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Special education in China has lagged behind regular education for many years, however, the past few decades, the government has made considerable efforts to develop and improve the special education system. While the citizens of China have had a generic moral interest in disability since ancient times, the development of special education schools did not occur until American and European missionaries started schools for the visually and hearing impaired in the 19th century. The next major influence in the development of the special education system occurred with China’s Cultural Revolution in 1978. Interestingly, there is not any exclusive legislation on special education but in the 1980s, the government started Learning in Regular Classrooms (LRC), which is China’s version of inclusion. LRC has progressed rapidly the past two decades; however, the quality of instruction is low due to a lack of specialists, a shortage of personnel, inadequate funding, and limited technology as well as other barriers that are delineated in the chapter. The chapter emphasizes the government’s recent efforts in in-service teacher training, the preparation of preservice teachers, working with families, developing community rehabilitation training programs, and implementing evidence-based practices. Special education in China today is at a good place but it has quite a way from the ideal situation.

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.

The purpose of this article is the effect of doping minor Ni on the microstructure evolution of a Sn-xNi (x = 0, 0.05 and 0.1 wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment. Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of interfacial layer was different due to the different mechanism of element diffusion of the two substrates. The PC Ni substrate mainly provided Ni atoms through grain boundary diffusion. The Ni₃Sn₄ phase of the Sn0.05Ni/PC Ni joint was finer, and the diffusion flux of Sn and Ni elements increased, so the Ni₃Sn₄ layer of this joint was the thickest. The SC Ni substrate mainly provided Ni atoms through the lattice diffusion. The Sn0.1Ni/SC Ni joint increases the number of Ni atoms at the interface due to the doping of 0.1Ni (wt.%) elements, so the joint had the thickest NiSn₄ layer.

The effects of doping minor Ni on the microstructure evolution of an Sn-xNi (x = 0, 0.05 and 0.1 Wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment was investigated in this study.

Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of the interfacial layer was different due to the different mechanisms of element diffusion of the two substrates.

In this study, the effect of doping Ni on the growth and formation mechanism of IMCs of the Sn-xNi/Ni (single-crystal) solder joints (x = 0, 0.05 and 0.1 Wt.%) was investigated.

The purpose of this paper is exploring the effects of segment dynamic and temporal dynamic triggered by the COVID-19 pandemic on classifying service quality attributes, thereby formulating improvement strategies to satisfy customers and respond to threats.

Given the dynamics of the attractive quality theory, this paper designs a framework with four phases by embedding techniques of text mining and deep learning based on evidence from online reviews.

This paper figures out dynamics of service quality attributes for distinct segments and their dynamic proportion along with different stages of the pandemic. Another finding demonstrates segment dynamic and temporal dynamic effects of sentiments toward service quality attributes on customer satisfaction under the impacts of pandemic. Classification results and improvement strategies are derived for varying segments at different pandemic situations.

This paper reveals dynamic effects on classifying service quality attributes, which contributes to assisting hospitality practitioners from different segments in improving service quality when facing with the challenges of crisis and potential risks.

Given hospitality industry is time- and segment-sensitive, the authors achieve the quantification of dynamics of attractive quality theory and extend it into hospitality marketing and crisis management from the perspective of dynamics with evidence from online reviews.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The purpose of this study is to decompose the effects of country-of-origin labeling (COOL) into multiple dimensions—macrolevel image, related to the country image, and microlevel image, related to dairy industry/product attributes—and investigate how each dimension affects Chinese consumers' evaluation of imported milk.

This study adopted the Becker–DeGroot–Marschak (BDM) auction mechanism to elicit consumers' willingness to pay (WTP) for milk from different countries (New Zealand, Australia, Germany, France and China). The experiment was conducted with 348 shoppers at supermarkets in three major cities of China (Hangzhou, Wuhan and Shijiazhuang). The study subject was ultrahigh-temperature processing (UHT) milk (200 mL Tetra Pak aseptic brick package).

The results show that Chinese consumers are willing to pay a premium for UHT milk from New Zealand, Australia, Germany and France compared to domestic milk, and the premiums are 59.4, 58.9, 57.9, and 52.9% respectively. Both microlevel and macrolevel images exert a substantial influence on consumers' WTP, and the microlevel image has a greater impact on consumers' evaluation of milk than the macrolevel image. Particularly, the macropolitical, microtechnology/quality and microdesign/package dimensions have a positive influence on WTP for milk.

This study contributes to the existing literature in introducing the country-of-origin image (COI) construct with different dimensions to get in-depth knowledge about the country-of-origin (COO) effect in food or agricultural economics.

This paper aims to investigate the singular Hopf bifurcation and mixed mode oscillations (MMOs) in the perturbed Bonhoeffer-van der Pol (BVP) circuit. There is a singular periodic orbit constructed by the switching between the stable focus and large amplitude relaxation cycles. Using a generalized fast/slow analysis, the authors show the generation mechanism of two distinct kinds of MMOs.

The parametric modulation can be used to generate complicated dynamics. The BVP circuit is constructed as an example for second-order differential equation with periodic perturbation. Then the authors draw the bifurcation parameter diagram in terms of a containing two attractive regions, i.e. the stable relaxation cycle and the stable focus. The transition mechanism and characteristic features are investigated intensively by one-fast/two-slow analysis combined with bifurcation theory.

Periodic perturbation can suppress nonlinear circuit dynamic to a singular periodic orbit. The combination of these small oscillations with the large amplitude oscillations that occur due to canard cycles yields such MMOs. The results connect the theory of the singular Hopf bifurcation enabling easier calculations of where the oscillations occur.

By treating the perturbation as the second slow variable, the authors obtain that the MMOs are due to the canards in a supercritical case or in a subcritical case. This study can reveal the transition mechanism for multi-time scale characteristics in perturbed circuit. The information gained from such results can be extended to periodically perturbed circuits.

The purpose of this study was to develop a new folding method for modeling complicated folded fabric with surfaces of revolution.

Irregular wrinkles and mesh distortions easily appear in the fold modeling of a complex curved surface. Aimed at this key technical problem, the segmentation mapping folding method (SMFM) is proposed in this paper. First, high-precision flattened planes were obtained by using segmentation mapping techniques. Second, the segmented planes were transformed into a folded and continuous geometric model by using matrix transformations. Finally, initial stress was used to modify the geometric folding errors, which ensured agreement with the inflated flexible fabric’s geometry and the original design.

Compared with the traditional folding method, SMFM has the advantages of good finite-element mesh quality, large radial compression rate, regular folds, etc. The surface area error and the volume error of the inflated single torus established by SMFM were only 1.2 per cent, showing that SMFM has high modeling accuracy. The numerical results of an inflatable re-entry vehicle are presented to demonstrate the reliability, feasibility and applicability of SMFM. Moreover, the stress modification reduced the problems of stress concentration and mesh distortions, improving the accuracy and stability of the numerical calculations.

In this paper, for the first time, a folding method for modeling complicated folded fabric is proposed. This methodology can be used to model the multidimensional compression and regular folds of complex surfaces of revolution that cannot be flattened and to improve the accuracy and stability of the numerical calculations.

In an intelligent transportation system (for short, ITS) environment, a vehicle’s motion is affected by the information in a large scale. The purpose of this paper is to study the integration effect of multiple vehicles’ delayed velocities on traffic flow.

This paper constructed a new car-following model to study the integration effect of multiple vehicles’ delayed velocities on traffic flow. The new model is analyzed by linear and nonlinear perturbation method theoretically and also verified by simulation.

It is found out that the integration of preceding vehicles’ delayed velocities affect the stability of traffic flow importantly, and three preceding vehicles’ delayed velocities information should be considered in real traffic.

The new car-following model by considering the integration effect of multiple vehicles’ delayed velocities is firstly proposed in this paper. The research result shows that three preceding vehicles’ delayed velocities information is the best choice to stabilizing traffic flow.