Appropriate flow forecasting for reservoir operation

The aim of the study presented in this thesis is to develop and apply a methodology to determine the appropriate model application by including the water management objective explicitly, and to demonstrate its benefits

Roles of TGFβ and FGF signals during growth and differentiation of mouse lens epithelial cell in vitro.

Transforming growth factor β (TGFβ) and fibroblast growth factor (FGF) signaling pathways play important roles in the proliferation and differentiation of lens epithelial cells (LECs) during development. Low dosage bFGF promotes cell proliferation while high dosage induces differentiation. TGFβ signaling regulates LEC proliferation and differentiation as well, but also promotes epithelial-mesenchymal transitions that lead to cataracts. Thus far, it has been difficult to recapitulate the features of germinative LECs in vitro. Here, we have established a LEC culture protocol that uses SB431542 (SB) compound to inhibit TGFβ/Smad activation, and found that SB treatment promoted mouse LEC proliferation, maintained LECs' morphology and distinct markers including N-cadherin, c-Maf, Prox1, and αA-, αB-, and β-crystallins. In contrast, low-dosage bFGF was unable to sustain those markers and, combined with SB, altered LECs' morphology and β-crystallin expression. We further found that Matrigel substrate coatings greatly increased cell proliferation and uniquely affected β-crystallin expression. Cultured LECs retained the ability to differentiate into γ-crystallin-positive lentoids by high-dosage bFGF treatment. Thus, a suppression of TGFβ/Smad signaling in vitro is critical to maintaining characteristic features of mouse LECs, especially expression of the key transcription factors c-Maf and Prox1

Appropriate spatial sampling of rainfall for flow simulation

The objective of this study is to find the appropriate number and location of raingauges for a river basin for flow simulation by using statistical analyses and hydrological modelling. First, a statistical method is used to identify the appropriate number of raingauges. Herein the effect of the number of raingauges on the cross-correlation coefficient between areally averaged rainfall and discharge is investigated. Second, a lumped HBV model is used to investigate the effect of the number of raingauges on hydrological modelling performance. The Qingjiang River basin with 26 raingauges in China is used for a case study. The results show that both cross-correlation coefficient and modelling performance increase hyperbolically, and level off after five raingauges (therefore identified to be the appropriate number of rain-gauges) for this basin. The geographical locations of raingauges which give the best and worst hydrological modelling performance are identified, which shows that there is a strong dependence on the local geographical and climatic patterns

Exploring the relative contributions of learning motivations and test perceptions to autonomous English as a foreign language learning and achievement

Past studies on the contributions of language learning motivations and test perceptions to language learning have been conducted relatively independently, with few simultaneously gauging the relative effects of these two types of variables on learning behaviors and outcome. In contexts where testing plays a significant role in language education, it is argued that both types of variables are likely to influence language learning. Through a series of multiple regression analyses, this study juxtaposed the relative effects of three types of language learning motivation (i.e., integrative, development and requirement motivation) and two types of perception of a high-stakes English test on Chinese high school students’ (n = 3,105) EFL learning practice and achievement, casting fresh lights on the motivational factors that may drive EFL learning. More specifically, it was found that integrative and development motivations were the major drives behind students’ overall effort expenditure on EFL learning for Year 1 students. For students from higher grades who were more closely confronted with the test, however, the effect of development motivation diminished and that of perceived test validity increased. The same pattern applied to students’ reported learning achievement. The motivational profiles behind each specific type of learning practice and their variational patterns across grades were also found to differ. Implications for both research and educational practice are discussed

The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training

Although current deep learning techniques have yielded superior performance on various computer vision tasks, yet they are still vulnerable to adversarial examples. Adversarial training and its variants have been shown to be the most effective approaches to defend against adversarial examples. These methods usually regularize the difference between output probabilities for an adversarial and its corresponding natural example. However, it may have a negative impact if the model misclassifies a natural example. To circumvent this issue, we propose a novel adversarial training scheme that encourages the model to produce similar outputs for an adversarial example and its ``inverse adversarial'' counterpart. These samples are generated to maximize the likelihood in the neighborhood of natural examples. Extensive experiments on various vision datasets and architectures demonstrate that our training method achieves state-of-the-art robustness as well as natural accuracy. Furthermore, using a universal version of inverse adversarial examples, we improve the performance of single-step adversarial training techniques at a low computational cost