Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

Pragmatic development of service based real-time change data capture

This thesis makes a contribution to the Change Data Capture (CDC) field by providing an empirical evaluation on the performance of CDC architectures in the context of realtime data warehousing. CDC is a mechanism for providing data warehouse architectures with fresh data from Online Transaction Processing (OLTP) databases. There are two types of CDC architectures, pull architectures and push architectures. There is exiguous data on the performance of CDC architectures in a real-time environment. Performance data is required to determine the real-time viability of the two architectures. We propose that push CDC architectures are optimal for real-time CDC. However, push CDC architectures are seldom implemented because they are highly intrusive towards existing systems and arduous to maintain. As part of our contribution, we pragmatically develop a service based push CDC solution, which addresses the issues of intrusiveness and maintainability. Our solution uses Data Access Services (DAS) to decouple CDC logic from the applications. A requirement for the DAS is to place minimal overhead on a transaction in an OLTP environment. We synthesize DAS literature and pragmatically develop DAS that eciently execute transactions in an OLTP environment. Essentially we develop effeicient RESTful DAS, which expose Transactions As A Resource (TAAR). We evaluate the TAAR solution and three pull CDC mechanisms in a real-time environment, using the industry recognised TPC-C benchmark. The optimal CDC mechanism in a real-time environment, will capture change data with minimal latency and will have a negligible affect on the database's transactional throughput. Capture latency is the time it takes a CDC mechanism to capture a data change that has been applied to an OLTP database. A standard definition for capture latency and how to measure it does not exist in the field. We create this definition and extend the TPC-C benchmark to make the capture latency measurement. The results from our evaluation show that pull CDC is capable of real-time CDC at low levels of user concurrency. However, as the level of user concurrency scales upwards, pull CDC has a significant impact on the database's transaction rate, which affirms the theory that pull CDC architectures are not viable in a real-time architecture. TAAR CDC on the other hand is capable of real-time CDC, and places a minimal overhead on the transaction rate, although this performance is at the expense of CPU resources.

Novel three-component blends based on poly(L-lactide)

A significant number of poly a-ester homologues of poly(L-lactide) (PLLA) have been synthesized and used in miscibility studies together with conventional isomeric diacid-diol polyester variants, poly ß-esters (based on ß-hydroxybutyrate (HB) and ß-hydroxyvalerate (HV)), poly e-caprolactone (PCL), poly e-caprolactone copolymers (e.g. poly(L-lactide-co-caprolactone), and a series of cellulose-based polymers (e.g. cellulose acetate butyrate (CAB), cellulose acetate propionate (CAP)). A combinatorial approach to rapid miscibility screening using 96-well plates and a uv-visible multi-wavelength plate reader has been developed enabling the clarity of PLLA-based multi-component blend films to be observed. Using these techniques and materials, the ternary phase compatibility diagrams of a range of three-component blend films was prepared, illustrating ranges of behavior varying from miscible blends giving rise to clear films to immiscible blends which are opaque. In this way, novel three-component blends of PLLA/CAB/PCL were developed which are miscible when the CAB content is more than 30%, PLLA less than 80% and PCL less than 60%.

The development and evaluation of an evidence-based drug information service

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