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The reaction dynamics of combustible clouds at high temperatures and pressures are a common form of energy output in aerospace and explosion accidents. The cloud explosion process is often affected by the external initial conditions. This study aims to numerically study the effects of airflow velocity, initial temperature and fuel concentration on the explosion behavior of isopropyl nitrate/air mixture in a semiconstrained combustor.

The discrete-phase model was adopted to consider the interaction between the gas-phase and droplet particles. A wave model was applied to the droplet breakup. A finite rate/eddy dissipation model was used to simulate the explosion process of the fuel cloud.

The peak pressure and temperature growth rate both decrease with the increasing initial temperature (1,000–2,200 K) of the combustor at a lower airflow velocity. The peak pressure increases with the increase of airflow velocity (50–100 m/s), whereas the peak temperature is not sensitive to the initial high temperature. The peak pressure of the two-phase explosion decreases with concentration (200–1,500 g/m³), whereas the peak temperature first increases and then decreases as the concentration increases.

Chain explosion reactions often occur under high-temperature, high-pressure and turbulent conditions. This study aims to provide prevention and data support for a gas–liquid two-phase explosion.

Sustained turbulence is realized by continuously injecting air and liquid fuel into a semiconfined high-temperature and high-pressure combustor to obtain the reaction dynamic parameters of a two-phase explosion.

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.

Product quality inspection is of importance in manufacturing industries to ensure that low quality or unqualified products are not delivered to the consumer. Human inspection has many limitations such as low accuracy or speed due to factors such as tiredness and boredom. Traditional 2D vision inspection also has limitations of product shape complexity or flexibility. Thus, automated 3D vision inspection is anticipated to meet the requirements of higher applicability. This paper seeks to address these issues.

In many product quality inspection problems, geometrical parameters of the industrial parts are commonly used as the basis of quality inspection. Machine vision is widely applied to acquire such kind of parameters. Comparing to traditional 2D vision, 3D vision can acquire 3D coordinates of the object directly, so that the inspection can be accomplished which is difficult to do with 2D vision. As an active vision technique, structure light system (SLS) is applied to acquire the 3D coordinate information of inspected object in this paper. On the basis of point cloud and regression analysis, features relative to quality are defined and extracted as the attributes for the product classification. Three data mining techniques are applied to accomplish the classification in this paper, which include decision trees, artificial neural networks and support vector machine.

A new intelligent automated 3D vision quality inspection for assembly lines has been developed, which comprises structure light system (SLS) and data mining approaches such as decision tree, artificial neutral networks and support vector machine.

The combination of structure light system (SLS) and data mining approaches makes the automated quality inspection available. The proposed system is easy to be implemented and flexible for different types of products.

Reports a study of 1,304 Chinese brand names of ten types of products in China. These brand names are content analyzed following a linguistic approach which the authors developed from their earlier studies. The ten types of brand names are presented in three broad categories representing the three different developing stages of the consumer product industry in China: brands of traditional products (illustrated by matches and spirits), brands of traditional products with current development (illustrated by bicycles, shoes, and toothpastes), and brands of new and modern products (illustrated by cosmetics, soft drinks, washing machines, refrigerators and TV sets). The conclusion drawn from the analysis is that one of the variables in determining how linguistic principles are being applied to Chinese brand naming is the respective stages of development of such products in the context of the Chinese market economy.

This paper proposes that if a political system is more like to facilitate a unified government, to establish a strong executive body and to respond to the needs of the majority, financial reforms are more likely to emerge from the policymaking process and produce positive results. On the contrary, political systems that discourage those governing features are less likely to produce reforms. This chapter compares financial reform processes in China, Taiwan and New Zealand. All of them performed low level of financial reforms in the early 1980s but resulted in different situations later. In the mid-2000s, New Zealand heralded the most efficient and stable financial system; while Taiwan lagged behind and China performed the worst. Evidence showed that China’s authoritarian system may be the most superior in forming a unified government with a strong executive, but the policy priority often responds more to the interests of a small group of power elites; therefore the result of financial reform can be limited. Taiwan’s presidential system can produce greater financial reform when the ruling party controls both executive and legislative bodies, but legislative obstructions may occur under a divided government. New Zealand's Westminster system produces the most effective and efficient financial reform due to its unified government and a strong executive branch with consistent and stable supports from the New Zealand Parliament.

This is the third of a series of studies on Chinese brand naming using content analysis from a linguistic perspective. The first study generalized the principles guiding Chinese brands in terms of syllable pattern, tone pattern, compounding structure and semantic preference. The second looked at specific branding rules, focusing on two entirely different products: cosmetic products and bicycles. The present study, following the same linguistic framework of analysis, analyzes three groups of closely related products: spirits, beers, soft drinks, to see how these brands are creatively and distinctively constructed. Finds that the brand naming patterns of the three drinks are basically in agreement with the general Chinese branding principles, and the differences among them directly reflect the development, the consumer markets and characteristics of each product.

Using the theoretical frameworks of public diplomacy and public relations, we mapped how the Chinese government has used panda imagery to build its national brand on Twitter and how this ‘panda diplomacy’ has facilitated its para-diplomatic actions. Our findings uncover new attempts by the Chinese government to engage in digital diplomacy. Mobilizing panda imagery on Twitter enhanced friendly relations with foreign political leaders and people and established a friendly and peaceful image of China on Twitter.

The purpose of this study is to look at the factors that drive people to participate in the sharing economy (SE). Based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), the study proposes a mathematical model. The study’s ultimate objective is to help businesses attract more involved customers and promote collaborative consumption as a sustainable alternative to typical consumption patterns. The study offers a conceptual framework established via a thorough literature review to examine Indian customers’ use behavior toward SE platforms. A one-sample two-tailed t-test is used to assess the framework’s efficacy. The research fills gap in the literature on the SE by investigating the factors that determine subjective norms (SN), attitudes (A), and perceived behavioral control (PBC). A framework is provided that takes behavioral intention (BI) contemplated as a mediating variable. The research improves TAM and TPB by including new factors such as technical characteristics. This research adds to the body of knowledge on the digital SE by underlining the relevance of usage behavior in comprehending Indian customers, where A, SN, and PBC are important aspects. The research presents a paradigm for better understanding customers’ attitudes and behaviors toward various SE platforms, which might help academics, practitioners, and policy makers situate their initiatives within the larger field of sharing. The study’s categorizations of Indian consumers’ A, SN, PBC, and BI toward the SE might potentially advise on future research and government policies.

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.