

Description: The reason for the self-similarity property of complex network is still an open issue. In this paper, we focus on the influence of degree, betweenness, and coreness on self-similarity of complex network. Some nodes are removed from the original network based on the definitions of degree, betweenness, and coreness in the ascending and descending order. And then, some new networks are obtained after removing nodes. The self-similarities of original network and new networks are compared. Moreover, two real networks are used for numerical simulation, including a network and the yeast protein interaction () network. The effects of the three statistical variables on the two real networks are considered. The results reveal that the nodes with large degree and betweenness have great effects on self-similarity, and the influence of coreness on self-similarity is small.

Description: A discrete allelopathic phytoplankton model with infinite delays and feedback controls is studied in this paper. By applying the discrete comparison theorem, a set of sufficient conditions which guarantees the permanence of the system is obtained. Also, by constructing some suitable discrete Lyapunov functionals, some sufficient conditions for the extinction of the system are obtained. Our results extend and supplement some known results and show that the feedback controls and toxic substances play a crucial role on the permanence and extinction of the system.

Description: We study the local dynamics and bifurcation analysis of a discrete-time modified Nicholson–Bailey model in the closed first quadrant . It is proved that model has two boundary equilibria: , and a unique positive equilibrium under certain parametric conditions. We study the local dynamics along their topological types by imposing method of Linearization. It is proved that fold bifurcation occurs about the boundary equilibria: . It is also proved that model undergoes a Neimark–Sacker bifurcation in a small neighborhood of the unique positive equilibrium and meanwhile stable invariant closed curve appears. From the viewpoint of biology, the stable closed curve corresponds to the period or quasi-periodic oscillations between host and parasitoid populations. Some simulations are presented to verify theoretical results. Finally, bifurcation diagrams and corresponding maximum Lyapunov exponents are presented for the under consideration model.

Description: In this paper, we focus on the asymptotic behavior of solutions to stochastic delay lattice equations with additive noise and deterministic forcing. We first show the existence of a continuous random dynamical system for the equations. Then we investigate the pullback asymptotical compactness of solutions as well as the existence and uniqueness of tempered random attractor in space. Finally, ergodicity of the systems is achieved.

Description: The population of Beijing has already come to its loading capacity. The China central government plans to build an ideal city named Xiong’an nearby Beijing. The city is expected to work as a carrying hub for noncapital functions of Beijing. The central government does not rush to build before a deliberated urban planning is accomplished. For sustainable development, a difficulty faced by urban planners is that the maximum number of people can be migrated from Beijing to Xiong’an with constraint on level of transport service. This paper developed a specialized bilevel programming model where the upper level is to ensure a predetermined transport service level regarding to population migration, while the lower level is feedback equilibrium between trip generation and traffic assignment. To be more specific, trip is generated by the gravity model, and traffic is assigned by the user equilibrium model. It is well known that the bilevel programming problem is tough and challenging. A try-and-error algorithm is designed for the upper-level model, and a method of successive average (MSA) is developed for the lower-level model. The effectiveness of the model and algorithm is validated by an experimental study using the current transport network between Beijing and Xiong’an. It shows that the methods can be very useful to identify the maximum population migration subject to level of transport service.

Description: Event-triggered average consensus of multiagent systems with switching topologies is studied in this paper. A distributed protocol based on event-triggered time sequences and switching time sequences is designed. Based on the inequality technique and stability theory of differential equations, a sufficient condition for achieving average consensus is obtained under the assumption that switching signal is ergodic and the total period over which connected topologies is sufficiently large. A numerical simulation is presented to show the effectiveness of the theoretical results.

Description: We propose a mathematical model that describes the dynamics of citizens who have the right to register on the electoral lists and participate in the political process and the negative influence of abstainers, who abstain from registration on the electoral lists, on the potential electors. By using Routh–Hurwitz criteria and constructing Lyapunov functions, the local stability and the global stability of abstaining-free equilibrium and abstaining equilibrium are obtained. We also study the sensitivity analysis of the model parameters to know the parameters that have a high impact on the reproduction number . In addition, we propose an optimal strategy for an awareness program that helps politicians and officials to increase the rate of citizens registered on the electoral lists with an optimal effort. Pontryagin’s maximum principle is used to characterize the optimal controls, and the optimality system is solved by an iterative method. Finally, some numerical simulations are performed to verify the theoretical analysis using Matlab.

Description: Due to information asymmetry, adverse selection exists largely in the multiagent market. Aiming at these problems, we develop two models: pure adverse selection model and mixed adverse selection and moral hazard model. We make the assumption that a type of agent is discrete and effort level is continuous in the models. With these models, we investigate the characters that make an optimal contract as well as the conditions under which the utility of a principal and agents can be optimized. As a result, we show that, in the pure adverse selection model, the conditions to reach the optimal utility of a principal and individual agents are that a principal needs to design different contracts for different types of agents, and an individual agent chooses the corresponding type of contracts. For the mixed model, we show that incentive constraint for agents plays a very important role. In fact, we find that whether a principal provides high-type contract or a separating equilibrium contract depends on the probability of existence of low-type agents in the market. In general, if a separating equilibrium contract is issued, then information asymmetry will cause the utility of the high-type agents to be less than that of the case in full information.

Description: The development of more effective environmental policies is a common concern among scholars, government and the public. This paper attempts to investigate whether the environmental policy mix can really work. Taking the “Five Water Co-Treatment” policy of Zhejiang Province as an example, we applied the synthetic control method to examine the impact of multi-objective environmental policies on industrial sewage discharge and urban sewage discharge in Zhejiang. Further, we analyzed the effect of industrial value added and the length of water pipelines on sewage discharge and examined the potential environmental Kuznets curve (EKC) relationships. Our results of synthetic control imply that the “Five Water Co-Treatment” policy has increased the industrial and urban sewage discharge. However, the results of the extended analysis show that this is a process of standardizing sewage discharge and an embodiment of enhanced sewage treatment capacity. Therefore, we believe that the “Five Water Co-Treatment” policy is effective and should continue to advance.

Description: The purpose of this work is to investigate the dynamic behaviors of the SIRS epidemic model with nonlinear incident rate under regime switching. We establish the existence of a unique positive solution of our system. Furthermore, we obtain the conditions for the extinction of diseases, and we show the existence of the stationary distribution for our stochastic SIRS model under regime switching. Numerical simulations are employed to illustrate our theoretical analysis.

Description: This paper investigates the finite-time synchronization of complex dynamical networks with nondelayed and delayed coupling. By designing a simple continuous function controller, sufficient criteria for finite-time synchronization of dynamical networks with nondelayed and delayed coupling are obtained. As a special case, the continuous function controller designed in this paper may be the simplest and easy to implement for the finite-time synchronization of dynamical networks without delay. Finally, numerical simulations are given to verify the effectiveness of the conclusions presented in this paper.

Description: This paper studies a class of nonlinear neutral set-valued functional differential equations. The globally asymptotic stability theorem with necessary and sufficient conditions is obtained via the fixed point method. Meanwhile, we give an example to illustrate the obtained result.

Description: In order to solve the problem of vehicle scheduling to feed parts at automobile assembly line, this study proposes a just-in-time delivery method combined with the mode of material supermarket. A mixed integer linear programming model with the primary objective of using the least number of tow trains is constructed by considering capacity of vehicle and inventory levels of line. On the basis of the minimum number of tow trains, the schedule of each tour is reasonably planned to minimize inventory of assembly line, which is the secondary objective of the part supply problem. Additionally, a heuristic algorithm which can obtain a satisfactory solution in a short time is designed to solve large-scale problems after considering continuity and complexity of modern automobile production. Furthermore, some cases are analyzed and compared with the widely used periodic delivery strategy, and the feasibility of just-in-time model and algorithm is verified. The results reveal that just-in-time delivery strategy has more advantages in reducing inventory level than periodic delivery strategy.

Description: For a (molecular) graph G, the first and the second entire Zagreb indices are defined by the formulas M1εG=∑x∈VG∪EGdx2 and M2εG=∑x is either adjacent or incident to ydxdy in which dx represents the degree of a vertex or an edge x. In the current manuscript, we establish some lower bounds on the first and the second entire Zagreb indices and determine the extremal trees which achieve these bounds.

Description: The range of light illumination in real scenes is very large, and ordinary cameras can only record a small part of this range, which is far lower than the range of human eyes’ perception of light. High-dynamic range (HDR) imaging technology that has appeared in recent years can record a wider range of illumination than the perceptual range of the human eye. However, the current mainstream HDR imaging technology is to capture multiple low-dynamic range (LDR) images of the same scene with different exposures and then merge them into one HDR image, which greatly increases the amount of data captured. The advent of single-pixel cameras (compressive imaging system) has proved the feasibility of obtaining and restoring image data based on compressive sensing. Therefore, this paper proposes a method for reduced-dimensional capture of high dynamic range images with compressive sensing, which includes algorithms for front end (capturing) and back end (processing). At the front end, the K-SVD dictionary is used to compressive sensing the input multiple-exposure image sequence, thereby reducing the amount of data transmitted to the back end. At the back end, the Orthogonal Matching Pursuit (OMP) algorithm is used to reconstruct the input multiple-exposure image sequence. A low-rank PatchMatch algorithm is proposed to merge the reconstructed image sequence to obtain an HDR image. Simulation results show that, under the premise of reducing the complexity of the front-end equipment and the amount of communication data between the front end and the back end, the overall system achieves a good balance between the amount of calculation and the quality of the HDR image obtained.

Description: The modified first Zagreb connection index ZC1∗ is a graph invariant that appeared about fifty years ago within a study of molecular modeling, and after a long time, it has been revisited in two papers ((Ali and Trinajstić, 2018) and (Naji et al., 2017)) independently. For a graph G, this graph invariant is defined as ZC1∗G=∑v∈VGdvτv, where dv is the degree of the vertex v and τv is the connection number of v (that is, the number of vertices having distance 2 from v). In this paper, the graphs with maximum/minimum ZC1∗ value are characterized from the class of all n-vertex trees with fixed number of pendent vertices (that are the vertices of degree 1).

Description: Let G be a simple undirected connected graph, then DαG=αTrG+1−αDG is called the α-distance matrix of G, where α∈0,1, DG is the distance matrix of G, and TrG is the vertex transmission diagonal matrix of G. In this paper, we study some bounds on the α-distance energy and α-distance Estrada index of G. Furthermore, we establish the relation between α-distance Estrada index and α-distance energy.

Description: This paper theoretically analyzes the direct impact of environmental regulation on carbon emissions and its indirect effects on carbon emissions through foreign direct investment (FDI), energy consumption, industrial structure, and technological innovation. Then, this paper constructs a spatial lag model to empirically test the dual effects of environmental regulation on carbon emissions based on the provincial panel data of 2003–2017 in China. The results show that the average Moran’s I value of carbon emissions during 2003–2017 is 0.2506, passing the significance test at 1% level, and carbon emissions have spatial correlation characteristics. The direct impact of environmental regulation on carbon emissions is significant and positive. Environmental regulation could indirectly influence carbon emissions by influencing FDI, energy consumption, and technological innovation, and meanwhile, FDI, energy consumption, and technological innovation help to reduce carbon emissions under the constraint of environmental regulation, specifically. However, the impact of environmental regulation on carbon emissions through industrial structure is not significant.

Description: Event-triggered average consensus of multiagent systems with switching topologies is studied in this paper. A distributed protocol based on event-triggered time sequences and switching time sequences is designed. Based on the inequality technique and stability theory of differential equations, a sufficient condition for achieving average consensus is obtained under the assumption that switching signal is ergodic and the total period over which connected topologies is sufficiently large. A numerical simulation is presented to show the effectiveness of the theoretical results.

Description: In this paper, we focus on the asymptotic behavior of solutions to stochastic delay lattice equations with additive noise and deterministic forcing. We first show the existence of a continuous random dynamical system for the equations. Then we investigate the pullback asymptotical compactness of solutions as well as the existence and uniqueness of tempered random attractor in space. Finally, ergodicity of the systems is achieved.

Description: The development of more effective environmental policies is a common concern among scholars, government and the public. This paper attempts to investigate whether the environmental policy mix can really work. Taking the “Five Water Co-Treatment” policy of Zhejiang Province as an example, we applied the synthetic control method to examine the impact of multi-objective environmental policies on industrial sewage discharge and urban sewage discharge in Zhejiang. Further, we analyzed the effect of industrial value added and the length of water pipelines on sewage discharge and examined the potential environmental Kuznets curve (EKC) relationships. Our results of synthetic control imply that the “Five Water Co-Treatment” policy has increased the industrial and urban sewage discharge. However, the results of the extended analysis show that this is a process of standardizing sewage discharge and an embodiment of enhanced sewage treatment capacity. Therefore, we believe that the “Five Water Co-Treatment” policy is effective and should continue to advance.

Description: The southern African kingdoms of Eswatini and Lesotho experience recurrent drought-induced disasters. Policies have been enacted, but no attempt has been made to synthesise the effects on disaster resilience. This review analyses the characteristics, quality, and comprehensiveness of drought-resilience policies in Eswatini and Lesotho. We have systematically reviewed public policies that shape responses to disaster resilience published between 1 January 1980 and 30 June 2019. A combination of keywords was used to search electronic bibliographic databases, multidisciplinary databases, key organisational websites, and the first 20 pages of Google for policies that addressed disaster and/or drought resilience. Identified documents were downloaded into an EndNote database and screened for eligibility using predetermined criteria. The logic of events framework was used for quality assessment, and a metaethnographic approach was applied for data synthesis. Three broad categories of characteristics, thematic outcomes and quality, and comprehensiveness of policy documents emerged and are presented. Policy responses contributing to disaster resilience were found in n = 32 out of 13,700 documents. Three (n = 3/32) policies were statutory, and the rest were nonstatutory. Eleven (n = 11/32) were assessed to be of high quality. Policy responses relating to drought resilience focused on reducing vulnerability to recurrent disasters; promoting drought and climate change adaptation; improving agriculture and food security; safeguarding cultural heritage; and preventing gender inequality and gender-based violence as well as improving disaster governance. However, the construct of drought resilience was not strongly articulated as a major policy goal across policy documents. There is an urgent need to promote better understanding of drought resilience in order to motivate policymakers to steer away from reactive interventions and position resilience as a major national policy goal in both countries to expedite inclusive growth and safeguard development gains and the health and wellbeing of the majority of their populations who are rural-based populations.

Description: This paper presents a new hybrid discriminant analysis method, and this method combines the ideas of linearity and nonlinearity to establish a two-layer discriminant model. The first layer is a linear discriminant model, which is mainly used to determine the distinguishable samples and subsample; the second layer is a nonlinear discriminant model, which is used to determine the subsample type. Numerical experiments on real data sets show that this method performs well compared to other classification algorithms, and its stability is better than the common discriminant models.

Description: The uncertainty caused by emergencies will influence the normal operation of the supply chain. Considering demand disruptions, a closed-loop supply chain consisting of one manufacturer and two competing retailers based on decentralized decision-making is considered. In the supply chain, one retailer recovers end-of-life products while the other does not. Analytic results show that, when the disturbance of demand occurs, the manufacturer and retailers adjust the wholesale price and retail prices of products according to the direction of the market demand disruptions. Under demand disruptions, the retailer who participates in recovering can gain more profits, especially in the case of the positive disruption. Theoretic and pragmatic references for the emergency decision-making of closed-loop supply chain enterprises are provided.

Description: In this paper, we consider a new discrete-time model that describes the spread of information by sharing in some kind of online environments such as Facebook, WhatsApp, and Twitter. The impact of sharing on the information amount is investigated, which is incorporated in the considered model as a supplement compartment. We consider the possible interactions between individuals and information on the Internet, such as posts, images, and videos. The theory of control is used to show the effectiveness of our optimal control strategy in reducing the information amount and sharers and then decreases the dissemination of false information that can lead to annoying situations and unstable state in the society. Numerical simulations are performed to investigate several scenarios before and after the use of our strategy of control. Furthermore, sensitivity analysis of the information amount on parameters is simulated and discussed.

Description: Environmental pollution has aroused extensive concern worldwide in recent years. Existing studies on the relationship between foreign direct investment (FDI) and environmental pollution have, however, paid little attention to spatial effects and regional corruption’s environmental performance from a spatial perspective. To address this gap, we investigate the spatial agglomeration effects of environmental pollution in China and the environmental effects of FDI and regional corruption using spatial econometric analysis method. The results indicate significant spatial agglomeration effects in environmental pollution. The results of spatial panel data models reveal that the estimation coefficient of FDI is significantly negative, and FDI inflows reduce China’s environmental pollution. Regional corruption is shown to increase environmental pollution, thereby contributing further to environmental degradation. The interaction coefficient of FDI and regional corruption is significantly positive, indicating that regional corruption reduces the environmental benefits derived from FDI. In addition, regional differences in spatial effects verify that regional corruption also reduces the environmental performance of FDI in the central region. Meanwhile, regional corruption increases the environmental aggravation effects of FDI in the eastern region but weakens it in the western region. Our findings lead to some policy recommendations with regard to environmental protection and pollution control.

Description: The hub-and-spoke network has demonstrated its economies of scale and scope in the rapid development of the civil aviation industry. In order to fit the development trend of green civil aviation, a series of environmental problems such as fuel consumption and pollutant emissions caused by air transportation cannot be ignored. Firstly, this paper selects six cities of Shenyang, Beijing, Qingdao, Zhengzhou, Guangzhou, and Nanjing as the research objects, collects the passenger flow and the distance information of the corresponding segment, determines the location of the hub airport, analyzes the operating environment of the aircraft in the hub-and-spoke network, establishes an aircraft emission assessment model, and calculates the mass of aircraft emissions and fuel consumption. Secondly, based on the calculation results, the comparison of aircraft emissions and fuel consumption between the hub-and-spoke network and the point-to-point network shows that the total carbon monoxide (CO) emissions are reduced by 35.84%, the total hydrocarbon compounds (HC) emissions are increased by 68.82%, and the total nitrogen oxides (NOx) emissions are increased by 24.87%. The total mass of pollutants (including CO, HC, and NOx) decreased by 29.37%, and the total fuel consumption decreased by 68.17%. In general, the use of a hub-and-spoke network reduces the pollutant emissions and fuel consumption of aircraft as a whole while ensuring the lowest passenger transportation cost. Finally, based on the current international situation and the enhancement of people’s awareness of environmental protection, a summary analysis of the hub-and-spoke network and the point-to-point network is obtained, and some enlightenment and research significance are obtained.

Description: “O2O” (online to offline) classification recycling is a new recycling mode. It is premised on the double lines of online service platform and offline recycling service system, thus forming a pattern of online disposal and offline trading. This mode is capable of integrating upstream and downstream resources on the network platform, creating a recycling and processing mode for the entire industry chain of waste sorting, and developing a circular development mode featuring “resources-products-waste-renewable resources” to realize the recycling of resources. In this paper, the abovementioned recycling mode is constructed using the dynamic method. Taking the recycling of electronic waste (e-waste) as an example, on the basis of the original recycling, an online recycling mode is added and the e-waste is reprocessed by means of classification. Besides, the final process of manufacturing is put into the market for new products. By comparing the efficiency of different classification processing channels and the efficiency of O2O recycling, it was found out that the higher the product quality, the higher the recycling efficiency, and the efficiency of online recycling was concluded due to offline recycling. The system effect is evaluated according to the environmental index. In addition, this paper demonstrates the applicability of the mode by introducing Gree Corp. The results of this research are believed as contributory to improving the efficiency of recycling and remanufacturing at corporate level. It also provides a valuable reference for the improvement of e-waste management work for governments both in China and other countries.

Description: In the paper, the pricing of the American put options under the double Heston model with Cox–Ingersoll–Ross (CIR) interest rate process is studied. The characteristic function of the log asset price is derived, and thereby Bermuda options are well evaluated by means of a state-of-the-art Shannon wavelet inverse Fourier technique (SWIFT), which is a robust and highly efficient pricing method. Based on the SWIFT method, the price of American option can be approximated by using Richardson extrapolation schemes on a series of Bermudan options. Numerical experiments show that the proposed pricing method is efficient, especially for short-term American put options.

Description: In the multilabel learning framework, each instance is no longer associated with a single semantic, but rather with concept ambiguity. Specifically, the ambiguity of an instance in the input space means that there are multiple corresponding labels in the output space. In most of the existing multilabel classification methods, a binary annotation vector is used to denote the multiple semantic concepts. That is, +1 denotes that the instance has a relevant label, while −1 means the opposite. However, the label representation contains too little semantic information to truly express the differences among multiple different labels. Therefore, we propose a new approach to transform binary label into a real-valued label. We adopt the low-rank decomposition to get latent label information and then incorporate the information and original features to generate new features. Then, using the sparse representation to reconstruct the new instance, the reconstruction error can also be applied in the label space. In this way, we finally achieve the purpose of label conversion. Extensive experiments validate that the proposed method can achieve comparable to or even better results than other state-of-the-art algorithms.

Description: The domination number γG of a nonempty graph G is the minimum cardinality among all subsets D⊆VG such that NGD=VG. The bondage number bG of a graph G is the smallest number of edges whose removal from G results in a graph with larger domination number. The exact value of bPn,2 for n=0,3,4mod 5 and the bounds of bPn,2 for n=1,2mod 5 are determined.

Description: In this paper, the asymptotic behavior of a multigroup SEIR model with stochastic perturbations and nonlinear incidence rate functions is studied. First, the existence and uniqueness of the solution to the model we discuss are given. Then, the global asymptotical stability in probability of the model with R01. Finally, several examples and numerical simulations are provided to illustrate the dynamic behavior of the model and verify our analytical results.