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In recent years, the application of blockchain in enterprise financing has become a hot topic in academic research. This study aims to review the existing literature, construct a knowledge framework for this research topic and propose an agenda for future research.

Based on 181 papers published from 2016 to 2020 in core journal databases in China and abroad, this study used bibliometric tools to identify and analyze an overview of literature publications, research hotspot trends and research theme clustering. This study also qualitatively analyzes literature from the dimensions of enabling mechanisms, multitechnology synergy, challenges, theoretical perspectives and research methods.

This study presents the research progress of blockchain applications in direct financing, bank credit, supply chain finance and other financing modes and analyzes the similarities and differences between domestic and international literature. This study also reveals enabling mechanisms of blockchain in enterprise financing, reflected as information quality improvement (data elements), trust mechanism innovation (business process) and collaboration structure enhancement (network structure). The study found several challenges (e.g. technological uncertainty, data security and organizational change) and trends (e.g. integrated innovation of multiple digital technologies). Additionally, the authors identified several gaps and opportunities for further research.

This study adopts a strict strategy of selecting search terms when retrieving the literature, leading to the exclusion of certain papers on this topic.

This study provides valuable insights into the innovative development of enterprise financing modes enabled by blockchain and emphasizes that managers should clarify the applicable boundaries and necessary conditions of blockchain innovation in different financing scenarios to match technological innovation with industrial expectations.

This study constructs a knowledge framework on this topic based on a comprehensive review of existing research and proposes several important issues for future research based on the identified research gaps.

The purpose of this paper is to test and explain the context where motivation to learn (MTL) reduces innovative behavior in the organizational context.

The authors used questionnaire survey to collect data in a field study. In order to test the moderating effect of transfer climate, MTL on the relationship between MTL and innovative behavior, a sample of 606 employees was analyzed to examine the theoretical expectation by using multiple regression and bootstrapping.

The authors found employees motivated to learn showed less innovative behavior when perceived transfer climate is less favorable. The authors further revealed that motivation to transfer mediates the moderating effect of transfer climate for the relationship between MTL and innovative behavior.

One suggestion for further research is to investigate the relationship among the four constructs by using multi-source, multi-wave and multi-level method.

This study provides several useful guidance of how organization and manager avoid the negative effects of MTL through encouraging employees to learn new knowledge and skills, and providing employee opportunities to use their acquired knowledge and skills.

The authors contribute to the motivational literature by taking a step further to understand the effect of MTL. The authors propose and confirm that employee MTL can lead to negative outcomes when individuals perceived transfer climate is low. The results offer new insight beyond previous findings on positive or non-significant relationship between MTL and innovative behavior. The results further show that this interactive effect is induced by motivation to transfer. Particularly, low transfer climate reduces individuals’ motivation to transfer, and individuals with high MTL have low innovative behavior when they are less motivated to transfer.

Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The mobile medical consultation (MMC) service is growing rapidly, but not all consumers are always willing to actively engage with it. To address this issue, based on IT identity theory, this study explores the underlying mechanism of how two types of platform-related consumer experience influence MMC platform identity, in turn, result in consumer negatively-valenced engagement in MMC.

The data was collected from 400 consumers with the experience of MMC and analyzed by the partial least square (PLS) method.

The findings unfold that these two distinct consumer experience, servicescape experience (i.e. perceived telepresence and perceived platform surveillance) and service search experience (i.e. perceived diagnosticity and perceived serendipity), are associated with MMC platform identity and consumer negatively valenced engagement with MMC.

Research on consumer negatively-valenced engagement in the field of MMC is still in a nascent stage. The study identifies consumer experience in accordance with the unique context of the MMC platform and fills the research gap on the role of IT identity in consumer negatively valenced engagement.

This paper aims to accelerate the iteration convergence for elliptic fluid flow problems, so that an under‐relaxation factor control method is developed.

There should be an optimal under‐relaxation factor that can result in the equivalence of the global residual norms of momentum equation u and momentum equation v. The two residual norms of the momentum equations will be equivalent through controlling the velocity under‐relaxation factors, and then the iteration convergence can be accelerated. Two expressions (α=(α⁰)^βγ and α=(α⁰)^(1/β)γ) are proposed to adjust the values of under‐relaxation factors for every n iterations.

From the five preliminary computations it is found that the value of γ can be larger than 1 and of n can be less than 5 for an open system, and the value of γ should be less than 1 and that of n should be larger than 10 for a closed system. These two pairs of parameters are then used in another five examples. It is found that the saving in CPU times is at least 43.9 percent for the closed system and 67.5 percent for the open system.

When the Re or Ra of the two‐dimensional problems are low, this control method is feasible. More research work is needed in order to apply it in three‐dimensional or high Re or Ra problems.

This method is helpful for the acceleration of iteration convergence in simple problems, and is a preparation for the advanced research in complicated problems.

The study aims to explore the composition and microstructure of clay functionally graded materials under the process of double-gradient direct ink writing (DIW).

The investigation focused specifically on the pore characteristics of barite-kaolin clay composite after three-dimensional (3D) printing and sintering as well as its bionic application in geophysical model.

The model with pore and material variations brought about spatial and nonlinear mechanical properties. Moreover, the vertical gradient and connected pores in the upper kaolin part simulated the natural phenomenon of the landslide model (take Chinese Majiagou landslides as an example). Both the thermal debinding behavior and the kaolin powder particles characteristics [large pore volume (0.019 cm³g^–1) and pore size (29.20 nm)] were attributed to the interconnection channels.

Hence, the macroscopic and microscopic pores achieved by dual-gradient DIW process make it possible to control the permeability and details of properties, precisely in the geological model.

The material point method (MPM)is a particle-based numerical method suitable for solid–liquid simulation and large deformation problems. However, MPM is generally used in solid deformation at present, to develop a multi-physics coupling MPM; the purpose of this study is to extend the MPM to simulate the heat and fluid flow and address the thermal-hydrological (TH) coupling problems.

The porous medium was discretized into two sets of Lagrangian points, and the motion of fluid points follows the Darcy’s law. Two sets of heat transport equations were established for the heat conduction and heat exchange in the pore fluid and solid skeleton. Fractures were considered by adding the porosity gradient term in the governing equations; also a transition function was introduced to smoothen the fracture boundary.

Four cases of heat and fluid flow in porous medium and fractures were presented to verify the feasibility of the proposed method. And the effects of fractures on heat and fluid flow were investigated. Additionally, a case of geothermal extraction was solved and the importance of the interstitial convective heat transfer coefficient was analyzed.

The proposed method extends the conventional MPM, using two sets of material points and two sets of heat transport equations to simulate the heat and fluid flow and address the TH coupling problems, which can be applied in both porous medium and fractures.

The purpose of this paper is to propose a robot constant grinding force control algorithm for the impact stage and processing stage of robotic grinding.

The robot constant grinding force control algorithm is based on a grinding model and iterative algorithm. During the impact stage, active disturbance rejection control is used to plan the robotic reference contact force, and the robot speed is adjusted according to the error between the robot’s real contact force and the robot’s reference contact force. In the processing stage, an RBF neural network is used to construct a model with the robot's position offset displacement and controlled output, and the increment of control parameters is estimated according to the RBF neural network model. The error of contact force and expected force converges gradually by iterating the control parameters online continuously.

The experimental results show that the normal force overshoot of the robot based on the grinding model and iterative algorithm is small, and the processing convergence speed is fast. The error between the normal force and the expected force is mostly within ±3 N. The normal force based on the force control algorithm is more stable than the normal force based on position control, and the surface roughness of the processed workpiece has also been improved, the Ra value compared with position control has been reduced by 24.2%.

As the proposed approach obtains a constant effect in the impact stage and processing stage of robot grinding and verified by the experiment, this approach can be used for robot grinding for improved machining accuracy.

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy.

In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter.

The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy.

Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors.

Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination.

This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

The purpose of this article is to develop a smart illuminated polymeric optical fibre (POF) chameleonic garment, using a wearable device technology for camouflage or safety warnings based on user needs.

This study integrates the theory of the optical foundation, control system, wireless communication, program development and apparel design into a chameleonic garment, displaying some vests, bags and shoes.

After selecting a pixel in the photo taken by the smart phone, the four modes of the application developed in this study are used to change the POF colour of the garment.

This study develops four modes of smart phone application; picked mode: picks a pixel colour on a smart phone canvas, contrastive mode: transfers to contrastive colour of the picked pixel, customized mode – gives input colour number manual and random mode – it based on a system random number. When users have different functional requirements, the four modes provide various choices.