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Aluminum nitride (AlN) ceramics are suitable substrate and package materials for high-power integrated circuits.

Dense AlN ceramics with Y₂O₃ and LaF₃ as sintering additives are prepared. The effects of these additives on the density, phase composition, microstructure and thermal conductivity of AlN ceramics are investigated.

Results show that 2 Wt.% Y₂O₃-doped additive is insufficient for the samples to achieve the full densification sintered at 1,700°C. When LaF₃ is added with Y₂O₃, the samples are perfectly densified at the same sintering condition. The relative density and thermal conductivity of the samples are 97.8-99.07 per cent and 169.104-200.010 W·m-1·K-1, respectively. The density of the samples and their microstructure, especially the content and distribution of secondary phases, is necessary to control the thermal conductivity of AlN ceramics.

Y₂O₃ and LaF₃ additives can effectively promote densification and enhance the thermal conductivity of AlN ceramics in a low sintering temperature, and the AlN ceramics added with Y₂O₃-LaF₃ might have potential applications in package materials for high-power integrated circuits.

This paper aims to reasonably quantify the radial deformation of turbine blade from a probabilistic design perspective. A probabilistic design for turbine blade radial deformation considering non-linear dynamic influences can quantify risk and thus control blade tip clearance to further develop the high performance and high reliability of aeroengine. Moreover, the need for a cost-effective design has resulted in the development of probabilistic design method with high computational efficiency and accuracy to quantify the effects of these uncertainties.

An extremum response surface method-based support vector machine (SVM-ERSM) was proposed based on SVM of regression to improve the computational efficiency and precision of blade radial deformation dynamic probabilistic design regarding non-linear material properties and dynamically thermal and mechanical loads.

Through the example calculation and comparison of methods, the results show that the blade radial deformation reaches at the maximum at t = 180 s; the probabilistic distribution and inverse probabilistic features of output parameters and the major factors (rotor speed and gas temperature) are gained; besides, the SVM-ERSM holds high computational efficiency and precision in the non-linear dynamic probabilistic design of aeroengine typical components.

The present efforts provide a method to design turbine besides other aeroengine components considering dynamic and non-linear factors base on probabilistic design for further research.

Moreover, the present study provides a way to design dynamic (motion) structures from a probabilistic perspective.

It is proved that the dynamic probabilistic design-based SVM-ERSM could produce a more reasonable blade radial deformation while maintaining low failure probability, as well as offer a useful reference for blade-tip clearance control and a promising insight to the optimal design of aeroengine typical components.

This paper aims to examine the attractiveness of the Tong Ren Tang (TRT) as a Chinese corporate heritage tourism brand and consider the significance of TRT for Chinese national identity. The study considers the saliency of Balmer’s augmented role identity notion vis-à-vis corporate heritage institutions/corporate brands. Insights are made from and for corporate heritage, heritage tourism and national identity literature.

A conceptual model comprising five hypotheses was developed and this informed a survey-based questionnaire administered to domestic tourists/customers visiting Tong Ren Tang’s flagship shop in Beijing.

The attractiveness to domestic Chinese tourists/customers of the TRT corporate heritage tourism brand was found to be attributable to its multiple role identities: national, corporate, temporal, familial and imperial. As such, this study lends credence to Balmer’s augmented role identity notion. Chinese domestic tourists/customers – as members of an ethnic Chinese community – in visiting TRT not only consume an extant corporate heritage by tangible and intangible means but can also be seen to express, and reaffirm, their sense of Chinese national identity.

For TRT’s managers, there should be an appreciation that the attractiveness of TRT as a corporate heritage tourism brand rests not only on what it sells but also in what it symbolises in national and cultural terms. This finding is applicable to the managers of many other corporate heritage/corporate heritage tourism brands.

Adopting a primordial perspective, the TRT pharmacy was found to be of singular significance to China’s national identity. Traditional Chinese Medicine, Confucian and Daoist religious/philosophical and China’s erstwhile Imperial polity are significant and enduring precepts of Chinese national identity. As such the TRT flagship shop/brand is of singular importance, as China has eviscerated much of its cultural heritage – particularly in relation to its corporate heritage brands.

This is the first empirical study to focus on corporate heritage tourism brands and one of the first studies to examine a Chinese corporate heritage/corporate heritage tourism brand. Also significant in focussing on the TRT corporate heritage brand. Established in 1669, TRT’s history spans five centuries: a corporate provenance which is exceptional within the People’s Republic of China. The study links the corporate brand notion with the nascent corporate heritage brand domain and the established area of heritage tourism.

The purpose of this paper is to target on designing a short-term load prediction framework that can accurately predict the cooling load of office buildings.

A feature selection scheme and stacking ensemble model to fulfill cooling load prediction task was proposed. Firstly, the abnormal data were identified by the data density estimation algorithm. Secondly, the crucial input features were clarified from three aspects (i.e. historical load information, time information and meteorological information). Thirdly, the stacking ensemble model combined long short-term memory network and light gradient boosting machine was utilized to predict the cooling load. Finally, the proposed framework performances by predicting cooling load of office buildings were verified with indicators.

The identified input features can improve the prediction performance. The prediction accuracy of the proposed model is preferable to the existing ones. The stacking ensemble model is robust to weather forecasting errors.

The stacking ensemble model was used to fulfill cooling load prediction task which can overcome the shortcomings of deep learning models. The input features of the model, which are less focused on in most studies, are taken as an important step in this paper.

The purpose of this paper is to investigate the impact of increasing trade and investment relations between China and Latin American economies. The paper focuses on the threats and opportunities that permeate this relationship.

The paper surveys existing literature and secondary data in Spanish, Portuguese, and in English to investigate the different ramifications of this dynamic relationship between China and Latin American economies.

After analyzing trade and investment trends and data, it is clear that Latin American economies must make changes to increase their participation in the Chinese market. Direct involvement with China is inherently risky, however, the opportunities obviously make the alliance necessary. Latin American economies are under increasing pressure to revamp their business environments and to implement long‐term strategies in order to compete more efficiently with China, domestically and in third‐markets. China has showed Latin American economies that investments in education, R&D, innovation, infrastructure, and friendly business policies, both facilitate and foster the creation of new competitive advantages.

This paper highlights and contributes to a better understanding of the ongoing challenges and opportunities permeating the Chinese Latin America's trade and investment relationship, as well as a indicating a number of areas for further study.

This paper aims to compare the Greek and Chinese rhetorical traditions and explore their influences on today’s business and marketing communication across relevant cultures. In particular, it uses the Aristotelian persuasive orientations as reference points to introduce the Chinese rhetoric, and interpret cultural differences in persuasion from a historical and sociocultural perspective. It has been found that Greek and Chinese rhetoric and persuasion were developed to meet the needs of the social and cultural environments and this rule still applies to today’s business communication. The logical approach has been emphasised in the English rhetorical tradition while both qing (emotional approach) and li (logical approach) are the focus of persuasion in the Chinese tradition. This difference is also the root of cultural differences in modern business communication. Findings from both English and Chinese texts and data are examined to substantiate our focal argument.

The purpose of this paper is to build a transient wear prediction model of surface topography of textured work roll, and then to investigate the wear performance of different original textured surfaces. The surface topography of steel sheets is one of the most important surface quality indexes, which is inherited from the textured work rolls in cold rolling. Surface topography of work roll is obviously changing in the cold rolling process. However, surface topography is difficult to measure in the industry production process.

This paper presents a numerical approach to simulate the wear process based on the mixed lubrication model of cold rolling interface developed by Wilson and Sheu (Sheu and Wilson, 1994). It is assumed that wear takes place at locations where the surfaces are in direct contact, and the volume is removed by an abrasive particle which is an abstract concept based on the wear phenomenon of textured work roll. At each simulation cycle, the distribution of the contact pressure is calculated by the lubrication model. The material is removed by an abstract abrasive particle and the surface topography is modified correspondingly. The renewed surface topography is then used for the next cycle.

Through comparative analysis, it can be found that the simulation results possess similar statistical characteristic with the measured data. A set of roughness parameters such as the amplitude, spacing and frequency-domain characteristics are introduced to analyze the wear performance of different textured surfaces. Numerical examples show that the surface topography has a significant effect on the wear performance of work roll in cold rolling.

The proposed model can accurately predict the wear process of the surface topography in the cold rolling process, which provides the foundation for optimization of original surface topography of textured work roll. The model can also be considered as a tool applicable for research on control of the surface topography of steel strip in the cold rolling process.