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Purpose – This chapter explores ways in which urban women in China balance work and family demands, as the state's protective and welfare functions in post-Mao reform are increasingly being replaced by market forces, and the chapter examines how urban women's enactment of work and family roles are shaped by changing workplaces as well as by their personal and family circumstances. The purpose is to understand the impact of marketization on gender configuration through the lens of the work-family nexus.

Research design – Data come from in-depth interviews conducted between 2005 and 2007 with 115 married women in four large cities. For analytical purposes, the informants were divided into three groups: stay-at-home moms, family-orientated working women, and work/career-oriented women.

Findings – Although market reform may create opportunities for some women to enhance their personal lives, as a consequence of workers' loss of the safety net and welfare benefits, the neglect of women's reproductive work, and the commercialization of child care and child education, it has generated, for many women, much role conflict between work and family. Work/career-oriented women are able to actively engage in market activities precisely because they are protected still by the state, can afford commercial services of domestic tasks, or have strong support from their extended families.

Originality/value – Women's varying role orientations reflect more their strategies of coping with structural changes than their mere adherence to certain gender ideologies.

Social implications – The chapter calls for curbing unbridled market forces and restoring public services so as to create a family/women-friendly work and social environment.

Purpose/approach – This introduction sets forth the main themes of the volume, reviews the methods employed by its contributors, and demonstrates the relationships among the chapters.

Research implications – The introduction demonstrates the ways gender research engages topics of current social, economic, and political importance and the ways in which focus on these topics advances an intersectional approach to gender research.

Practical and social implications – Drawing on each of the chapters, the authors point to the ways in which the global movement of people, media, and ideas foster changes in self-concepts, behavior, and social policy.

Value of the chapter – The essay serves as an overall introduction to the volume.

Cay Anderson-Hanley, Ph.D., is assistant professor of psychology at Union College in Schenectady, NY. She obtained her doctorate from the University at Albany, and completed a postdoctoral fellowship in geriatric neuropsychology at UCLA. Her scientific work has focused on the neuropsychological effects of aging, cancer, and exercise interventions. She teaches clinically oriented courses, including psychological assessment. Cay has served as a co-PI on the NSF Advance grant awarded to Skidmore and Union Colleges since 2008, and contributed to the development and analysis of the climate survey utilized in the chapter in this volume. She has interest in understanding and finding solutions for the challenges of achieving professional-personal life balance for all faculty members, especially as it pertains to facilitating women's advancement in the sciences.

The stock indexes are an important issue for investors, and in this paper good trading strategies will be aimed to be adopted according to the accurate prediction of the stock indexes to chase high returns.

To avoid the problem of insufficient financial data for daily stock indexes prediction during modeling, a data augmentation method based on time scale transformation (DATT) was introduced. After that, a new deep learning model which combined DATT and NGRU (DATT-nested gated recurrent units (NGRU)) was proposed for stock indexes prediction. The proposed models and their competitive models were used to test the stock indexes prediction and simulated trading in five stock markets of China and the United States.

The experimental results demonstrated that both NGRU and DATT-NGRU outperformed the other recurrent neural network (RNN) models in the daily stock indexes prediction.

A novel RNN with NGRU and data augmentation is proposed. It uses the nested structure to increase the depth of the deep learning model.

This article was based on the information from The 5th International Conference of Institutes and Libraries for Chinese Overseas Studies held in the University of British Columbia in Vancouver, BC, Canada in which the author was a presenter in session 4.2.9a of the Early life of Yuan Shikai and the formation of Yuan family. The paper aims to include comprehensive analysis and development of the history of Chinese migration. An annotated bibliography of suggested readings was offered to highlight the subject knowledge for further research in this area.

The paper includes comprehensive analysis and development of the history of Chinese migration and the experiences and family histories of overseas Chinese in Canada. An annotated bibliography of suggested readings was offered to highlight the subject knowledge for further research in this area.

The paper offers full description and comprehensive analysis of the history of Chinese migration and overseas Chinese studies in Canada. A bbibliography of suggested readings was offered for further research in this area.

This research study has a strong subject focus on Chinese migration, overseas Chinese studies, and resource-sharing in the subject area. It is a specific field for research in Asian studies.

The result of this study will assist students, researchers, and the general public in the area of overseas Chinese studies and developing their interests in the social and historical value of Chinese migration history and resource-sharing in the area.

Very little research has been done in the area of Chinese migration and historical development. The paper would offer historians, sociologists, ethnologists, librarians, administrations, professors, as well as students in the fields of Asian history, anthropology, sociology, political science, geography, and other Asian-related interdisciplinary studies.

The paper aims to provide an adaptive neural network controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple and EMI noise.

The design methodology is based on vector control used for electrical machines. MATLAB simulations supported with experimental study under C++ are used.

The simulated and experimental results show that considerable torque ripple as well as current ripple and EMI noise reduction can be achieved by utilizing adaptive neural switching algorithm to fire the inverter supplying the PMSM.

This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied: the effects of harmonics in control signals on the torque ripple can be analyzed; the actual mathematical relation between the torque and flux ripple can be studied to set the flux and torque bands width in reasonable value; different neural network algorithms can be applied to the system to solve the similar problems.

Based on existing DTC control system, it is only required to change the software switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 MHz and the system is supplied with timers. In addition a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC.

In this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are used neural network structure to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a neural network controller is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with EMI noise reduction.

This paper aims to introduce a new structure for coaxial magnetic gears.

The study discusses the design and electromagnetic modeling of a triple-speed coaxial magnetic gear (TSCMG) for three different levels of torques in special applications such as wind energy conversion and electrical vehicles. The proposed TSCMG consists of inner, middle and outer rotor, which has one rotor more than its conventional counterpart. The suggested TSCMG’s related equations such as transform ratio and torque are calculated, then TSCMG is simulated in a finite element environment. A comprehensive study has been done on TSCMG, and results are compared with two other magnetic gears with the same volume but two speeds.

The obtained results show that the proposed structure for TSCMGs is significantly practical and applicable in higher ranges of torques. Finally, an experimental TSCMG is prototyped to verify the results.

The achievements are excellent and confirm that TSCMG can be used as powerful equipment in a wide range of application like permanent wind turbines to generate electricity in 24 h per every single day.