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The online profile picture of a doctor serves as a pivotal source of visual information, playing a key role in shaping the doctor’s professionalism in the online health market. Doctors can strategically curate the elements of their online profile pictures, such as attire and background, to either reinforce a formal image or craft a casual image, thereby influencing patients’ doctor choices. Despite this, the relative effectiveness of formal or casual images in swaying patient choices remains unclear. This study endeavors to bridge this knowledge gap.

This study tested the influence of a doctor’s attire and background in their profile picture on patient decision-making, with a focus on discerning variations in impact among patient groups differentiated by the severity of their illnesses (i.e. high-severity versus low-severity conditions). We formulated four hypotheses and tested them through an econometric analysis and a controlled laboratory experiment.

The empirical findings reveal that doctors’ formal profile pictures, characterized by formal attire and backgrounds, exert a more pronounced influence on patient choices than casual images. The severity of a patient’s illness positively moderated the relationship between formal images and patient choices.

These insights make a significant contribution to the understanding of patient behavior in selecting doctors within the online health market. Furthermore, they offer valuable guidance for doctors in optimizing their online profile presentation to better align with patient preferences and expectations.

As older adults are increasingly active in virtual communities (VCs), these platforms for knowledge exchange present opportunities for companies to use elder human capital. The purpose of this study is to understand the antecedent factors that motivate older adults’ knowledge contribution and knowledge seeking (KS) behaviors in VCs.

Rooted in socio-emotional selectivity and social cognitive theories, this study included five key variables and developed models for older adults’ knowledge contributing (KC)/KS behaviors. This paper tested the hypotheses using data from a sample of 204 older adults in 3 VCs in China.

The results provide support for most of the hypotheses and show that while other members’ participation (MP) acts as a substitute for meaning in life and attitude toward aging, it acts as a complement for outcome expectations (OE) focused on others and OE focused on oneself in their impacts on KC/KS activities.

The study provides practical insights for developing elder human resources via VCs to avoid knowledge loss.

This study described older adults’ unique characteristics when modeling their information and communication technologies-related behaviors and built two models to explain their KC/KS behaviors. It confirmed that the same factor has different levels of impact on older adults’ KC/KS behaviors in VCs. In addition, it confirmed and reinforced the complementary and substitutive effects of other MP as an environmental factor on these behaviors.

Human-like musculoskeletal robots can fulfill flexible movement and manipulation with the help of multi joints and actuators. However, in general, sophisticated structures, accurate sensors and well-designed control are all necessary for a musculoskeletal robot to achieve high-precision movement. How to realize the reliable and accurate movement of the robot under the condition of limited sensing and control accuracy is still a bottleneck problem. This paper aims to improve the movement performance of musculoskeletal system by bio-inspired method.

Inspired by two kinds of natural constraints, the convergent force field found in neuroscience and attractive region in the environment found in information science, the authors proposed a structure transforming optimization algorithm for constructing constraint force field in musculoskeletal robots. Due to the characteristics of rigid-flexible coupling and variable structures, a constraint force field can be constructed in the task space of the musculoskeletal robot by optimizing the arrangement of muscles.

With the help of the constraint force field, the robot can complete precise and robust movement with constant control signals, which brings in the possibility to reduce the requirement of sensing feedback during the motion control of the robot. Experiments are conducted on a musculoskeletal model to evaluate the performance of the proposed method in movement accuracy, noise robustness and structure sensitivity.

A novel concept, constraint force field, is proposed to realize high-precision movements of musculoskeletal robots. It provides a new theoretical basis for improving the performance of robotic manipulation such as assembly and grasping under the condition that the accuracy of control and sensory are limited.

Social media greatly enhances public access to health information and thus attracts older adults who tend to attach more importance to their health. This study aims to identify the factors that contribute to the likelihood of older adults' health information sharing on social media.

By drawing on health belief (HBM) and elaboration likelihood models (ELM), a novel conceptual model integrating older adults' health belief and information processing is established to uncover the factors. Online survey data from 290 Chinese older adult users of WeChat, the most popular social media platform in China, were collected to test the research model.

As health belief-related variables, perceived susceptibility is positively associated with health information-sharing intention (HISI), while perceived severity negatively influences HISI, which is contrary to prior findings. For information processing, the positive impacts of argument quality and source credibility on HISI are fully mediated by perceived usefulness.

This study is one of the first studies to explore the initiative use of information and communication technology among older adults. The new theoretical perspective proposed herein considers health belief and information processing perspectives in a complementary manner and can facilitate an overall analysis of the factors influencing older adults' HISI in a social media context. This study also furthers understandings of the ELM and expands the theory of HBM to take the age of decision makers into account.

The purpose of this paper is to investigate the effects of the environment of a virtual community (users’ interactions inside and outside of a community which are defined as the fundamental and supplemental interaction (FI and SI), respectively) on its users’ knowledge sharing (KS) and the underlying cognitive mechanism.

A survey was conducted among the users who had experience of participating in a domain knowledge specific online community. A total of 479 valid observations were collected. Structural equation modeling was used to test the research model and hypotheses.

The empirical results show that the fundamental interaction (FI) not only directly affects users’ knowledge acquisition (KA) and contribution, but also indirectly affects users’ KA and contribution partially through the users’ self-efficacy and outcome expectation. While the supplemental interaction (SI) negatively affects users’ KA, it positively affects the users’ knowledge contribution and this effect is also partially mediated by the users’ self-efficacy and outcome expectation. The mediators of self-efficacy and outcome expectation play distinct role on users’ KA and contribution in virtual communities (VCs).

This research conceptualizes the users’ interaction inside and outside of a particular virtual community as FI and SI, respectively, and reveals the mechanism how they affect users’ KA and contribution. The results shed light on the literature of KS in VCs and extend social cognitive theory's application into a complex environment with blended interactions in a virtual world. The research also provides insights for virtual community designers, administrators and users.

This paper aims to investigate the anti-icing performance of the nanosecond dielectric barrier discharge (NSDBD) plasma actuator.

With the Lagrangian approach and the Messinger model, two different ice shapes known as rime and glaze icing are predicted. The air heating in the boundary layer over a flat plate has been simulated using a phenomenological model of the NSDBD plasma. The NSDBD plasma actuators are planted in the leading edge anti-icing area of NACA0012 airfoil. Combining the unsteady Reynolds-averaged Navier–Stokes equations and the phenomenological model, the flow field around the airfoil is simulated and the effects of the peak voltage, the pulse repetition frequency and the direction arrangement of the NSDBD on anti-icing performance are numerically investigated, respectively.

The agreement between the numerical results and the experimental data indicates that the present method is accurate. The results show that there is hot air covering the anti-icing area. The increase of the peak voltage and pulse frequency improves the anti-icing performance, and the direction arrangement of NSDBD also influences the anti-icing performance.

A numerical strategy is developed combining the icing algorithm with the phenomenological model. The effects of three parameters of NSDBD on anti-icing performance are discussed. The predicted results show that the anti-icing method is effective and may be helpful for the design of the anti-icing system of the unmanned aerial vehicle.

Lattice Boltzmann method (LBM) has made great success in computational fluid dynamics, and this paper aims to establish an efficient simulation model for the polymer injection molding process using the LBM. The study aims to validate the capacity of the model for accurately predicting the injection molding process, to demonstrate the superior numerical efficiency in comparison with the current model based on the finite volume method (FVM).

The study adopts the stable multi-relaxation-time scheme of LBM to model the non-Newtonian polymer flow during the filling process. The volume of fluid method is naturally integrated to track the movement of the melt front. Additionally, a novel fractional-step thermal LBM is used to solve the convection-diffusion equation of the temperature field evolution, which is of high Peclet number. Through various simulation cases, the accuracy and stability of the present model are validated, and the higher numerical efficiency verified in comparison with the current FVM-based model.

The paper provides an efficient alternative to the current models in the simulation of polymer injection molding. Through the test cases, the model presented in this paper accurately predicts the filling process and successfully reproduces several characteristic phenomena of injection molding. Moreover, compared with the popular FVM-based models, the present model shows superior numerical efficiency, more fit for the future trend of parallel computing.

Limited by the authors’ hardware resources, the programs of the present model and the FVM-based model are run on parallel up to 12 threads, which is adequate for most simulations of polymer injection molding. Through the tests, the present model has demonstrated the better numerical efficiency, and it is recommended for the researcher to investigate the parallel performance on even larger-scale parallel computing, with more threads.

To the authors’ knowledge, it is for the first time that the lattice Boltzmann method is applied in the simulation of injection molding, and the proposed model does obviously better in numerical efficiency than the current popular FVM-based models.

The purpose of this paper is to develop a finite volume approach for the simulation of three-dimensional two-phase (polymer melt and air) flow in plastic injection molding which is capable of robustly handling the mesh non-orthogonality and the discontinuities in fluid properties.

The presented numerical method is based on a cell-centered unstructured finite volume discretization with a volume-of-fluid technique for interface capturing. The over-relaxed approach is adopted to handle the non-orthogonality involved in the discretization of the face normal derivatives to enhance the robustness of the solutions on non-orthogonal meshes. A novel interpolation method for the face pressure is derived to address the numerical stability issues resulting from the density and viscosity discontinuities at the melt–air interface. Various test cases are conducted to evaluate the proposed method.

The presented method was shown to be satisfactorily accurate by comparing simulations with analytical and experimental results. Besides, the effectiveness of the proposed face pressure interpolation method was verified by numerical examples of a two-phase flow problem with various density and viscosity ratios. The proposed method was also successfully applied to the simulation of a practical filling case.

The proposed finite volume approach is more tolerant of non-orthogonal meshes and the discontinuities in fluid properties for two-phase flow simulation; therefore, it is valuable for engineers in engineering computations.

The purpose of this paper is to develop a coupled approach to solve the pressure–velocity-coupled problem efficiently in the three-dimensional injection molding simulation.

A fully coupled pressure–velocity algorithm is developed to solve the coupled problem, by treating the pressure gradient term implicitly. And, the Schur complement preconditioned FGMRES is applied to decompose the resulting coupled pressure–velocity equation into pressure and velocity subsystems. Then, BoomerAMG is adopted to solve the pressure subsystem, and block Jacobi preconditioned FGMRES is applied to the velocity subsystem.

According to the several experiments, the fully coupled pressure–velocity algorithm was demonstrated to have faster convergence than the traditional SIMPLE algorithm, and the calculating time was reduced by up to 70 per cent. And, the Schur complement preconditioned FGMRES worked more efficiently than block Gauss–Seidel preconditioned FGMRES, block-selective AMG and AMG with block ILU(0) smoother and could take at least 47.4 per cent less time. The proposed solver had good scalability for different-size problems, including various cases with different numbers of elements. It also kept good speedup and efficiency in parallel performance.

A coupled solver has been proposed to effectively solve the coupled problem in the three-dimensional injection molding simulation, which is more robust and efficient than existing methods.

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.