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P450 enzymes activate C-H bonds via the insertion of an oxygen atom from atmospheric dioxygen under ambient conditions in water and accept a broad array of endogenous and exogenous organic substrates. P450BM3 (CYP102A1) has a unique structure, with the electron-transfer reductase domain fused to the haem monooxygenase domain. This makes P450BM3 catalytically self-sufficient and promotes high turnover rates. Functionalised cyclic amines are versatile intermediates in drug synthesis and important fragment molecules in drug discovery. Selective oxidation of unactivated ring aliphatic C-H bonds is an attractive route to cyclic amine derivatives; however, classical synthetic methods are limited in scope and lack enantioselectivity. The application of engineered P450 enzymes for selective functionalisation of cyclic amines is surprisingly under-explored. Chapter 2 describes the substrate and enzyme engineering to access remote hydroxylation products of the medium-sized cyclic amines azepane and azocane. Variant library screening is deployed to identify key residues affecting product selectivity, substrate engineering is utilised to alter the selectivity patterns, and rational design is conducted to improve product selectivity. In Chapter 3, the iterative docking-guided mutagenesis (IDGM) approach is explored. Comparative analysis of the correct binding poses and unwanted poses leads to targeted mutation design to disfavour unwanted poses and increase both the activity and product selectivity of amine oxidation. In Chapter 4, the combined enzyme evolution strategies are used for more complex cyclic amines - the bicyclic, 7-azabicyclo[2.2.1]heptane, and spirocyclic, 8-azaspiro[5.4]decane. These approaches led to scalable enantioselective oxidation of all but one of the unactivated C-H bonds in these important cores of drugs and fragment libraries.

The study of decision making under uncertainty is important in many areas (e.g. portfolio theory, control theory and utility theory). The exogenous and endogenous uncertainties, such as variations in stock prices, changes in consumer demand and ambiguity about investor's risk attitude, are beyond deciders' control and knowledge and significantly influence the effectiveness of any decision. In this thesis, we concentrate on this issue and propose some efficient models to deal with the uncertainties. Specifically, (a) we introduce a utility-based reward-risk ratio (URR) optimization model and consider a situation where an investor does not have complete information on the probability distribution of the underlying random variables, and we propose a distributionally robust URR optimization model to mitigate the risk arising from ambiguity of the true probability distribution; (b) we introduce a multivariate utility-based shortfall risk measure (MSR) and focus on a case that a decision maker's true loss function in the definition of MSR is unknown but it is possible to elicit a set of plausible loss functions with partial information, and consequently propose a robust formulation of MSR based on the worst case loss function; (c) we investigate an issue that whether a statistical estimator such as the optimal value of a preference robust optimization model based on empirical data is reliable when the empirical data contain some noise, and we derive moderate sufficient conditions under which the optimal value of the model is robust against perturbation of the exogenous uncertainty data.

The failure of highly active antiretroviral therapy may be due to pharmacological factors such as drug transporters and metabolism enzymes. Drug transporters and metabolism enzymes played complementary roles in drug absorption, distribution, metabolism and excretion by biotransformation and counter-transport, particularly in the intestine while nuclear receptors as transcription factors regulate the expression of drug transporters and metabolism enzymes. In this thesis, a positive correlation between nuclear receptors expression and the expression of ABC transporters and OATP transporters in intestine were observed while a negative correlation was found between the gene expression of nuclear receptors and cytochrome P450 enzymes in intestine. Single nucleotide polymorphisms in genes could potentially impact on gene expression of drug transporters and metabolism enzymes. The polymorphisms of nuclear receptors were associated with the expression of ABC transporters. Drug concentrations have a high inter-individual variability in patients receiving the same dose of antiretroviral drugs, which could affect outcome of antiretroviral therapy. There are many factors that may affect plasma concentrations such as age, gender, body weight, ethnicity, genetic factors and so on. In a Ghanaian cohort, a negative correlation was found between the body weight and the EFV plasma concentration. Genetic factors such as the polymorphisms of cytochrome P450 enzymes also influenced efavirenz plasma concentrations. Meanwhile, efavirenz plasma concentrations were associated with the viral load in plasma within a UK cohort. Nanomedicine involves new and promising technologies that may enable and improve the targeted delivery of antiretroviral drugs. The permeability of lopinavir in the Caco-2 cell line was improved by formulation of nanodispersions. However, the permeability of efavirenz was decreased for all nanodispersions in MDCKII and MDCKII-ABCB5 cell lines. Comparing efficiency of efavirenz nanodispersions transcellular permeability in MDCKII and MDCKII-ABCB5 cell lines indicated that ABCB5 is able to transport efavirenz when incubated as dissolved molecule or nanodispersion. It is support by the copy number variation of ABCB5 had no relationship with EFV plasma concentrations. In summary, this thesis has attempted to determine the pharmacological factors influencing pharmacokinetics of HIV drugs, including drug transporters, metabolism enzymes and nuclear receptors. Data illustrating the factors that influence efavirenz plasma concentrations which are important for viral suppression were also generated. Furthermore, the nanodispersion technology is worthy of further study in order to improve drug delivery and drug distribution of antiretroviral drugs.

The current study adopts Spencer-Oatey's theory of rapport management as the main framework, and examines the IT A participants' perceptions of their management of rapport, i.e. social relationship, with their American undergraduates, which are also compared with perceptions of American counterparts, including American professor and ATA participants. An analysis is also made on how these perceptions are manifested in the interaction between instructor participants and undergraduate student participants. The current research employs two categories of data: interview data from instructor participants, and naturally occurring interactional data from instructor participants and their respective students. 9 ITAs, 11 ATAs, and 9 American professors participated in the interview, and interactional data, in the form of office-hour or in-class talk, were collected from 2 ITAs, 2 ATAs, and 1 American professor and their respective students. Both types of data were recorded with audio-recorder and were transcribed for analysis. The current study has shown that ITA participants have acquired the essence in their understanding of American interpersonal rapport culture with respect to teaching, and they are capable of employing a certain number of strategies to strengthen rapport with American undergraduates, as well as strategies for other rapport orientations, including rapport maintenance, rapport neglect and rapport challenge. The study has shown that ITAs' choices of rapport strategy are driven by their constructed identity, and their identities are still under negotiation. The current study makes contributions to the research regarding the ITA population in terms of its implications for ITA training and their pedagogical skill improvement, a new model to explain speaker's investment in a learned or used language, as well as the cultural conceptualization of the teacher-student role relationship in the American university context. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Phosphorylcholine (ChoP) is a ubiquitous biomolecule found in various organisms including the platelet-activating factor (PAF) in the mammalian hosts and the surface structures of commensal and pathogenic bacteria such as lipooligosaccharide/lipopolysaccharide (LOS/LPS) and pili. The presence of ChoP on these structures could facilitate bacterial-host interactions through the mimicry mechanism. ChoP has been shown to promote bacterial colonisation by binding to the platelet-activating factor receptor and is essential for pathogenesis. Furthermore, the antigenic activity and immunomodulatory properties of ChoP demonstrate that its significance as a small zwitterionic molecule. The human-adapted bacterial pathogen, Neisseria meningitidis, is the causative agent of meningococcal septicaemia and meningitis. Pili-ChoP modification is one of the most important virulence factors of N. meningitidis and is required for early colonisation of human airway epithelium by mediating adhesion to the platelet-activating factor receptor. Unlike bacteria that contain ChoP-linked glycoconjugates, N. meningitidis does not have the previously identified LOS/LPS core (Lic-1) ChoP biosynthetic pathways. Thus, the pathway(s) required for ChoP biosynthesis prior to post-translational modification are unknown. In this thesis, we aimed to characterize the ChoP biosynthetic pathway in N. meningitidis. [...]

Owing to an expanding economy and growing population, there is increasing consumer demand for freshwater. However, with global climate change and water pollution issues, there is rising water stress in many countries worldwide. Electrochemical water desalination technologies such as capacitive deionization (CDI) utilize electrical energy to store ions in porous materials and provide energy-efficient water desalination. However, due to the cation and anion exchange process during the charging and discharging processes, CDI is considered suitable for low salinity water desalination (salinity of 1-10 g/L). This dissertation explores novel approaches to next-generation CDI for better desalination performances and water desalination at high ionic strength. In particular, the ability of sub-nanometer carbon pores (ultramicropores) to enable highly efficient CDI even at seawater salinity is demonstrated based on unexpected simulation predictions. This unique ability originates from the energy barrier of ion solvation for pores smaller than the solvation shell. Consequently, uncharged carbon ultramicropores behave ionophobic and overcome the limitation of CDI only to be suitable for remediation of brackish water. Ultramicropores also provide novel perspectives for ion separation via the interplay of intrinsic and kinetic ion selectivity. This work also establishes electrocatalytic fuel cell desalination, whereby conventional fuel cell technology can easily be adapted to generate electricity, heat, and desalinated water concurrently.

With an emerging interest in personalized medicine and quality healthcare, the design of clinical trials that incorporates multiple stages of randomization and intervention, for example, a sequential multiple assignment randomized trial (SMART), has become a popular choice for investigators as it facilitates the construction and analysis of dynamic treatment regimes (DTRs). There exists a comprehensive body of literature on various statistical methods to analyze data collected from such trials and estimate the optimal DTR for an individual subject, among which Q-learning with linear regression is widely used due to its simplicity and ease of interpretation. This thesis discusses three important challenges that cause problems in the implementation of Q-learning and proposes multiple modifications of Q-learning to address them.The first challenge arises from the repeatedly monitored outcome of interest at intermediate stages of randomization and at longer follow-up intervals after the final stage of randomization. Clinical investigators are usually interested in identifying the optimal DTR and estimating the outcome trajectory under the optimal DTR. However, in the presence of stagewise repeated-measures outcomes, standard Q-learning fails to provide point estimates of the optimal trajectory with time-specific heterogeneous causal effects. To address this problem, we propose a modified algorithm of Q-learning with a generalized estimating equation to estimate each Q-function. The second challenge is model misspecification. Model misspecification is a common problem in Q-learning, but little attention has been given to its impact when treatment effects are heterogeneous across subjects. We describe the integrative impact of two possible types of model misspecification related to treatment effect heterogeneity: unexplained early-stage treatment effects in late-stage main effect model, and misspecified linearity between pseudo-outcomes and predictors as a result of the optimization operation. The proposed method, aiming to deal with both types of misspecification concomitantly, builds interactive models into residual-modified parametric Q-learning. The third challenge is generalizing modified Q-learning to dichotomous outcomes. It is difficult to include informative residuals from estimation of late-stage models into early-stage pseudo-outcomes due to the non-identity link function. We propose a modification based on monotonicity of preferences to address model misspecification in Q-learning with probit regression. The improvement in robustness of the proposed modification is subject to the extent of model misspecification and can be limited. Thus, we take a latent variable approach and propose a novel algorithm using sampled surrogates of the underlying continuous outcome conditional on the binary observations. The methods proposed in this thesis are assessed via simulations and illustrated using the M-bridge study, a SMART with embedded tailoring which develops and evaluates adaptive interventions for preventing binge drinking among college students.

Arabinogalactan-proteins (AGPs) are a diverse family of plant hydroxyproline-rich glycoproteins implicated to function in a number of physiological processes including growth, development, cellular signaling, somatic embryogenesis, programmed cell death, and wounding. AGPs are known for the abundance of sugars present on their molecular surface. Addition of the various sugars to AGPs requires the action of numerous distinct enzymes called glycosyltransferases (GTs). Glucuronic acid (GlcA), which is the only negatively charged sugar on AGPs, is added by the action of three glucuronic acid transferases (GLCATs), namely GLCAT14A, GLCAT14B, and GLCAT14C. Hydroxyproline-Galactosyltransferases (GALTs) are responsible for initiating sugar addition to AGPs by adding galactose (Gal) to hydroxyproline residues in the AGP core protein. To date, eight GALTs, namely GALT2-6 and Hyp-O-galactosyltransferases 1-3 (HPGTs 1-3) have been identified. To overcome gene redundancy within these two GT families, I applied a cutting-edge clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9 ) gene multiplexing approach to produce higher order genetic mutants (i.e., mutants with multiple gene family members being mutated). Seven CRISPR mutants were generated including glcat14b, glcat14c, glcat14a glcat14b, glcat14b glcat14c, and glcat14a glcat14b glcat14c for the GLCAT gene family and galt3 galt4 galt6 and galt2 galt3 galt4 galt5 galt6 for the GALT gene family. These CRISPR mutants along with two existing T-DNA mutants, namely galt2 galt5 and hpgt1 hpgt2 hpgt3, were subjected to extensive biochemical and physiological phenotypic characterization. Biochemical analysis of the glcat mutants revealed that the double and triple mutants generally had small increases of Ara and Gal and concomitant reductions of GlcA, particularly in the glcat14a glcat14b and glcat14a glcat14b glcat14c mutants. Moreover, all the glcat mutants displayed significant reductions in calcium binding by their AGPs compared to wild type (WT) plants. Physiological analyses revealed that both the glcat14a glcat14b and glcat14a glcat14b glcat14c mutants exhibited significant delays in seed germination, reductions in root hair length, reductions in trichome branching, and accumulation of defective pollen grains. Additionally, both the glcat14b glcat14c and glcat14a glcat14b glcat14c mutants displayed significantly shorter siliques and reduced seed set. Finally, all higher-order mutants exhibited significant reductions in adherent seed coat mucilage. Biochemical analysis of the higher-order galt mutants showed that all the galt mutants (galt2 galt5, galt3 galt4 galt6, galt4 galt6, and galt2 galt3 galt4 galt5 gal6) contained much less glycosylated AGPs in rosette leaves, stems, and siliques compared to WT. Monosaccharide compositional analysis revealed significant decreases of arabinose (Ara) and galactose (Gal) in all the higher order galt mutants. Further biochemical analysis found that loss of two or more GALTs were able to overcome the growth inhibitory effect of β-D-Gal-Yariv reagent. Physiological analysis revealed that the galt2 galt3 galt4 galt5 gal6 mutant exhibited a delay in overall aboveground growth and development, impaired root growth, abnormal pollen, shorter siliques, and reduced seed set. Higher order genetic mutants of GTs generated in these two research projects facilitated the understanding of functional importance of the GlcA residues (added by the GLCATs) and Gal residues (added by the GALTs) and revealed sugar structure/function relationships for AGPs. The CRISPR/Cas9 gene editing approach described here provides a simpler and faster way to generate higher order plant mutants for functional characterization compared to conventional genetic crossing of T-DNA mutant lines. This CRISPR/Cas9 mediated multiplexing approach will be especially useful for editing multigene families with members having redundant functions as is the case for many GT families and other cell wall related gene families.

Natural products have always been a valuable source for scientists who try to identify molecules possessing unique bioactivities and functions. Due to the rapid evolution of synthetic methodologies and strategies over the past two centuries, the field of natural product total synthesis has advanced to an awe-inspiring level. Meanwhile, a number of new concepts to guide the development of next generation total synthesis have emerged. One of the most evoking terms is divergent synthesis, which is also known as common intermediate-based synthesis. It aims to efficiently assemble a collection of structurally distinct natural products, instead of one single molecule, via a well-designed common synthetic intermediate. Such process is of particular significance for research in the pharmaceutical industry, material science, and agricultural industry, where high level of molecular diversity is demanded. This dissertation describes our efforts to utilize a divergent approach in completing a range of natural products in the Laurencia ethers and the manginoid family. Thus, Chapter 1 will provide a brief overview of divergent total synthesis and introduce the general challenges and opportunities in this area. Three previous successful works using this principle are discussed to showcase how the common intermediates of their choice necessitate innovation of new chemical tools. Moreover, these examples will also highlight how the development of novel strategies could lead to a versatile common intermediate and synthetic route with high degree of divergence. Chapter 2 will detail our efforts to synthesize five members of the Laurencia ethers encompassing two distinct 8-menbered ring motifs from a common intermediate. In this work, we will describe a new variant of BDSB-induced ring expansion with an enyne substrate, which could fashion the 8-membered ring with the bromoallene appendage present in microcladallenes. Meanwhile, we will also demonstrate that the BDSB-induced ring expansions (with an alkene or enyne) could proceed in the presence of an additional ring attached to the tetrahydrofuran core. These results, along with the completion of our five targets, will showcase the power of common intermediate-based strategy in the synthesis of Laurencia natural products. Finally, in Chapter 3, we will propose a divergent synthesis towards members of the manginoid family and a range of natural products containing a similar trans-hydrindane system. Then the first total synthesis of manginoid A via a number of highly chemo- and stereo-selective operations based on the designed common intermediate will be presented. The establishment of a concise and robust preparation of the plausible common intermediate lays the foundation for our global approach towards all other target molecules.

Why is the term information in English an uncountable noun, whereas in information theory it is a well-defined quantity? Since the amount of information can be quantified, what is the meaning of a fraction of that amount? This dissertation introduces a quasi-entropy matrix which developed from Claude Shannon's information measure as an analytical tool for behavioral studies. Such matrix emphasizes the role of relative characteristics of individual level data across different collections. The real challenge in the big data era is never the size of the dataset, but how data lead scientists to individuals rather than arbitrarily divided statistical groups. This proposed matrix, when combining with other statistical measures, provides a new and easy-to-do method for identifying pattern in a well-defined system because it is built on the idea that uneven probability distributions lead to decrease in system entropy. Although the matrix is not superior to classical correlation techniques, it allows an interpretation not available with traditional standard statistics. Finally, this matrix connects heterogeneous datasets because it is a frequency-based method and it works on the modes of data rather than the means of values. It also visualizes clustering in data although this type of clustering is not measured by the squared Euclidean distance of the numerical attributes.

Mice deficient in LTα1β2 or LTβR develop splenomegaly in a microbiota-dependent manner. This was observed following the treatment of antibiotics and using germfree (GF) mice. The derivation of GF Ltbr-/- mice resulted in the absence of splenomegaly. Furthermore, this work also suggests the presence of specific gut bacteria that causes splenomegaly in an LT-dependent manner. In addition, previous work has demonstrated the importance of ILC3 in mediating mucosal immunity and maintaining mucosal barrier homeostasis in the intestinal tissue. Through the use of various LTβ and LTβR conditional knockout mice, we were able to demonstrate that retinoic acid-related orphan receptor γT (RORγt) cells expressing LTα1β2, and providing active LT signaling, prevents the development of splenomegaly. Specifically, ILC3s expressing LTα1β2 is both necessary and sufficient to prevent microbial-induced inflammation. Going further, previous work had characterized the importance of the gut microbiota In processing carbohydrates for nutrient absorption and demonstrated that in the absence of the gut microbiota, GF mice fed a high fat diet (HFD) were resistant to weight gain. This work demonstrates that the complexity of the carbohydrates used in HFD experiments in GF mice alter weight gain, not necessarily the presence or absence of the microbiota. Specifically, we characterized that GF mice fed a diet rich in maltodextrin were resistant to DIO compared to GF mice fed a diet rich in sucrose. Thus we have contributed to the current understanding of how the gut microbiota promotes DIO. Finally, we sought to understand whether the increased basal inflammation in specific pathogen-free (SPF) Ltbr-/- mice prevented the mice from gaining weight on HFD. We determined that a HFD alters the colonic tissue and decreases colonic tissue density in a diet-dependent manner. We demonstrated that in addition to GF Ltbr-/- mice not developing splenomegaly, but GF Ltbr-/- mice also were able to gain weight and developing DIO. This implies the microbiota-induced inflammation has a role in the previously observed leanness phenotype.

This dissertation includes two articles examining the connection among important educational factors at student, teacher, and school levels using data from international large-scale survey and assessment studies in four education systems that have distinct cultural and social background and achieve at varying levels on international assessments. The first article discusses engagement as a multidimensional construct and explores its relationship with achievement and instruction in mathematics, applying structural equation modeling techniques—confirmatory factor analysis and path analysis. The second article examines the impact of various types of professional development activities on mathematics teachers’ self-efficacy, focusing on their self-efficacy in two aspects studied in the first article (i.e., instruction and engagement), applying propensity score methods—inverse probability of treatment weighting techniques with stabilized weights. Analyses in both articles incorporate the complex survey design to produce appropriate population estimates and standard errors. Findings reveal different patterns in the relationships among engagement, achievement, and teacher-reported/student-reported instruction across various settings and highlight the importance of student perception in the education production process. In addition, reform types of professional development activities that are collaborative and job-embedded in nature (e.g., teacher network and mentoring) are found to be more effective than traditional types of professional development activities (e.g., workshops and conferences) in enhancing teachers’ self-efficacy in instruction and student engagement. Implications and future research directions are discussed at the end of each article as well as in the concluding chapter.

Benefitting from the modernization of power system, electricity end-users, especially residential customers, have played more active roles in the demand side. With authority to choose among a diversity of electricity plans and knowledge of household power consuming patterns, residential customers are inspired to employ advanced cost management strategies, e.g. demand response (DR) and the switch in electricity plans, to reduce electricity expenditures. Considering the unavoidable limitations of DR, this thesis focuses on the strategy of switching plan, with the development of electricity plan recommender system (EPRS). EPRS recommends cost-effective electricity plans identified among all the active candidates according to preferences of neighbours, households similar to the user of EPRS in power consuming pattern. This principle is firstly achieved through clustering-based EPRS (C-EPRS), the user of which is ascribed to one of the predefined clusters and attributed with neighbours as all the cluster members. Electricity plans generally preferred by these neighbours are then selected for recommendation. Followed by C-ERPS, neighbourhood collaborative filtering-based EPRS (NCF-EPRS) is developed. With modified neighbourhood-based collaborative filtering (CF) algorithm, NCF-EPRS compares its user to other households through a novel similarity metric and employs the obtained similarities in neighbour detection and plan assessment. Considering the sparsity of practical electricity datasets, hybrid CF-based EPRS (HCF-EPRS) is constructed next by expanding NCF-ERPS with model-based CF algorithm for missing feature estimation. Multiple similarity metrics requiring dense inputs are allowed in HCF-EPRS. Finally, Bayesian HCF-EPRS (BHCF-EPRS) is proposed by applying Bayesian inference in feature estimation model and in relevance vector machine-based user classifier modelling to improve the time efficiency and discretising variables to receive higher feasibility. The efficiencies of all the EPRS models, especially the superiority of BHCF-EPRS, are evaluated through case studies in two real electricity markets. The resulting EPRSs are applicable for ordinary residential customers to identify cheap electricity plans and for retail companies to assess cost competitiveness in practical markets. With the profits brought by EPRS, both customers and retailers are motivated in retail competitions, which further contributes to the deregulation of the electricity market.

Abstract: Decades of efforts by Sinologists like Marcel Granet, A.C. Graham, and Roger Ames, have been put into explicating the notion of “correlative thinking” in the Laozi and other early Chinese texts. There is, however, no consensus among scholars of the field about exactly what they mean by the term “correlative thinking.” Some scholars consider this early stream of Chinese thought to be “pre-logical,” “irrational,” or “intuitive-associative,” which if not self-refuting, is at least misleading. This essay, acknowledging binary oppositions as the key to the gateway of correlative thinking, begins with analyzing the operation of those opposite terms in the Laozi, in which they always appear in concept-clusters valorizing the one commonly recognized as the lower-status. In this regard, the Laozi is interpreted providing a technique for tracing the fluidity of correlative language, especially the correlative thinking of binary oppositions. Moreover, aiming at recovering the cultural value of correlative thinking, this essay attempts to illustrate how this distinguished language model could be used to revise more familiar methods of post-Derridean hermeneutics. To do so, it turns to Plato’s Phaedrus, expecting that the model of correlative language could provide an alternative foothold for deconstructive interpretation, which distinguishes itself from a Derridean exegesis. The main approach is to demonstrate the tension between logic and non-rational elements in Plato’s Phaedrus. Though the methodology of dialectic is highly valued, philosophical argumentation also relies heavily on the correlativity of terms in the text. Further argumentation proceeds with characterizing the rhetoric habits in the Laozi, as a contrast to those dialectical principles described in the Phaedrus. The purpose is to explore the possibility, necessity and benefit to build up a correlative perspective. Instead of being a “prelogical” stage of thinking, the correlative thinking operates in its own effective way of argumentation, which is wholly capable of defending itself. There are reasons to believe that such a revaluation would, on the one hand, provide the gateway for entering into a dramatically different cultural context developed in China, while, on the other, echo with the poststructuralist critiques of the ultimacy of fact and the foundation of rationality in language.

RESEARCH QUESTIONS: Main question: How can a catchment-based green infrastructure network better achieve low-impact storm water attenuation goals for urban and community development in Auckland in the context of climate change? Sub-questions: How well does existing green infrastructure deal with flooding and seconding pollution issues via existing overland flows and stormwater management? How can Low-Impact Design (LID) and stormwater management methods better utilize a range of values (i.e., ecological, economic and social) to accomplish urban design objectives for Auckland city? Within the boundaries of unitary plan, is it possible to create a Green Infrastructure Network (GIN) that provides positive environmental change for urban development? The pressures of global population growth, migration and increasing urban densities present significant issues which can negatively impact on the health of cities. These pressures are more evident in midsize global cities (Allen et al., 2016) where there are often significant conflicts between the development of human infrastructure and the maintenance of natural ecosystems. The conflict leads many times to major environmental degradation. Urban studies tend to describe development patterns negatively, and often point to environmental problems that stem from development, such as landscape fragmentation (Forman, 2014), degrading water quality (Marjorie van Roon et al., 2004), flooding and increasing water-borne pollution (Pickett et al., 2013; Pickett & Cadenasso, 2007), reduction of green space and biodiversity (Wu, 2014). However, many of these authors reflect on the values and opportunities that arise from urban development to link ecology and urban development through green space networks as described by Borrett (2014), Derbyshire and Wright (2014), Li et al. (2015) and Niemelä (1999). This project explores a new, valuable and sustainable urban development paradigm through creating a new Green Infrastructure Network (GIN) model based on hydrological catchment in urban Auckland. This GIN connects current LID and WSD stormwater management practices, as is already in use at present, with a new sustainable spatial mode for intensified urban area. The Oakley Creek catchment is used as a case study to show the details and functions of the GIN. Through classifying Oakley Creek catchment into four scales: 1 block scale; 2 neighbourhood scale; 3 community scale and 4 urban stream scale to form a ‘nested catchment’. Then manage the catchment by designed GIN nodes and corridors to deal with multiple urban environmental and hydrological issues. Additionally, design a local area network (LAN) model and shared infrastructures in the GIN to create social and economic benefits to the local community. The new GIN and LAN models show the interrelated character of ecological, social and economic conditions in a local community design.

Network data represent​ ​ connections between units of analysis and lead to many interesting research questions​ with diverse applications​. In this thesis, we focus on inferring the structure underlying an observed network, which can be thought of as a noisy random realization of the unobserved true structure. ​Different applications focus on different types of underlying structure; one question of broad interest is finding a community structure, with communities typically defined as groups of nodes that share similar connectivity patterns. ​One common and widely used model for describing​ a community structure​ in a network is the stochastic block model. This model has attracted a lot of attention because of its tractable theoretical properties, but it is also well known to oversimplify the structure observed in real world networks and often does not fit the data well. Thus there has been a recent push to expand the stochastic block model in various ways to make it closer to what we observe in the real world, and this thesis makes several contributions to this effort.

This dissertation studies electric polar molecular self-assemblies and artificial electric polar molecular rotors via low temperature ultrahigh vacuum scanning tunneling microscopy. The influence of molecular dipole interaction on two fluorinated sexiphenyl (2F-6P) isomers self-assembly processes is investigated. The slight modification on 6P induces a dipole moment in the molecule and results a completely different assembly structure. Analysis of cluster dipolar energy and atom specific interactions between molecules reveals that fluorinated 2F-6P self-assembly is under more influence of H-F interaction than the dipolar interaction for closer intermolecular distances.A comprehensive study of a double decker molecular rotor [phthalocyaninato-porphyrinato-europium] is conducted on different substrates. Single molecular rotor has its alkyl chains removed after adsorption on Au(111). With thermal energy provided from the substrate, the rotor spins at both ~ 80 K and ~ 5 K surface temperatures. Molecule rotations can be terminated mechanically using a blocker fragment and its rotation can be reinitiated after the removal of this blocker. Single molecular rotor survives rotation during lateral movement under tip manipulation.On Ag(111) surface, the molecular rotors self-assemble into parallelogram clusters. Alkyl chains of the stators are also intact leading to large inter-molecular distances. No cluster rotation is observed in experiments because the dipole interaction energy in a parallelogram network needs to be overcome. On Cu(111), the molecular rotors self-assemble into infinite hexagonal networks, which is the most compact assembly. STM tip provides electrical energy for rotor network to rotate through its electrical field. The dipolar interaction energy between rotors has a degenerate ground state for such rotors network, which makes a synchronized rotation of the network achievable. Synchronized rotation by means of STM lateral manipulation and imaging are observed in large flat areas. Detail analysis of the rotation process reveals that synchronized rotation of the rotors do not propagate into areas close to step edges, and consequently it creates the rotor domains.

Drosophila embryonic dorsal-ventral (D-V) polarity is defined by the expression of the gene pipe in the ventral cells of the follicular epithelium surrounding the developing oocyte. pipe encodes a sulfotransferase that transfers sulfate groups to several protein components of the vitelline membrane layer of the eggshell, including Vitelline Membrane-Like protein (VML). These sulfated proteins represent a ventral cue embedded in the eggshell, which, during embryogenesis, leads to the spatially-restricted activation of a serine protease cascade involving Gastrulation Defective (GD), Snake and Easter. Several important pieces of information missing from our understanding of Drosophila D-V patterning include the structures of the carbohydrates borne by the Pipe targets that represent the direct substrates for Pipe and how the Pipe-sulfated ventral cue triggers the spatially-regulated activation of the serine protease cascade. Two major goals of my studies on VML are to elucidate the structures of Pipe-sulfated carbohydrates associated with VML and to identify proteins that interact with VML in a Pipe-dependent manner. To achieve the first goal, I explored different purification systems to isolate VML and eventually found a way of partially purifying VML from Drosophila ovaries. Mass spectrometric analysis of the purified VML is underway to determine the carbohydrate structures on VML and the sites of Pipe-mediated sulfation. Future experiments will involve identification of putative enzymes responsible for the glycosylation of VML and examination of their requirements in D-V patterning. To identify interacting partners of VML, a strategy combining in vivo biotinylation of VML, reversible protein crosslinking and Streptavidin purification of crosslinked complexes will be used. In the second section of my studies, I have demonstrated that VML bearing a biotin acceptor peptide (BAP) tag can be efficiently biotinylated in vivo by co-expressing it with a biotin protein ligase BirA in the follicle cells. As an extension of the application of the approach, I also show that the Torso-like protein, which is localized to the poles of the vitelline membrane and whose polar localization is crucial for Drosophila terminal patterning, can also be biotinylated in vivo when the BAP-tagged protein is co-expressed with BirA in the follicle cells.

For the last couple of decades, Permanent Magnet Synchronous Machines (PMSMs) have attracted great attention in various industry applications such as hybrid electric vehicle systems, direct drive wind power generation applications, direct drive washing machines and servo systems etc. due to their high power density, wide range of constant power operation and good torque-speed response. This work focuses on developing and implementing simple yet reliable sensorless vector control algorithms for PM machines for the full speed range including zero speed.Speed or position sensors used to obtain the rotor position information for high performance vector control of PM machines add more complexity to the hardware system, have poor immunity to electromagnetic noise and reduce the reliability of the system. Two sensorless algorithms are investigated in this work: 1) High frequency carrier signal injection based sensorless algorithm for zero and low speed operation; 2) Voltage model based sensorless algorithm for the middle and high speed operation. Initial rotor position is identified using the magnetic saturation effect.Difference in the d- and q-axis inductances results in additional reluctance torque in Interior Permanent Magnet (IPM) synchronous machines, which makes them very suitable for operation with a constant output power over a very wide speed range theoretically. It is known that the field weakening control is required to achieve the constant power operation. Literature review indicates that stable control of IPM machines in the deep field weakening operation region still remains an issue to achieve the largest possible speed range. A single-current-regulator algorithm which gives a fixed command for the q-axis voltage and only controls the d-axis current is investigated in this work. The criteria of selecting the optimal q-axis voltage in terms of variable speeds and load conditions are proposed to achieve better operating efficiency and robustness of the system in the deep field weakening operation region.The sensorless vector control algorithms and the single-current-regulator algorithm with optimal q-axis voltage control are tested on a 50 kW IPM machine system across the full range of speed and load to substantiate the theoretical work.

The main objective of this research is to investigate the magnetic pulse welding (MPW) process, the resulting joint strength and the interface welding metallurgy. It is known that traditional fusion welding is not able to weld dissimilar materials with different thermal properties, but MPW has been applied to both similar and dissimilar materials. MPW is a solid state impact welding technology that may provide metallurgical bonding without melting and solidification, and there is no significant heat affected zone (HAZ). It shares the same physical principle with explosive welding (EXW) and is good for workpiece with length scale in the order of millimeter to centimeter. This research first compares three impact welding technologies, EXW, MPW and laser impact welding (LIW), for different length scale with different driving system. The joining is likely the result of an instability associated with jetting, which scours the surface clean during impact. It was found that the metallurgical bonding by oblique impact was only realized at the combination of certain impact velocity and impact angle. Taking 0.254mm thick copper alloy 110 plate to plate joint as an example, the suitable impact velocity was larger than 250m/s and the suitable impact angle was within 2°~7°. As a result, the joint interface undergoes high strain rate deformation and the strain rate was established in the order of 106~107s-1. In this research, aluminum alloy, copper alloy, and low carbon steel were welded by MPW using electromagnetic force to accelerate the metal. The strengths for both similar and dissimilar material joints were examined by lap shearing test, peeling test and microhardness test, and the similar materials joint was also tested by nanoindentation. The joint strength was greater than that of the base metals and the welded region was hardened by high velocity impact. The tensile failure and peeling failure were outside of the welded region. The welded interface microstructure was characterized by optical microscopy, scanning electron microscopy, electron backscatter diffraction, transmission electron microscopy, and field ion atom probe microscopy. The welded interface indicated wave interface morphology. Due to adiabatic heating and high strain rate deformation, the welded interface microstructure exhibited various features, including grain refinement with large grain boundary misorientation angle, formation of band structure, deformation twins, lamellar grains, and high dislocation density (~estimated to be 1011m-2). Similar materials welding suggested pure solid state bonding, while dissimilar materials joints sometimes contained small amount of intermetallic phase distributed discontinuously in the vertex region of certain waviness along the welded interface. In order to identify the coupled thermal, electromagnetic, and mechanical properties during the impact welding process, a finite element analysis was attempted via LS-DNYA®. Some of the simulation results were compared to the instrumented experiments and the validated model can be used to investigate the successful welding criterion with regard to the impact angle and impact velocity for other materials.

In the thesis we present a new algorithm for the assembly of ESTs based on a minimum spanning tree construction. By representing the EST input as a graph, quickly assigning edge weights with a new distance heuristic for detecting edge overlap, and calculating a minimum spanning tree, we find that we can use a quick transversal of this tree to accurately order the EST set, filter out extraneous ESTs, correct errors and infer the actual transcript sequence from which the set was generated. Implementing this into a software tool, we find that our tool gives us results better than CAP3, the leading EST assembly tool in the literature. In this paper we will explain the EST assembly problem, outline the assembly algorithm, and present a quantitative comparison against the results of CAP3.

Under an enriched notion of “inside debt”, the unique benefits of bank financing from screening and monitoring processes have been well documented in a large number of studies investigating the information content of bank loan announcements. Thus, bank loan announcements convey positive signals to the market, and the market response should be positive. However, previous studies were conducted extensively in the non-government-controlled banking systems, such as the U.S., the U.K., Canada and Australia. It is unclear whether the traditional predictions on the functions of banks for non-government-controlled banking systems also hold for government-controlled banking systems. This study examines the market reaction to bank loan announcements in the Chinese financial market, where the banking system is highly controlled by the Chinese government. The study also investigates the possible characteristics of lending banks, borrowers and loans that may influence share price reaction to bank loan announcements in the Chinese financial market. Standard event study methodology is employed to test the share price returns of the borrowing firms in response to the bank loan announcements. The event window comprises of 21 trading days from the period beginning 10 days before the event date (day 0) and ending 10 days before the event date (day −10 to day 10). Data used in this study are collected from the China Stock Market and Accounting Research Database and China Financial Newspaper Database. This study samples all bank loan announcements from companies listed on the Shanghai Stock Exchange (SHSE) and the Shenzhen Stock Exchange (SZSE) between 1996 and 2009. The share-split reform started in 2005 which affected the stock price of listed Chinese companies considerably. In order to avoid the influence of the share-split reform, this study divides the sample period into two sub-samples, namely, 1996 to 2004 and 2005-2009. A total of 501 bank loan announcements are collected in the final sample for period 1996 to 2004 and 106 bank loan announcements for the period 2005 to 2009. Contrary to what previous studies have found for bank loan announcements in non-government-controlled banking systems, this study finds significant declines in stock values of Chinese borrowing firms during bank loan announcements for the sample period 1996 to 2004. The result implies that both positive and negative bank loan announcement effects are possible, depending on whether the banking system is run on purely commercial goals in non-government-controlled banking systems or is subject to political intervention in government-controlled banking systems. Banks controlled by the government may have to lend to bail out poorly performing firms for political reasons. If these weak borrowing firms are prevalent, the direction of the market response to bank loan announcement should be negative, and vice versa. The results show that the negative effect is particularly significant for loans from Big Four state banks, state owned or controlled banks, banks with lower ranking and banks in provinces with lower marketization in credit allocation. The negative effect is also particularly significant for problematic borrowing firms including firms that are opaque, have a higher possibility of expropriation or tunnelling, have ineffective expropriation-reduction mechanisms, and are controlled by the state. The results also show that the negative effect is particularly significant for loans with greater amount, shorter term, with covenants/collateral, and less syndication. There is a significant difference in the market response to bank loan announcements among different bank loan purposes and among different industries. This study finds no significant market response to bank loan announcements in the Chinese financial market for the sample period 2005 to 2009. However, the result shows that there is a significantly negative market response to bank loan announcements in the Chinese financial market for the sample period 1996 to 2004. This implies that the Chinese stock market does not view bank loan announcements unfavourably any longer after a series of reforms in the Chinese banking system.