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Spherical robot plays an essential role in the field of mobile robot because of its unique shape and omni-directional mobility, especially in the application of planet detection. Although spherical robot has many advantages over leg robot, its obstacle climbing performance is still not satisfactory, that is exactly the motivation of this paper. The purpose of this paper is to propose a high-performance hopping mechanism for spherical robot, which can adapt to different terrain and effectively cross obstacles.

The hopping system uses torque spring as part of the energy storage mechanism, and converts the kinetic energy of rotation into elastic potential energy with a particularly designed turntable. Moreover, the track of the turntable, based on the Archimedes spiral principle, has the attributes of equidistance and equivelocity that enable better stability of energy storage process.

Experiments show that the proposed hopping mechanism can make a 250 g spherical robot jump up to 58 cm with the take-off angle of 60°. Finally, the influence of friction and take-off angle on the hopping height and distance of the robot is also analyzed, which provides a prior guidance for optimizing its jumping process.

This paper shows how to easily design a lightweight, compact and embedded spring hopping structure so that a spherical hopping robot with detection ability can be developed.

This paper investigates the dual interactive effects of manufacturer encroachment on the supply chain and retailer provision of retail services.

Consider a supply chain dominated by manufacturers, retailers, and e-commerce platforms, with the manufacturers selling the same product online and offline. Utilizing Stackelberg’s game theory, examples of wholesale and retail prices and profits of participants in the supply chain under different channels are analyzed. An effective encroachment strategy for manufacturers facing different retail service investment strategies of traditional retailers is given.

When traditional retailers do not invest in retail services, they will lose more profit due to competition with the manufacturer. At this time, the retailer does not want the manufacturer to encroach. The traditional retailer’s investment in retail services will enhance its and the manufacturer’s profits, incentivizing the manufacturer to pursue an aggressive expansion strategy.

(1) Considers a situation where the selling efficiency of the manufacturer is lower than that of the traditional retailer. (2) The interaction between traditional retailers’ retail service investment strategies and manufacturers’ encroachment strategies is investigated where the manufacturer is the dominant player. The three modes of online direct sales, resale, and third-party platform agency are compared to provide a basis for decision-making on different types of manufacturers’ encroachment. (3) Offline retail services not only directly increase sales in the offline market but also indirectly have a negative effect on the online market.

The purpose of this study is to restore the spatial distribution of overseas remittance businesses in Shantou during the 1940s. It explores various socioeconomic factors that influenced the concentration of local remittance business investment in real estate. By reconstructing the spatial distribution of remittance business activities in Shantou, this study hopes to lay a foundation for further analysis of the business strategies of Chaoshan merchants.

This research draws on information from the published Swatow Guide, archival sources and cadastral maps to identify the location of remittance enterprises and the native place and overseas networks of property owners.

This study reveals that the spatial distribution of the remittance enterprises was determined by the native place origins of local property owners, and that the inflow of overseas Chinese capital contributed to real estate development in Shantou.

Despite the limited access to Chinese official archives, this paper manages to identify several building blocks and neighbors in Shantou for spatial analysis.

This study is the first attempt to use the geographical information system (GIS) method in Chinese urban history research and hopes to establish a larger historical database of Shantou as a sample for comparison.

This investigation advances the spatial study of urban history and overseas Chinese remittances in the maritime society of South China.

Cobalt is an extremely useful element, but there are very few separate cobalt deposits in China and imported cobalt ores are usually toxic. In order to develop more low-toxicity cobalt resources, China has to encourage exploration and development of this element. Samples are taken from Hanxing iron ore tailings and analyzed by ICP-MS and barium chloride titration experiments. The results indicate that the cobalt content is relatively high in Hanxing iron ore tailings, and some exceed the industrial grade. Therefore, with the depletion of cobalt resources, iron ore tailings are bound to become an important resource in China, and as these tailings are abundant in the Hanxing area, this area is expected to be of high development value.

The performance of the classical car-following system is easily affected by external disturbances. To enhance the performance of the classical car-following model under sudden external disturbances, a novel car-following model is established to smooth traffic flow.

This paper proposed a Proportion Integration Differentiation (PID) control strategy based on classical control theory and developed a novel car-following model. The linear system theory and Laplace transform are used to derive a closed-loop transfer function. Then, the stability condition is obtained by using the Routh stability criterion and the small gain theorem. Finally, the validity and feasibility of the PID control strategy is proved by numerical simulations.

The analytic results and the numerical simulation results show that both the integration part and the differential part have the positive effect to suppress traffic oscillation efficiently; the collaboration of these two parts has more power to improve the stability of traffic flow. It means that the proposed model integrated with the PID control strategy has the ability of anti-interference and smooth traffic compared with the classical car-following model.

This paper introduces the PID control strategy into the classical car-following system, which enhances the stability of the system and also provides an efficient method for optimizing the traffic flow system.

The current studies on remaining useful life (RUL) prediction mainly rely on convolutional neural networks (CNNs) and long short-term memories (LSTMs) and do not take full advantage of the attention mechanism, resulting in lack of prediction accuracy. To further improve the performance of the above models, this study aims to propose a novel end-to-end RUL prediction framework, called convolutional recurrent attention network (CRAN) to achieve high accuracy.

The proposed CRAN is a CNN-LSTM-based model that effectively combines the powerful feature extraction ability of CNN and sequential processing capability of LSTM. The channel attention mechanism, spatial attention mechanism and LSTM attention mechanism are incorporated in CRAN, assigning different attention coefficients to CNN and LSTM. First, features of the bearing vibration data are extracted from both time and frequency domain. Next, the training and testing set are constructed. Then, the CRAN is trained offline using the training set. Finally, online RUL estimation is performed by applying data from the testing set to the trained CRAN.

CNN-LSTM-based models have higher RUL prediction accuracy than CNN-based and LSTM-based models. Using a combination of max pooling and average pooling can reduce the loss of feature information, and in addition, the structure of the serial attention mechanism is superior to the parallel attention structure. Comparing the proposed CRAN with six different state-of-the-art methods, for the predicted results of two testing bearings, the proposed CRAN has an average reduction in the root mean square error of 57.07/80.25%, an average reduction in the mean absolute error of 62.27/85.87% and an average improvement in score of 12.65/6.57%.

This article provides a novel end-to-end rolling bearing RUL prediction framework, which can provide a reference for the formulation of bearing maintenance programs in the industry.

The proposed model aims to tackle the data quality issues in multivariate time series caused by missing values. It preserves data set integrity by accurately imputing missing data, ensuring reliable analysis outcomes.

The Conv-DMSA model employs a combination of self-attention mechanisms and convolutional networks to handle the complexities of multivariate time series data. The convolutional network is adept at learning features across uneven time intervals through an imputation feature map, while the Diagonal Mask Self-Attention (DMSA) block is specifically designed to capture time dependencies and feature correlations. This dual approach allows the model to effectively address the temporal imbalance, feature correlation and time dependency challenges that are often overlooked in traditional imputation models.

Extensive experiments conducted on two public data sets and a real project data set have demonstrated the adaptability and effectiveness of the Conv-DMSA model for imputing missing data. The model outperforms baseline methods by significantly reducing the Root Mean Square Error (RMSE) metric, showcasing its superior performance. Specifically, Conv-DMSA has been found to reduce RMSE by 37.2% to 63.87% compared to other models, indicating its enhanced accuracy and efficiency in handling missing data in multivariate time series.

The Conv-DMSA model introduces a unique combination of convolutional networks and self-attention mechanisms to the field of missing data imputation. Its innovative use of a diagonal mask within the self-attention block allows for a more nuanced understanding of the data’s temporal and relational aspects. This novel approach not only addresses the existing shortcomings of conventional imputation methods but also sets a new standard for handling missing data in complex, multivariate time series data sets. The model’s superior performance and its capacity to adapt to varying levels of missing data make it a significant contribution to the field.

This investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.

In this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

The provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.

In this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.

Does the choice of listing process matter in determining a firm's future crash risk? It is understood that the main function of an equity market is to provide price discovery, however, it is not clear whether the choice of listing methods would matter to the shareholders' wealth in the long term. We are the first to answer this question by utilising a hand-collected dataset that identifies all companies that went public via reverse merger (RM) in a growing emerging market.

Using hand-collected data from 2000 to 2018 in China, we follow the literature to construct two crash risk measures for RM and IPO firms. Our main analysis is performed using OLS regressions on the full sample as well as a sample using Propensity Score Matching. Our results hold with a number of robustness checks.

We find that reverse merger (RM) firms exhibit higher future stock price crash risk than initial public offering (IPO) firms. This relationship is more predominant in non-state-owned enterprises, and we find weak evidence suggesting such relationship weakens as firms stay longer in the market. There is no significant difference in future stock price crash risk between RM firms listed during IPO suspension periods and normal IPO firms.

We are the first to study the choice of listing method and its impact on firms' future stock price crash risk.

This study aims to uncover the mechanisms behind the marginalization of county-level public libraries.

The research surveyed 25 counties in central China, including Hubei, Chongqing, Hunan, and Guizhou provinces. Semi-structured interviews were conducted with library directors and deputy directors, focusing on main and branch library construction, cultural inclusivity, library assessment, and digital services.

Contributing factors to library marginalization were identified as economic pressure, institutional domain, longstanding issues, organizational entity, and societal misconceptions. Building on this, the study introduces the HBAC model to explain county-level public library marginalization. Considering the actual social context of these libraries, the article proposes a “3 + 1” approach to mitigate their marginalization.

The research methodology, analysis process, theoretical model, and recommendations provided could shed light on academic research and practical exploration in the field of public libraries globally.