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The accuracy and reliability of upper limb motion assessment have received great attention in the field of rehabilitation. Grasping test is widely carried out for motion assessment, which requires patients to grasp objects and move them to target place. The traditional assessments test the upper limb motion ability by therapists, which mainly relies on experience and lacks quantitative indicators. This paper aims to propose a deep learning method based on the vision system of our upper limb rehabilitation robot to recognize the motion trajectory of rehabilitation target objects automatically and quantitatively assess the upper limb motion in the grasping test.

To begin with, an SRF network is designed to recognize rehabilitation target objects grasped in assessment tests. Moreover, the upper limb motion trajectory is calculated through the motion of objects’ central positions. After that, a GAE network is designed to analyze the motion trajectory which reflects the motion of upper limb. Finally, based on the upper limb rehabilitation exoskeleton platform, the upper limb motion assessment tests are carried out to show the accuracy of both object recognition of SRF network and motion assessment of GAE network. The results including object recognition, trajectory calculation and deviation assessment are given with details.

The performance of the proposed networks is validated by experiments that are developed on the upper limb rehabilitation robot. It is implemented by recognizing rehabilitation target objects, calculating the motion trajectory and grading the upper limb motion performance. It illustrates that the networks, including both object recognition and trajectory evaluation, can grade the upper limb motion functionn accurately, where the accuracy is above 95.0% in different grasping tests.

A novel assessment method of upper limb motion is proposed and verified. According to the experimental results, the accuracy can be remarkably enhanced, and the stability of the results can be improved, which provide more quantitative indicators for further application of upper limb motion assessment.

The purpose of this study is to explore the effect of transformational leadership (TL) on tacit and explicit knowledge sharing (KS) of teachers through the mediating role of knowledge-centered school culture (KSC). This study also attempts to bring a deeper insight into the correlation between KSC and KS behaviors by exploring the moderating effect of perceived organizational support (POS).

The paper used a quantitative approach and structural equation modeling to examine the relationship among the latent factors in the research model using data collected from 293 teachers in Vietnamese universities.

The findings indicated that TL positively influences tacit and explicit KS behaviors of teachers directly or indirectly through its positive effect on KSC. In addition, the paper highlights the moderating role of POS in strengthening the impact of TL on tacit and explicit KS behaviors of teachers.

This paper emphasizes the need to practice TL as an effective pathway to foster tacit and explicit KS behaviors of teachers in higher education.

The paper significantly contributes to enhancing understanding of the antecedent role of TL in fostering knowledge-centered culture and KS behaviors of teachers under the moderating effects of POS in higher education.

Owing to the growing importance of frugal innovation to the development of firms in the developing and emerging countries, the purpose of this paper is to investigate the effect of inclusive leadership (IL) on frugal innovation through the mediating roles of tacit and explicit knowledge sharing (EK). It also explores the possible moderating role of competitive intensity (CI) in the relationship between knowledge sharing (KS) and frugal innovation.

This study collected data via a questionnaire survey of a sample of 325 participants from 112 manufacturing and service firms to validate the relationship between inclusive leadership, knowledge sharing behaviors, competitive intensity and frugal innovation. Structural equation modeling and regression are adopted to estimate the effects of inclusive leadership on frugal innovation through the mediating role of knowledge sharing and moderating role of competitive intensity.

Findings reveals the significant impacts of inclusive leadership on aspects of knowledge sharing and frugal innovation. Moreover, the influences of tacit and explicit knowledge sharing on frugal innovation capability are enhanced in the intensive competitive environments.

Future research should investigate the potential moderating role of perceived organizational support in the relationship between specific aspects of knowledge sharing behaviors and frugal innovation.

The paper provides a valuable understanding and novel approach for managers and directors of firms in developing and emerging countries to improve frugal innovation capability through inclusive leadership practices and promotion of knowledge sharing in organizations.

The paper is unique in its attempt to fill theoretical gaps on the relationship between inclusive leadership and frugal innovation, and advance the insights of how inclusive leadership directly and indirectly fosters frugal innovation via mediating roles of tacit and explicit knowledge sharing.

Due to the vital role of innovation for firms to respond to the change and achieve competitive advantage, the purpose of this study is to investigate the influence of knowledge-oriented leadership (KOL) on innovation performance via the mediating role of knowledge sharing (KS). This study also explores the moderating role of organizational justice in the relationship between KS and innovation performance.

Analysis of moment structures and structural equation modeling are applied to examine the relationship among the latent factors in the proposed research model using data collected from 335 participants in 121 manufacturing and service firms in Vietnam.

The findings revealed that KOL serves as a key precursor to foster innovation performance directly or indirectly through active and passive KS behaviors. In addition, the paper highlights the moderating role of organizational justice in strengthening the impact of KS activities on innovation performance.

By highlighting the important role of KOL for stimulating KS behaviors, this paper provides a valuable understanding and novel approach for firms to improve innovation performance. The research findings support the idea that building a climate of justice is crucial to enhance the effects of KS on innovation performance.

This study contributes to bridging the research gaps in the literature and advances the insights of how KOL directly and indirectly stimulates innovation performance via mediating roles of active and passive KS processes under the climate of justice.

Due to the vital role of innovation for firms to respond to the change and achieve competitive advantage, the purpose of this study is to investigate the influence of knowledge-oriented leadership (KOL) on innovation performance (IP) via the mediating role of knowledge sharing (KS). This study also clarifies the KS-IP relationship by exploring the moderating role of market turbulence.

Analysis of moment structures and structural equation modeling are applied to examine the relationship among the latent factors in the proposed research model using data collected from 281 participants in 112 manufacturing and service firms in Vietnam.

The findings revealed that KOL serves as a key precursor to foster IP, directly or indirectly, through knowledge-oriented leaders’ effect on tacit and explicit KS behaviors. In addition, the paper highlights the moderating role of market turbulence in strengthening the impact of KS activities on IP.

By highlighting the important role KOL practice for stimulating KS behaviors, this paper provides a valuable understanding and novel approach for firms to improve IP. The research findings support the idea that market turbulence significantly contributes to increasing the effects of KS behaviors on IP.

This study contributes to bridging research gaps in the literature and advances the insights of how KOL directly and indirectly fosters IP via mediating roles of tacit and explicit KS processes under the effects of market turbulence.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

This paper aims to explore the influencing factors of public perceived efficacy of emergency infrastructure projects based on the triadic interactive determinism, and analyze the relationship among these factors.

Based on the triadic interactive determinism, we explored the factors influencing public perceived efficacy of emergency infrastructure project and empirically verified the relationship among these factors and perceived efficacy by using data drawn from a questionnaire survey of 491 residents near Leishenshan Hospital, Jiangxia District, Wuhan, China.

Prior experience, emotional response, personal expectation, public trust, context message and interactivity level, namely behavior, individual and environment, affect the perceived efficacy of public emergency infrastructure projects.

The results offer an insight into public perceived efficacy of emergency infrastructure project from the perspective of antecedents in a triadic reciprocal determinism, which provides a reference basis for the sustainable development of the emergency infrastructure projects. This study also suggests valuable practical implications to government departments to improve the quality of administrative decision-making effectively.

Although existing studies have found some influencing factors of public perceived efficacy in general infrastructure, there is still a lack of systematic carding and quantitative description of influencing factors of public perceived efficacy of emergency infrastructure projects. This study bridges this gap by exploring the determinants and their influencing relationship of public perceived efficacy especially for emergency infrastructure projects.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.