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An accurate prediction of the deformation of retaining structures is critical for ensuring the stability and safety of braced deep excavations, while the high nonlinear and complex nature of the deformation makes the prediction challenging. This paper proposes an explainable boosted combining global and local feature multivariate regression (EB-GLFMR) model with high accuracy, robustness and interpretability to predict the deformation of retaining structures during braced deep excavations.

During the model development, the time series of deformation data is decomposed using a locally weighted scatterplot smoothing technique into trend and residual terms. The trend terms are analyzed through multiple adaptive spline regressions. The residual terms are reconstructed in phase space to extract both global and local features, which are then fed into a gradient-boosting model for prediction.

The proposed model outperforms other established approaches in terms of accuracy and robustness, as demonstrated through analyzing two cases of braced deep excavations.

The model is designed for the prediction of the deformation of deep excavations with stepped, chaotic and fluctuating features. Further research needs to be conducted to expand the model applicability to other time series deformation data.

The model provides an efficient, robust and transparent approach to predict deformation during braced deep excavations. It serves as an effective decision support tool for engineers to ensure the stability and safety of deep excavations.

The model captures the global and local features of time series deformation of retaining structures and provides explicit expressions and feature importance for deformation trends and residuals, making it an efficient and transparent approach for deformation prediction.

The purpose of this paper is to present a novel swarm intelligence optimizer — pigeon-inspired optimization (PIO) — and describe how this algorithm was applied to solve air robot path planning problems.

The formulation of threat resources and objective function in air robot path planning is given. The mathematical model and detailed implementation process of PIO is presented. Comparative experiments with standard differential evolution (DE) algorithm are also conducted.

The feasibility, effectiveness and robustness of the proposed PIO algorithm are shown by a series of comparative experiments with standard DE algorithm. The computational results also show that the proposed PIO algorithm can effectively improve the convergence speed, and the superiority of global search is also verified in various cases.

In this paper, the authors first presented a PIO algorithm. In this newly presented algorithm, map and compass operator model is presented based on magnetic field and sun, while landmark operator model is designed based on landmarks. The authors also applied this newly proposed PIO algorithm for solving air robot path planning problems.

WeChat official account (WCOA) is an emerging and important platform for academic library services, which greatly accelerates the development of this field. This article aims to identify key evaluation indicators for users' satisfaction of the Academic Library WeChat Official Account (ALWCOA) as a reference for future improvements.

Based on the updated DeLone and McLean (D&M)’s model and Delphi method, an evaluation system of ALWCOA satisfaction was constructed. Then 212 university students were recruited to fill out a questionnaire on evaluation indicators. The grey relational analysis (GRA) and Pareto's principle were employed to analyze the questionnaire and select key evaluation indicators.

An ALWCOA service satisfaction evaluation system with three evaluation dimensions and 15 evaluation indicators was constructed, and three key evaluation indicators were identified, including service responsiveness, information timeliness and system security.

This article provides a strategy for assessing ALWCOA service satisfaction, as well as insights for improving of ALWCOA service. Specifically, academic libraries should pay more attention to improving service responsiveness, information timeliness and system security.

This article innovatively applied the updated D&M model in academic library service. Additionally, it facilitates the development of research fields, such as academic library services, microservices and user service evaluation, and provides a case study to better understand the WCOA.

A significant number of Chinese companies are listed overseas. The authors aim to examine whether overseas locations affect their financing decision, specifically their capital structure choice.

Most of the Chinese overseas listed companies are listed in the USA and Hong Kong. As the institutional quality of the USA is better than Hong Kong, the authors, therefore, choose to build the hypotheses from the “law and finance” literature. Specifically, the authors argue that the better institutional environment of the USA can mitigate the information asymmetry problem and the agency problem of financing via equity. Consequently, firms listed in the USA will rely more on equity and have lower leverage ratio. The difference in leverage ratio of US listed and Hong Kong listed companies should be larger when the marginal benefit of better information environment is larger.

Referring to various data sources, the authors construct a comprehensive list of overseas listed companies in the USA and Hong Kong. The authors collect the accounting and stock performance information from Datastream/Worldscope and the equity offering data from Global New Issue database. The empirical findings provide strong support of the hypotheses: the leverage is 15 percent lower for US listed companies than the Hong Kong listed companies; the results are stronger when the firms face more severe information asymmetry problem; the stock price reacts less negatively for seasoned equity offering in the USA than in Hong Kong.

Most of the Chinese companies decided to be listed overseas because they cannot be listed in the Mainland Chinese stock exchanges. One of the most important motivation is to access to external capital to support firm growth. As the main channel of external financing in the overseas markets is equity since debt is still mainly domestically based, one implication of this paper is that Chinese companies can gain better access to external capital in the USA than in Hong Kong and relax their financial constraint.

There are a considerable number of Chinese companies listed in the overseas markets. Many successful and famous companies are among them. However, almost no research has been done based on them. This paper documents some very important phenomenon of this market. The authors wish that more studies will be conducted. In addition, the study also complements the existing studies on how institutional environment affects corporate financial behavior.

Taking a 2,000 r/min 10 kW permanent magnet motor as an example, the purpose of this paper is to study the influence of driving modes on the performance of permanent magnet motor at limit conditions, and researched the variation mechanism of motor performance influenced by different driving modes.

A two-dimensional electromagnetic field model of the permanent magnet motor was established, and a rectangular-wave driving circuit was built. By using the finite element method, the electromagnetic field, current, harmonic content and eddy current loss were calculated when the motor operated at rated load and limit load. On the basis of the motor loss calculation, the temperature field of the motor operating at rated condition and limit condition was researched, and the factors that influence motor limit overload capacity were analyzed. By analyzing the motor loss variation at different load conditions, the change mechanism of the motor temperature field was determined further. Combined with the related experiments, the correctness of the above analysis was verified.

Permanent magnet synchronous motor (PMSM) driven by sine wave is better compared with brushless direct current motor (BLDCM) driven by rectangular wave in reducing the magnetic field harmonics, motor losses and optimizing the temperature distribution in the motor. The method driven by sine wave could improve the motor output performance including the motor efficiency and the motor overload capacity. The winding temperature is the most important factor that limits the output capability of PMSM operating for a long time. However, because of the large rotor eddy current losses, the permanent magnet temperature is the most important factor that limits the output capability of BLDCM operating for a long time.

The influence of driving modes on the motor magnetic field, losses and temperature distribution, efficiency and overload capacity was determined, and the influence mechanism was also analyzed. Combined with the analysis of the electromagnetic and temperature fields, the advantages of different driving modes were presented. This study could provide an important basis for the design of permanent magnet motors with different driving modes, and it also provides reference for the application of permanent magnet motor.

This paper presents the influence of driving modes on permanent magnet motors. The limit output capacity of the motor with different driving modes was studied, and the key factors limiting the motor output capability were obtained.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.