Dissertation Defense Announcements

This dissertation investigates a newly emerging phenomenon in Chinese higher education in which a Chinese university partners with an overseas university to open a new university campus in China which began in 2004. This form of university was established in the context of economic growth and education reform in Chinese society. It has brought a change to the rebuilding of nonpublic higher education in China since the late 1980s. It also reinforces the emphasis on internationalization and diversification of higher education set by Chinese government for the 21st century. However, as a joint venture in higher education, this form of education is still unknown to many education scholars with respect to its formation mechanisms and motivations. Moreover, given the changing landscape of Chinese higher education, the current status and future prospects of this type of university are worthy of study considering its benefits as well as challenges for Chinese and the global higher education development. What is more, the social, economic, and policy implications of these universities are even more enormous than its education perspective.
This dissertation is an exploratory case study involving intensive interviews with seven administrators and nine students from four institutions in this study along with content analysis of mission statements and school documents involving all nine institutions in this group. Findings suggest that the emergence of joint venture universities is consistent with the growing trend of globalization and internationalization in worldwide higher education development. Motivations and goals of institutions in pursuing this cooperation may vary among countries. China’s governmental involvement in this kind of education signifies a new trend in higher education collaboration that incorporates governmental interest in political, economic, and global pursuits rather than focusing on the education per se. Thus, this type of joint venture universities is neither public nor private. An unexpected finding is that the emergence of this form of education did not improve education inequality existing in Chinese higher education due to geographical location but reinforce the reproduction of inequality. Also, the small number of special joint venture universities in China seem to aim more for advancing China’s international goals to engage on the global stage, foster China’s active globalization efforts, and prepare Chinese students to be academically and socially ready for globalization. These findings thus have substantial implications for policymakers in relevant areas and help them in policymaking decisions.

Deep neural networks (DNN) are proved to be effective and improve the performance dramatically in various kinds of computer vision tasks. The end-to-end learning manner in training DNN consistently shows the powerful modeling ability and consequently mitigates the dedicated efforts for expert feature engineering. On the other hand, it raises the issue that how to improve the black-box network with better representation (feature) learning especially when the learned representations and classifiers are tied together in the manner of supervised learning. In this work, representation learning is studied in four perspectives of different fields, i.e. diversity in ensemble learning, aspect ratio in image aesthetics assessment, invariance in identification task, and composition in color attribute recognition.

In light of analyzing the bottleneck of black-box network and designing better representation learning for target tasks, we introduce that: (a) Ensemble learning relies on the diversity of the complementary neural networks, in both feature representations and classifier representations. A diverse representation learning method, namely learning-difficulty-aware embedding, is proposed to adaptively reconcile learning attentions for different categories by training a series of networks with diversified representations sequentially; (b) Widely-adopted data augmentation method in image recognition deteriorates aspect ratios, which is an important factor in image aesthetics assessment. An aspect ratio representation learning method, namely adaptive fractional dilated convolution, is proposed to explicitly preserve the learning representation related to aspect ratios by adjusting the receptive fields adaptively and natively; (c) Identification tasks, e.g. person re-identification, aim at learning representations that are robust to interfering variances, e.g. lighting variances, view variances, pose variances. An invariance representation learning method, namely anchor loss, is proposed to train a robust feature extractor, which distills the identity-related representations while disentangling and removing interfering variances by global supervision under local mini-batch training; (d) Color recognition is entangled with compositional representation in both visual perception and language attentions. A compositional learning module with attention to key colors is proposed to learn better color representations. Besides, another compositional learning method, namely classifier as descriptor, is proposed for long-tail color recognition by incorporating the rich knowledge in classifier representations to remove the bias from bias-trained
model.

Through extensive experiments and thorough analysis, we demonstrate some novel insights about the impacts of four factors, i.e. diversity, receptive field, invariance, and composition. Several methods are proposed to learn better representations for those factors, achieving state-of-the-art results in different tasks.

This quantitative study explores the potential school-level and school district-level factors associated with North Carolina school performance grades in K-5 elementary schools. The desire was to examine if any of the school- or school district-level factors were associated with the outcome variable of North Carolina school performance grades. This study used the data from the North Carolina school report cards and Civil Rights Data Collection from the 2015 – 2016 school year. The sample had 1096 schools and 92 school districts. A hierarchical linear model was created with the overall school performance grade as the outcome variable and the sixteen school level predictors and thirteen school district predictors. Results indicated that twelve out of sixteen school-level variables were statistically significant. One out of thirteen school district-level variables were statistically significant and two additional variables approached significance. Recommendations for improving student achievement were provided for United States policymakers, university education programs, North Carolina policymakers, local governments, school districts, and schools. These recommendations are presented as opportunities to ensure equitable educational practices and outcomes for all students.

The maintenance of genome integrity and fidelity is essential for the proper function and survival of all organisms. Recent studies have revealed that APE2 is required for the activation of an ATR-Chk1 DNA damage response (DDR) pathway in response to oxidative stress and a defined DNA single-strand break (SSB) in Xenopus laevis egg extracts. However, it remains unclear whether APE2 is a general regulator of DDR pathway and what the biological significance of APE2 is in mammalian cells. Here, I provide evidence using mammalian cultured cell lines including human pancreatic cancer cells that APE2 is important for ATR DDR pathway activation in response to different stressful conditions including oxidative stress, DNA replication stress, and DNA double-strand breaks. Fluorescence microscopy analysis shows that APE2-knock-down (KD) leads to enhanced γH2AX foci and increased micronuclei formation. In addition, a small molecule compound is identified as APE2 inhibitor that specifically compromises the binding of APE2 to ssDNA, its 3′-5′ exonuclease activity, and the defined SSB-induced ATR Chk1 DDR pathway in Xenopus egg extracts. Notably, cell viability assays demonstrate that APE2-KD or APE2 inhibitor sensitizes pancreatic cancer cells to chemotherapy drugs. Overall, APE2 is proposed as a general regulator for DDR pathway in genome integrity maintenance in mammalian cells.