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This paper aims to propose a novel system design and control algorithm of lower limb exoskeleton, which provides walking assistance and load sharing for the wearer.

In this paper, the valve-controlled asymmetrical hydraulic cylinder is selected for driving the hip and knee joint of exoskeleton. Pressure shoe is developed that purpose on detecting changes in plantar force, and a fuzzy recognition algorithm using plantar pressure is proposed. Dynamic model of the exoskeleton is established, and the sliding mode control is developed to implement the position tracking of exoskeleton. A series of prototype experiments including benchtop test, full assistance, partial assistance and loaded walking experiments are set up to verify the tracking performance and power-assisted effect of the proposed exoskeleton.

The control performance of PID control and sliding mode control are compared. The experimental data shows the tracking trajectories and tracking errors of sliding mode control and demonstrate its good robustness to nonlinearities. sEMG of the gastrocnemius muscle tends to be significantly weakened during assisted walking.

In this paper, a structure that the knee joint and hip joint driven by the valve-controlled asymmetrical cylinder is used to provide walking assistance for the wearer. The sliding mode control is proposed to deal with the nonlinearities during joint rotation and fluids. It shows great robustness and frequency adaptability through experiments under different motion frequencies and assistance modes. The design and control method of exoskeleton is a good attempt, which takes positive impacts on the productivity or quality of the life of wearers.

The restoration and strengthening of QT600 is an industry bottleneck challenge. The Co-12 cladding layer has great wear and corrosion resistance. The purpose of this paper is to quantitatively reveal the transient evolution law of the corrosion process of Co-12 cladding layer on QT600 surface.

In this paper, a three-dimensional numerical model of the corrosion process of Co-12 cladding layer by QT600 laser cladding is established. The interaction between pitting pits and corrosion medium is considered to reveal the transient evolution of ion concentration, electrode potential, pH and corrosion rate at different locations.

The calculation shows that the ion concentration in pitting pit changes Cl⁻>Co²⁺>Na⁺, pH value decreases from top to bottom and corrosion rate at bottom is greater than that at top. The electrochemical corrosion test of Co-12 cladding layer was carried out. It is shown that the current density of QT600 increases by an order of magnitude compared to the Co-12 cladding layer, and the corrosion rate is 4.862 times higher than that of the cladding layer.

The results show that Co-12 cladding layer has great corrosion resistance, which provides an effective way for QT600 protection.

Rapid development of information technology (IT) has posed constant challenges to business information management. By using a case study, this paper discusses the main components and development of an information system (IS) for public housing management in Singapore. It was found that the IS has evolved around a core of transaction processing system, with value‐adding sub‐systems which reflect the use of the latest IT. The paper not only contributes to the understanding of IS for public housing management, but also to the planning of IS for business management.

This study investigates the impact of ESG rating disagreements on stock performance in the Chinese A-share market, focusing on immediate and short-term market reactions and the risk of future stock price crashes. Using data from the Shanghai and Shenzhen stock exchanges, we analyze 17,006 firm-year observations from 2010 to 2021. Stock return data are sourced from the Wind database, while additional financial metrics are obtained from the China Stock Market and Accounting Research (CSMAR) database. Corporate governance information is drawn from the China National Research Data Service (CNRDS) database. Our findings indicate that higher levels of ESG divergence significantly increase the risk of future stock price crashes. Furthermore, the presence of independent directors moderates this relationship, reducing the likelihood of such crashes. Immediate market reactions to ESG rating disagreements are also significant, underscoring the need for transparency and alignment among rating agencies. The study highlights the importance of robust corporate governance and standardized ESG rating methodologies to mitigate associated risks. Policy recommendations include promoting transparency in ESG rating processes and enhancing the role of independent directors in corporate governance.

This study aims to introduce a novel noise filter module designed for LiDAR simultaneous localization and mapping (SLAM) systems. The primary objective is to enhance pose estimation accuracy and improve the overall system performance in outdoor environments.

Distinct from traditional approaches, MCFilter emphasizes enhancing point cloud data quality at the pixel level. This framework hinges on two primary elements. First, the D-Tracker, a tracking algorithm, is grounded on multiresolution three-dimensional (3D) descriptors and adeptly maintains a balance between precision and efficiency. Second, the R-Filter introduces a pixel-level attribute named motion-correlation, which effectively identifies and removes dynamic points. Furthermore, designed as a modular component, MCFilter ensures seamless integration into existing LiDAR SLAM systems.

Based on rigorous testing with public data sets and real-world conditions, the MCFilter reported an increase in average accuracy of 12.39% and reduced processing time by 24.18%. These outcomes emphasize the method’s effectiveness in refining the performance of current LiDAR SLAM systems.

In this study, the authors present a novel 3D descriptor tracker designed for consistent feature point matching across successive frames. The authors also propose an innovative attribute to detect and eliminate noise points. Experimental results demonstrate that integrating this method into existing LiDAR SLAM systems yields state-of-the-art performance.

This study aims to investigate how the COVID-19 pandemic has impacted and changed Airbnb market in the Greater Melbourne area in terms of its temporal and spatial patterns and identify possible shifts in underlying trends in travel activities.

A panel data set of Airbnb listings in Melbourne is analysed to compare temporal patterns, spatial distribution and lengths of stay of Airbnb users before and after the COVID outbreak.

This study found that the COVID disruption did not fundamentally change the temporal cycle of the Airbnb market. Month-to-month fluctuations peaked at different levels from pre-pandemic times mainly because of lockdowns and other restrictive measures. The impact of COVID-19 disruptions on neighbourhood-level Airbnb revenues is associated with distance to CBD rather than number of COVID cases. Inner city suburbs suffered major loss during the pandemic, whereas outer suburbs gained popularity due to increased domestic travel and long stays. Long stays (28 days or more, as defined by Airbnb) were the fastest growing segment during the pandemic, which indicates the Airbnb market was adapting to increasing demand for purposes like remote working or lifestyle change. After easing of COVID-related restrictions, demand for short-term accommodation quickly recovered, but supply has not shown signs of strong recovery. Spatial distribution of post-pandemic supply recovery shows a similar spatial variation. Neighbourhoods in the inner city have not shown signs of significant recovery, whereas those in the middle and outer rings are either slowly recovering or approaching their pre-COVID levels.

The COVID-19 pandemic has significantly impacted short-term rental markets and in particular the Airbnb sector during the phase of its rapid development. This paper helps inform in- and post-pandemic housing policy, market opportunity and investment decision.

To the best of the authors’ knowledge, this is one of the first attempts to empirically examine both temporal and spatial patterns of the COVID-19 impact on Airbnb market in one of the most severely impacted major cities. It is one of the first attempts to identify shifts in underlying trends in travel based on Airbnb data.

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine economy shows positive developmental trends with potential for further growth. The purpose of this research is to analyse the prosperity of China's marine economy, reveal trends therein and forecast the likely turning point in its operation.

Based on the periodicity and fluctuation of China's marine economy development, China's marine economic prosperity indicator system is established from five perspectives. On this basis, China's marine economic operation prosperity index can be synthesised and calculated, then a dynamic factor model is constructed. Using the filtering method to calculate China's marine economic operational Stock–Watson index, Markov switching has been used to determine the trend to transition. Furthermore, China's current marine economic prosperity is evaluated through analysis of influencing factors and correlation analysis.

The analysis shows that, from 2017 to 2019, the operation of the marine economy is relatively stable, and the prosperity index supports this finding; meanwhile it also exposes problems in China's marine economy, such as an unbalanced industrial structure, low marine economic benefits and insufficient capacity for sustainable development.

Through the analysis of the prosperity of China's marine economy, the authors reveal the trends in China's marine economy and forecast its likely future turning point.

The purpose of this study is to provide an in-depth understanding about the indoor-orbital electrical inspection robot, which is useful for motivating the further investigation on the inspection of electrical equipment. Currently, electric energy has a strong correlation with the economic development of the country. Intelligent substations play an important role in the transmission and distribution of the electricity; the maintenance of the substation has attracted intensive attention due to the requirement of reliability and safety. The indoor-orbital electrical inspection robot has increasingly become the main tool to realize the unmanned. Hence, a systematic review is conducted systematically reviewing the current technical status of the indoor-orbital electrical inspection robot and discuss the existed problems.

In this paper, the most essential achievements in the field of indoor-orbital electrical inspection robots were reported to present the current status, and the mechanical structures and key inspective technologies were also discussed.

Four recommendations are provided from the analyzed review, which have made constructive comments on the overall structural design, functionality, intelligence and future development direction of the indoor-orbital electrical inspection robot, respectively.

To the best of the authors’ knowledge, this is the first systematic review study on indoor-orbital electrical inspection robots; it fills the theoretical gap and proffers design ideas and directions for the development of the indoor-orbital electrical inspection robot.

This study aims to analyze the relevance of the city spatial structure for smart city innovation from the perspective of agglomeration externalities, and discusses whether there is heterogeneity in innovation across different geographical areas and population scales of cities.

The authors construct the centralization and concentration indexes to conceptualize the city spatial structure of 286 cities (prefecture-level) in China based on the LandScan Global Population Dataset from 2001 to 2016. A fixed-effects panel data model is employed to analyze the relationship between the spatial structure and the innovation ability of smart cities; the results were validated through robustness tests and heterogeneity analyses.

The study found that the more concentrated and more evenly the distribution of urban population, namely the more city spatial structure tends to be weak-monocentricity, the higher the level of innovation in smart cities. The relevance of the weak-monocentricity structure and smart city innovation varies significantly depending on their geographical location and the size of the city. This result is more applicable to cities in the eastern and central regions, as well as to cities with smaller populations.

The adjustment and optimization of the city spatial structure is important for enhancing smart city construction. Unlike previous studies, which mostly use a single dimension of “the proportion of population in sub-centres to the population of all central areas” to measure city spatial structure, the authors employed the spatial centralization and spatial concentration. It is hoped that this study can guide smart city construction from the perspective of the development model of city spatial structure.

Anchored on social trust theory, social identity theory and signalling theory, this study investigates the process of how consumers respond to online retailers' corporate social responsibility (CSR).

Following the hypo-deductive research design, a unique model was developed to link online retailers' CSR with consumer purchase intention through brand identification and word of mouth (WOM). This model was subsequently tested and validated by conducting an online survey to 239 customers of a major online retailer in China, that is, JD.com.

Analysis using structural equation modelling demonstrates that online retailers' CSR is positively associated with consumer purchase intention, and brand identification positively mediates such an association. In addition, WOM exhibits a mediating effect on the relationship between perceived online retailers' CSR and consumer purchase intention and between brand identification and consumer purchase intention.

Online retailers must endeavour to employ CSR as a strategy to enhance consumer purchase intention and behaviour. Moreover, they should develop communication programmes that highlight their engagement in CSR activities to improve their brand image and facilitate consumers' positive WOM.

To the best of the researchers' knowledge, this study is the first to examine the mediating roles of brand identification and WOM in the relationship between online retailers' CSR and customer purchase intention. Furthermore, this study extends current knowledge about online retailers' CSR and its potential impact in emerging economies by focussing on the context of China.