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Environmental pollution has become an important obstacle on the path of ecological civilization construction, and it is urgent to control environmental pollution. By establishing an evolutionary game model, this thesis focuses on analyzing how paper-making enterprises choose their own emission reduction strategies under the reward and punishment mechanism. It further analyzes how social welfare changes under the reward and punishment mechanism, and finally through simulation research, this thesis analyzes the evolutionary paths of paper-making enterprises' pollution emission strategies under the reward and punishment mechanism. The results of the reward and punishment mechanism are as follows: under the static reward and punishment mechanism, the game system will repeatedly oscillate around a point. There is no stable equilibrium point at this time. However, under the dynamic reward and punishment mechanism, the game system will tend to a stable equilibrium point. The results of social welfare analysis show that high-intensity rewards will reduce the amount of pollution discharged by paper-making enterprises, thereby maximizing social welfare. On the contrary, when paper-making enterprises discharge a large amount of pollution, they will be subject to high-intensity penalties. When facing high-intensity punishments, paper-making enterprises will tend to not to discharge. So social welfare is also maximized. The simulation research results show that reasonable punishment strategies are more effective than reward ones. Based on this, the author proposes countermeasures, such as establishing a reasonable reward and punishment mechanism, reasonably determining the reward and punishment intensity for polluting enterprises. The emission reduction strategies of paper-making enterprises will be affected by the government's reward and punishment mechanism. A deep study of its internal mechanism is not only of great significance for pollution control but also of great significance for the development of a green economy. [ABSTRACT FROM AUTHOR]

This paper combines the digital twin system modeling method to conduct an in-depth study and analysis of graph-theoretic combinatorial optimization. This paper provides new ideas and approaches for optimal numerical analysis work by studying the digital twin modeling method that integrates digital modeling and graph theory combination, provides theoretical support for safe, stable, and economic operation of the system, proposes a solution for digital twin model based on big data platform, focuses on the nearest neighbor propagation (AP) and graph theory combination, solves the digital twin real-time monitoring data asynchronous, incomplete problem, and applies the algorithm to the digital twin model based on the big data platform for data preprocessing to achieve better results. This paper also presents a web-based digital twin system based on intelligent practical needs, analysis, and comparison of existing models, combined with digital twin technology, detailing the differences and connections between the various levels of numerical analysis and the implementation of this data in various fields, such as user management, equipment health management, product quality management, and workshop 3D navigation and detailed modeling of the digital twin system based on this numerical analysis to realize remote online monitoring, analysis, and management. In this paper, for the numerical analysis process, firstly, the key technologies of modeling and simulation operation control of production line based on digital twin are studied, and the rapid response manufacturing system based on a digital twin is designed and validated. Secondly, a scheduling technology framework for capacity simulation evaluation and optimization is established, and batching optimization, outsourcing decision, and rolling scheduling techniques are thus proposed to form a batching optimization algorithm based on priority rules, which realizes batching processing, outsourcing decision, and rolling scheduling of production orders to optimize equipment utilization and capacity. Finally, digital twin-based modeling is designed, and the validation results demonstrate the system's superior performance in achieving information interaction between physical and virtual production lines, optimization of numerical analysis, and display of results. [ABSTRACT FROM AUTHOR]

Current technology trends have been gradually integrated into the production of all walks of life, which play an indispensable part in promoting the intelligent development of enterprises, and have brought a greater impact on production and reformation. With the rapid development of the economy and technology, the manufacturing industry has played a very important role. For this reason, the introduction of artificial intelligence into machinery manufacturing can not only improve production efficiency but also save labor and reduce labor costs. The application of artificial intelligence in machinery manufacturing has a critical good role in promoting industrial upgrading and transformation. This time, through the application of smart algorithms in machinery manufacturing and its automation, we expect that such a technological revolution can provide a new development prospect for the development of manufacturing intelligence and automation. Taking the malfunction identification of string striking machinery as an example, this paper studies the smart identification method of mechanical malfunction based on multisensor. In the process of malfunction identification of keyboard stroke machinery, the accuracy of malfunction identification results is low due to the influence of the identification model. Moreover, a malfunction identification and analysis method for keyboard stroke machinery based on BP optimized by GA is proposed. The mechanical data of keyboard chords are acquired by sound-sensitive sensors, and the data features are extracted by wavelet packet decomposition. Based on the optimized BP, a mechanical malfunction judgment model is constructed, and various parameters in the model are calculated. The results show that the intelligent identification method proposed has exhibited strong adaptability and superiority compared with the traditional method. [ABSTRACT FROM AUTHOR]

Since 2007, knowledge graphs, an important research tool, have been applied to education and many other disciplines. This paper firstly overviews the application of knowledge graphs in education and then samples the knowledge graph applications in CSSCI- (Chinese Social Sciences Citation Index-) indexed journals in the past two years. These samples were classified and analyzed in terms of research institute, data source, visualization software, and analysis perspective. Next, the situation of knowledge graph applications in education was summarized and evaluated in detail. Furthermore, the authors discussed and assessed the normalization of knowledge graph applications in education. The results show that in the past 15 years, knowledge graphs have been widely used in education. The academia has reached a consensus on the paradigm of the research tool: examining the hotspots, topics, and trends in the related fields from the angles of keyword cooccurrence network (KCN), time zone map, clustering network, and literature/author cocitation, with the aid of CiteSpace and other visualization software and text analysis. However, there is not yet a thorough understanding of the limitations of the visualization software. The relevant research should be improved in terms of scientific level, normalization level, and quality. [ABSTRACT FROM AUTHOR]

The differential equations with state-dependent delay are very important equations because they can describe some problems in the real world more accurately. Due to the complexity of state-dependent delay, it also brings challenges to the research. The value of delay varying with the state is the difference between state-dependent delay and time-dependent delay. It is impossible to know exactly in advance how far historical state information is needed, and then the problem of state-dependent delay is more complicated compared with time-dependent delay. The dominating work of this paper is to solve the stability problem of neural networks equipped with state-dependent state delay. We use the purely analytical method to deduce the sufficient conditions for local exponential stability of the zero solution. Finally, a few numerical examples are presented to prove the availability of our results. [ABSTRACT FROM AUTHOR]

Traditional short‐term traffic volume forecasting approaches make it difficult to predict the highly spatiotemporally coupled short‐time traffic. To tackle the problem, this paper first proposes a variational modal algorithm (GWO‐VMD) based on the optimization of the gray wolf search algorithm. It aims to decompose and reduce the noise of short‐time traffic flows. Meanwhile, it reduces the intricacy of data sequences and enhances the regularity pattern. To address the insufficient utilization of spatiotemporal features, this paper presents an innovative deep‐learning traffic prediction framework based on the stacking of multiple temporal trend‐aware graph attention (TGA) layers and gated temporal convolution (GTC) layers, which are called trend‐aware temporal graph neural network (TTGAN). TGA dynamically models the space‐time relationships of traffic data, and GTC models the temporal characteristics of traffic data. The experimental findings demonstrate that the MAPE model, as presented, achieves a reduction of 9% and 2% compared to the AGCRN and GWNET models, respectively, in the domain of deep spatiotemporal graph modeling. Data decomposition and noise reduction are necessary to achieve accurate results. This model has superior performance in terms of mean absolute error (MAE), coefficient of determination (R2), and explained variance score (EVAR). [ABSTRACT FROM AUTHOR]

This paper focuses on the finite‐time synchronization issue for reaction‐diffusion competitive neural networks (RCNNs) with different time scales and time‐varying delays. To reduce the waste of network resources, a periodically intermittent control strategy is presented based on two time scales (short and long memory) and time‐varying delay. By constructing the Lyapunov–Krasovskii functional, with the help of Lyapunov stability theory and auxiliary inequality technique, the finite‐time synchronization can be guaranteed and the settling time is exactly estimated. Finally, an exhaustive numerical analysis is presented to illustrate the effectiveness of the controller and the correctness of theoretical results. [ABSTRACT FROM AUTHOR]

Over the past few decades, numerous scholars have conducted research on global value chains, and the amount of literature in this field has grown rapidly to become "big data." In order to deeply analyze and explore the current research status and development trends in the field of global value chains, this article conducted a systematic and quantitative study on the global value chain. Based on the Web of Science Core Collection SCIE and SSCI databases, this article searched 8273 articles published between 2001 and 2021 with the theme of "Global Value Chain" and used visualization and bibliometric analysis methods. The research field was analyzed using VOSviewer software. Research has shown that the number of papers published in the global value chain field has been continuously increasing over time and has entered a period of rapid development since 2016. The main disciplines are economics and management. A few researchers and research institutions have a strong influence, but the cooperation between scholars and institutions is relatively weak. The United States, the United Kingdom, and China dominate the research field. The complex impact of the natural environment and public health on the global value chain, and the impact of big data and artificial intelligence on the global value chain, has become a new direction for future research. Countries should actively promote the development of the digital economy and green economy, promote the effective allocation of global value chain resources by enterprises, and adhere to the development of good bilateral political relations to reduce the uncertainty of enterprise participation in the global value chain caused by political risks. [ABSTRACT FROM AUTHOR]

As an important measure to achieve high‐quality economic development in China, the implementation of low‐carbon city pilot policy (LCCP) will inevitably have an impact on enterprises' environmental protection behavior, but the empirical evidence in this field is limited. Therefore, based on the data of Chinese A‐share listed industrial enterprises in Shanghai and Shenzhen from 2008 to 2020, this paper empirically tests the impact of LCCP on corporate environmental performance (EP) and its mechanism of action by using the multiperiod difference‐in‐difference (DID) method. The results show that (1) the implementation of LCCP has significantly improved EP, and after a series of necessary tests such as parallel trend and placebo, the conclusion remains robust. (2) LCCP promotes enterprises to improve their EP mainly through the pressure of environmental supervision, financing constraints, and market competition. (3) The policy effect of LCCP varies with the nature of enterprise property rights, pollution attributes, and technical level. State‐owned enterprises, heavily polluting enterprises, and high‐tech enterprises respond more positively to LCCP, and the effect of EP improvement affected by the policy is more obvious. Further analysis shows that facing the pressure of environmental policy, state‐owned enterprises mainly deal with it through two methods: increasing environmental protection investment and strengthening green innovation; heavy‐polluting enterprises tend to increase investment in environmental protection; high‐tech enterprises mainly benefit from the improvement of the green innovation level. Our findings have important policy implications for improving LCCP to achieve high‐quality economic development based on the improvement of EP. [ABSTRACT FROM AUTHOR]

This paper presents an evolutionary game model of the "government‐platform‐platform user" based on the assumption of bounded rationality. The model explores the copyright governance mechanism of user‐generated content (UGC) in China by analyzing the strategic interaction between managers and the managed and the influence of various factors. The findings highlight that the government plays a leading role in the governance mechanism of UGC copyright, and the participation of the platform, as the direct manager of information content, can greatly improve the efficiency of supervision. Increasing government penalties, reducing excess revenue from passive platform filtering, and imposing additional payments for users' infringing use can expedite the adoption of evolutionary stability strategies. Furthermore, there exists a practical threshold for government incentives for platforms. Therefore, the construction and optimization of the UGC copyright governance mechanism need to be supported by a dynamic and coordinated reward and punishment system, diversified business objectives, and continuously improving users' copyright awareness. [ABSTRACT FROM AUTHOR]

The collaborative R&D of new products between enterprises is prone to the "free‐rider effect" due to knowledge spillover. To avoid that, this paper establishes a three‐stage dynamic game to explore the collaborative R&D co‐competition behavior between asymmetric horizontal supplier enterprises. In this paper, we incorporate the uncertainty of R&D success probability into the model and reverse induction is applied to solve it. In the model, two asymmetric enterprises play dynamic games under three modes: complete noncooperation, semicooperation, and complete cooperation. We discuss the sensitivity of various asymmetric factors to the R&D investment level and profit of enterprises. The results indicate that the R&D investment level of supplier enterprises is positively correlated with the absorptive capacity, technology spillover, and R&D success probability, and negatively correlated with the initial R&D investment and innovation efficiency under the three co‐competition modes. Especially, when the absorptive capacity of the enterprise or the degree of technological spillover of the other party exceeds a certain value, the profits of the enterprise in the mode of complete noncooperation and semicooperation will intersect, which can easily lead to "free‐riding" behavior. It provides a decision‐making basis for the direction and extent of enterprises' R&D efforts. In addition, some methods are proposed to improve the level of R&D investment and increase the income of enterprises under three modes. [ABSTRACT FROM AUTHOR]

In this paper, a fractional‐order unified system with complex variables is proposed. Firstly, the basic properties of the system including the equilibrium points and symmetry are analyzed. Bifurcations of the system in commensurate‐order and incommensurate‐order cases are studied. Tangent and period‐doubling bifurcations can be observed when a derivative order or a parameter is varied. The stabilization the system is investigated via the predict feedback method. Based on the stability theory of fractional‐order systems, a projective synchronization for the fractional‐order unified complex system is proposed by designing an appropriate controller. Numerical simulations are applied to verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Facing the dual background of risk society and the fourth scientific and technological revolution, digital emergency management (DEM) research has attracted wide attention worldwide. Based on the comparative analysis of data from Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) databases, the research draws the knowledge map by CiteSpace, in order to analyse the spatiotemporal distribution, hotspots, and trends of DEM research. The following are the results: (1) DEM research shows a spiral growth, with a significant increase in the number of papers. Existing highly cited references are mainly carried out from the perspective of management or technology. (2) The complex countries' cooperation network has been formed from the USA, China, and other countries; the complexity of the institutions' cooperation network must be strengthened, and the density of the authors' cooperation network is low; DEM research has significant interdisciplinary attributes. (3) The hotspots of DEM research can be divided into three categories: means, processes, and objects, but the research emphases between international and China are different. (4) The evolution of DEM research can be divided into three stages between international and China: embryonic, development, and deepening stages, and research contents in each stage show some differences. (5) The trends of DEM research between international and China are different. The former are information technology, artificial intelligence, and machine learning, whereas the latter are emergency decision making, scenario analysis, and public health. [ABSTRACT FROM AUTHOR]

To measure the gray relation between the core competence of research universities and its influencing factors, this paper took the same period statistical data of the five research universities directly subordinate to the Ministry of Education of China as the research samples, all these five schools were shortlisted in the "World Top 300" rankings of USNews, QS, THE, and ARWU from 2014 to 2018, and the indicator systems of the four authoritative lists were taken as the basis; 30 representative indicators affecting the core competence of research universities were selected, and the gray relation model was adopted for the research; moreover, this paper applied the information entropy method to calculate the weight of each indicator and estimate the comprehensive gray relation between the core competence of research universities and the entire factor system. This research gives the rankings of the influencing factors of the core competence of research universities, and there is a 0.8485 degree comprehensive gray relation between the influencing factors and the core competence of research universities, which has further clarified the future development direction of research universities. [ABSTRACT FROM AUTHOR]

This paper aims at identifying the causal relationship between the reform of the cultural system and the upgrading of industrial structure, revealing the causal relationship between the reform of the cultural system and the upgrading of industrial structure, which is of great significance for promoting the reform of the cultural system and the upgrading of industrial structure. The impact of cultural administrative reform on industrial structure upgrading is empirically tested using panel data from 261 prefecture-level cities in China from 2001 to 2017. The double difference model and PSM-DID method are used. This includes conducting placebo tests and examining the robustness of empirical findings using other methods. The findings indicated that (1) the influence coefficient of the cultural administrative system reform on industrial structure upgrading is positive and passed the significance level test, indicating that the cultural administrative system reform significantly promoted industrial structure upgrading, and on average, it can improve the level of the urban industrial structure by 11.81 percent. (2) Theoretical analysis of the mechanism demonstrates that the innovation level acts as a link between cultural administrative system reform and industrial structure upgrading, implying that cultural administrative system reform promotes industrial structure upgrading by stimulating the innovation level of cultural enterprises. (3) The results of the heterogeneity analysis indicate that the influence of cultural administrative reform on industrial structure upgrading is highly regionally and economically differentiated. The higher the economic level of the local community, the more effective the promotion effect on industrial structure upgrading. The reform of the cultural administrative system has a greater impact on industrial structure upgrading in the eastern region than in the central and western regions. On the basis of the foregoing research findings, this paper makes some policy recommendations for releasing the overall system reform dividend based on the cultural system and promoting regional industrial structure upgrading. [ABSTRACT FROM AUTHOR]

Low energy consumption and green transformation of automobile product portfolio is the trend of the times. Automotive manufacturers make product portfolio decisions by setting multiple criteria such as fuel consumption, sales, and volume. It is also important to take into account the symbiotic interaction effects between automotive products. In order to achieve the above research objectives, this paper constructs the Lotka–Volterra MCGP model to make multicriteria decisions on automobile product portfolio design from the perspective of energy sustainability with BMW Brilliance is taken as an example to illustrate the process of using the multicriteria model. The empirical analysis successively measures product growth using the logistic model, analyzes the symbiotic relationship of product portfolios using the Lotka–Volterra model, and finally performs multicriteria evaluation using the MCGP model. In order to verify the reliability of the model, this paper verifies the robustness of the model from the perspectives of parameter dynamics, system boundaries, and model scalability. The results of empirical analysis and robustness analysis show that the Lotka–Volterra MCGP model proposed in this paper is applicable to the multicriteria decision-making of automobile product portfolio design from the perspective of energy sustainability. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China's attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation. [ABSTRACT FROM AUTHOR]

Background. Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. Methods. Through the intelligent transformation of jig, this paper proposes an intelligent washing method with cooperated deep reinforcement learning and evolutionary computation. First, it designs a fault warning method based on statistical analysis, helping to recover the normal running state of jig with manual maintenance. Then, it constructs a regulation strategy generation method with deep reinforcement learning supported by the fusion of artificial experience and historical data. Last, for the lack of monitoring data caused by poor communication quality and environment, the regulation strategy prediction method with evolutionary computation and surrogate model is proposed. Results. In practice, this method shows accurate fault warning accuracy and rapid cleaned coal ash adjustment response ability. Conclusions. This shows that the method proposed in this paper is of great significance for intelligent washing and can better cope with the special situation when the washing equipment sensing data are missing. [ABSTRACT FROM AUTHOR]

This paper simulates the behavior mechanism of each subject in the equipment manufacturing industry-university-research (IUR) collaborative innovation system based on NetLogo, and constructs the input-output model of each subject. Secondly, the reasonable value of each parameter is determined through expert consultation, and finally 6 scenarios are selected to simulate the evolution of the IUR collaborative innovation system. The results show that different decision-making behaviors of each subject will lead to different operating states of the innovation collaborative system. When the conditions of each subject are exactly the same, the innovation system can achieve stable and continuous operation. However, if the initial conditions are different, the IUR collaborative innovation system needs an authoritative intermediary to coordinate the behavioral strategies of each subject, strengthen the willingness to cooperate, and ensure its stable operation. Reasonable reward and punishment measures are also an effective and important measure, which can mobilize the enthusiasm of all subjects for collaborative innovation. This paper is of great significance for the IUR collaborative innovation in equipment manufacturing industry. [ABSTRACT FROM AUTHOR]

This paper takes 286 prefecture-level Chinese cities from 2011 to 2019 as research objects. It empirically examines the influence of digital finance on green development by using the EBM model, two-way fixed effect model, and instrumental variable method. It is found that digital finance can significantly promote the green development of Chinese cities, and this conclusion is still valid after the robustness tests, such as the instrumental variable method dealing with endogeneity and two-sided winsorization. The mechanism analysis results suggest that only the breadth of digital finance can significantly promote green development in the internal mechanism of digital finance, but the effect of coverage depth and digitization degree is not significant. The external mechanism of industrial structure upgrading assumes the mediating role of digital finance in improving the level of green development. The heterogeneity analysis results show that digital finance has a stronger impact on green development in the central and western cities and small-scale cities. This paper contributes to the study of the relationship between digital finance and green development and puts forward relevant suggestions. [ABSTRACT FROM AUTHOR]

For the purpose of understanding the effect of green marketing on brand image, this paper has added mediation variable namely brand image into the research model; meanwhile, in order to better discuss about this issue in the context of green marketing, the paper considers that greenwash is an indispensable element in adjusting green marketing's effect on the brand. The paper has used the method of a questionnaire survey to distribute questionnaires on online social platforms. A total of 500 questionnaires have been distributed, and 415 valid questionnaires have been collected with an effective collection rate of 83%. In this paper, SPSS 24 and AMOS 23 are applied to verify its theoretical model and structural model. The result manifests that the design of the questionnaire is well reliable and highly effective; meanwhile, variables are significantly correlated. Besides, it concludes that the relationship between green marketing and brand trust differentiate in the following two dimensions: spontaneity and compulsion. Moreover, brand image plays an obviously intermediary role between green marketing and brand trust, which also proves that greenwash works as a significantly negative regulatory role. [ABSTRACT FROM AUTHOR]

This paper develops a time‐space double radial basis function (TSDRBF) method to solve PDEs arising from multiasset option pricing. By TSDRBF discretization for the high‐dimensional PDEs, a linear system (LS) is obtained. After solving the LS, multi‐asset options of European and American style are restored, with number N of space discretization, number M¯ of time nodes, and number M of time RBF discretization. Numerical examples confirm that the TSDRBF method has exponentially convergent rates for the number N and number M, while the convergence is linear for the number M¯. Compared with finite difference, TSDRBF avoids the difficulty of space discretization, and the convergence is greatly improved. [ABSTRACT FROM AUTHOR]

In recent years, because the complex system discrete model has brought good results in the application of many research directions such as human management analysis, control system prediction, and animal group prediction, how to combine the complex system discrete model with the prediction of enterprise brand communication effect has become a current research hotspot. Based on this, this paper studies the application of the discrete model based on the complex system in sports club to enterprise brand communication and designs a model of the impact of professional sports club on enterprise brand communication based on the SIR model and PSO algorithm. Firstly, this paper analyzes the research status of the impact on enterprise brand communication at home and abroad and optimizes and improves the impact of professional sports clubs on enterprise brand communication and the shortcomings of big data analysis technology in the current research. The complex system discrete model can accurately analyze the enterprise brand communication and conduct big data mining analysis with known professional sports clubs to achieve accurate calculation. The results show that in the process of analyzing the impact of professional sports clubs and enterprise brand communication, the communication mode design of professional sports clubs based on SIR-PSO algorithm can not only effectively deal with various complex discrete data evaluated by club users but also analyze and evaluate the impact of professional sports clubs on enterprise brand communication. [ABSTRACT FROM AUTHOR]

Accurate risk assessment of international scientific and technological (S&T) cooperation is significant to international cooperation. In this paper, 5 risk dimensions with respect to the political, economic, social, cultural as well as technological of the regional comprehensive economic partnership countries (RCEP) are selected to establish a proper S&T cooperation index system for risk assessment. To calculate the weight of each index, a cross-entropy combination weighting method is proposed based on the combination weighting method of game theory. Furthermore, the standard cloud model is constructed by using the golden ratio, and the risk of S&T cooperation among the RCEP countries is analyzed by the cloud model. The results show that the combination weighting method proposed in this paper is effective, and its calculation is simpler than that of the game theory combination weighting method. Besides, compared with political, social, cultural, and technological indicators, economic indicators have a greater impact on S&T cooperation risk. Furthermore, it is also obtained from the results that the risk of S&T cooperation with China and the Philippines is at a lower to low level and medium to higher level, respectively, and the risk of S&T cooperation with other countries is all at a lower to medium level. [ABSTRACT FROM AUTHOR]

This paper proposes an improved whale optimization algorithm with chaotic mapping and adaptive iteration strategy (CMAIS-WOA). This algorithm addresses the issues of the WOA algorithm that is prone to local optimal solutions with low stability. CMAIS-WOA utilizes chaotic mapping to enhance the diversity and coverage of the initial population. Also, it adaptively adjusts the weight values based on the current distribution of whale populations and the fitness of search agents. In addition, CMAIS-WOA uses an improved nonlinear convergence factor to adjust the breadth-first and depth-first search during the optimization process. The performance of the proposed CMAIS-WOA is evaluated by using 13 classical benchmark functions and IEEE CEC2014 test suite. The experimental results show that CMAIS-WOA effectively improves the stability of the optimal solution and helps the algorithm to approach the global optimal solution. The method proposed in this paper contributes to the field of optimization which solves problems more powerfully and efficiently. [ABSTRACT FROM AUTHOR]

Under the background of the rapid development of digital economy, this paper empirically analyzes the impact of digital transformation on enterprise innovation and selects the panel data of China's Shanghai and Shenzhen A-share listed companies from 2013 to 2021 as the research objective is to study the impact of digital transformation on enterprise innovation from theoretical and empirical perspectives. First, we find that digital transformation accelerates enterprise innovation, a conclusion that has been validated through robustness testing. Second, digital transformation impacts enterprise innovation by enhancing productivity and information transparency. Third, financing constraints and financial redundancy play distinct regulatory roles in the process. Fourth, heterogeneity analysis finds that the role of digital transformation in promoting enterprise innovation has different effects in state-owned and non-state-owned enterprises, high-tech and non-high-tech enterprises, and enterprises with different life cycles. Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. Overall, this study contributes to a deeper understanding of digital transformation and innovation-driven practices and encourages more significant integration of the real and digital economies. [ABSTRACT FROM AUTHOR]

It is important in image restoration to remove noise while preserving sharp edges and fine details such as blurred thin edges and low-contrast fine feature. The Perona–Malik (P-M) model is a well-known anisotropic diffusion denoising model, which can effectively remove noise while preserving edges. However, its diffusion coefficient only associates with the gradient of each pixel but not with the local region information; thus, the P-M model is not able to effectively preserve the important details of image. To address this problem, this paper proposes an anisotropic diffusion denoising model based on local entropy. The diffusion coefficient of the new model not only depends on the gradient of image but also on the local region information described by local entropy. On this basis, a coupled anisotropic diffusion scheme is proposed for detail-and edge-preserving smoothing. Experimental results show that the proposed model not only can effectively remove noise while preserving the boundaries better but also can maintain important details in an image very well. [ABSTRACT FROM AUTHOR]

With the development of digital technology, the curriculum design of art majors is also quite different from traditional courses. With the continuous development of information technology and the continuous maturity of campus network technology, teaching resources have become an important part of information resources. High-quality teaching resources play an important role in improving teaching quality and excavating educational development potential. However, traditional classroom teaching is difficult to meet people's needs. In the context of the current new normal, the way of social and economic management has changed. On the one hand, traditional course teaching resources store information in the forms of paper lesson plans, PPT courseware, discrete pictures, and video files. These forms of storage are not conducive to the distribution and sharing of resources. On the other hand, these teaching resources are scattered among the teaching teachers. As the curriculum develops, the courses taught by teachers change. Because schools lack effective means for unified management, these teaching resources are easily lost. The used method is not conducive to the accumulation of teaching resources or the continuation and development of courses. In order to present good results, these materials usually occupy a large amount of storage space. Therefore, some existing information-based teaching platforms cannot meet the demand. We use network and web technology to develop a teaching file management system, which is very necessary. This paper firstly compares the mature teaching resource management system on the market and some problems in its professional application. Secondly, the article analyzes the actual situation of teaching resource management of art design majors in China and generally describes the system development background and technology. Then, the paper analyzes the requirements of the system in detail by using the object-oriented method and gives the overall design and implementation method of the system. These methods include the use case diagram of the subsystem, the flow chart of the main module, the system architecture, and the design and application of UML. Finally, this paper designs a test case for the teaching resource management system. [ABSTRACT FROM AUTHOR]

As an important component of modern service industry, tourism is regarded as a "green" driver to regional economic growth and industrial upgrading. Applying the "quasi-natural experiment" advocated by the "The Belt and Road" initiative, this paper, based on the method of DID, assessed the influence of this initiative on regional tourism development by analyzing panel data collected from 286 prefecture-level cities in China over the period of 2007–2018. It is found that the "The Belt and Road" initiative has stimulated market dynamics and promoted tourism development in the regions along the route and has significantly improved indicators such as per capita domestic and inbound tourism revenue and per capita domestic and inbound tourist receipt. Also, the degree of contribution of domestic tourists to the tourism economy of the regions where the policy has been implemented is stronger than that of inbound tourists. In sum, the results of this paper not only confirm that the "The Belt and Road" initiative has significantly contributed to the high-quality tourism development of Chinese provinces along the routes but also provide important policy enlightenment for the upgrading of regional tourism industry and regional economic balance. [ABSTRACT FROM AUTHOR]

The China Securities Regulatory Commission (CSRC) proposed the green channel policy for poverty alleviation Initial Public Offerings (IPOs), aiming to help poverty-stricken areas reduce poverty and increase income, but it has an impact on the business performance of the companies involved. This paper uses data from public annual reports of listed companies to construct a policy intervention group and a control group and comparatively analyzes the degree of annual performance downturn of newly listed companies in A-share from 2016 to 2017 through a counterfactual method, and the results show that the "IPO green channel" policy for poverty alleviation has an obvious negative effect on listed enterprises in poverty-stricken counties. The results show that enterprises listed via the green channel have more significant performance downturn than those listed normally during the same period. This paper suggests that the distortion of the market issuance system causes the declining of the quality of IPO firms. Finally, this paper suggests that regulators should cooperate with local governments actively to ensure the smooth implementation of the government's poverty alleviation efforts while balancing market equity and efficiency. The SFC should take more consideration of institutional compatibility for policy output in financial poverty alleviation to avoid institutional alienation and distortion of corporate behavior. [ABSTRACT FROM AUTHOR]

Logo design is related to the image of a company, unit, product, etc. A good logo can leave a deep impression on people and intuitively understand the content of the product. With the increasing emphasis on intellectual property protection, the design of logos should also pay more attention to the protection of property rights. It can be said that the logo of some big brands is enough to represent the enterprise itself; for example, seeing the red cross as a hospital. This paper aims to propose a logo design process and method under the background of intellectual property big data, so as to make the logo design more procedural and efficient, and to better focus on the protection of property rights. By introducing the relevant knowledge of logo design and trademark registration, it is indicated that trademark search can be used as an auxiliary tool for logo design. Combined with digital media and big data technology, a logo image recognition and classification method is designed so that the trademark registration and screening stage can avoid the infringement design to the greatest extent, so as to put forward the design process and method to improve the innovation ability of logo design. According to the research, the classification accuracy rate of the algorithm proposed in this paper is 91.5%, and the recognition rate of various defects is also above 95%. In addition, in design practice, the stability of design proposals should be monitored through multiple search methods using trademark search tools. If a high similarity is found in the search results, the design direction should be adjusted in time until the final design scheme is determined. [ABSTRACT FROM AUTHOR]

The research on emergency response systems usually only considers the role of professional rescuers in emergency rescue or the activities taken by the victims in the process of self-rescue, and the joint research of the victims and rescuers in the same environment is relatively few. Multiagent modeling technology is a promising tool for simulating natural disaster emergency response systems. Based on the background of the earthquake rescue operation, this paper studies the related contents of the cooperative emergency response system of disaster victims and rescuers by using the modeling and simulation method of the multiagent. On the premise of making full use of the victims' ability to obtain information and move, it is proposed that the rescuers and the victims move together to the cluster point to complete the treatment to reduce the time wasted by the rescuers moving among the victims. This paper simulates different degrees of disaster through many experiments and simulates the influence of the relative speed of victims and rescuers by changing the moving speed of victims. It can be found that when there are many disaster victims, the collective rescue operation can reduce the overall emergency response time; when the movement speed of the victims is lower than that of the rescuers, the effect of the clustered rescue is similar to that of the victims waiting for rescue. When the movement speed of the victims is similar to that of the rescuers, the clustered emergency response is better than that of the victims waiting. [ABSTRACT FROM AUTHOR]

Job insecurity reflects the desire and expectation of organizational managers for employees' exhibition of innovative behavior. Ubiquitous and inevitable, it has gradually become a concern psychological problem for job survival and stability. As a key driver of innovation, employee innovation depends heavily on knowledge workers, who are best able to spot problems and identify and capture opportunities. Based upon the transactional theory of stress and coping (TTSC), this paper discusses the influencing mechanism of knowledge workers' job insecurity and innovative behavior in enterprises, emphatically analyzes the mediating effects of two coping strategies, i.e., proactive work behavior and working withdrawal behavior, and verifies the moderating effect of organizational climate for innovation. With the data from 665 questionnaires of enterprise knowledge workers, this paper shows that job insecurity can influence knowledge workers' innovative behavior either positively through proactive work behavior or negatively through working withdrawal behavior, thus forming a dual-channel effect model of influencing their innovative behavior, and that organizational climate for innovation has a moderating effect on the relationship between job insecurity and proactive work behavior/working withdrawal behavior. The organizational innovation climate played a moderating role between job insecurity and proactive work behavior and work withdrawal behavior and detected the value of the boundary where the organizational innovation climate played a mediating role. [ABSTRACT FROM AUTHOR]

When using tubular MBR to treat sewage, the water production is an important parameter to measure the efficiency of the tubular MBR system. The problem to be solved in this paper is to calculate the water yield of the tubular MBR system, so as to evaluate the sewage treatment efficiency of the MBR system. This research uses the CFD simulation software ANSYS 16.0 to study the water yield of the tubular MBR system. The MBR model of a single membrane filament tube was established using the ICEM CFD preprocessor in ANSYS 16.0, and the structured grid was divided to obtain a grid file. Then, the fluid solver was used to solve the mesh file and through the flow monitoring window to obtain the water output of the tubular MBR system. Finally, the CFD postprocessor in ANSYS 16.0 was used to visualize the calculation results and compare them with the waste-water treatment results of some actual MBR systems. The results show that the water yield calculated by the fluent solver is basically the same as that of the actual MBR system. This research realizes the purpose of calculating the water yield of the tubular MBR system with CFD technology, solves the problem of evaluating the working efficiency of the tubular MBR system with water consumption, and realizes the MBR before deployment The evaluation of the working efficiency of the system has certain reference value for the planning, design, and deployment of MBR. [ABSTRACT FROM AUTHOR]

In the current complex global economic background, international capital flows are becoming more frequent. Based on this, this paper takes international portfolio investment as the research object and empirically tests the causal relationship and control channel between international portfolio flows and macrofinancial risk in emerging economies. It selects the panel data of emerging economies from 2001 to 2020, constructs macrofinancial risk indicators by using contingent claim analysis and the entropy-based TOPSIS method, tests the effect of international portfolio flows on macrofinancial risk by using the panel distributed lag regression model, and explores the management effect of foreign exchange reserves and capital controls on the risk effect by using the panel threshold regression model. The results show that long-term international portfolio flows help reduce macrofinancial risk, but short-term capital flows appear to increase macrofinancial risk. In addition, both foreign exchange reserves and capital controls effectively reduce the risk effect of portfolio flows. However, when considering different types of portfolios, we find that foreign exchange reserves do not effectively control the risk effect of equity securities flows, while stricter capital controls do. This paper argues that emerging economies should be more open to international long-term portfolio flows, focus on the monitoring of short-term portfolio capital flows and equity securities flows, and coordinate the use of foreign exchange reserves and capital control instruments to manage the risk effects of portfolio flows. This paper verifies the risk effect of international portfolio investment flows through empirical analysis, tests the effectiveness of foreign exchange reserves and capital controls, and provides a decision-making reference for emerging economies to timely identify, effectively manage, and prevent the risk effect of international capital flows. [ABSTRACT FROM AUTHOR]

Although the port industry is very important in the Korean economy, there are few literature studies that shed light on the macroeconomic implications of the business cycles in this industry. This paper examines the roles played by foreign economic factors in the business cycle in the Korean port industry. Specifically, it aims to estimate the impulse response of the seaborne freight volume in the port industry due to the shocks of the foreign economy and analyze the contributions of each shock considered on the variation in the freight volume. The structural FAVAR (SFAVAR) model was employed to extract the unobserved foreign economic factors. This paper estimates the four foreign economic factors and the parameters of the model using the one-step Bayesian Gibbs sampling method. The findings of this study show that foreign economic activity statistically affects the freight volume of the Korean ports. Specifically, the shocks to the foreign real economic activity increased freight transportation for nearly one year. Following the world inflation shocks, the freight transportation was enhanced. However, this impact disappeared after a year. Similarly, the rise in global liquidity was shown to encourage transportation activity; nevertheless, this activity declined after five quarters. Moreover, the increase in the world interest rates exerted a negative effect on the volume of transportation. Furthermore, the variance decomposition analysis shows that 49.2% of the variation in the transportation volume could be attributed to foreign economic activity. This analysis can contribute to drawing useful implications in establishing the port industry policy in response to the change in the economic environment such as the foreign economy. [ABSTRACT FROM AUTHOR]

In China, private enterprises are becoming more and more important subjects of technological innovation, however(at the same time) financing difficulties of private enterprises are also ubiquitous. The research on the impact of financing methods on technological innovation behavior of private enterprises is conducive for the government to launch more targeted financing support policies.I men private enterprises are becoming the mainbody of technological innovation, but the difficulties in financing is especially heavy in China. Based on the data of the World Bank survey on China's enterprises in 2012, this paper studies the impact of different financing methods on technological innovation behavior of private enterprises. The results show that (1) internal financing can promote the technological innovation behavior of enterprises better than external financing can do and (2) among the various forms of external financing, bank loans have the most significant impact on the technological innovation behavior of private enterprises, followed by commercial credit. [ABSTRACT FROM AUTHOR]

In 2019, the Chinese government has put forward comprehensive plan for reducing social insurance premium rate, which will affect the measurement of the pension security level. In order to evaluate the pension level, this paper uses CHIPs data from 1988 to 2018 to calculate "empirical" pension replacement rate by "empirical" method based on different wage calibers. The result shows that the pension replacement rate and income replacement rate of urban employees have gradually declined in the past 30 years. The pension level of nonprivate employees is lower than that of insured employees, and that of insured employees is lower than that of full-scale employees. The pension level of male, high-income groups, the older generation, organs, and institutions is much higher than that of female, low-income groups, the younger generation, and enterprises relatively. Compared with other countries, the pension replacement rate of urban employees in China is not low, but the income replacement rate is relatively low. This paper makes an in-depth analysis of the actual pension level under the new policy. As a result, it is necessary to vigorously develop multilevel and multipillar pension system such as enterprise annuity, occupational annuity, and commercial pension insurance, so as to improve the pension level of urban employees. [ABSTRACT FROM AUTHOR]

The stock market is a real and continuously evolving extremely complex dynamic system. This paper analyzes the change of stock market efficiency from the perspective of dynamic evolution, and the recursive graph method is used to obtain the dynamic characteristics of stock price time series. For the sharp rise and fall of stock prices, this paper uses the heuristic segmentation algorithm of nonlinear time series mutation detection to study the detection of market dynamics characteristics before the stock market crash. Based on the above research results, this paper studies the dynamic evolution of financial markets and the construction of a complex network of dynamic characteristics between financial markets. The simulation results show that there are typical characteristics of small world network in stock market complex network, the stock market complex network shows stronger synchronization ability, and the transmission range of information between the stock markets in the complex network is significantly expanded. [ABSTRACT FROM AUTHOR]

This paper uses data mining technology to mathematically model the training movements of tennis players, establish a three-dimensional data information database of athletes utilizing depth imaging, analyze the data with data mining algorithms, and derive the results after comparative evaluation and analysis with a database of movement characteristics of tennis dribblers. This paper uses video observation and mathematical modeling to construct a tennis player training action evaluation model, which provides a reference basis for tennis players to improve and enhance their tactical level; it can also provide a reference for the development of sports training special theory of tennis projects and enrich the tactical diagnosis method of tennis matches. To improve the accuracy of 3D human pose estimation, this paper adopts a 3D skeleton point extraction method based on RGBD images; for the action alignment problem, this paper uses a dynamic time warping (DTW) algorithm; for the similarity measure, this paper gives a Pearson correlation coefficient method based on the joint point features of human parts. This paper aims to conduct a systematic theoretical analysis of tennis players' training movements based on theories and methods such as system science theory and social network analysis. On this basis, the characteristics of tennis training technology development are analyzed from a combination of qualitative and quantitative perspectives, while the development of tennis player training is explored based on tracking observations of tennis player movement training, and finally, the attack and service characteristics of tennis training are analyzed to better provide some reference for the sustainable development of tennis. [ABSTRACT FROM AUTHOR]

The traveling salesman problem (TSP) is a well‐known NP‐hard combinatorial optimization problem. In TSP, the objective is to find the shortest distance to the most appropriate route to the starting city. Finding an optimal solution in a reasonable time becomes difficult as the number of cities increases. In recent years, metaheuristic methods obtained optimal or near‐optimal solutions in TSP in an acceptable time. This paper proposes a new hybrid metaheuristic method for solving the TSP. The proposed method is developed by combining the 3‐Opt method and the improved discrete cuckoo search algorithm. The performance of the proposed method is tested on 39 different benchmark problems in the TSPLIB library. For the 39 different benchmark problems with a size of less than 150 cities, the proposed hybrid method found optimal solutions. In addition, it was observed that as the problem size increases, the results obtained are closer to the optimum compared to other methods. When compared to studies in the literature using the same problem, similar or better results were obtained. For 500 iterations, the average best solution of the proposed method differed from the average optimal solution by 0.07%. In the results of the improved discrete cuckoo search algorithm (CSA), this rate was calculated to be 0.08%. In terms of processing time, the average time of the proposed algorithm was 11.46 seconds, while the average time of the improved discrete CSA was 92.86 seconds. For 1000 iterations, the deviation of the proposed method from the average optimal solution is 0.05%, and the average processing time is 23.72 seconds. The experimental results showed that the proposed new hybrid‐improved discrete CSA is effective for solving TSP. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a general maximum principle for discrete fractional stochastic difference system of mean‐field type. The admissible control domain is nonconvex. We give Malliavin calculus for discrete‐time case to deal with the fractional terms. The maximum principle of general type is derived by classical variation and linear operator methods. In addition, a linear‐quadratic problem is solved to illustrate the main result and we also figure out a numerical result in this case. [ABSTRACT FROM AUTHOR]

Rubella is a highly contagious viral disease that can be transmitted through contact with infected people or objects. If a pregnant woman is infected with rubella, the virus can be transmitted to the fetus, which can cause birth defects. To prevent rubella, children need to receive the MMR vaccine twice. In this study, we developed a deterministic and stochastic mathematical model to investigate the dynamics of rubella infection, considering vertical transmission and environmental factors. The model divides the population into five groups: susceptible, first vaccinated, protected, infected, and recovered. From the perspective of the qualitative behavior of the model, the model is bound to an invariant domain, and all solutions within the compartment are positive. We analyzed the equilibrium point of the model and its stability, and we determined the basic reproductive number using the next‐generation matrix. The basic reproductive number for the stochastic model is smaller than that for the deterministic model due to randomness. By comparing the two models in terms of the basic reproductive number, extending the deterministic model to a stochastic model can provide more realistic information about the disease, predict its dynamic propagation, and give suggestions for control mechanisms. Numerical simulations and sensitivity analyses were performed to study the influence of fundamental parameters, and the simulation results were displayed graphically using the MATLAB computer software. Parameter values were obtained from published papers, some of which were assumed. The simulation results show that the stochastic curve is not as smooth as the deterministic curve due to the randomness of the rubella. The consideration of the double vaccination dose and white noise intensity plays an important role in predicting disease status and minimizing and eradicating rubella. Therefore, reducing vertical infection and transmission rates and increasing vaccination and recovery rates will help to prevent and control the spread of rubella. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic evolution and volatility spillovers between China's green bond market and conventional financial markets (bond, stock, commodity, and foreign exchange markets) using time and frequency connectedness measures. The empirical findings are as follows: firstly, there is a significant volatility spillover effect between the green bond market and other traditional financial markets, with the spillover effect showing clear time‐varying characteristics. The total spillover effects among all markets increase notably during extreme market conditions. Secondly, the green bond market primarily acts as a net risk spillover transmitter in most periods. Thirdly, compared to the stock, foreign exchange, and commodity markets, the green bond market has a more significant spillover effect on the traditional fixed‐income market. Finally, the volatility spillover effect of the green bond market on other markets exhibits a time‐frequency evolution, predominantly driven by short‐term factors. However, as market maturity increases, the influencing factors of the spillover effect gradually shift from short‐term to medium and long‐term factors. These findings offer insights for portfolio and risk management. [ABSTRACT FROM AUTHOR]

Let S(Γ) be a Seidel matrix of a graph Γ of order n and let D(Γ) = diag(n − 1 − 2d1, n − 1 − 2d2, ..., n − 1 − 2dn) be a diagonal matrix with di denoting the degree of a vertex vi in Γ. The Seidel Laplacian matrix of Γ is defined as SL(Γ) = D(Γ) − S(Γ). In this paper, we obtain an upper bound, and a lower bound on the Seidel Laplacian Estrada index of graphs. Moreover, we find a relation between Seidel energy and Seidel Laplacian energy of graphs. We establish some lower bounds on the Seidel Laplacian energy in terms of different graph parameters. Finally, we present a relation between Seidel Laplacian Estrada index and Seidel Laplacian energy of graphs. [ABSTRACT FROM AUTHOR]

This paper presents an inventory model with a price‐dependent stochastic demand and finite replenishment rate mode. It establishes a production‐inventory system with a controllable deterioration rate, preservation technology, different types of rework process, promotional effort, and carbon emission reduction. This study finds the optimal solution and determines the most efficient production and safety technology investments to maximize the manufacturer's total profit over the planning horizon. Also, this inventory model balances sustainability and profitability to maximize the profit and to determine the optimal cycle length. In addition, the research highlights the most advantageous investments in production and preservation technology, emphasizing their critical role in increasing profitability and identifying the most effective duration of the production cycle. The study presents a comprehensive approach to inventory optimization that tackles practical and strategic challenges in manufacturing contexts. This research refers to cases and numerical examples, providing management insights and sensitivity analysis to determine the optimal course of action to change the parameters of the model. [ABSTRACT FROM AUTHOR]

Coal-resource-based cities, as one of the important types of typical resource-based cities in China, have strong characteristics of instability, sensitivity, and fragility, exhibiting a series of vulnerability features of the human-land system. Previous studies have lacked a deeper investigation into the vulnerability of such cities from the perspective of coupling feedback mechanisms among various elements or subsystems. This paper adopts Bohle et al.'s "Dual Structure Model" of vulnerability to establish an indicator system for vulnerability warning in coal-resource-based cities. Using Fushun City as a sample, a dynamic simulation model of vulnerability in coal-resource-based cities is constructed based on system dynamics for warning simulation calculations, analyzing the evolution trend of vulnerability in Fushun City from 2010 to 2022. The results show the following: (1) from 2010 to 2022, the urban vulnerability of Fushun City transitioned from a medium warning level to a relatively safe level, showing a trend of annual reduction and improvement, undergoing three development stages of significant reduction, fluctuation stabilization, and slight rebound. (2) Due to the causal relationships among various elements within the vulnerability subsystems of Fushun City, differences exist in the contribution levels of vulnerability subsystems during the period 2010–2022, under the combined effects of sensitivity and adaptability factors. The contribution rate of the natural subsystem was the highest from 2010 to 2014, while, from 2016 to 2019, urban vulnerability began to shift towards an economically and socially dominant type. Influenced by the pandemic, Fushun City's overall vulnerability has shown an upward trend since 2020 compared to the previous stage. Finally, specific policy suggestions are proposed for Fushun City to cope with vulnerability changes based on the analysis results, providing a theoretical basis for achieving sustainable development in such coal-resource-based cities. [ABSTRACT FROM AUTHOR]

Nowadays, construction industries are using flyash as a potential alternative for cement. Due to its improved mechanical properties, ecofriendly nature, and low cost, geopolymer technology makes use of flyash as a promising future binder material. In this paper, 7 factors such as liquid-to-flyash ratio, silicate-to-hydroxide ratio, curing temperature, curing period, concentration of NaOH (molarity), rest period prior to curing, and dosage of superplasticizer that influence the compressive strength and temperature drop are screened using the Plackett–Burman method for optimization. Here, compressive strength and temperature drop are taken as the main indices of response to analyze the parameters. The significant variables determined from the Plackett–Burman design are further considered for the process of optimization using the response surface methodology. From the analysis, the optimum values of 0.4071 liquid-to-flyash ratio, 2.5 silicate-to-hydroxide ratio, and 6 hours curing period give maximum compressive strength and temperature drop of 28.87 MPa and 5.3°C under the optimized medium in the validation experiment which varies by only 3.93% and 1.85% from the observed value of 27.20 MPa and 5.4°C. [ABSTRACT FROM AUTHOR]

In this paper, a fractional model in the Caputo sense is used to characterize the dynamics of HPV with cervical cancer. Generalized mean value theorem has been used to examine whether the infection model has a unique positive solution. The model has two equilibrium points: the disease-free point and the endemic point. The examination of the system's local and global stability is provided in terms of the basic reproductive number R p ° . The global stability analysis has been carried out using an appropriate Lyapunov function and the LaSalle invariant principle. The results demonstrate that in the infection model, if R p ° < 1 , then the solution converges to the disease-free equilibrium, which is both locally and globally asymptotically stable. Whilst R p ° > 1 , the endemic equilibrium is considered to exist. Simulations are implemented via a finite difference method with Grünwald-Letnikov discretization approach for Caputo derivative operator to define how changes in parameters impact the dynamic behavior of the system using Matlab. [ABSTRACT FROM AUTHOR]