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The paper aims to build a new objective evaluation method of fabric pilling by combining an integrated image analysis technology with a deep learning algorithm.

Series of image analysis techniques were adopted. First, a Fourier transform transformed images into the frequency domain. The optimal resolution matrix of an exponential high-pass filter was determined by combining the energy algorithm. Second, the multidimensional discrete wavelet transform determined the optimal division level. Third, the iterative threshold method was used to enhance images to obtain a complete and clear pilling ball images. Finally, the deep learning algorithm was adopted to train data from pilling ball images, and the pilling levels were classified according to the learning features.

The paper provides a new insight about how to objectively evaluate fabric pilling grades. Results of the experiment indicate that the proposed objective evaluation method can obtain clear and complete pilling information and the classification accuracy rate of the deep learning algorithm is 94.2%, whose structures are rectified linear unit (ReLU) activation function, four hidden layers, cross-entropy learning rules and the regularization method.

Because the methodology of the paper is based on woven fabric, the research study’s results may lack generalizability. Therefore, researchers are encouraged to test other kinds of fabric further, such as knitted and unwoven fabrics.

Combined with a series of image analysis technology, the integrated method can effectively extract clear and complete pilling information from pilled fabrics. Pilling grades can be classified by the deep learning algorithm with learning pilling information.

Pyrolysis for coal gas generation changes the composition, pore structure, permeability and adsorption capacity of coal. This work aims to discuss the utilization of coal pyrolysis on enhancing coalbed methane (CBM) production in the Gujiao area, Shanxi province, China.

This research was conducted mainly by the methods of thermogravimetry mass spectrometry (TG-MS) analysis, liquid nitrogen adsorption experiment and methane isothermal adsorption measurement.

The results can be concluded as that 400-700°C is the main temperature range for generating CH₄. Pore volume and specific surface area increase with increasing temperature; however, the proportion of micro pore, transition pore and macro pore has no difference. The optimum temperature for enhancing CBM production should be letter than 600°C because the sedimentation of tar and other products will occupy some pores and fissures after 600°C.

Here in, to accurately recognize the suitable maximum temperature for heating development, a method enhancing CBM production, TG-MS, was adopted to analyze the products and the weight loss of coals with different ranks in the Gujiao area at temperature of 30-1,100°C. And then the pore structure, porosity, permeability, methane adsorption capacity and thermal maturity of coals during pyrolysis were investigated with increased temperature from 30°C to 750°C. On these bases, the favorable condition for enhancing CBM production and the thermal evolution of coal were recognized.

Enterprise social media can be the organizational transactive memory in which the knowledge dialogue provides users with the metaknowledge to support knowledge transfer. The purpose of this study is to examine a mediation model to show how perceived critical mass, openness and affiliation climate affect organizational knowledge transfer through the mediation of improving the metaknowledge of who knows what and whom.

To test the mediation model and corresponding hypotheses, this study employs structural equation modeling analysis using 264 valid questionnaires.

The study found the two mediators fully explained the effects of the three preconditions on knowledge transfer.

These results help us to better understand the benefits of enterprise social media and the functions of transactive memory in organizations.

This study aims to improve the robot’s performance during interactions with human and uncertain environments.

A joint stiffness model was established according to the molecular current method and the virtual displacement method. The position and stiffness coordination controller and fuzzy adaptive controller of variable stiffness joint are designed, and the principle prototype of variable stiffness joint is built. The position step and trajectory tracking performance of the variable stiffness joint are verified through experiments.

Experimental test shows that the joint stiffness can be quickly adjusted. The accuracy of position and trajectory tracking of the joint increases with higher stiffness and decreases with increasing frequency. The fuzzy adaptive controller performed better than the position and stiffness coordination controller in controlling the position step and trajectory tracking of the variable stiffness joint.

A hybrid flux adjustment mechanism is proposed for the components of variable stiffness robot joints, which reduces the mass of the output end of variable stiffness joints and the speed of joint stiffness adjustment. Aiming at the change of system controller performance caused by the change of joint stiffness, a fuzzy adaptive controller is proposed to improve the position step and trajectory tracking characteristics of variable stiffness joints.

The purpose of this paper is to improve the surface electrical conductivity and corrosion resistance of AISI 430 stainless steel (430 SS) as bipolar plates for proton exchange membrane fuel cells (PEMFCs), a protective Nb-modified layer is formed onto stainless steel via the plasma surface diffusion alloying method. The effect of diffusion alloying time on electrochemical behavior and surface conductivity is evaluated.

In this work, the surface electrical conductivity and corrosion resistance of modified specimen are evaluated by the potentiodynamic and potentionstatic polarization tests. Moreover, the hydrophobicity is also investigated by contact angle measurement.

The Nb-modified 430 SS treated by 1.5 h (1.5Nb) presented a lower passivation current density, lower interfacial contact resistance and a higher hydrophobicity than other modified specimens. Moreover, the 1.5 Nb specimen presents a smoother surface than other modified specimens after potentionstatic polarization tests.

The effect of diffusion alloying time on electrochemical behavior, surface conductivity and hydrophobicity of modified specimen is evaluated. The probable anti-corrosion mechanism of Nb-modified specimen in simulated acid PEMFC cathode environment is presented.

The purpose of this paper is to demonstrate a novel 3D system-in-package (SiP) approach. This new packaging approach is based on stacked silicon submount technology. As demonstrators, a smart lighting module and a sensor systems were successfully developed by using the fabrication and assembly process described in this paper.

The stacked module consists of multiple layers of silicon submounts which can be designed and fabricated in parallel. The 3D stacking design offers higher silicon efficiency and miniaturized package form factor. This platform consists of silicon submount design and fabrication, module packaging, system assembling and testing and analyzing.

In this paper, a smart light emitting diode system and sensor system will be described based on stacked silicon submount and 3D SiP technology. The integrated smart lighting module meets the optical requirements of general lighting applications. The developed SiP design is also implemented into the miniaturization of particular matter sensors and gas sensor detection system.

SiP has great potential of integrating multiple components into a single compact package, which has potential implementation in intelligent applications.

Considering there is a lack of research in determining the optimal levels of government guarantee and revenue cap, the objective of this research is to determine their optimal levels to achieve a reasonable financial risk allocation between governments and private investors while avoiding overly lucrative conditions for private investors.

Expanded net present value (NPV) analysis and bargaining game theory are employed to construct the core of the determination process. The risk gap between governments and private investors is assessed via an expanded NPV analysis to see if the financial risk has been shared reasonably, based on which the range of the government guarantee is decided. A bargaining model is then created to help locate the optimal level of the government guarantee. Finally, a revenue cap, often combined with the government guarantee in public–private partnership (PPP) agreements, will be determined if overly lucrative conditions for private investors are observed or governments suffer a risk spillover.

Referring to a real PPP project in Australia, Project BA is created to validate the applicability of the proposed determination process. The outcome shows that the proposed determination process in this paper is capable of determining the optimal levels of government guarantee and revenue cap. The government preferences towards risk allocation will influence the values of the optimal levels. Governments may also consider to alleviate the control over investors' net profits to mobilise private investors into PPP projects.

There is a potential possibility that the revenue cap fails to control the financial risk for governments or the overly lucrative condition for private investors. In other words, even though the revenue cap is set at the minimal level, the financial risk for governments still beyond their tolerance range or the overly lucrative condition for private investors still occurs. Future research may focus on other financial protective schemes which help to better control the financial risks for governments and profits for private investors.

Government guarantees are frequently used as an investment incentive to reduce the probabilities of suffering loss for private investors. Nevertheless, the financial risks for governments may increase after providing guarantees and, as a result, revenue cap is required by governments to avoid placing themselves in an unprotected situation. By recognising the importance of the two contractual parameters, many scholars dig into their option values. However, there are very rare research works focussing on the method of determining the specific levels of government guarantee and revenue cap. To overcome the limitations of existing models and enrich the methodology for government guarantee and revenue cap determination, this paper contributes to the body of knowledge by developing a government guarantee and revenue cap determination process which contributes to a reasonable allocation of financial risks between governments and private investors.

This study aims to fabricate the reduced graphene oxide (rGO)/ethylene vinyl acetate copolymer (EVA) composite films with electric-driven two-way shape memory properties for deployable structures application. The effect of dicumyl peroxide (DCP) and rGO on the structure and properties of the rGO/EVA composite films were systematically investigated.

The rGO/EVA composite films were fabricated by melting blend and swelling-ultrasonication method, DCP and rGO were used the crosslinking agent and conductive filler, respectively.

The research results indicate that the two-way shape memory properties of rGO/EVA composite films were significantly improved with the increase of DCP content. The rGO endowed rGO/EVA composite films with excellent electric-driven reversible two-way shape memory and anti-ultraviolet aging properties. The sample rGO/EVA-9 can be heated above Tm within 8 s at a voltage of 35 V and can be heated above the Tm temperature within 12 s under near-infrared light (NIR). Under a constant stress of 0.07 MPa, the reversible strain of the sample rGO/EVA-9 was 8.96% and its electric-driven shape memory behavior maintained great regularity and stability.

The rGO/EVA composite films have potential application value in the field of deployable structures.

With the increase of DCP content, the two-way shape memory properties of rGO/EVA composite films were significantly improved, which effectively solved the problem that the shape memory properties of EVA matrix decreased caused by swelling. The rGO endowed rGO/EVA composite films with excellent electric/NIR driven reversible two-way shape memory properties.

China has a new rural revitalization strategy to stimulate rural transformation through modernizing rural areas and resolving their social contradictions. While social capital is recognized as an important element to rural revitalization and entrepreneurship, research into the role of psychological capital is less developed. Therefore, this paper assesses the impact of both social and psychological capital on entrepreneurial performance of Chinese new-generation rural migrant entrepreneurs (NGRMEs) who have returned to their homes to develop businesses as part of the rural revitalization revolution.

Based on a survey, data were collected from 525 NGRMEs in Shaanxi province. This paper uses factor analysis to determine variables for a multiple linear regression model to investigate the impacts of dimensions of both social capital and psychological capital on NGRMEs’ entrepreneurial performance.

Through the factor analysis, social capital of these entrepreneurs consists of five dimensions (reputation, participation, networks, trust and support), psychological capital has three dimensions (innovation and risk-taking, self-efficacy and entrepreneurial happiness) and entrepreneurial performance contains four dimensions (financial, customer, learning and growth, and internal business process). Furthermore, the multiple linear regression model empirically verifies that both social capital and psychological capital significantly influence and positively correlate with NGRMEs' entrepreneurial performance.

This study shows the importance of how a mixture of interrelated social and psychological dimensions influence entrepreneurial performance that may contribute to the success of the Chinese rural revitalization strategy. This has serious implications when attempting to improve the lives of over 100 million rural Chinese citizens.

There is a pressing need for research on the difference in entrepreneurial performance influenced by the integration of migrant workers’ psychological capital and entrepreneurial opportunity identification. In addition, there is limited research on the association of entrepreneurial performance with different dimensions of psychological capital and how these dimensions affect the entrepreneurial performance of migrant workers. This research will partially address this gap in knowledge by assessing the influence of psychological capital and entrepreneurial opportunity identification on the entrepreneurial performance of migrant workers in China.

This paper conducts a theoretical analysis of psychological capital, entrepreneurial opportunity identification and entrepreneurial performance and proposes a theoretical model of entrepreneurial opportunity identification acting as the intermediary role between psychological capital and the entrepreneurial performance of migrant workers. Based on the data collected from 899 rural households in Shaanxi Province, a structural equation model and a bootstrap method are used to verify the association between psychological capital, entrepreneurial opportunity identification and entrepreneurial performance.

Both entrepreneurial opportunity identification and psychological capital are conducive to the improvement of entrepreneurial performance. However, the entrepreneurial opportunity identification is found to exert a more significant impact on the entrepreneurial performance of migrant workers than psychological capital does. Findings have also revealed that the intermediary role of entrepreneurial opportunity identification is more prominent in the relationship between adventure and innovation and the entrepreneurial performance of migrant workers than that of self-confidence and optimism and entrepreneurial performance of migrant workers.

Based on the results of empirical analysis, the paper proposes corresponding policy recommendations for guiding migrant workers to capitalize on their psychological capital, identify entrepreneurial opportunities, weigh up entrepreneurial risks and ultimately improve their entrepreneurial performance.