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The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making the train stranded in the interval between stations. This study aims to reduce the impact of interrupt events and improve service levels.

To address this issue, this paper considers the constraints of train operation safety, capacity and dynamic passenger flow demand. It proposes a method for adjusting small loops during interruption events and constructs a train operation adjustment model with the objective of minimizing the total passenger waiting time. This model enables the rapid development of train operation plans in interruption scenarios, coordinating train scheduling and line resources to minimize passenger travel time and mitigate the impact of interruptions. Regarding the proposed train operation adjustment model, an improved genetic algorithm (GA) is designed to solve it.

The model and algorithm are applied to a case study of interruption events on Beijing Subway Line 5. The results indicate that after solving the constructed model, the train departure intervals can be maintained between 1.5 min and 3 min. This ensures both the safety of train operations on the line and a good match with passengers’ travel demands, effectively reducing the total passenger waiting time and improving the service level of the urban rail transit system during interruptions. Compared to the GA algorithm, the algorithm proposed in this paper demonstrates faster convergence speed and better computational results.

This study explicitly outlines the adjustment method of using short-turn operation during operational interruptions, with train departure times and station stop times as decision variables. It takes into full consideration safety constraints on train operations, train capacity constraints and dynamic passenger demand. It has constructed a train schedule optimization model with the goal of minimizing the total waiting time for all passengers in the system.

This work aims to integrate the concepts generated by a systematic literature review on patient flows in emergency departments (ED) to serve as a basis for developing a generic process model for ED.

A systematic literature review was conducted using PRISMA guidelines, considering Lean Healthcare interventions describing ED patients’ flows. The initial search found 141 articles and 18 were included in the systematic analysis. The literature analysis served as the basis for developing a generic process model for ED.

ED processes have been represented using different notations, such as value stream mapping and workflows. The main alternatives for starting events are arrival by ambulance or walk-in. The Manchester Triage Scale (MTS) was the most common protocol referred to in the literature. The most common end events are admission to a hospital, transfer to other facilities or admission to an ambulatory care system. The literature analysis allowed the development of a generic process model for emergency departments. Nevertheless, considering that several factors influence the process of an emergency department, such as pathologies, infrastructure, available teams and local regulations, modelling alternatives and challenges in each step of the process should be analysed according to the local context.

A generic business process model was developed using BPMN that can be used by practitioners and researchers to reduce the effort in the initial stages of design or improvement projects. Moreover, it’s a first step toward the development of generalizable and replicable solutions for emergency departments.

Agricultural workers represent an important part of the population exposed to high heat-related health and productivity risks. This study aims to estimate the heat-related productivity loss (PL) for moderate work activities in sun and shady areas and evaluating the economic cost locally in an Italian farm and generally in the whole province of Florence. Benefits deriving by working in the shade or work-time shifting were provided. Comparisons between PL estimated in Mediterranean (Florence, Italy) and subtropical (Guangzhou, China) areas were also carried out.

Meteorological data were collected during summers 2017–2018 through a station installed in a farm in the province of Florence and by two World Meteorological Organization (WMO)‐certified meteorological stations located at the Florence and Guangzhou airports. These data were used to calculate the wet-bulb globe temperature and to estimate the hourly PL and the economic cost during the typical working time (from 8 a.m. to 5 p.m.) and by advancing of 1 h and 2 h the working time. Significant differences were calculated through nonparametric tests.

The hourly PL and the related economic cost significantly decreased (p < 0.05) by working in the shade and by work-time shifting. Higher PL values were observed in Guangzhou than in Florence. The decrease of PL observed by work-time shifting was greater in Florence than in Guangzhou.

Useful information to plan suitable heat-related prevention strategies to counteract the effects of heat in the workplace are provided. These findings are essential to quantify the beneficial effects due to the implementation of specific heat-related adaptation measures to counter the impending effects of climate change.

The purpose is using generative adversarial network (GAN) to solve the problem of sample augmentation in the case of imbalanced bearing fault data sets and improving residual network is used to improve the diagnostic accuracy of the bearing fault intelligent diagnosis model in the environment of high signal noise.

A bearing vibration data generation model based on conditional GAN (CGAN) framework is proposed. The method generates data based on the adversarial mechanism of GANs and uses a small number of real samples to generate data, thereby effectively expanding imbalanced data sets. Combined with the data augmentation method based on CGAN, a fault diagnosis model of rolling bearing under the condition of data imbalance based on CGAN and improved residual network with attention mechanism is proposed.

The method proposed in this paper is verified by the western reserve data set and the truck bearing test bench data set, proving that the CGAN-based data generation method can form a high-quality augmented data set, while the CGAN-based and improved residual with attention mechanism. The diagnostic model of the network has better diagnostic accuracy under low signal-to-noise ratio samples.

A bearing vibration data generation model based on CGAN framework is proposed. The method generates data based on the adversarial mechanism of GAN and uses a small number of real samples to generate data, thereby effectively expanding imbalanced data sets. Combined with the data augmentation method based on CGAN, a fault diagnosis model of rolling bearing under the condition of data imbalance based on CGAN and improved residual network with attention mechanism is proposed.

Managerial discourses tend to portray work-related mobility practices in a positive light, presenting mobility assignments as a place of stimulus and differentiation. A conception of mobility as an opportunity, may contrast, in specific economies and business settings, with lived personal experiences. This article reports the results of a three-year study, aimed to question how multinational companies (MNCs) located in a small and developing European economy (Portugal) are building talent pools for expatriate assignments. Interaction effects, as proposed by the job demands-resources (JD-R) theory, are considered as lens to understand the interplay of company expatriate policies, willingness profiles and psychological contracts of expatriates. By using a Portuguese sample, the study examines whether prior findings in mature economies and consolidated MNCs can be generalized to less developed international business settings.

A three-year study, encompassing 24 expatriate cases observed in five multinational firms born or located in Portugal. Two techniques of empirical data collection were used: statistical sources and documental analysis and in-depth interviews. A total of 37 interviews were conducted, both in-person and remotely, of which 13 were with company managers and representatives, and 24 with expatriates (as defined and referred like this by the companies under study).

Heterogeneous company policies, ranging from juvenile, functionalist to more dynamic and flow-based approaches, are presented as qualifying resources of willingness levels and psychological contracts of expatriates. Observed interaction effects between policies, willingness and psychological contracts, empirically mirrored in three profiles (conformist, protean and disrupted expatriates) suggest that incentive effects (emanating from company policies) and job demand-resource balance, factored as terms of social and economic trade, are non-linear and asymmetric, influencing firm propensity to succeed while using international work to support company expansion goals. As job resources, expatriate policies are presented as operating as pull or push factors: functionalist HR approaches seem to act as push factors generating more conformist or compelled willingness profiles.

Generalization of study's outcomes has limitations. Future studies are encouraged to use comparative and longitudinal research designs. Furthermore, future research should include business expatriates with entry-level positions, and increase the number of interviewees, as results can also be considered as limited by sample size.

It is suggested that further strategic work is needed to present expatriation development value, formally screen and consider willingness level as selection criteria, and enlarge the pool (from internal to external) of candidates, in peripheral economic settings such as Portugal. A shift to more dynamic and job resource-dense policies are suggested as beneficial, as pathway to optimize social and economic value from expatriation assignments and work experiences.

By putting the interplay between macro and micro-level processes into perspective, the study provides empirical evidence on how company expatriate policies have come to promote unforeseen differentiation of employee willingness and psychological contracts at the heart of MNCs. This is particularly relevant in developing economies such as Portugal, challenging the need to build talent pools for international work assignments. Empirical data illustrating company policies interactive effects with different willingness profiles and psychological contracts of expatriates is provided.

This paper aims to study the affecting factors on bird nesting on electronic railway catenary lines and the impact of bird nesting events on railway operation.

First, with one year’s bird nest events in the form of unstructured natural language collected from Shanghai Railway Bureau, the records were structured with the help of python software tool. Second, the method of root cause analysis (RCA) was used to identify all the possible influencing factors which are inclined to affect the probability of bird nesting. Third, the possible factors then were classified into two categories to meet subsequent analysis separately, category one was outside factors (i.e. geographic conditions related factors), the other was inside factors (i.e. railway related factors).

It was observed that factors of city population, geographic position affect nesting observably. Then it was demonstrated that both location and nesting on equipment part have no correlation with delay, while railway type had a significant but low correlation with delay.

This paper discloses the principle of impacts of nest events on railway operation.

This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price.

The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.

This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles.

Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.