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This study aims to identify the prominent topics, the distribution and association characteristics of topics and the topic evolutionary trends of Documentary Heritage Preservation and Conservation (DHPAC) research in China.

Keywords of relevant papers in China National Knowledge Infrastructure (CNKI) were extracted as the data source in this study. First, frequency and co-occurrence of keywords of the selected papers were obtained by using SATI. Second, co-word network indicators were calculated with the Pajek software. Then, VOSviewer was applied to optimize the visualization of the sub-communities. Finally, a topics evolution map of this research field was implemented by CorTexT.

The research topics of DHPAC research in China were unbalanced but distinct. Topics of DHPAC research in China possessed inconspicuous orientation and consistency. The core topics had less influence on the overall network. A research system had formed with archival conservation and ancient books conservation as the core research directions. Research in this field had formed four continuous evolutionary paths about ancient books conservation, salvage conservation, archival conservation and archives conservation technology science with topics fusion and differentiation coexisting. Attentions on “ancient books conservation”, “paper relics conservation”, “electronic record”, “digitization”, “minority”, “documents in the republic of China” had increased during the past two decades and new hot topics of DHPAC research kept appearing in China.

This study synthesized and analyzed the research results of DHPAC research in China from a more comprehensive perspective and revealed the topic structure and longitudinal evolution process intuitively with co-word analysis and social network analysis, which can assist researchers to improve research systematization, discover new research directions and seek cooperative research path.

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure, energy-saving performance of the whole metro system cannot be guaranteed.

A cooperative train control framework is formulated to regulate a novel train operation mode. The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train. An improved brute force (BF) algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.

Case studies on the actual metro line in Guangzhou, China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters. The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.

Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process, which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation. This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea, where energy-efficient train operation can be realised once train running time is determined, thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

According to the real environment of China, the authors collect micro data about Chinese family firms (FFs) to explain why some Chinese FFs still tend to introduce external managers though they have to face governance conflict between family-based managers and external managers.

This study analyzes the effect of governance conflict between family-based managers and external managers on firm performance by using ordinary least square test, which is also used to test which factor has influence on governance conflict’s profit promotion effect.

This study finds that governance conflict significantly improves firm performance (profit promotion effect). The governance conflict caused by the introduction of external managers in Chinese FFs can significantly improve a firm’s performance by raising its management efficiency and capital investment.

The governance conflict of the family business needs to be further refined in following research. Besides, this study is only based on the empirical study of cross-section data.

Different from the existing related research is mainly based on the sample data of listed family enterprises, the China employer-employee matched survey data includes a large number of small and medium-sized FFs, and has obtained the actual situation of how many of the middle and senior managers are external not family members.

The purpose of this paper was to study the relationship between safe storage life and storage mode of hot-rolled sheet (Q235, X70) in humid environment, and a prediction model of safe storage life under different storage modes was established.

The corrosion behavior of hot-rolled sheets under different storage conditions was studied with immersion experiment and morphology observation.

The results show that pitting occurs on the hot-rolled sheets in humid environment, and the corrosion behavior is strongly related with the storage mode. When they are stored separately, the number and depth of pits first increase and then decrease as the Cl⁻ concentration rises, while for the stack storage, pit depth increases with increasing Cl⁻ concentration. The safe storage time of separate storage is longer than that of stack storage. Based on this, a model of chloride ion concentration and storage life was established.

A storage safe life model of hot-rolled sheet in humid environment is proposed.

The purpose of this paper is to elucidate the influences of the animal fat and fatty acid type on the formation of polycyclic aromatic hydrocarbons (PAHs) and to propose a formation mechanism of PAHs in fat during electric roasting, which is a method of non-direct-contact-flame heating.

The effects of animal fats and model fat on the formation of PAHs were valued on the basis of the ultra high-performance liquid chromatography data. The corresponding products of the FAME pyrolysis were detected by TG-FTIR. The proposal formation mechanism of PAHs was based on the summary of the literature.

Contrary to the International Agency for Research on Cancer, DF had higher risk with 280.53 ng/g of concentration after being roasted than the others animal fats of red meat in terms of PAHs formation. This research also ensured the importance of fat on PAHs formation, the concentration of PAHs in pure fats was higher after being electric roasted than that in meat patties and juice which made from corresponding animal fat. What is more, during pure animal fats and meat products being processed, less PAHs formed in the fat with lower extent of unsaturation and lower content of linolenate. In the same way, methyl linolenate demonstrated the significant increasement to PAHs formation compared to the other fatty acids. And, the number of carbon atom and the extent of unsaturation in fatty acid affects the formation of PAHs during roasting. The detection of alkene and alkane allows to propose a formation mechanism of PAHs during model fat being heated. Further study is required to elucidate the confirm moleculars during the formation of PAHs.

This work studied the effect of the carbon atom number and the unsaturation extent of fats and model fats on the formation of PAHs. This work also assure the important of alkene and alkane on the pyrolysis of model fats. This study also researched the formation and distribution of PAHs in pure fats and meat products after being heated.

To evacuate passengers arriving at intercity railway stations efficiently, metros and intercity railways usually share the same station or have stations close to each other. When intercity trains arrive intensively, a great number of passengers will burst into the metro station connecting with the intercity railway station within a short period, while the number of passengers will decrease substantially when intercity trains arrive sparsely. The metro timetables with regular headway currently adopted in real-world operations cannot handle the injected passenger demand properly. Timetable optimization of metro lines connecting with intercity railway stations is essential to improve service quality.

Based on arrival times of intercity trains and the entire process for passengers transferring from railway to metro, this paper develops a mathematical model to characterize the time-varying demand of passengers arriving at the platform of a metro station connecting with an intercity railway station. Provided the time-varying passenger demand and capacity of metro trains, a timetable model to optimize train departure time of a bi-direction metro line where an intermediate station connects with an intercity railway station is proposed. The objective is to minimize waiting time of passengers at the connecting station. The proposed timetable model is solved by an adaptive large neighborhood search algorithm.

Real-world case studies show that the prediction accuracy of the proposed model on passenger demand at the connecting station is higher than 90%, and the timetable model can reduce waiting time of passengers at the connecting station by 28.47% which is increased by 5% approximately than the calculation results of the generic algorithm.

This paper puts forward a model to predict the number of passengers arriving at the platform of connection stations via analyzing the entire process for passengers transferring from intercity trains to metros. Also, a timetable optimization model aiming at minimizing passenger waiting time of a metro line where an intermediate station is connected to an intercity railway station is proposed.

To determine the optimal software warranty period in continuous and discrete circumstances where the difference between the software testing environment and the operational environment can be characterised by an environment factor.

Software reliability models based on continuous and discrete time non‐homogeneous Poisson processes are assumed to describe the failure occurrence phenomena under both environments. Based on the idea of accelerated life testing for hardware products, the operational profile of the software is modeled, and the total expected software cost incurred in both testing and operational phases is formulated.

Under a milder condition, the optimal warranty period which minimizes the total software cost is derived analytically.

This paper introduces the operational profile of software to model the difference between the testing environment and the operational environment.

Identifies some of the problems occurring in the Guangzhou compulsory education programme and suggests suitable solutions. Reports on a situation analysis to determine how the education system works in practice. Describes policies, personnel and other resources contributing to the system, including contingencies related to the Chinese context. Suggests that evaluation concepts and practices can make a positive contribution to the Guangzhou compulsory education programme.