Thesis (Ph. D.)--University of Wisconsin--Madison, 1969. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 136-140).

Thesis (M.Sc.)--University of Hong Kong, 2008. / Includes bibliographical references (p. 57-60).

This study shows that investor sentiment plays an important role in affecting the pricing dynamics between the spot and futures markets. The empirical evidence suggests that investor sentiment has a positive impact on price volatility and the bid–ask spread on both the spot and futures markets, which induces higher arbitrage risk and trading costs during high sentiment periods. As a consequence, during high sentiment periods, informed traders become less willing to leverage their information advantages on the futures market, which diminishes the futures markets’ leading informational role and contributions to price discovery. My findings provide support for the theory of limits to arbitrage.

abstract: Service based software (SBS) systems are software systems consisting of services based on the service oriented architecture (SOA). Each service in SBS systems provides partial functionalities and collaborates with other services as workflows to provide the functionalities required by the systems. These services may be developed and/or owned by different entities and physically distributed across the Internet. Compared with traditional software system components which are usually specifically designed for the target systems and bound tightly, the interfaces of services and their communication protocols are standardized, which allow SBS systems to support late binding, provide better interoperability, better flexibility in dynamic business logics, and higher fault tolerance. The development process of SBS systems can be divided to three major phases: 1) SBS specification, 2) service discovery and matching, and 3) service composition and workflow execution. This dissertation focuses on the second phase, and presents a privacy preserving service discovery and ranking approach for multiple user QoS requirements. This approach helps service providers to register services and service users to search services through public, but untrusted service directories with the protection of their privacy against the service directories. The service directories can match the registered services with service requests, but do not learn any information about them. Our approach also enforces access control on services during the matching process, which prevents unauthorized users from discovering services. After the service directories match a set of services that satisfy the service users' functionality requirements, the service discovery approach presented in this dissertation further considers service users' QoS requirements in two steps. First, this approach optimizes services' QoS by making tradeoff among various QoS aspects with users' QoS requirements and preferences. Second, this approach ranks services based on how well they satisfy users' QoS requirements to help service users select the most suitable service to develop their SBSs. / Dissertation/Thesis / Ph.D. Computer Science 2011

In recent years, there has been a major movement in the pharmaceutical industry towards the development of molecules that selectivity inhibit a previously-validated specific target. This is referred to as target-based drug discovery. It was hoped that adopting this approach would usher in a new golden age of drug discovery. However, this has not been the case, with issues arising such as the target’s mechanism of action being poorly understood, with it not playing the expected role in the disease progression, or feedback resistance mechanisms causing the target to lose its role in the disease. In contrast to this, in the past 20 years it has been argued that developing drugs in a target-agnostic way and screening them against an expressed phenotype i.e. phenotypic drug discovery, has been more successful, despite fewer programs being run in the manner. The AXL kinase is a receptor tyrosine kinase (RTK) and a member of the TAM family, along with MER and TYRO3. AXL has long been associated with numerous types of cancer. Having been first discovered in 1991 in acute myeloid leukaemia (AML), it has gone on to be more associated with advanced solid tumours such as brain, breast, and lung, with the trend being that increased AXL correlates with a poorer prognosis for the patient. Upon the activation of AXL by the vitamin K ligand GAS6, a series of downstream pathways are activated that go on to encourage cell survival, proliferation, and migration. In addition to this, AXL has been shown to be involved in crosstalk with other kinase pathways, resulting in AXL expression being associated with chemoresistance and survival mechanisms. Despite the promising outlook for AXL inhibitors, to date only one selective AXL inhibitor, BGB324 (formally R428) has entered clinical trials, with selective AXL inhibitors being difficult to develop due to a lack of a crystal structure or a reliable homology model. To address the aforementioned issues that target-based approaches can suffer from, and due to AXL lacking a crystal structure, the work in this thesis utilised a pragmatic drug design method that started from ligands/existing scaffolds known to inhibit the target from the literature (publications, clinical trials and patents). A series of small libraries were prepared and then tested against a selected phenotype e.g. cell viability, in at least two cell types: one that expressed the target (e.g. AXL) and one that did not. Hits were optimised for potency against the desired phenotype. The compounds then went through target deconvolution (kinase screening) to confirm the target of the inhibitors. Employing this approach, we initially synthesised two small libraries of potential AXL inhibitors. The potency of these compounds was tested using cell-based phenotypic assays, by evaluating cell viability in both native and chemo-resistant breast cancer cells. These libraries were optimised through focused combinatorial synthesis and phenotypic screening, to yield a small collection of antiproliferative hits. These hits were then profiled against a panel of twelve select kinases. The first library, while giving some important structural information, did not inhibit the kinases screened in a meaningful manner. However, the second library gave several potent compounds, inhibiting AXL, FLT3, and RET, with one compound being selective for AXL. The leads from this series were optimised further, through SAR studies, gaining important structural information in order to improve potency and selectivity of the compounds. The flexibility of the phenotypic cell-based approach allowed the pursuit of FLT3 inhibitors, resulting in the synthesis of one of the most potent FLT3 inhibitors synthesised to date.

New affinity molecules such as nucleic acid aptamers are in demand in the science and medical fields. Current aptamer selection technologies can generate unique aptamers with desired properties to targets of interest. My thesis describes a series of investigations on the protection of an oncolytic virus, the isolation of target cells from biological fluids, and aptamer-facilitated biomarker discovery. We tested individual aptamers and constructed a tetramer aptamer structure (quadramer) to increase virus infectivity. The quadramer protects vesicular stomatitis virus (VSV) during freeze–thaw cycles, shields the virus from neutralizing antibodies and increases viral active units. In addition to aptamers, we screened carbohydrate-based ice recrystallization inhibitors for the possible elimination of the cold chain of Vaccinia virus, VSV, and Herpes virus-1. N-octyl-gluconamide provides the longest shelf life for Vaccinia virus and Herpes virus-1 as tested according to the World Health Organization’s requirements for viral vaccines efficiency during transportation and distribution. We generated switchable aptamers capable of isolating cells expressing LIFR, NRP1, DLL4, uPAR, or PTCH1. These aptamers bind to the receptor positive cells in the presence of Mg2+ and Ca2+, and release the pure cells upon addition of EDTA. The aptamers were applied for a sequential positive immunomagnetic isolation of cells from mice bone marrow. We also utilized fluorescence-activated cell sorting (FACS) in our aptamer selections to develop switchable aptamers to positive isolation of monocytes from human blood. Moreover, we have selected non-switchable aptamers as an affinity probe to the cells expressing Axl receptor for immunofluorescent analysis and cell sorting. We determined aptamers to CD107a and applied them for biomarker discovery with mass spectrometry and found that CD107a was co-expressing with PD-1. Furthermore, we identified CD91 as binding partners to our aptamers in human monocytes using FACS and orbitrap mass spectrometry.

Leishmaniasis is a disease caused by obligate intracellular parasites of the genus Leishmania, including 20 species that are pathogenic to humans. Female sand fly is the known vector that can transmit the disease. Visceral leishmaniasis is the severe form of the disease that affects internal organs and can be fatal with inappropriate diagnosis or treatment. Leishmania donovani is the causative agent of visceral leishmaniasis. Approximately 350 million in 89 countries are at risk of infection. Around 2 million new cases are reported annually with 500,000 of these are visceral leishmaniasis. Current drug therapies are inadequate due to their toxicity, high cost, severe adverse reaction, limited availability, and the emergence of resistance. With all these limitations, the need for new drugs is urgent. Pentavalent antimonials are the first line of treatment for leishmaniasis since the 1940s. Although amphotericin B, pentamidine and paromomycin are current drugs that treat leishmaniasis, they were discovered initially as a treatment for other pathogens. Furthermore, miltefosine the only available oral drug for leishmaniasis is an anticancer drug that found to be active against Leishmania. Therefore, we used our quantitative Leishmania donovani axenic amastigote assay and the clinically relevant infected macrophage assay to identify new antileishmanial hits from unstudied or understudied natural product sources such as mangrove endophytic fungi, Antarctic deep-sea coral, and terrestrial plants. We also used the same assays to screen synthetic compounds form multiple chemical scaffolds. Our well-established assays led to the identification of new antileishmanial hits from unstudied natural products and the discovery of new classes of molecules from synthetic compounds that possess potent activity against Leishmania donovani. Finally, we conducted an in vivo hamster study on an active hit that revealed high efficacy against Leishmania donovani in this severe model leading to promising antileishmanial drug development.

viii, 61 p. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Set in the turbulence of 1968, Uwe Timm's novel, Heißer Sommer, focuses on two themes: self-discovery and the exploration of boundaries. The protagonist in Timm's novel is Ullrich, a university student who embodies the unrest of his time. Timm intertwines Ullrich's inner private sphere with the outer political sphere, which allows him to understand himself through the frame of his political activism. Moreover, Ullrich is used as an instrument by Timm to critique and shed an ironical light on the glamorization of the West German student movement. Timm illuminates several political (as well as personal) contradictions and criticisms through his protagonist's exposure to the revolutionary movement. / Adviser: Alexander Mathas

Doctor en Ciencias, Mención Computación / Este trabajo de tesis presenta soluciones para al problema de detección de anomalı́as en flujo de datos multivariantes. Dado una subsequencia de serie temporal (una pequeña parte de la serie original) como entrada, uno quiere conocer si este corresponde a una observación normal o es una anomalı́a, con respecto a la información histórica. Pueden surgir dificultades debido principalmente a que los tipos de anomalı́a son desconocidos. Además, la detección se convierte en una tarea costosa debido a la gran cantidad de datos y a la existencia de variables de dominios heterogéneos. En este contexto, se propone un enfoque de detección de anomalı́as basado en Discord Discovery, que asocia la anomalı́a con la subsecuencia más inusual utilizando medidas de similitud. Tı́picamente, los métodos de reducción de la dimensionalidad y de indexación son elaborados para restringir el problema resolviéndolo eficientemente. Adicionalmente, se propone técnicas para generar modelos representativos y consisos a partir de los datos crudos con el fin de encontrar los patrones inusuales. Estas técnicas también mejoran la eficiencia en la búsqueda mediante la reducción de la dimensionalidad. Se aborda las series multivariantes usando técnicas de representación sobre subsequencias no- normalizadas, y se propone nuevas técnicas de discord discovery basados en ı́ndices métricos. El enfoque propuesto es comparado con técnicas del estado del arte. Los resultados ex- perimentales demuestran que aplicando la transformación de translación y representación de series temporales pueden contribuir a mejorar la eficacia en la detección. Además, los métodos de indexación métrica y las heurı́sticas de discord discovery pueden resolver eficien- temente la detección de anomalı́as en modo offline y online en flujos de series temporales multivariantes. / Este trabajo ha sido financiado por beca CONICYT - CHILE / Doctorado para Extranjeros, y apoyada parcialmente por el Proyecto FONDEF D09I1185 y el Programa de Becas de NIC Chile

Online social networks (OSNs) have become the most popular Internet application that attracts billions of users to share information, disseminate opinions and interact with others in the online society. The unprecedented growing popularity of OSNs naturally makes using social network services as a pervasive phenomenon in our daily life. The majority of OSNs service providers adopts a centralised architecture because of its management simplicity and content controllability. However, the centralised architecture for large-scale OSNs applications incurs costly deployment of computing infrastructures and suffers performance bottleneck. Moreover, the centralised architecture has two major shortcomings: the single point failure problem and the lack of privacy, which challenges the uninterrupted service provision and raises serious privacy concerns. This thesis proposes a decentralised approach based on peer-to-peer (P2P) networks as an alternative to the traditional centralised architecture. Firstly, a self-organised architecture with self-sustaining social network adaptation has been designed to support decentralised topology maintenance. This self-organised architecture exhibits small-world characteristics with short average path length and large average clustering coefficient to support efficient information exchange. Based on this self-organised architecture, a novel decentralised service discovery model has been developed to achieve a semantic-aware and interest-aware query routing in the P2P social network. The proposed model encompasses a service matchmaking module to capture the hidden semantic information for query-service matching and a homophily-based query processing module to characterise user’s common social status and interests for personalised query routing. Furthermore, in order to optimise the efficiency of service discovery, a swarm intelligence inspired algorithm has been designed to reduce the query routing overhead. This algorithm employs an adaptive forwarding strategy that can adapt to various social network structures and achieves promising search performance with low redundant query overhead in dynamic environments. Finally, a configurable software simulator is implemented to simulate complex networks and to evaluate the proposed service discovery model. Extensive experiments have been conducted through simulations, and the obtained results have demonstrated the efficiency and effectiveness of the proposed model.