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At present, the enzyme washing process is widely used in hemp garment in the industry. However, it has many disadvantages. First, it is inefficient and labor-intensive, which can only be produced in small quantities and will take much time for workers to check. Second, its cost is high. The strength loss of the garment is up to 20 percent, with a bad damage. Presently, the enzyme washing process of the gray fabric is not industrialized. The purpose of this paper is to obtain a stable and efficient process for the enzyme washing of the gray fabric.

The whiteness, weight loss rate, strength, dyeing property and fabric style of enzyme washed gray fabrics were studied.

The results showed that the enzyme treated fabric has soft handle, smooth surface, good elasticity and high levelness, as well as low strength reduction rate under the optimized condition of bath ratio of 1:12, cellulase dosage of 0.3 percent, pectinase dosage of 1 g/L, treatment temperature of 55°C, treatment time of 80 min and pH of 6.

First, the process is environment friendly, green and sustainable and, second, it will make the industrialization of the enzyme washing process of gray fabrics, with a high commercial value.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

This paper aims to focus on the liquefaction of soybean protein to obtain a homogeneous protein solution with a high solid/protein content but low viscosity, which may improve the bond properties and technological applicability of soybean protein adhesive.

The liquefactions of soybean protein in the presence of various amounts of sodium sulphite, urea and sodium dodecyl sulphate (SDS) are investigated, and their effects on the main properties of liquefied soybean protein and soybean protein adhesives are characterized by Fourier transform infrared spectroscopy (FT-IR), gel permeation chromatography (GPC), viscosity tracing and plywood evaluation. Meanwhile, the applicability of soybean protein adhesive composed of liquefied protein for particleboard is also investigated.

Soybean protein can be effectively liquefied to form a homogeneous protein solution with a soybean protein content of 25 per cent and viscosity as low as 772 mPa.s; the addition of sodium sulphite, urea and SDS are beneficial for the liquefaction of soybean protein and have important effects on the technological applicability and water resistance of the obtained adhesive. The optimal liquefying technology of soybean protein is obtained in the presence of 1.5 Wt.% of sodium sulphite, 5 Wt.% of urea, 1.5 Wt.% of SDS and 3 Wt.% of sodium hydroxide. The optimal soybean protein adhesive has the desired water resistance in terms of the boiling-dry-boiling aged wet bond strength, which is up to 1.08 MPa higher than the required value (0.98 MPa) for structural use according to the commercial standard JIS K6806-2003. The optimal liquefied protein has the great potential to prepare particleboard.

The protein content of liquefied soybean protein is expected to further increase from 25 to 40 Wt.% or even higher to further reduce the hot-pressing cycle or energy consumption of wood composites bonded by soybean protein adhesives.

The soybean protein adhesive composed of optimal liquefied protein has potential use in the manufacturing of structural-use plywood and has comparable applicability as a commercial urea-formaldehyde resin for the manufacturing of common particleboard.

Soybean protein adhesive is an environmentally safe bio-adhesive that does not lead to the release of toxic formaldehyde, and the renewable and abundant soybean protein can be used with higher value added by the application as wood adhesive.

A novel liquefaction approach of soybean protein is proposed, and the soybean protein adhesive based on the liquefied protein is obtained with good technological applicability and desired bond properties that extend the applications of the soybean protein adhesive from interior plywood to particleboard and exterior or structural plywood.

Detecting objects in images and videos is a difficult task that has challenged the field of computer vision. Most of the algorithms for object detection are sensitive to background clutter and occlusion, and cannot localize the edge of the object. An object's shape is typically the most discriminative cue for its recognition by humans. The purpose of this paper is to introduce a model‐based object detection method which uses only shape‐fragment features.

The object shape model is learned from a small set of training images and all object models are composed of shape fragments. The model of the object is in multi‐scales.

The major contributions of this paper are the application of learned shape fragments‐based model for object detection in complex environment and a novel two‐stage object detection framework.

The results presented in this paper are competitive with other state‐of‐the‐art object detection methods.

The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is high, while the absolute positioning accuracy and distance accuracy are low. Many factors affect the absolute positioning accuracy and distance accuracy, and the calibration method of the industrial robot is an important factor. When the traditional calibration methods are applied on the industrial robot, the accumulative error will be involved according to the transformation between the measurement coordinate and the robot base coordinate.

In this manuscript, a distance accuracy-based industrial robot kinematic calibration model is proposed. First, a simplified kinematic model of the robot by using the modified Denavit–Hartenberg (MDH) method is introduced, then the proposed distance error-based calibration model is presented; the experiment is set up in the next section.

The experimental results show that the proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

The proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

This paper explores whether fintech paves the way for the transition to carbon neutrality in the context of China’s climate policy uncertainty (CCPU) and the influence of the ocean carbon sink market.

We apply a novel wavelet analysis technique to investigate the time-frequency dependence between the CCPU index, the CSI (China Securities Index) Fintech Theme Index (CFTI) and the Carbon Neutral Concept Index (CNCI).

The empirical results show that CCPU and CFTI have a detrimental effect on CNCI in high-frequency bands. Furthermore, in low-frequency domains, the development of CFTI can effectively promote the realization of carbon neutrality.

Our findings show that information from the CCPU and CFTI can be utilized to forecast the movement of CNCI. Therefore, the government should strike a balance between fintech development and environmental regulation and, hence, promote the use of renewable energy to reduce carbon emissions, facilitating the orderly and regular development of the ocean carbon sink market.

The development of high-quality fintech and positive climate policy reforms are crucial for achieving carbon neutrality targets and promoting the growth of the marine carbon sink market.

Laser powder bed fusion (LPBF) can be used to fabricate complex extrusion die without the limitation of structures. Layer-by-layer processing leads to differences in microstructures and wear properties. This study aims to investigate the microstructure evolution and effects of tungsten carbide (WC) on the wear properties of LPBF-printed 18Ni300.

Economical spherical granulation-sintering-deoxygenation (GSD) WC-reinforced 18Ni300 steel matrix composites were produced by LPBF from powder mixtures of WC and 18Ni300. The effects of WC contents on anisotropic microstructures and wear properties of the composites were investigated.

The relative density is more than 99% for all the composites except 25% WC/18Ni300 composite. The grain sizes distributed on the top cross-section are smaller than those on the side cross-section. After adding WC particles, more high-angle grain boundaries and larger Schmid factor generate, and deformed grains decrease. With increasing WC contents, the hardness first decreases and then increases but the wear volume loss decreases. The side cross-section of the composite has higher hardness and better wear resistance. The 18Ni300 exhibits adhesive wear accompanying with abrasive wear, while plowing and fatigue wear are the predominant wear mechanisms of the composites.

Economical spherical GSD WC particles can be used to improve the wear resistance. The novel WC/18Ni300 composites are suitable for the application under the abrasive wear condition with low stress.

In recent years, to solve the contradiction between energy supply and demand, the Chinese Government has vigorously promoted shale gas development. With the rapid development of the shale gas industry, the environmental impact problems have become increasingly serious. Therefore, it is of great significance to carry out a comprehensive environmental impact assessment of shale gas development. This study aims to provide a theoretical basis for enterprises to make development decisions on shale gas projects by constructing a model of comprehensive environmental impact assessment for shale gas development.

In this paper, the comprehensive environmental impact factors of shale gas development are analyzed from the two aspects of the natural environment and macro environment, and the index system of comprehensive environmental impact assessment for shale gas development including 7 secondary indicators and 24 tertiary indicators is constructed. Owing to the fact that qualitative indicators are difficult to quantify in the evaluation process, the method of intuitionistic fuzzy analytic hierarchy process (IFAHP) is adopted for evaluation. This method (IFAHP) can delicately describe the hesitancy degree of the decision-makers in the process of assigning a weight to the indicators, and make the weight assignment of each index more accurate. Furthermore, this method overcomes the shortcomings of the conventional methods, such as the complexity of calculation and the large amount of calculation.

The evaluation model is applied to a shale gas platform drilling project in Southwest China. Based on the ratings from 13 experts, the comprehensive environmental impact assessment grade of this project is good, indicating that the shale gas development project is feasible. The result is basically in line with the actual situation.

Based on the consideration of the natural environmental impacts of shale gas development, this paper also has considered the macro environmental impact of shale gas development, and has established the index system of comprehensive environmental impact assessment for shale gas development from the two aspects of the natural environment and macro environment. To overcome such difficulties as incomplete evaluation by decision-makers, cumbersome calculation process and a large amount of calculation, this paper has adopted the method of IFAHP to evaluate and has established a comprehensive environmental impact assessment model for shale gas development based on IFAHP.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.