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The purpose of this study is to assess the spatiotemporal patterns of future meteorological drought in the Yellow River Basin under different representative concentration pathway (RCP) scenarios.

Delta method is used to process the future climate data of the global climate models, then analyzed the spatiotemporal variation trend of drought in the Yellow River Basin based on standardized precipitation evaporation index (SPEI) under four RCP scenarios.

This research was funded by the National Natural Science Foundation of China (41901239), Soft Science Research Project of Henan Province (212400410077, 192400410085), the National Key Research and Development Program of China (2016YFA0602703), China Postdoctoral Science Foundation (2018M640670) and the special fund of top talents in Henan Agricultural University (30501031).

This study can provide support for future meteorological drought management and prevention in the Yellow River Basin and provide a theoretical basis for water resources management.

Understanding China's carbon dioxide (CO2) emission status is crucial for getting Carbon Neutrality status. The purpose of the paper is to calculate two possible scenarios for CO2 emission distribution and calculated input-output flows of CO2 emissions for every 31 China provinces for 2012, 2015 and 2017 years.

In this study using the input and output (IO) table's data for the selected years, the authors found the volume of CO2 emissions per one Yuan of revenue for the industry in 2012 and the coefficient of emission reduction compared to 2012.

Results show that in the industries with a huge volume of CO2 emissions, such as “Mining and washing of coal”, the authors cannot observe the reduction processes for years. Industries where emissions are being reduced are “Processing of petroleum, coking, nuclear fuel”, “Production and distribution of electric power and heat power”, “Agriculture, Forestry, Animal Husbandry and Fishery”. For the “construction” industry the situation with emissions did not change.

“Transport, storage, and postal services” and “Smelting and processing of metals” industries in China has the second place concerning emissions, but over the past period, emissions have been sufficiently reduced. “Construction” industry produces a lot of emissions, but this industry does not carry products characterized by large emissions from other industries. Authors can observe that Jiangsu produces a lot of CO2 emissions, but they do not take products characterized by significant emissions from other provinces. Shandong produces a lot of emissions and consumes many of products characterized by large emissions from other provinces. However, Shandong showed a reduction in CO2 emissions from 2012 to 2017.

In time and accurate detection of cancer can save the life of the person affected. According to the World Health Organization (WHO), breast cancer occupies the most frequent incidence among all the cancers whereas breast cancer takes fifth place in the case of mortality numbers. Out of many image processing techniques, certain works have focused on convolutional neural networks (CNNs) for processing these images. However, deep learning models are to be explored well.

In this work, multivariate statistics-based kernel principal component analysis (KPCA) is used for essential features. KPCA is simultaneously helpful for denoising the data. These features are processed through a heterogeneous ensemble model that consists of three base models. The base models comprise recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU). The outcomes of these base learners are fed to fuzzy adaptive resonance theory mapping (ARTMAP) model for decision making as the nodes are added to the F_2ˆa layer if the winning criteria are fulfilled that makes the ARTMAP model more robust.

The proposed model is verified using breast histopathology image dataset publicly available at Kaggle. The model provides 99.36% training accuracy and 98.72% validation accuracy. The proposed model utilizes data processing in all aspects, i.e. image denoising to reduce the data redundancy, training by ensemble learning to provide higher results than that of single models. The final classification by a fuzzy ARTMAP model that controls the number of nodes depending upon the performance makes robust accurate classification.

Research in the field of medical applications is an ongoing method. More advanced algorithms are being developed for better classification. Still, the scope is there to design the models in terms of better performance, practicability and cost efficiency in the future. Also, the ensemble models may be chosen with different combinations and characteristics. Only signal instead of images may be verified for this proposed model. Experimental analysis shows the improved performance of the proposed model. This method needs to be verified using practical models. Also, the practical implementation will be carried out for its real-time performance and cost efficiency.

The proposed model is utilized for denoising and to reduce the data redundancy so that the feature selection is done using KPCA. Training and classification are performed using heterogeneous ensemble model designed using RNN, LSTM and GRU as base classifiers to provide higher results than that of single models. Use of adaptive fuzzy mapping model makes the final classification accurate. The effectiveness of combining these methods to a single model is analyzed in this work.

This paper aims to present a detailed mechanical design of a seven-degrees-of-freedom mobile parallel robot for the tungsten inert gas (TIG) welding and machining processes in fusion reactor. Detailed mechanical design of the robot is presented and both the kinematic and dynamic behaviors are studied.

First, the model of the mobile parallel robot was created in computer-aided design (CAD) software, then the simulation and optimization of the robot were completed to meet the design requirements. Then the robot was manufactured and assembled. Finally, the machining and tungsten inert gas (TIG) welding tests were performed for validation.

Currently, the implementation of the robot system has been successfully carried out in the laboratory. The excellent performance has indicated that the robot’s mechanical and software designs are suitable for the given tasks. The quality and accuracy of welding and machining has reached the requirements.

This mobile parallel industrial robot is particularly used in fusion reactor. Furthermore, the structure of the mobile parallel robot can be optimized for different applications.

This paper introduces a new mathematical model for analyzing the economic benefits of incorporating the fourth party logistics (4PL), which is a contractor (i.e. agent) for the supply chain coordination and construction based on the division of community and the outsourcing development. Based on the physical theory and the wave-particle duality, a supply chain is the special organization whose characteristic has wave-particle duality. The mathematical model enriches the connotation of 4PL and it broadens the thought for 4PL development. Secondly, the proposed mathematical model predicated on transaction costs, is supported by Transaction Cost Theory (TCT) and acts as the theoretical analysis tool of 4PL for coordinating 3-party generic supply chain. Through the model, some trendy conclusions can be drawn to provide theoretical support for 4PL’s practices. Finally, a case illustrates our conclusions.

The purpose of this paper is to establish criteria for evaluating strategic partners in a network of logistics service providers (LSPs) to show how analytical network process (ANP) can be used to identify the weights of these criteria on a case-specific basis, and to investigate whether the ANP model can be used as a starting point to evaluate strategic partners for other LSP networks.

Based on a literature review of vertical cooperation, the authors develop an overview of criteria for the evaluation of partners in a network of LSPs. The authors then apply ANP at LSP1 to validate the criteria, identify weights for these criteria and to validate model outcomes. Furthermore, the authors investigate whether the ANP model developed for LSP1 can be applied to another LSP with similar characteristics (LSP2). In-depth interviews are used to draw conclusions on the modeling approach and the model outcomes.

The research shows that evaluation criteria for partners in vertical partnerships between shippers and LSPs are applicable to LSP partners in horizontal partnership networks. The ANP model with criteria weights provides a good starting point for LSPs to customize the evaluation framework according to their specific needs or operating environments.

Limited research is available on evaluating LSP partners in horizontal partnerships. To the best of the authors’ knowledge, this paper is the first to bring forward horizontal LSP partner evaluation criteria to develop an ANP model for LSP partner evaluation and to apply this to two cases, and to provide a starting point for evaluating partners in similar horizontal LSP networks.

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).

The recent promotion of prefabricated housing (PH) in China has resulted in a prosperous period for its implementation. However, transaction costs (TCs) cause low economic efficiency to stakeholders and hinder the further promotion of PH. No relevant study has yet been made to investigate the TCs and their causes in the PH field. This paper identifies critical TCs and explores the influencing factors from the developers' perspective.

Semi-structured interviews and a questionnaire survey were used to collect data about TCs and influencing factors. The most influential factors are identified with their impacts on particular TCs, yielded from correlation analysis and logistic regression.

From the developers' perspective in China's PH market, this study identified that the most concerning sources of TCs are: hidden costs arising from disputes, extra workloads from design changes, learning costs, intensive communication and coordination in assembly and unexpected information costs in decision-making. The use of an ordered logistic regression approach indicates that the four most influential factors are: qualification of the general contractor, mandatory local policies, owner type and competitiveness of the developer.

To reduce the TCs, experiencing learning and ensuring the design scheme's complicity are recommended to save information searching and exchanging costs. The implications for the PH developers are for them to: (1) professionalize their own organization and (2) procure high-qualified general contractors. For the policymakers, this means they should improve the clarity of the mandatory local policies for PH step-by-step.

By applying the TCs economic theory, this study explores factors that influence TCs in the PH industry. It sheds light on the influencing mechanism behind the TCs in the context of prefabricated housing.

Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.

An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.

The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.

Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.

This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.

The purpose of this study is to sort out the potential dark sides of shared leadership so as to promote a more comprehensive and balanced views of the impact of shared leadership and provide directions for future research.

Through extensive database and manual searches, 766 literature records were obtained. After three rounds of literature screening, 17 studies were retained. On this basis, the 17 studies were coded and analyzed.

From the perspectives of individual motivation, hierarchical functionalism and leadership role configuration, the existing studies have explored the negative impacts of shared leadership on team members, formal team leaders and the overall work teams. Specifically, for team members, shared leadership may cause negative consequences like power struggle, role stress and knowledge hiding. For formal team leaders, shared leadership may cause negative consequences like psychological territorial loss, leadership motivation declines and the dualistic paradox of self and group. For the overall work teams, shared leadership may cause negative consequences like team performance inhibition, low decision-making efficiency, team responsibility dispersion and team creativity decline. Meanwhile, contextual factors play a key role in determining the effects of shared leadership.

Through a systematic review of the negative impact of shared leadership, this study responds to the research calls for exploring the dark sides of shared leadership, provides the academic community with a more comprehensive and balanced view of the impact of shared leadership and identifies several directions for future research.