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This paper aims to study the turning strategies for the bounding quadruped robot with an active spine and explore the significant role of the spine in the turning locomotion.

Firstly, the bounding gait combining the pitch motion of the spine with the leg motion is presented. In this gait, the spine moves in phase with the front legs. All the joints of the legs and spine are controlled by cosine signals to simplify the control, and the initial position and oscillation amplitude of the joints can be tuned. To verify the effectiveness of the proposed gait, the spine joints are set with different initial positions and oscillation amplitudes, and the initial position and oscillation amplitude of the leg joints are tuned to make the virtual model do the best locomotion in terms of the speed and stability in the simulation. The control signals are also used to control a real robot called Transleg. Then, three different turning strategies are proposed, including driving the left and right legs with different strides, swaying the spine in the yaw direction and combining the above two methods. Finally, these strategies are tested on the real robot.

The stable bounding locomotion can be achieved using the proposed gait. With the spine motion, the speed of the bounding locomotion is increased; the turning radius is reduced; and the angular velocity is increased.

A simple and flexible planning of the bounding gait and three turning strategies for the bounding quadruped robot are proposed. The effectiveness of the proposed bounding gait, along with the beneficial effect of the spine motion in the yaw direction on the turning locomotion is demonstrated with the computer simulations and robot experiments. This will be instructive for the designing and actuating of the other quadruped robots.

This paper aims to tele-operate the movement of an unmanned aerial vehicle (UAV) in the obstructed environment with asymmetric time-varying delays. A simple passive proportional velocity errors plus damping injection (P-like) controller is proposed to deal with the asymmetric time-varying delays in the aerial teleoperation system.

This paper presents both theoretical and real-time experimental results of the bilateral teleoperation system of a UAV for collision avoidance over the wireless network. First, a position-velocity workspace mapping is used to solve the master-slave kinematic/dynamic dissimilarity. Second, a P-like controller is proposed to ensure the stability of the time-delayed bilateral teleoperation system with asymmetric time-varying delays. The stability is analyzed by the Lyapunov–Krasovskii function and the delay-dependent stability criteria are obtained under linear-matrix-inequalities conditions. Third, a vision-based localization is presented to calibrate the UAV’s pose and provide the relative distance for obstacle avoidance with a high accuracy. Finally, the performance of the teleoperation scheme is evaluated by both human-in-the-loop simulations and real-time experiments where a single UAV flies through the obstructed environment.

Experimental results demonstrate that the teleoperation system can maintain passivity and collision avoidance can be achieved with a high accuracy for asymmetric time-varying delays. Moreover, the operator could tele-sense the force reflection to improve the maneuverability in the aerial teleoperation.

A real-time bilateral teleoperation system of a UAV for collision avoidance is performed in the laboratory. A force and visual interface is designed to provide force and visual feedback of the slave environment to the operator.

Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.

The purpose of this paper is to figure out the exact knowledge demand of makers. Furthermore, the paper aims to construct the knowledge space based on makers’ knowledge demand.

The first step of this research is to explore the makers’ knowledge demand by the methods of field investigation, non-interventional study and in-depth interviews. On that basis, the elements, principles, framework and mechanism of the knowledge space were discussed. The grounded theory and NVivo software were used in the data analysis.

The investigation shows that interest and competition are the main motivations for makers’ knowledge demand. The findings also indicate that the characteristics are active knowledge needs, “informal learning” preferences, divergent thinking, close community ties and interdisciplinary. According to the makers’ knowledge demand node conceptual model, the content of makers’ knowledge demand is principle knowledge, empirical knowledge and knowledge situation. Based on the above findings, the elements, principles, operation framework and inherent operation mechanism of the knowledge space construction are systemically described.

This study gives precise details about makers’ knowledge demand and the construction of makers’ knowledge space by libraries. This is the first research that comprehensively explores the knowledge demand of makers. The findings can help the library plan and implement the construction of makerspace, and also improve the service for makers.

Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience.

The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized.

Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly.

This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.

At present, the research on energy consumption of human clothing mainly focuses on behavior observation method, questionnaire survey method, heart rate monitoring method and electronic motion sensor, etc. In order to solve the problem of energy consumption caused by clothing with different characteristics, an identification method of energy consumption for different types of clothing was proposed.

The model robot was designed to reproduce the motion state by simulating the human body in the working mode, and the protective energy consumption test platform was built. In order to explore the influence of different characteristics of clothing on the energy consumption of equipment system, orthogonal experiments were carried out on the model robot experimental platform, and a mathematical model for predicting the energy consumption of clothing based on Tabu search algorithm to optimize support vector machine regression (TS-SVR) optimized by tabu algorithm was proposed.

Compared with three regression prediction algorithms, the accuracy of the model was quantified by the determination coefficient and root mean square error according to the predicted value of the model and the actual value of the experiment. The results showed that the model based on TS-SVM can predict the energy consumption of human body more accurately.

Based on TS-SVR model, it can well predict the relationship between clothing with different characteristics and physical energy consumption, and can accurately evaluate the clothing grade of different characteristics.

Functionalization of organic cotton fabrics (OCFs) by in situ deposition of chitosan reduced-stabilized silver nanoparticles (AgNPs). No other toxic chemicals used to warrant an ecofriendly synthesis protocol. Human toxicity of silver systematically avoided to use as textile clothing. Primary colors (nearly-red, yellow and blue) were imparted on OCFs via localized surface plasmon resonance (LSPR) of AgNPs. Decent mechanical properties and laundering durability in terms of antibacterial/fastness test improved mechanical properties.

Silver nanoparticles can be synthesized by using silver nitrate along with commercially available chitosan. Due to the surface LSPR property of silver nanoparticles, it exhibits versatile colors depending on the synthesizing procedures. The coloration occurs due to the electrostatic interaction between the AgNPs and chitosan-treated OCF. The nanotreated fabrics provide excellent mechanical properties with improved antibacterial effects.

X-ray fluorescence (XRF) analysis quantifies the developed materials in the substrates. Scanning electron microscopy (SEM) characterization indicates the appearance and morphologies of silver nanoparticles into the fabric surface after the coloration process. It proves that the treated cotton knit fabric exhibits the LSPR optical features of AgNPs. The antibacterial and mechanical properties confirm the improved functionality of products.

Improved mechanical properties, antibacterial performances and coloration effects on organic cotton substrates in terms of chitosan-mediated nanosilver are not yet studied.