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To enhance the quality and efficiency of computer-enabled generation of papers for Test for English Majors Band 8 (TEM-8), a paper generation model supported by sparrow search algorithm-genetic algorithm was studied. First, a simplified test paper generation mathematical model was set up after analyzing and studying types and characteristics of TEM-8 tasks. In the model, quantity, type, difficulty, discrimination degree, scores, exposure, and answering time of test questions were taken into consideration. To enhance the optimizing effect of the genetic algorithm for searching test questions, the traditional genetic algorithm was improved by introducing the sparrow search algorithm into the model to achieve a better crossover rate, variance rate, optimization precision, and speed of the genetic algorithm. A new sparrow search-genetic algorithm (SSA-GA) was designed, and the optimizing effect of SSA-GA was verified to be ideal through optimizing six standard test functions. Then, SSA-GA was applied to conduct experimentation with test paper generation, and comparison with traditional genetic algorithms was also made. The values of best and average fitness of SSA-GA were better than those of the traditional genetic algorithm (GA) in the paper generation. Exposure rate and success rate in TEM-8 paper generation of SSA-GA were higher than those of traditional GA in TEM-8 paper generation. Results showed that the studied SSA-GA could implement test paper generation with higher speed and better quality. [ABSTRACT FROM AUTHOR]

Aim: To explore connections between spiritual metaparadigm and the nursing metaparadigm and advocate for a progressive spiritualization of nursing management. Background: Relationship between the spiritual holistic metaparadigm of love, communion and gift and the holonic nursing metaparadigm of care, relationship and practice is not completely understood. Method: The construction of a theoretical explanation on the basis of accumulated knowledge in the fields of nursing and spirituality (especially Christian spirituality) for the purpose of constructing a meaningful description. Results: Deep connectivity between the elements of both metaparadigms: love and care, communion and relationship, and gift and practice. Conclusion: The connection between the spiritual and nursing metaparadigms is real in nursing education, practice and management because of the holistic character of spirituality. In collective intentions and cultural values are the main channels of interaction between the nursing and the spiritual metaparadigms. Implications for nursing management: Spirituality influences nursing management by, among other things, (a) providing meaning and purpose; (b) promoting cohesion in health communities; (c) fostering respect for ethics; (d) stimulating innovation; (e) encouraging leadership; and (f) illuminating the workplace. [ABSTRACT FROM AUTHOR]

This article points out some of the shortcomings of a paper by Ceballos et al. In particular, representations of the indecomposable six‐dimensional complex nilpotent Lie algebras are corrected. In addition, the class of representations is extended so as to include all the indecomposable six‐dimensional real nilpotent Lie algebras. A test case is studied in detail in which it is shown that there is no representation of one of the six‐dimensional real nilpotent Lie algebras using 5 × 5 matrices. This test case points up some of the severe difficulties that one will encounter when implementing an algorithm such as the one developed by Ceballos et al. The case of the seven‐dimensional complex nilpotent Lie algebras is briefly touched upon and several representations are corrected. [ABSTRACT FROM AUTHOR]

There is a lack of study on fault detection methods of medical equipment at home and abroad. The main reason is that the research of fault features is diverse and not systematic. This paper aims to propose a fault recognition method for medical equipment combining the electrical performance parameter features with fault events. First, it treats the equipment as a whole system, setting up the analysis model. Then, we are going to analyze the signal for indicator. This paper chooses the multi-index electrical performance parameters (MEPP) method for the fault identification an indicator. It is proved that the electrical performance signal can evaluate the status of equipment. Thus, it can also be used to recognize the fault or other working statuses. Then, the features of current, voltage, and power are studied exhaustively using a mathematical model. After that, the weight of each parameter feature in any specific event will be determined according to the influence of each parameter feature on fault events. At that time, the recognition method basically realizes the correlation between multi-index features and fault events through weight. Next, the above method needs to be verified in the experiment. This paper chooses six monitors for setting the rules of normal status. The normal status is the baseline for fault identification. Then, feature intervals of other faults are established around this reference. Finally, each feature interval will be constantly adjusted to meet the preset recognition rate and updated to the rules in the subsequent measurement. In this paper, 10 monitors are selected as samples to update a set of basic fault judgment rules based on MEPP, and by adjusting the overlapping interval, the fault recognition rate reaches more than 90% in this study. To sum up, this paper uses the MEPP method to find out the relationship of features of current, voltage, and power with fault events. It will become a new direction for fault recognition studies on electrical medical equipment and other device. [ABSTRACT FROM AUTHOR]

This paper reports the findings of a thematic narrative review of peer‐reviewed articles exploring innovation in UK independent homecare services published between January 2009–August 2021. Our analysis of 15 papers reveals four broad innovation types: personalised funding, operational models, workforce development and assistive technology. We conclude that research focused on innovation in independent homecare offers important insights into the positive and negative outcomes of different types of innovation for providers, care workers and people receiving care. There are, however, also areas which are neglected and need further elaboration, including more robust evidence of outcomes and clearer articulation of innovation processes. [ABSTRACT FROM AUTHOR]

Finally, the last paper presents a design-task-oriented model assignment framework that involves model value selection, multiobjective model establishment, and multiobjective optimization algorithm. We hope that the papers presented in this Special Issue will be useful and stimulating for further developments and applications of multicriteria and multiobjective models and that we again have been able to highlight the extensive range of contexts over which these methods can be used. This is the Fourth Special Issue (SI) dealing with "Building Mathematical Models for Multicriteria and Multiobjective Applications.". [Extracted from the article]

In this paper, a mathematical model is formulated, suitable to explain the evolution of income distribution over a population in the presence of production. The model is conceived from the perspective of complexity. Indeed, the income distribution emerges as the result of a myriad of economic exchanges taking place between individuals. In fact, the aim of the paper is to provide a framework and mathematical tools for the construction and the investigation of models having an exploratory character. The framework is expressed in the form of a system of nonlinear ordinary differential equations, as many as the income classes are, involving transition probabilities. Numerical solutions of these systems are constructed under different assumptions on the law of production and in the presence of different fiscal systems, which provides an example of the versatility of the method. [ABSTRACT FROM AUTHOR]

Purpose. As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively. Conclusion. The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other. [ABSTRACT FROM AUTHOR]

Distribution process is the core of logistics enterprise system. Efficient distribution process is the key for enterprises to improve logistics service level, gain competitive advantage, and win customers. In order to reduce the design error of the system and ensure the effective operation of the system, this paper establishes the system model and analyzes the properties of the model through the evaluation and analysis of various resources of the distribution system. The future development of intelligent logistics system is not only the key for logistics enterprises to win competition, but also a new measure to promote China's economic development. This is not only a typical NP hard problem, but also a major challenge for the rational and scientific development of the intelligent logistics industry. Based on the previous theoretical research results, this paper intends to explore the intelligent logistics distribution route selection scheme by using mathematical modeling methods such as particle swarm optimization, so as to provide new technologies and methods for logistics distribution operation and management decision-making. The results show that compared with the traditional genetic algorithm, the accuracy of the improved particle swarm optimization algorithm is improved by 10.36%. This method effectively improves the operation cycle and link efficiency and achieves the purpose of optimization. The improved particle swarm optimization algorithm proposed in this paper is not only more suitable and effective for enterprise decision makers to deal with subjective judgments in an imprecise environment. It is also based on the evaluation sequence of each indicator of the alternative obtained from the evaluation and the comprehensive evaluation of all indicators. By weighting and considering the results, the best solution for enterprise logistics and distribution is selected. [ABSTRACT FROM AUTHOR]

The constant expansion of higher education has led to the continuous increase of the teaching staff and the complexity of the work in the modern era of education, forcing the traditional colleges and universities (it is abbreviated as CU in this article) to participate in trade union activities to open up the road of innovation. What kind of method can effectively and quickly optimize trade union work (TUW) and improve satisfaction has become one of the research topics that has attracted much attention. Aiming at this problem, it has great research significance for the field of CU to participate in trade union activities. With the in-depth research on the work of trade unions in CU, the research on multivariate optimal design in the work of trade unions in CU is gradually carried out, and its advantages are of great significance for solving problems in the work of trade unions in CU. The purpose of this paper is to study the innovation of TUW mode in CU based on multivariate optimization. Through the analysis and research of the multivariate optimization idea, it can be applied to the innovation of the construction of the labor union work model in CU, and the multiobjective linear weighting method is used to solve the objective function, so as to solve the problem of improving the evaluation of labor union work satisfaction in CU. This paper analyzed the TUW in CU (it is abbreviated as TUW in this article) and the multivariate optimization design, conducted an experimental analysis on the improved TUW mode in CU, and used relevant theoretical formulas to explain. The results have shown that the overall evaluation score of the college TUW method proposed in this paper is higher than the traditional college TUW method, and the difference between the two is 18.7%. It can be seen that the university TUW based on mathematical modeling and multivariable optimal design can meet the innovation needs of university TUW, and the satisfaction and work efficiency are greatly improved. [ABSTRACT FROM AUTHOR]

In the consumer goods supply chain, there are three different modes of demand: real, false, and semireal. It is an interesting topic to discuss the optimal profit of enterprises according to these three demand patterns. This paper develops three mathematical models that can be used to investigate the factors that affect retailers with respect to the design of product supply strategies for individual customers under a semireal demand pattern and thereby addresses the problem of retailers' maximum profitability. The results of the present study show that these models may effectively help retailers develop appropriate supply strategies for individual customers under a semireal demand pattern; in turn, this may help retailers improve operational performance. The main contribution of the current study lies in the construction of mathematical models of product supply strategies for the individual customer in the off-invoice mode, the scan-back mode, and the unsold-item processing mode under the semireal demand pattern. The effectiveness of the models has been verified through numerical calculations. In concrete management practice, the mathematical model given in this paper can be used to effectively adjust the quantity of goods purchased, correct retail prices, and optimize sales discounts to maximize profits. [ABSTRACT FROM AUTHOR]

With the in-depth development of social reforms, the scientificization of enterprise online examinations has become more and more urgent and important. The key to realizing scientific examinations is the automation and rationalization of propositions. Therefore, the construction and realization of the test question bank is also more important. In the realization of the entire test question database, how to select satisfactory test questions randomly from a large number of test questions through the selection of test questions so that the average difficulty, discriminability, and reliability of the test are satisfactory? These requirements are also more important. Among them, random selection of questions is an important difficulty in the realization of the test question bank. In order to solve the difficulties of random selection of these test questions, the author combines the experience of constructing the test question bank and uses the discrete binomial distribution to draw conclusions. Random variables established the first mathematical model for topic selection. By determining the form of the test questions and the distribution of the difficulty of the test questions and then making it use a random function to select questions, this will achieve better results. [ABSTRACT FROM AUTHOR]

In this paper, the impact of viral illnesses on the predator-prey relationship with an optimal control analysis is studied. An ecoepidemiological model of four compartments, namely, susceptible prey, susceptible predator, infected prey, and infected predator populations, in the interaction of the prey-predator system is formulated. The fundamental tenet of our ecoepidemiology model is that sick predators do not engage in predation. It is confirmed that the system's solution exists, is positive, and is bounded. The system's equilibrium points are determined and computed. Lyapunov functions and a linearizing form are used for local and global stability analysis, respectively. The next generation matrix approach is used to calculate the threshold value for diseased predators and prey at the disease-free equilibrium point. Optimal treatment options for vulnerable and infected populations are established by applying optimal control theory to the ecoepidemiology model of a prey-predator system. MATLAB software is utilized to obtain numerical simulations that validate the analytical outcomes. The optimal control problem simulations demonstrate that the number of infected populations in a given prey-predator system can be decreased by implementing control measures. [ABSTRACT FROM AUTHOR]

Gumboro disease is a viral poultry disease that causes immune suppression on the infected birds leading to poor production, mortality, and exposure to secondary infections, hence a major threat in the poultry industry worldwide. A mathematical model of the transmission dynamics of Gumboro disease is developed in this paper having four compartments of chicken population and one compartment of Gumboro pathogen population. The basic reproduction number R og is derived, and the dynamical behaviors of both the disease-free equilibrium (DFE) and endemic equilibrium are analyzed using the ordinary differential equation theory. From the analysis, we found that the system exhibits an asymptotic stable DFE whenever R og < 1 and an asymptotic stable EE whenever R og > 1. The numerical simulation to verify the theoretical results was carried out using MATLAB ode45 solver, and the results were found to be consistent with the theoretical findings. [ABSTRACT FROM AUTHOR]

Background. In addition to the usual difficulty of managing human capital in any organization, healthcare institutions have other problems to solve arising from the circumstances and the very nature of the work they perform, such as the ethical pressure on staff, emotional exhaustion, the distribution of work shifts, or the general shortage for nurses. In many cases, this situation has an impact on the quality of care. Objective. The main objective of this research is to compile, in a single document, human resource practices that help health centre managers improve results in terms of performance and quality of care, as well as avoid the intention of abandoning the job, specifically related to the work of nurses. Methods. To this end, a systematic literature review has been performed based on 229 papers published in the Web of Science database, from which the practical implications for nurses proposed by these authors have been extracted. Results. The main results suggest that developing affective commitment helps to improve organizational performance and enhance patient safety culture. Furthermore, improving communication and meaningfulness of work, recognition by superiors, or job flexibility would improve the quality of outcomes, for the work of nurses. Conclusions and Implications for Nursing. Stimulating normative commitment, reducing excessive control, and paying attention to job burnout and job stress help combat the intention of voluntary turnover or leaving the job, especially in the case of nurses. [ABSTRACT FROM AUTHOR]

One of the main concepts in group technology (GT) is the cellular manufacturing system (CMS) with three main problems of cell formation (CF), cell layout (CL), and cell scheduling (CS). This paper studies the cell layout problem (CLP), aiming to find the optimal layout of machines within each cell (intracellular layout) and the optimal layout of cells in each workshop (intercellular layout). To adapt to reality, the dimensions of the cells and machines (inside each cell) were considered unequal, and also the cells and machines could rotate. We believe that a cellular layout that assumes unequal dimensions of the cells and machines can be used for batch production. This kind of production has a wide variety of low to medium demand. Furthermore, a cellular layout can be applied in CMSs and also in noncontinuous industries that have a job shop layout. Our main contribution is considering the possibility of rotating the cells and machines inside the cells. For this purpose, a mixed nonlinear programming model was developed to solve the CLP with the minimum cost of intracellular and intercellular material flows. The proposed nonlinear model was first converted into a linear model, and then a problem was generated and solved with GAMS software to validate the resulting linear model. This model finds the best layout of cells within the workshop and the best layout of machines inside each cell. Then, because of the NP-hardness of the CLP and the fact that even exact methods cannot solve large-scale examples in an acceptable computational time, an imperialist competitive algorithm (ICA) was designed and used to solve the problem. To evaluate the efficiency of the proposed algorithm, its numerical results in small dimensions were compared with the results of GAMS software. In large dimensions, 30 random problems were created, and the results of ICA were compared with the results of the particle swarm optimization (PSO) algorithm and genetic algorithm (GA). Finally, the parameters of the three meta-heuristic algorithms were set by the Taguchi method. Numerical results indicated that ICA was superior to both the PSO algorithm and GA. It could also achieve efficient solutions in a shorter computational time. [ABSTRACT FROM AUTHOR]

Mobile Healthcare Social Media (MHSM) is an innovative combination of mobile devices and mobile communication technology. How can users shift from spontaneous to conscious cognitive mode, break their usage inertia, and actively adapt to the social structure of mobile health social media to improve information-sharing performance? This study uses adaptive structuring theory as the theoretical foundation to deeply analyze adaptive information-sharing behavior and its specific forms in the mHealth social media environment; it uses cognitive shift theory and social exchange theory as the theoretical framework to comprehensively explore the antecedent motivations of users engaging in adaptive information-sharing behavior and its posterior effects. Theoretically, it promotes the innovation and development of information-sharing behavior research and the further deepening of the application of adaptive structuring theory at the information behavior level. It is also conducive to bridging the digital divide and maximizing the value of health information resources. This paper takes 1000 survey data as the experimental data source for studying the influence of mobile social media sharing behavior on the subjective well-being and mental health regulation of Internet users and concludes that in practice, it is beneficial to optimize the design of information-sharing-related functions in mobile health social media, improve the effect of user information sharing in mobile health social media environment, and enhance the efficiency of information sharing so that mobile social media sharing behavior can better contribute to the subjective well-being and mental health regulation of Internet users. This paper has an obvious psychological adjustment effect on groups who use too much social media and can help them analyze why they are affected by some social media, thereby producing psychological effects. [ABSTRACT FROM AUTHOR]

This paper comprehensively analyzes the characteristics of flexible job shop scheduling problem (FJSSP), takes the dynamic factors in the actual scheduling process such as the arrival and departure of jobs, the breakdown and recovery of machines into account at the same time, and establishes a new dynamic multi-objective mathematical model. Take the Squirrel Search Algorithm (SSA) as the core evolution strategy, and combine the multi-objective framework and the dynamic processing technology to solve the established mathematical model. Experimental results show that the mathematical model proposed in this paper can solve the flexible job shop scheduling problem effectively. Compared with other mathematical models, the mathematical model established in this paper can keep better balance between the efficiency and stability. [ABSTRACT FROM AUTHOR]

Analysis of multisource errors accompanying process execution and study of the propagation effects of the corresponding multiprocess manufacturing process are the basic prerequisites for optimizing the generation process and improving the quality of the product. This paper proposes an analytical framework for error propagation effects in multiprocess manufacturing, which completely covers error source analysis, mathematical calculation of error propagation accumulation, and description of error propagation effects, which can provide better support for error traceability, error propagation monitoring, and error dissipation in manufacturing production. First of all, establish the process state model into the features of the manufacturing level, analyze the type of multisource error, and its mode of action when executing the process operation; second, establish the mathematical calculation model of error propagation accumulation based on state space equation is established, so as to realize calculation and analysis of error propagation; and finally, establish the link graph and link matrix of error propagation influence in multiprocess manufacturing process are established to further reveal the scope and path of error propagation influence. In this section of the case study, a plate cover part had been taken as an example, the multisource error in its manufacturing was analyzed, and the propagation and accumulation of these error values are obtained by state space and state transition theory. On this basis, the link graph and its corresponding link matrix were used to explicitly describe the error propagation effects during the multiprocess manufacturing of the example part. The example analysis illustrated the proposed error analysis framework could analyze and calculate the multisource error of multiprocess manufacturing and visually describe the error propagation effects, which showed the effectiveness and feasibility of the proposed method framework. [ABSTRACT FROM AUTHOR]

Multipath data transmission is a key problem that needs to be solved urgently in wireless sensor networks. In this paper, sensor node failure, link failure, energy exhaustion, and external interference affect the stability and reliability of network data transmission. A multipath transmission strategy for wireless sensor networks based on improved shuffled frog leaping algorithm is proposed. A mathematical model of multipath transmission in wireless sensor networks is established. In the shuffled frog leaping algorithm, combined with the transition probability in the particle swarm optimization algorithm, random individuals in the subgroup are introduced to assist the search when updating the frog individual position, which improves the algorithm's ability to jump out of the local optimum and improves the quality of the optimization algorithm solution. The model is applied to multipath transmission in wireless sensor networks. Then, the shuffled frog leaping algorithm is used to update, divide, and reorganize the sensor nodes to select the optimal node to establish the optimal transmission path and improve the stability and reliability of the network. Simulation experiments show that the algorithm in this paper can ensure the reliability of data transmission, reduce the network packet loss rate and network energy consumption, and reduce the average delay of data transmission. [ABSTRACT FROM AUTHOR]

With the support of big data technology, the field of education is also facing new problems and opportunities. Network teaching has become the mainstream means of higher education. In order to explore the changes of students' learning effect in the process of online teaching, this paper proposes to build an online teaching effect evaluation model with the support of data mining technology and decision tree algorithm. This paper records the factors and objects that reflect the teaching effect in network teaching and traditional teaching, respectively. A decision tree algorithm is used to divide the attributes of influencing factors from relevant rules. Using the Kirschner model to build the evaluation system, add two attribute elements: students' teaching evaluation and teachers' self-evaluation. Data mining technology is used to preprocess and clean up the sample set, which improves the accuracy of the calculation results. In the evaluation model, the association rule algorithm is also constructed to classify the data of the same element type and delete the data of different elements after marking. Through this evaluation model, teachers can accurately judge students' learning interests and improve students' academic performance. The results show that compared with the traditional data mining algorithm, the decision tree algorithm has obvious advantages in computing speed and accuracy. [ABSTRACT FROM AUTHOR]

In order to find a chaotic trajectory sequence with strong global optimization ability to help the genetic selection of direction after the reversal of chemotaxis, an improved genetic algorithm based on chaos optimization is proposed by combining the characteristics of chaotic motion with the improved genetic algorithm. The optimal coverage problem in sensor networks can carry out fine optimization search on local areas. The results show that the overall trend of fitness and optimization efficiency is relatively stable. The optimization efficiency will be gradually improved with the continuous progress of time and genetics, and the error analysis will be reduced. This will greatly improve the impact of various adverse factors in the optimization process. In addition, the change rate of fitness is basically kept at a high change rate, which also reflects that the basic framework of the model is very excellent, and the whole algorithm structure and data processing are improved by 54%. The improved genetic algorithm proposed in this paper is used to adjust and optimize the controller parameters. When the uncertain parameters change greatly, the control system still has good control quality and strong robustness. [ABSTRACT FROM AUTHOR]

Building a new development pattern based on the "double-cycle" is a major strategic plan of China. Under the background of the new development pattern of the "double-cycle" and the context of environmental constraints, this paper tries to explore the impact of marine economic development on marine cultural industry and marine innovation development, the extent of the impact of marine cultural industry on marine economic growth, and the internal relationship between them under the new development pattern of double circulation. In this paper, Fujian Province is taken as the research object to construct an indicator system of the marine culture development to reflect the living standard, employment level, and spiritual and cultural levels of people in the marine area, and the external influence of the marine economy and marine culture industry is taken as the indicator variable to measure the integrated development. The internal changes are regarded as the index to assess the integration level of the two, and the evaluation theoretical model of the dynamic evolution level of the marine economy and marine cultural industry is constructed. The vector autoregression model and impulse response function are used to study the interactive correlation between the growth of the marine economy and the development of the cultural industry. The results show the following: In the long run, there is a cointegration relationship between the marine culture industry and the gross ocean product (GOP), which is a long-term balanced and stable relationship. The development level of the marine economy and the development of marine culture industry are mutually influencing and promoting. [ABSTRACT FROM AUTHOR]

Preferential access to scarce resources can bring competitive advantages and better performance to enterprises. However, the existing literature has a relatively single research path on the influencing factors of enterprise resource access, which has lack of sufficient research from the perspective of multidimensional environment. In particular, as an important factor affecting enterprises' access to external resources, few studies have given empirical results on the impact of political factors such as government structure on enterprise resource access. Preferential access to scarce resources can bring competitive advantages and better performance to enterprises. However, the existing literature has a relatively single research path on the influencing factors of enterprise resource access, which lacks sufficient research from the perspective of multidimensional environment. In particular, as an important factor affecting enterprises' access to external resources, few studies have given empirical results on the impact of political factors such as government structure on enterprise resource access. Through the discussion of multidimensional environmental factors, this paper can provide theoretical reference for the reform of government institutions and the establishment of good political relations between enterprises and the government. Focusing on the multidimensional environment of government structure, political relations, and enterprise resource acquisition, this paper takes 129 enterprises in Central China as samples and uses the structural equation model to empirically verify the relationship between the formalization of government structure, liaison mechanism, decentralization, and enterprise resource acquisition, especially the easing effect of political relations. The results show that the formalization of government structure is promoting enterprises to obtain policy resources and financial resources; the liaison mechanism helps enterprises to obtain financial resources and market resources; decentralization has a significant positive impact on enterprises' access to policy resources and market resources; and political connection magnifies the positive effect of government structure on enterprise resource acquisition, but there are differences in different dimensions. [ABSTRACT FROM AUTHOR]

In order to improve the scientificity of sports action analysis, this paper constructs a sports action analysis model based on machine learning based on the greedy algorithm and the bat algorithm. According to the structural characteristics of the model, the structure of the model is reflected in the form of face order, that is, the face neighborhood structure. Moreover, this paper judges the degree of similarity between model faces through the pros and cons of the order and applies it to the structural similarity matrix between models. In addition, this paper establishes corresponding mathematical models for the shape and structure of the model and constructs the shape similarity matrix, the surface neighborhood structure similarity matrix, and the structure similarity matrix between the source model and the target model. Finally, this paper designs and implements CAD model retrieval methods based on greedy algorithm and bat algorithm and designs experiments to compare the performance of the algorithm proposed in this paper with traditional algorithms. The result of the experiment shows that the algorithm proposed in this paper has obvious advantages in sports action analysis compared with the traditional algorithm. [ABSTRACT FROM AUTHOR]

Agricultural sustainable development is one of the themes of human and nature harmonious coexistence. Adjusting and optimizing agricultural structure are an important direction to improve the level of agricultural sustainable development. In this paper, related research status of the sustainable development of agriculture is analyzed; it shows that there is lack of scientific theories guidance for agricultural sustainable development. In order to optimize sustainable development of agriculture industry structure, the guidance theory of and its optimization are studied. Based on multiobjective optimization theory, several key factors that affect agricultural sustainable development and the main target indexes of agricultural sustainable development are analyzed, the mathematical model of the evaluation of the sustainable development of agriculture is established, and the solution to optimize the multiobjective model is studied. Finally, the agricultural industry sustainable development in a certain area is taken as the research object in this paper; the mathematical model and solving method of agricultural sustainable development evaluation are studied; it provides a guidance to optimize the regional agricultural industrial structure and improve the quality of agricultural sustainable development. [ABSTRACT FROM AUTHOR]

The financial investment risk management system refers to an analysis and control of the intelligent system to invest in the lower financial situation so that investors quickly understand the situation in the financial industry. The purpose of this article is to use a digital model to evaluate financial investment risk management system. The investment risk value can be better evaluated by building a digital model. This paper first introduces financial investment risks and then elaborates the evaluation system and related digital models. The standards of the evaluation system are also given. The GARCH model is established to analyze the LME copper and LME aluminum case selected by this paper by investigation and analysis of the current status of corporate financial investment risks. The experimental results show that the evaluation results are often close to the reality when using the GARCH model evaluation of financial investment risk management system, and the accuracy is quite high. In addition to the EGARCH-N model, the established model is more accurate at 90% confidence level, which is more accurate and is relatively close to a given significance level. [ABSTRACT FROM AUTHOR]

Giardiasis is among the ignored zoonotic illnesses accorded by the World Health Organization that is caused by Giardia duodenalis. The disease is ignored regardless of the harm it causes to people and other creatures. In this paper, a mathematical model for giardiasis illness transmission is formed, which considers sickness carriers and control measures such as screening, treatment, and sanitation of the environment around people. In the assessment, the basic reproduction number, R 0 , which is used for analyzing the local stability of the equilibria is determined using the state-of-the-art next-generation matrix, while the Metzler constancy speculation is used to show the overall adequacy of the global stability of the equilibrium point free from the disease. In addition, a Lyapunov function has been used to study the stability of the endemic equilibrium point. The assessment of parameters is performed to explore the limits that significantly influence the transmission components of the disease disorders using the normalizing sensitivity index method. The result revealed that the recruitment rate is the most sensitive limit to the reproduction number. The environment-human interaction parameter is the second influential factor in the transmission of giardiasis in the community. In the same manner, the outcomes recommend that carriers assume an expected part in the rate of giardiasis subsequently; disregarding them could risk endeavors to control the pestilence. Besides, the mathematical recreation of the model shows that a mix of each of the three interventions fundamentally affects the control of giardiasis. In this way, we advise implementing the strategies simultaneously in endemic areas to effectively stop the spread of the giardiasis disease in humans. [ABSTRACT FROM AUTHOR]

This paper uses Python programming to improve the existing price index method and calculate the integration level of the forest products market in China. Based on the model, the influencing factors of domestic forest product market integration were examined empirically. The results show that the integration degree of the forest product market in recent years lags behind the average level in China. In this paper, the improvement of the existing price index method can calculate the level of market integration more quickly and accurately, and this improvement has obvious advantages in the case of a large amount of data. In terms of development, the overall pattern shows an increasing trend, and the eastern, central, and western provinces are gradually converging, although the differences between provinces continue to expand. In terms of influencing factors, the coefficient of the local government's emphasis on forestry, the prosperity of international trade in forest products, and highway density were significantly positive factors, while the number of foreign investors and the railway density had no significant effects. In this paper, the optimization of the measurement method of market integration makes it easier for scholars to obtain the data on the level of market integration and promote in-depth research in the field of market integration. [ABSTRACT FROM AUTHOR]

In order to improve the ability of enterprises to cope with financial risks, this paper analyzes the financial early warning of enterprises combined with intelligent mathematical models and builds an intelligent financial early warning model to assist in analyzing the financial status of enterprises. Moreover, this paper combines the existing information technology and expenditure business scenarios to construct an intelligent early warning frame for enterprise financial control based on an intelligent mathematical model. In addition, this paper combines the K-means clustering algorithm to design a financial approval process integrity control early warning method to warn the integrity of the financial approval process. Finally, this paper presents the early warning of financial standard compliance control based on the C4.5 decision tree algorithm. The experimental research shows that the enterprise financial early warning model based on the intelligent mathematical model proposed in this paper can play an important role in the enterprise financial management and effectively improve the ability of the enterprise to cope with financial risks. [ABSTRACT FROM AUTHOR]

The development of artificial intelligence has brought rapid changes to human life and brought great convenience to human activities. The development of various modes of transportation has also brought convenience to people's travel and commodity transactions, but it has also added more issues that need to be carefully considered. Because of the diversification of transportation methods, transportation problems also arise many fields, such as air transportation, water transportation, and land transportation. The development of mathematical models and algorithms for transportation problems is also in full swing, and it is a major trend to introduce mathematical models and algorithms into the solution of transportation problems. This paper deals with the multi-index transportation problem by establishing a multi-index mathematical model and algorithm to find a scientific transportation method for the goods to be transported, so as to save the cost and time of transportation. Experiments show that the mathematical model established in this paper has high efficiency for solving the multi-index transportation problem. At the same time, the most suitable transportation method can also be selected for the transportation of goods, and the route planned by the mathematical model and algorithm can reduce the risk to 12.34%. [ABSTRACT FROM AUTHOR]

Based on the knowledge organization method, this paper explores the construction method of the traditional Chinese medicine (TCM) clinical knowledge coding model by taking TCM clinical electronic medical record data as the research object. Firstly, extracting technology is used to obtain the required data in the electronic medical record. Then, by constructing the clinical knowledge coding model, the tacit knowledge is made explicit, establishing the clinical knowledge base and exploring the connotation of TCM clinical knowledge. It provides necessary data resources for deepening the expression level of TCM clinical knowledge, constructing accurate TCM clinical diagnosis, intervention, and evaluation models, and promoting the inheritance, innovation, and development of TCM. In this paper, we extracted the data of 318 cases of distention and established the TCM clinical database from the basic information of patients, clinical diagnosis information, clinical diagnosis and treatment information, and clinical evaluation information. Based on the knowledge coding model and the connotation of knowledge attributes, the established TCM clinical knowledge base was to explore the law of TCM clinical precision diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Digital sports training based on digital video image processing promises to reduce the reliance on the experience of coaches in the table tennis training process and to achieve a more general physical education base. Based on this approach, this paper describes the specific forms of exercise content, movement characteristics, and skill levels in the table tennis framework and specifies the calculation methods of motion capture and movement characteristics suitable for table tennis. Meanwhile, to further improve the accuracy of the inertial motion capture system in restoring the position posture of the trainees, this paper improves the original inertial motion capture system from two aspects: contact judgment of both feet and correction of the position posture based on the contact position constraint. The simulation results show that the corrected human posture has good action smoothness. This paper first proposes a knowledge-based generic sports-assisted training framework based on generalizing the traditional sports training model. The framework contains four main modules: domain knowledge, trainees, sport evaluation, and controller. The domain knowledge module is a digital representation of the knowledge of the exercise content, improvement instructions, and skill indicators of the sport; the trainee module is the active response of the trainee to the exercise content and improvement instructions; the motion evaluation module uses motion capture technology to obtain the raw motion data of the trainee and further calculates the motion characteristics; the controller module proposes improvement instructions to the trainee or makes him/her practice new content based on the results of the motion evaluation. Based on the results of the motion evaluation, the controller module proposes improvement instructions or makes the trainee practice new content until the trainee achieves the desired goal. [ABSTRACT FROM AUTHOR]

Mobile robots are widely used in medicine, agriculture, home furnishing, and industry. Simultaneous localization and mapping (SLAM) is the working basis of mobile robots, so it is extremely necessary and meaningful for making researches on SLAM technology. SLAM technology involves robot mechanism kinematics, logic, mathematics, perceptual detection, and other fields. However, it faces the problem of classifying the technical content, which leads to diverse technical frameworks of SLAM. Among all sorts of SLAM, visual SLAM (V-SLAM) has become the key academic research due to its advantages of low price, easy installation, and simple algorithm model. Firstly, we illustrate the superiority of V-SLAM by comparing it with other localization techniques. Secondly, we sort out some open-source V-SLAM algorithms and compare their real-time performance, robustness, and innovation. Then, we analyze the frameworks, mathematical models, and related basic theoretical knowledge of V-SLAM. Meanwhile, we review the related works from four aspects: visual odometry, back-end optimization, loop closure detection, and mapping. Finally, we prospect the future development trend and make a foundation for researchers to expand works in the future. All in all, this paper classifies each module of V-SLAM in detail and provides better readability to readers. This is undoubtedly the most comprehensive review of V-SLAM recently. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamics of systemic risk in banking networks by analyzing equilibrium points and stability conditions. The focus is on a model that incorporates interactions among distressed and undistressed banks. The equilibrium points are determined by solving a reduced system of equations, considering both homogeneous and heterogeneous scenarios. Local and global stability analyses reveal conditions under which equilibrium points are stable or unstable. Numerical simulations further illustrate the dynamics of systemic risk, while the theoretical findings offer insights into the behavior of distressed banks under varying conditions. Overall, the model enhances our understanding of systemic financial risk and offers valuable insights for risk management and policymaking in the banking sector. [ABSTRACT FROM AUTHOR]

In this paper, a class of integrodifferential equations with the Caputo fractal-fractional derivative is considered. We study the exact and numerical solutions of the said problem with a fractal-fractional differential operator. The abovementioned operator is arising widely in the mathematical modeling of various physical and biological problems. In our scheme, first, the integrodifferential equation with the fractal-fractional differential operator is converted to an integrodifferential equation with the Riemann–Liouville differential operator. Additionally, the obtained integrodifferential equation is then converted to the equivalent integrodifferential equation involving the Caputo differential operator. Then, we convert the integrodifferential equation under the Caputo differential operator using the Laplace transform to an algebraic equation in the Laplace space. Finally, we convert the obtained solution from the Laplace space into the real domain. Moreover, we utilize two techniques which include analytic inversion and numerical inversion. For numerical inversion of the Laplace transforms, we have to evaluate five methods. Extensive results are presented. Furthermore, for numerical illustration of the abovementioned methods, we consider three problems to demonstrate our results. [ABSTRACT FROM AUTHOR]

This paper aims to establish strategies of coping with COVID-19 pandemic adopted by the clients of social assistance from the perspective of social workers. The qualitative research among Polish social workers and family assistants was conducted from September to November 2021. Based on 30 in-depth interviews with social work professionals, groups of social assistance clients' behaviours were identified and classified into the theoretical models of reactions to social change by Merton and Giddens. The following types of behaviour have been selected and categorized into four groups of reactions when dealing with social workers in a pandemic situation: coolheaded calculation, defiance, confusion, and adaptation. At the same time, reactions to the situation of social change were categorized into one of the strategies of active or passive behaviour: innovation, contestation, retreat, and acceptance. In addition, we discussed the impact of clients' coping strategies on social workers and established three attitudes of the surveyed social workers: adapting to the pandemic situation and customer behaviour, assuming the role of an emotional buffer and informant, and expecting support from superiors and coworkers. Knowing the behaviour of social assistance clients in a challenging situation makes it possible to adopt tailor-made measures. [ABSTRACT FROM AUTHOR]

Coffee berry disease (CBD) is a fungal disease caused by Colletotrichum kahawae. CBD is a major constraint to coffee production to Kenya and Africa at large. In this research paper, we formulate a mathematical model of the dynamics of the coffee berry disease. The model consists of coffee plant population in a plantation and Colletotrichum kahawae pathogen population. We derived the basic reproduction number R k 0 , and analyzed the dynamical behaviors of both disease-free equilibrium and endemic equilibrium by the theory of ordinary differential equations. Using the MATLAB ode45 solver, we carried out numerical simulation, and the findings are consistent with the theoretical results. [ABSTRACT FROM AUTHOR]

A mission reliability evaluation methodology for a signal traffic controller is presented in this paper. To develop the new evaluation methodology, this paper combines the Discrete Event System Specification (DEVS) formalism which has been popular in manufacturing area for three reasons: (1) its features compatible with the object-oriented modeling; (2) its rigorous formal definition; and (3) its support for the specifications of discrete event models in a hierarchical and modular manner. By using the DEVS formalism, we construct a simulation model which takes into account not only the characteristics of a traffic signal controller but also the operating environment. Once a model is constructed, it is possible to perform simulation experiments. The proposed methodology computes the mission reliability of a traffic signal controller by using a simulation record, and this information plays a vital role in preparing optimized maintenance policies that maximize availability or minimize life cycle costs. [ABSTRACT FROM AUTHOR]

Migrants face several unmet health needs due to the inability of the healthcare system to address their healthcare challenges. As a result, they adopt coping strategies to overcome their healthcare needs. Consequences can include infrequent but severe adverse reactions, dangerous drug interactions, incorrect dosage etc. Little is known in Ghana about the role played by cultural and linguistic barriers in shaping migrants' access to formal healthcare and the coping mechanisms adopted by these migrants to overcome their healthcare challenges. Surprisingly, most of the studies that have been conducted have focused on financial barriers to care accessibility. This presents a loss opportunity for any health programme aimed at addressing this inequity. Thus, the purpose of this paper is to fill this gap by exploring the challenges of healthcare accessibility and coping strategies adopted by migrants to overcome their healthcare needs in the informal urban settlement of Madina, in the Greater Accra Region. The author employed a narrative type of qualitative research design. A purposive and then snowball sampling technique were used to select 20 participants to participate in the study after saturation was reached. Twelve in‐depth interviews (IDIs) and six key informants' interviews (KIIs), as well as two focus group discussions (FGDs), were conducted. The study is consistent with the ecological model, which posits that health is determined by influences at multiple levels. The author found linguistic, cultural, stigmatisation and financial challenges as the main barriers to healthcare accessibility among the migrants. As a result, self‐medication and the use of lay health personnel for addressing healthcare needs were more pronounced. The study also found other means of survival that posed a health risk to the migrants. Based on this, it was recommended that healthcare systems take into account the healthcare needs of migrants who are people with culturally and linguistically diverse backgrounds. [ABSTRACT FROM AUTHOR]

Numerous mathematical models simulating the phenomenon in science and engineering use delay differential equations. In this paper, we focus on the semilinear delay differential equations, which include a wide range of mathematical models with time lags, such as reaction-diffusion equation with delay, model of bacteriophage predation on bacteria in a chemostat, and so on. This paper is concerned with the stability and convergence properties of exponential Runge–Kutta methods for semilinear delay differential equations. GDN-stability and D-convergence of exponential Runge–Kutta methods are investigated. These two concepts are generalizations of the classical AN-stability and B-convergence for ordinary differential equations to delay differential equations. Sufficient conditions for GDN-stability are given by a newly introduced concept of strong exponential algebraic stability. Further, with the aid of diagonal stability, we show that exponential Runge–Kutta methods are D-convergent. The D-convergent orders are also examined. Numerical experiments are presented to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Rehabilitation nursing teaching is one of the key points of nursing teaching. The quality of rehabilitation nursing teaching directly affects the comprehensive ability of clinical interns. Therefore, teachers must further deepen the reform of clinical nursing teaching, improve the teaching system, and explore effective clinical nursing teaching methods. This paper introduces the application of the network teaching mode based on sandwich in rehabilitation nursing teaching, which provides guidance and help for the clinical nursing teaching mode. Through sandwich teaching activities for third year students of the nursing department, taking mastering theoretical knowledge, changing critical thinking ability, and changing learning initiative as indicators, this paper analyzes the sandwich teaching mode and discusses the cultivation of nursing students' ability. The experimental results showed that after the intervention, there was a statistically significant difference in the learning initiative of students in the experimental group (t = − 29.713 , p ≤ 0.001). After the intervention, there was a significant difference in the learning initiative of the control group (t = − 3.368 , p ≤ 0.001). [ABSTRACT FROM AUTHOR]

Lots of resource-consuming intelligent tasks need to be handled in vehicular networks, and traditional resource allocation schemes are hard to meet the intelligent demands. Therefore, this paper proposes a task-oriented resource allocation scheme for intelligent tasks in vehicular networks. First, we propose a task-oriented communication system and formulate a resource allocation problem, which is aimed at maximizing the task performance. Second, based on the system model, an intelligent task-oriented resource allocation optimization criterion is proposed, which is formulated as a mathematical model, and its parameters are solved by the proposed gradient descent-based algorithm. Third, to solve resource allocation problem, a multiagent deep Q -network- (MADQN-) based algorithm is proposed, whose convergence and complexity are further analyzed. Last, experiments on real datasets verify the performance advantages of our proposed algorithms. [ABSTRACT FROM AUTHOR]

In order to solve the problem of resource ecological compensation, this paper proposed a model of resource ecological compensation mechanism based on a rural leisure sports environment. The model is carried out in many places in China. The survey data involves 31 provinces, 10 years, and 43 indicators, with a total of 43 × 10 × 31 = 13,330 data. The preliminary basis of mechanism construction is summarized from four aspects. Finally, make full use of modern information technology to improve the network platform of the compensation mechanism, promote the efficient allocation and comprehensive utilization of ecotourism resources, and lay a solid foundation for establishing a reasonable and perfect resource ecological compensation mechanism and ensuring the long-term and stable operation of the mechanism. Through the experiment, it is found that the timely and effective publication of information can eliminate the inner estrangement between the two sides, so as to make the behavior of both sides more rational. A special information feedback department is established to deal with the opinions put forward by all compensation parties in tourism development, extract effective information, summarize and publish reasonable guidance information, and guide the compensation of both sides to an ideal balance through the feedback of this information. The effectiveness of the experiment is verified. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of trombone timbre feature extraction, this paper combines the CNN model to construct a trombone timbre feature extraction model and summarizes the principle of trombone timbre signal. Moreover, this paper deduces the parameters of the trombone timbre signal and the corresponding network model and uses mathematical expressions to model the trombone timbre signal, which is convenient for theoretical analysis and processing of the trombone timbre signal. In addition, this paper provides a detailed discussion of time-frequency analysis techniques, including their advantages and limitations, which provide an algorithmic basis for working with trombone timbre signals. It can be seen that time-frequency analysis technology still has great advantages in trombone timbre signal processing. Finally, the simulation results show that the trombone timbre feature extraction method based on the CNN model proposed in this paper can effectively identify the trombone timbre in various musical performances. [ABSTRACT FROM AUTHOR]

The current WSN is vulnerable to a variety of malicious attacks, resulting in the decline of its comprehensive performance. Multihop routing involves a number of safety and privacy issues. Problems such as snooping, sinkhole, manipulation, cloning, wormhole, spoofing, and so on affect the integrity, availability, and confidentiality of the WSNs. Therefore, this paper mainly studies the mathematical modeling of WSN multiattack behavior discrimination based on the incidence matrix. The WSN node model is used to collect relevant data and mark and map the disguised data, so as to determine the characteristics of multiattack behavior and establish the WSN multiattack behavior discrimination model based on the incidence matrix. The experimental results show that the designed multiattack behavior discrimination model can distinguish the attack type according to the characteristics, has high recognition ability, can spend a short time to effectively distinguish the attack behavior, has a low false positive rate, and can effectively improve the antiattack ability of the WSN. [ABSTRACT FROM AUTHOR]

The present paper investigates the problem of capital portfolio selection under uncertain conditions and uses a robust optimization approach for modeling. The model provided in this paper is a three-objective model that aims to maximize returns, maximize liquidity, and minimize risk. The data extracted from the site of the Tehran Stock Exchange are as follows. These data are related to twenty shares from July 2020 to July 2021. The robust approach used in this research has been analyzed by the real data of the Tehran Stock Exchange and then the optimal portfolio for different robust costs has been formed by solving the robust model. In the following section, the relevant model is solved through real stock market data and using the goal programming approach, and the results are investigated and analyzed. [ABSTRACT FROM AUTHOR]