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This study aims to propose a novel method based on model learning with sparsity inducing norms for estimating dynamic gravity terms of the serial manipulators. This method is realized by operating the robot, acquiring data and filtering the features in signal acquisition to adapt to the dynamic gravity parameters.

The core principle of the method is to analyze the dictionary composition of the basis function of the model based on the dynamic equation and the Jacobian matrix of an arm. According to the structure of the basis function and the sparsity of the features, combined with joint-angle and driving-torque data acquisition, the effective features of dynamic gravity parameters are screened out using L1-norm optimization and learning algorithms.

The theoretical analysis revealed that training data obtained based on joint angles and driving torques could rapidly update dynamic gravity parameters. The simulation experiment was carried out by using the publicly available robot model and compared with the previous disassembly method to evaluate the feasibility and performance. The real 7-degree of freedom (DOF) industrial manipulator was used to further discuss the effects of the feature selection. The results show that this estimation method can be fully operational and efficient in industrial applications.

This approach is applicable to most serial robots with multi-DOF and the dynamic gravity parameters of the robot are estimated through learning and optimization. The method does not require prior knowledge of the robot arm structure and only requires joint-angle and driving-torque data acquisition under low-speed motion. Furthermore, as it is a data-driven-based method, it can be applied to gravity parameters updating.

Different from previous general robot dynamic modelling methods, the sparsity of the analytical form of dynamic equations was exploited and model learning was formulated as a convex optimization problem to achieve effective gravity parameters screening. The novelty of this estimation approach is that the method does not only require any prior knowledge but also does not require a specifically designed trajectory. Thus, this method can avoid the laborious work of parameter calibration and the induced modelling errors. By using a data-driven learning approach, the new parameter updating process can be completed conveniently when the robot carries additional mass or the end-effector changes for different tasks.

Although knowledge sharing in online communities has been studied for many years, little is known about the determinants for individuals' knowledge sharing in online health communities (OHCs) surrounding smoking cessation. Examining the determinants of knowledge sharing in such OHCs from the social capital perspective may prove particularly enlightening.

A questionnaire-based online user survey of two smoking cessation OHCs, one based in Finland and one based in China, was performed. Performing data analysis with partial least squares (SmartPLS 3.0), the authors developed a model conceptualizing the structural, cognitive and relational dimensions of social capital as drivers for knowledge sharing in smoking cessation OHCs, with users' stage in giving up smoking as a moderator.

The results show that structural capital (social ties) and relational capital (reciprocity) are important motivators behind knowledge sharing in smoking cessation OHCs, and the authors found a moderating effect of the stage in quitting on the antecedents' relationship with knowledge sharing in these OHCs.

The study enriches understanding of knowledge sharing in smoking cessation OHCs, contributing to theory and identifying practical implications for such groups' administration.

Humanoid social robots (HSRs) are an innovative technology revitalizing various service sectors, such as the hospitality industry. However, limited research has explored how anthropomorphic features of HSRs influence user satisfaction with the services delivered by HSRs. To address this, a research model was proposed to evaluate how three distinct anthropomorphic features: appearance, voice and response, impact the perceived values (i.e. utilitarian, social and hedonic values) of HSRs, which, in turn, influence user satisfaction.

Data from an online survey of hotel customers was utilized to test the research model (N = 509).

The results indicated that appearance, voice, and response affect perceived utilitarian, hedonic and social values differently. The response feature of HSRs demonstrated the strongest impact on perceived utilitarian, social and hedonic values. In addition, voice affected all three perceived values, while appearance only affected perceived utilitarian and social values. Furthermore, perceived utilitarian, hedonic and social values showed positive impacts on user satisfaction, with hedonic value being the most influential factor.

This study contributes to the literature on HSRs and anthropomorphism by explaining how different anthropomorphic features affect users’ value perceptions and user satisfaction with HSR services by utilizing the stimulus-organism-response (SOR) framework.

The purpose of this study is to examine how the interplay of stressor (e.g. fear of missing out, FoMO) and strains (e.g. perceived social overload, communication overload, information overload and system feature overload) in social networking sites (SNS) use can contribute to users’ SNS fatigue from a configurational view.

Data were collected among 363 SNS users in China via an online survey, and fuzzy-set qualitative comparative analysis (fsQCA) was applied in this study to scrutinize the different combinations of FoMO and overload that contribute to the same outcome of SNS fatigue.

Six combinations of casual conditions were identified to underlie SNS fatigue. The results showed that FoMO, perceived information overload and system feature overload are the core conditions that contribute to SNS fatigue when combined with other types of overloads.

The current work supplements the research findings on SNS fatigue by identifying the configurations contributing to SNS fatigue from the joint effects of stressor (FoMO) and strain (perceived social overload, communication overload, information overload and system feature overload) and by providing explanations for SNS fatigue from the configurational perspective.

The paper aims to explore how perceived prosumer content quality (PPCQ) and perceived interaction quality (PIQ) improve users' co-creation experiences and subsequently influence their co-creation intentions in the future. In addition, the paper examines users' prosumer ability into consideration.

The research model based on stimulus-organism-response (S-O-R) paradigm is developed to observe users' participation in value co-creation activities. In total, 318 valid responses were collected from a survey. Structural equation modeling was used to examine the model and Statistical Package for the Social Sciences (SPSS) PROCESS macro (Model 58) by Hayes was applied to investigate the moderating effect of prosumer ability in mediation paths.

It is observed that co-creation intention is determined by user-learning value, social-integrative value and hedonic value, which are influenced by PPCQ and PIQ. Besides, uses' prosumer ability moderates the indirect effects of PPCQ and PIQ on co-creation intentions through co-creation experiences.

The paper provides a prosumption perspective to explain users' co-creation intentions in social commerce and proposes the importance of user-learning, social-integrative and hedonic values in determining co-creation intentions.

Social commerce platforms can encourage prosumption activities and cultivate multi-level prosumers to achieve a win–win situation.

Little prior research has explicitly examined how and why users participate in value co-creation activities in social commerce from prosumption perspective. The current paper seeks to fill this gap and open new avenues for other value co-creation researchers.

The purpose of this paper is to separate and purify flavonoids from glycyrrhiza by macroporous adsorption resin (MAR) mixed-bed technology.

The adsorption performance of MAR and MAR mixed bed for flavonoids was studied using ultraviolet-visible spectrophotometry.

The research shows that the MAR mixed bed of LZ-50+LZ-59 with a mass ratio of LZ-50:LZ-59(m:m) = 1:1 was the optimized combination with the optimal conditions of adsorption (pH = 6, T = 45°C) and desorption (liquid ratio R = 70%, T = 50°C, pH = 8) obtained, relatively.

This paper provides a novel way to separate flavonoids from glycyrrhiza. Under the optimal conditions, the adsorption rate (F) of MAR mixed-bed LZ-50+LZ-59 to the flavonoids was 62.5 per cent/g, the desorption rate (D) was 89.23 per cent and the purity was achieved at 80 per cent.

Immersion is one of the key steps during the preparation of silane-based hybrid films, which has important effects on the performance of films after curing. In this paper, the formation process of Zr-doped silane film (i.e. the adsorption of silane and deposition of zirconium compounds) on carbon steel immersed in Zr(NO₃)₄/silane mixed solutions was investigated.

The method of in situ monitoring the open circuit potential of a two-electrode system, consisting of carbon steel and saturated calomel electrode, was used. The effects of immersion conditions (i.e. the concentration of Zr(NO₃)₄ and pH of Zr(NO₃)₄/silane mixed solution) on the open circuit potential were investigated in detail. Furthermore, the surface coverage rate of different cured films (i.e. Zr cured film, silane cured film and Zr/silane composite cured film) after curing on carbon steel was calculated according to the results of polarization curves. Electrochemical impedance spectroscopy (EIS) was used to study the self-healing property of Zr-doped silane cured film.

The results indicate that in Zr(NO₃)₄/silane mixed solutions, most zirconium compounds deposit on the surface of carbon steel at the initial immersing stage, then the adsorption of silane on the residual surface of carbon steel dominates the following immersing stage. EIS results show that the Zr-doped cured film has improved self-healing property.

First, the method of in situ monitoring the open-circuit potential of two-electrode system was applied to investigate the deposition of Zr and the adsorption of silane on carbon steel immersed in Zr(NO₃)₄/silane mixed solutions. Second, the formation process of Zr-doped silane film was proposed.

The dimple is adopted into a double wall cooling structure which is widely used in hot gas components to increase the heat transfer effects with relatively low pressure drop penalty. The purpose of this paper is to study the effect of dimple depth and dimple diameter on the target surface heat transfer and the inlet to outlet friction factor.

The study is carried out by using the numerical simulations. The impingement flow is directly impinging on the dimple and released from the film holes after passing the double wall chamber. The ratio between dimple depth and dimple diameter is varied from 0 to 0.4 and the ratio between dimple diameter and impingement hole diameter is ranging from 0.5 to 3. The Reynolds number is between 10,000 and 70,000. Results of the target surface Nusselt number, friction factor and flow structures are included. For convenience of comparison, the double wall cooling structure without the dimple is considered as the baseline.

It is found that the dimple can effectively enhance the target surface heat transfer due to thinning of the flow boundary layer and flow reattachment as well as flow recirculation outside the dimple near the dimple rim especially for the large Re number condition. However, the stagnation point heat transfer is reduced. It is also found that for a large dimple depth or large dimple diameter, a salient heat transfer reduction occurs for the toroidal vortex. The thermal performance indicates that the intensity of the heat transfer enhancement depends upon the dimple depth and dimple diameter

This is the first time to adopt a dimple into a double wall cooling structure. It suggests that the target surface heat transfer in a double wall cooling structure can be increased by the use of the dimple. However, the heat transfer characteristic is sensitive for the different dimple diameter and dimple depth which may result in a different flow behavior

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.

In the supply chain disruption risk, the issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Considering the influence of irrational emotions of decision makers, an evaluation model is designed by the regret theory and VIKOR method, which makes the decision-making process closer to reality.

The paper has some innovations in the evaluation index system and evaluation model construction. The method has good stability under the risk of supply chain interruption.

The mixed evaluation information is used to describe the attributes, and the evaluation index system is constructed by the combined method of the social network analysis method and the literature research method to ensure the accuracy and accuracy of the extracted attributes. The issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.