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The purpose of this paper is to evaluate the effectiveness of negotiation training delivered to senior clinicians, managers and executives, by exploring whether staff members implemented negotiation skills in their workplace following the training, and if so, how and when.

This is a qualitative study involving face-to-face interviews with 18 senior clinicians, managers and executives who completed a two-day intensive negotiation skills training course. Interviews were transcribed verbatim, and inductive interpretive analysis techniques were used to identify common themes. Research setting was a large tertiary care hospital and health service in regional Australia.

Participants generally reported positive affective and utility reactions to the training, and attempted to implement at least some of the skills in the workplace. The main enabler was provision of a Negotiation Toolkit to assist in preparing and conducting negotiations. The main barrier was lack of time to reflect on the principles and prepare for upcoming negotiations. Participants reported that ongoing skill development and retention were not adequately addressed; suggestions for improving sustainability included provision of refresher training and mentoring.

Limitations include self-reported data, and interview questions positively elicited examples of training translation.

The training was well matched to participant needs, with negotiation a common and daily activity for most healthcare professionals. Implementation of the skills showed potential for improving collaboration and problem solving in the workplace. Practical examples of how the skills were used in the workplace are provided.

To the authors’ knowledge, this is the first international study aimed at evaluating the effectiveness of an integrative bargaining negotiation training program targeting executives, senior clinicians and management staff in a large healthcare organization.

This paper aims to study the temporal and spatial variation of vegetation and the influence of climate change on vegetation coverage in the Yellow River basin, China. The current study aimed to evaluate the role of a series of government-led environmental control projects in restoring the ecological environment of the Yellow River basin.

This paper uses unary linear regression, Mann–Kendall and wavelet analyses to study the spatial–temporal variations of vegetation and the response to climate changes in the Yellow River, China.

The results showed that for the past 17 years, not only the mean annual increase rate of the Normalized Difference Vegetation Index (NDVI) was 0.0059/a, but the spatial heterogeneity also yields significant results. The vegetation growth in the southeastern region was significantly better than that in the northwestern region. The variation period of the NDVI in the study area significantly shortened, and the most obvious oscillation period was half a year, with two peaks in one year. In addition, there are positive and negative effects of human activities on the change of vegetation cover of the Loess Plateau. The project of transforming cultivated land to forest and grassland promotes the increase of vegetation cover of the Loess plateau. Unfortunately, the regional urbanization and industrialization proliferated, and the overloading of grazing, deforestation, over-reclamation, and the exploitation and development of the energy area in the grassland region led to the reduction of the NDVI. Fortunately, the positive effects outweigh the negative ones.

This paper provides a comprehensive insight to analysis of the vegetation change and the responses of vegetation to climate change, with special reference to make the planning policy of ecological restoration. This paper argues that ecological restoration should be strengthened in areas with annual precipitation less than 450 mm.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.

This paper studies the political economy of the endogenous urban–rural divide in two dimensions: labor market and provision of public goods.

This paper gives a dual-sector model endogenously depending on the consumption of public goods (club goods), the number of rural–urban migrants and the tax rate (transfer payments).

According to the research findings in this paper, the constraints on the participation of rural residents portray the rural residents' bargaining power, and in the game between the urban elites and the rural residents, tax rates depend on the preferences of the urban elites and the constraints urban elites and the rural residents jointly face. Therefore, the urban elites have to set tax rates deviating from the most preferred ones. The model in this paper can explain a series of empirical findings and yield new theoretical findings for empirical testing.

Significantly, the paper finds that the increase in agricultural productivity will lead to industrialization, accompanied by the disintegration of the dual-sector model. However, though the increase in industrial productivity can accelerate industrialization, it will further expand the urban–rural divide.