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The managerial questions of this paper are as follows, and the authors are trying to solve them: How revenue sharing contract (CSR) degree and government subsidy affect the agri-food quality? What kind of model (WPC, revenue-sharing contract [RSC] and cooperative) would be more effective in motivating manufacturers and retailer to increase effort and improve agri-food quality? What kind of model (WPC, RSC and cooperative) would make manufacturer and retailer better off?

Considering the jointing quality effort and contract decision in green agri-food supply chain, this paper proposes six models that consider CSR of manufacturer and retailer, and then the obtained optimal solutions are compared and analyzed. At the same time, the impact of government subsidies is analyzed, and corresponding conclusions are drawn.

The results show that, first of all, whether the increasing CSR of the manufacturer or the retailer can motivate both parties to improve the agri-food quality effort investment. Second, the WPC and RSC contract may play different role in different cases. Finally, under the model with government subsidies, regarding positive influence of government subsidies on efforts of manufacturer and retailer, quality and profits of members is investigated. Based on these conclusions, this study puts forward the following policy suggestions. Firstly, governments should formulate reasonable subsidy policies to support manufacturer and retailer to improve the agri-food quality, thereby promoting green industries' development. Secondly, manufacturer and retailer should actively improve CSR and strengthen the effort of agri-food so as to advance quality. Finally, manufacturer and retailer can choose cooperative model or WPC contract.

In this paper, one manufacturer and one retailer are considered. Since the agri-food supply chain structure in reality is more complicated, the future research direction can consider the supply chain structure with one manufacturer and multiple retailers. In addition, this paper only considers the subsidy, and future research can classify the subsidy into different types.

The study makes two substantive contributions to the body of knowledge in the field of sustainable operations:(1) incorporating quality-based demand function in supply chain and dynamic process of agri-food quality; (2) exploring the impact of CSR awareness of members and subsidy of government on agri-food quality, and comparing the influence in different models.

This paper aims to present an unconditionally energy-stable scheme for approximating the convective heat transfer equation.

The scheme stems from the generalized positive auxiliary variable (gPAV) idea and exploits a special treatment for the convection term. The original convection term is replaced by its linear approximation plus a correction term, which is under the control of an auxiliary variable. The scheme entails the computation of two temperature fields within each time step, and the linear algebraic system resulting from the discretization involves a coefficient matrix that is updated periodically. This auxiliary variable is given by a well-defined explicit formula that guarantees the positivity of its computed value.

Compared with the semi-implicit scheme and the gPAV-based scheme without the treatment on the convection term, the current scheme can provide an expanded accuracy range and achieve more accurate simulations at large (or fairly large) time step sizes. Extensive numerical experiments have been presented to demonstrate the accuracy and stability performance of the scheme developed herein.

This study shows the unconditional discrete energy stability property of the current scheme, irrespective of the time step sizes.

The managerial questions of this paper are as follows: What are the equilibrium conditions of transfer price, quantity and profits when considering dynamic subsidies from the government? Which collection channel is better for a manufacturer, direct collection by itself or through an online platform?

This research investigates the three collection models: the manufacturer-driven model, the online platform-driven model and the competitive model. Based on the differential game, this research explores the transfer price, collection cost, subsidy and manufacturer and online platform profit in different models when considering the dynamic subsidy.

The results show that the collection strategy for the manufacturer depends on its collection cost. If the collection cost is lower, then the manufacturer may prefer to collect by itself. When the collection cost meets a certain range, the manufacturer may collect the used product through an online platform. The online platform-driven model is the most efficient because both the manufacturer and the online platform can make a higher profit.

This research bridges the gap between waste electrical and electronic equipment collection and government subsidies by demonstrating the dynamic condition of subsidies. It offers an approach to address the influence of dynamic subsidy, which can provide practical insights for the government implementing the subsidy policy.

The purpose of this study is to propose a mathematical optimization model to solve the yacht mooring area re-allocation problem (YMARP). The objective of the problem is to allow the maximum number of yachts to be moored at their ideal mooring areas.

In this paper, the YMARP is introduced, formally defined and discussed. The authors develop a 0-1 integer programing optimization model for the problem, which can be solved efficiently using off-shelf solvers. The performance of the model is tested on extensive numerical experiments.

The results of the numerical experiments demonstrate that the proposed model can solve the YMARP very efficiently using off-shelf solvers like CPLEX. In particular, problems with up to 30,000 yachts and 400 mooring areas can be solved to optimum within 30 s.

This study is one of the preliminary studies to consider problems arising in yacht management in a quantitative manner. The proposed model has three main merits. First, it enables the government to better manage yachts and mooring areas. Second, with more yacht owners assigned with ideal mooring areas, the model helps reduce the traveling time of the yacht owners to yacht mooring areas. Third, by reducing the traveling time of the yacht owners, the model contributes to lessening the traffic burden in cities.

Helical coil electromagnetic launchers (HEMLs) using motion-induced commutation strategy solve the problem of synchronization control perfectly. HEMLs can meet the requirements of multiple applications such as the electromagnetic catapult, electromagnetic mortar and high-velocity coilgun. The trade-off between the velocity and efficiency is an important basis for these different applications. To optimize such objectives before actual design, the purpose of this paper is to focus on the efficient and flexible calculation model and algorithm. A novel structure of HEML is proposed after the transient simulation by this algorithm, which can improve the energy conversion efficiency and suppress the muzzle arc without affecting the velocity too much.

The equivalent circuit model of the launcher is established and the governing equations are derived. A combination of the four-stage Runge–Kutta method and the trapezoidal quadrature formula are used to solve the governing equations.

With smaller number of turns in the coils of HEML, the velocity is larger and the efficiency is lower. The non-uniform HEML is an effective option to improve the energy conversion efficiency and to suppress the muzzle arc with almost the same muzzle velocity as the conventional HEML.

The paper presents a common model and a flexible fast numerical method which can be used in multi-objective optimization of HEMLs such as the genetic algorithm. A new structure of the non-uniform HEML is proposed to improve the energy conversion efficiency and to suppress the muzzle arc of the launcher.

The purpose of this paper is to study the landing performance of the Mars lander considering uncertain landing conditions under two landing modes.

A dynamics analysis model for the legged Mars lander is established for landing simulation, where the nonlinear large-deformation flexible buffer rods are equivalently modeled with a rigid-body mechanism with external forces and movement limit. Sensitivities of the landing stability to various landing conditions are analyzed using the Quasi–Monte-Carlo-based Sobol’ method and computer-aided landing simulations. Moreover, based on the results of sensitivity analysis, sensitive parameters are selected for estimating the safe boundaries for stability indices of rotation and clearance.

It can be concluded from this study that the lander has excellent ability against overturning. The shutdown-before-touchdown strategy helps to maintain than landing pose, and the shutdown-at-touchdown strategy helps to prevent the nozzle from colliding with the surface of Mars.

This study provides a theoretical reference to choose the better landing strategies for Mars landers considering uncertain landing conditions.

A parameterized dynamics Mars lander model and a simplification method are proposed to simulate the landing on Mars. Uncertain landing conditions are parameterized and considered in the dynamics model. Sensitivity analysis and safe boundary methods are used to compare the landing performances with two landing strategies.

This study aims to investigate how market orientation (MO) motivates firms to develop business model innovation and how such effects are moderated by strategic flexibility.

In this study, a questionnaire-based survey was undertaken to test the proposed hypotheses. The empirical study was conducted on a sample of 204 firms using two key informants (408 respondents) in China. The regression model is used to test the proposed model.

This research finds that both responsive market orientation (RMO) and proactive market orientation (PMO) have a positive effect on business model innovation. The effects of RMO and PMO on business model innovation are contingent on resource (coordination) flexibility in different ways. More importantly, this study finds that resource flexibility enhances the positive effect of RMO and weakens the positive effect of PMO. The study also finds that coordination flexibility enhances the positive effect of PMO.

Future research can explore the internal mechanisms through which RMO and PMO promote business model innovations. Although the study finds that both the MOs promote business model innovation, they may promote business model innovation through different mediating effects. Future research can explore the role of external dynamic capabilities. This research mainly focuses on the internal dynamic capability of focal firms. However, as a focal firm-centered boundary spanning activity system, to transform into a new business model, firms not only need to reconfigure internal resource base, but also need to realign external collaboration network.

This research also bears important managerial implications. First, firms should be aware of the positive effect of MO on business model innovation. Firms with higher level of RMO or PMO can promote business model innovation. Second, when firms implement RMO for business model innovation, managers should focus on resource flexibility. Where MO is responsive, marketing managers need to be concerned with ensuring various applications of existing resource so as to understand effectively the current customers and market domain. Third, to leverage PMO for business model innovation, firms should adopt coordination flexibility. For firms with higher level PMO, firms should try to find the new internal coordination process for customer latent needs.

The conclusion extends the business model innovation research from the view of dynamic capabilities. As one of types of dynamic capabilities, MO is also the important antecedent of business model innovation. Further, this research also discusses the role strategic flexibility plays in business model innovation.

In computational chemistry, the chemical bond energy (pKa) is essential, but most pKa-related data are submerged in scientific papers, with only a few data that have been extracted by domain experts manually. The loss of scientific data does not contribute to in-depth and innovative scientific data analysis. To address this problem, this study aims to utilize natural language processing methods to extract pKa-related scientific data in chemical papers.

Based on the previous Bert-CRF model combined with dictionaries and rules to resolve the problem of a large number of unknown words of professional vocabulary, in this paper, the authors proposed an end-to-end Bert-CRF model with inputting constructed domain wordpiece tokens using text mining methods. The authors use standard high-frequency string extraction techniques to construct domain wordpiece tokens for specific domains. And in the subsequent deep learning work, domain features are added to the input.

The experiments show that the end-to-end Bert-CRF model could have a relatively good result and can be easily transferred to other domains because it reduces the requirements for experts by using automatic high-frequency wordpiece tokens extraction techniques to construct the domain wordpiece tokenization rules and then input domain features to the Bert model.

By decomposing lots of unknown words with domain feature-based wordpiece tokens, the authors manage to resolve the problem of a large amount of professional vocabulary and achieve a relatively ideal extraction result compared to the baseline model. The end-to-end model explores low-cost migration for entity and relation extraction in professional fields, reducing the requirements for experts.

This paper aims to present a multi-scale stochastic damage model (SDM) for concrete and apply it to the stochastic response analysis of reinforced concrete shear wall structures.

The proposed SDM is constructed at two scales, i.e. the macro-scale and the micro-scale. The general framework of the SDM is established on the basis of the continuum damage mechanics (CDM) at the macro-scale, whereas the detailed damage evolution is determined through a parallel fiber buddle model at the micro-scale. The parallel buddle model is made up of micro-elements with stochastic fracture strains, and a one-dimensional random field is assumed for the fracture strain distribution. To represent the random field, a random functional method is adopted to quantify the stochastic damage evolution process with only two variables; thus, the numerical efficiency is greatly enhanced. Meanwhile, the probability density evolution method (PDEM) is introduced for the structural stochastic response analysis.

By combing the SDM and PDEM, the probabilistic analysis of a shear wall structure is performed. The mean value, standard deviation and the probability density function of the shear wall responses, e.g., shear capacity, accumulated energy consumption and damage evolution, are obtained.

It is noted that the proposed method can reflect the influences of randomness from material level to structural level, and is efficient for stochastic response determination of shear wall structures.