Supported Group II Transition Metal Catalysts in Liquid Phase Reactions using Borrowing Hydrogen Methodology

Ph.DDOCTOR OF PHILOSOPH

An empirical study on the endogeneity of directed technical change in China

Research on the endogeneity of directed technical change is very interesting and meaningful. If the direction of technical change is endogenous, policy makers can adjust the technical change value of factors according to specific purpose. We establish a theoretical model of the direction of technical change, relative price of factors and international trade under nested and non-nested CES production functions. We use mature measurement methods such as the unit root test and cointegration analysis to test the theoretical model in practice. We find that the direction of technical change is endogenous in China. The change in the relative price of factors in China causes a technical change in the same direction. Meanwhile, international trade intensifies and accelerates the labour augmenting technical change, but blocks the pace of capital augmenting technical change. Under a substitution elasticity of less than one, technical change is biased toward energy and capital in China, and this bias is brought about by the decrease in their relative price and international trade

Are Smell-Based Metrics Actually Useful in Effort-Aware Structural Change-Proneness Prediction? An Empirical Study

Bad code smells (also named as code smells) are symptoms of poor design choices in implementation. Existing studies empirically confirmed that the presence of code smells increases the likelihood of subsequent changes (i.e., change-proness). However, to the best of our knowledge, no prior studies have leveraged smell-based metrics to predict particular change type (i.e., structural changes). Moreover, when evaluating the effectiveness of smell-based metrics in structural change-proneness prediction, none of existing studies take into account of the effort inspecting those change-prone source code. In this paper, we consider five smell-based metrics for effort-aware structural change-proneness prediction and compare these metrics with a baseline of well-known CK metrics in predicting particular categories of change types. Specifically, we first employ univariate logistic regression to analyze the correlation between each smellbased metric and structural change-proneness. Then, we build multivariate prediction models to examine the effectiveness of smell-based metrics in effort-aware structural change-proneness prediction when used alone and used together with the baseline metrics, respectively. Our experiments are conducted on six Java open-source projects with up to 60 versions and results indicate that: (1) all smell-based metrics are significantly related to structural change-proneness, except metric ANS in hive and SCM in camel after removing confounding effect of file size; (2) in most cases, smell-based metrics outperform the baseline metrics in predicting structural change-proneness; and (3) when used together with the baseline metrics, the smell-based metrics are more effective to predict change-prone files with being aware of inspection effort

Industry’s going upstairs: The innovative usage of industrial land and evaluation of its economic effects

The concept of ‘Industry’s Going Upstairs (IGU)’ represents an innovative usage of industrial land that transfers the enterprises’ production to high-rise industrial buildings. It is emerging in the developed areas of eastern China. This study discusses IGU policies to promote local economic development and conducts an empirical test using Guangdong city-level data and a differencein- differences model. Theoretical analysis shows that IGU can broaden the development space of enterprises and realise industrial and labour agglomeration under supporting policies provided by local governments. The empirical results demonstrate that IGU can improve land-use efficiency and promote local industrial development. IGU is a feasible approach for addressing the current shortage of industrial land in China and is worthy of promotion and replication in other regions

Overcoming Catastrophic Forgetting in Graph Neural Networks

Catastrophic forgetting refers to the tendency that a neural network "forgets" the previous learned knowledge upon learning new tasks. Prior methods have been focused on overcoming this problem on convolutional neural networks (CNNs), where the input samples like images lie in a grid domain, but have largely overlooked graph neural networks (GNNs) that handle non-grid data. In this paper, we propose a novel scheme dedicated to overcoming catastrophic forgetting problem and hence strengthen continual learning in GNNs. At the heart of our approach is a generic module, termed as topology-aware weight preserving~(TWP), applicable to arbitrary form of GNNs in a plug-and-play fashion. Unlike the main stream of CNN-based continual learning methods that rely on solely slowing down the updates of parameters important to the downstream task, TWP explicitly explores the local structures of the input graph, and attempts to stabilize the parameters playing pivotal roles in the topological aggregation. We evaluate TWP on different GNN backbones over several datasets, and demonstrate that it yields performances superior to the state of the art. Code is publicly available at \url{https://github.com/hhliu79/TWP}.Comment: Accepted by AAAI 202

Application of Time-Fractional Order Bloch Equation in Magnetic Resonance Fingerprinting

Magnetic resonance fingerprinting (MRF) is one novel fast quantitative imaging framework for simultaneous quantification of multiple parameters with pseudo-randomized acquisition patterns. The accuracy of the resulting multi-parameters is very important for clinical applications. In this paper, we derived signal evolutions from the anomalous relaxation using a fractional calculus. More specifically, we utilized time-fractional order extension of the Bloch equations to generate dictionary to provide more complex system descriptions for MRF applications. The representative results of phantom experiments demonstrated the good accuracy performance when applying the time-fractional order Bloch equations to generate dictionary entries in the MRF framework. The utility of the proposed method is also validated by in-vivo study.Comment: Accepted at 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019

Genome Editing of \u3cem\u3eWnt-1\u3c/em\u3e, a Gene Associated with Segmentation, via CRISPR/Cas9 in the Pine Caterpillar Moth, \u3cem\u3eDendrolimus punctatus\u3c/em\u3e

The pine caterpillar moth, Dendrolimus punctatus, is a devastating forest pest. Genetic manipulation of this insect pest is limited due to the lack of genomic and functional genomic toolsets. Recently, CRISPR/Cas9 technology has been demonstrated to be a promising approach to modify the genome. To investigate gene functions during the embryogenesis, we introduced CRISPR/Cas9 system in D. punctatus to precisely and effectively manipulate gene expressions inmutant embryos. Compared to controls, knocking out of DpWnt-1, a gene well known for its role in the early body planning, led to high embryonic mortality. Among these mutants, 32.9% of the embryos and larvae showed an abnormal development. DpWnt-1 mutants predominantly exhibited abnormal posterior segments. In addition, multiple phenotypes were observed, including the loss of limbs and the head deformation, suggesting that DpWnt-1 signaling pathway is necessary for anterior segmentation and appendage development. Overall, our results demonstrate that CRISPR/Cas9 system is feasible and efficient in inducing mutations at a specific locus in D. punctatus. This study not only lays the foundation for characterizing gene functions in a non-model species, but also facilitates the future development of pest control alternatives for a major defoliator

Genome Editing of \u3cem\u3eWnt-1\u3c/em\u3e, a Gene Associated with Segmentation, via CRISPR/Cas9 in the Pine Caterpillar Moth, \u3cem\u3eDendrolimus punctatus\u3c/em\u3e

The pine caterpillar moth, Dendrolimus punctatus, is a devastating forest pest. Genetic manipulation of this insect pest is limited due to the lack of genomic and functional genomic toolsets. Recently, CRISPR/Cas9 technology has been demonstrated to be a promising approach to modify the genome. To investigate gene functions during the embryogenesis, we introduced CRISPR/Cas9 system in D. punctatus to precisely and effectively manipulate gene expressions inmutant embryos. Compared to controls, knocking out of DpWnt-1, a gene well known for its role in the early body planning, led to high embryonic mortality. Among these mutants, 32.9% of the embryos and larvae showed an abnormal development. DpWnt-1 mutants predominantly exhibited abnormal posterior segments. In addition, multiple phenotypes were observed, including the loss of limbs and the head deformation, suggesting that DpWnt-1 signaling pathway is necessary for anterior segmentation and appendage development. Overall, our results demonstrate that CRISPR/Cas9 system is feasible and efficient in inducing mutations at a specific locus in D. punctatus. This study not only lays the foundation for characterizing gene functions in a non-model species, but also facilitates the future development of pest control alternatives for a major defoliator