Value Assessment of Orphan Drugs and Treatments for Rare Diseases

Thesis (Master's)--University of Washington, 2016-06

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

Using the R package Shiny to create web applications that facilitate quantitative gene expression analysis

Thesis (Master's)--University of Washington, 2016-06

Fuzzy logic in web data mining for website assessment

This paper proposes a novel application of fuzzy logic to web data mining for two basic problems of a website: popularity and satisfaction. Popularity means that people will visit the website while satisfaction refers to the usefulness of the site. We will illustrate that the popularity of a website is a fuzzy logic problem. It is an important characteristic of a website in order to survive in Internet commerce. The satisfaction of a website is also a fuzzy logic problem that represents the degree of success in the application of information technology to the business. We propose a framework of fuzzy logic for the representation of these two problems based on web data mining techniques to fuzzify the attributes of a website.

A novel route to the synthesis of mesoporous Titania with full anatase nanocrystalline domains

A porous, high surface area TiO2 with anatase or rutile crystalline domains is advantageous for high efficiency photonic devices. Here, we report a new route to the synthesis of mesoporous titania with full anatase crystalline domains. This route involves the preparation of anatase nanocrystalline seed suspensions as the titania precursor and a block copolymer surfactant, Pluronic P123 as the template for the hydrothermal self-assembly process. A large pore (7 - 8 nm) mesoporous titania with a high surface area of 106 - 150 m(2)/g after calcination at 400degreesC for 4 h in air is achieved. Increasing the hydrothermal temperature decreases the surface area and creates larger pores. Characteristics of the seed precursors as well as the resultant mesoporous titania powder were studied using XRD analysis, N-2-adsorption/desorption analysis, and TEM. We believe these materials will be especially useful for photoelectrochemical solar cell and photocatalysis applications.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Multiresolution spatial databases: Making web-based spatial advances faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

Reflective web interface agent

Web interface agent is used with web browsers to assist users in searching and interactions with the WWW. It is used for a variety of purposes, such as web-enabled remote control, web interactive visualization, and e-commerce activities. User may be aware or unaware of its existence. The intelligence of interface agent consists in its capability of learning and decision-making in performing interactive functions on behalf of a user. However, since web is an open system environment, the reasoning mechanism in an agent should be able to adapt changes and make decisions on exceptional situations, and therefore use meta knowledge. This paper proposes a framework of Reflective Web Interface Agent (RWIA) that is to provide causal connections between the application interfaces and the knowledge model of the interface agent. A prototype is also implemented for the purpose of demonstration.

A web recommendation technique based on probabilistic latent semantic analysis

Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of click-stream data will lead to capture usage pattern information. Nowadays Web usage mining technique has become one of most widely used methods for Web recommendation, which customizes Web content to user-preferred style. Traditional techniques of Web usage mining, such as Web user session or Web page clustering, association rule and frequent navigational path mining can only discover usage pattern explicitly. They, however, cannot reveal the underlying navigational activities and identify the latent relationships that are associated with the patterns among Web users as well as Web pages. In this work, we propose a Web recommendation framework incorporating Web usage mining technique based on Probabilistic Latent Semantic Analysis (PLSA) model. The main advantages of this method are, not only to discover usage-based access pattern, but also to reveal the underlying latent factor as well. With the discovered user access pattern, we then present user more interested content via collaborative recommendation. To validate the effectiveness of proposed approach, we conduct experiments on real world datasets and make comparisons with some existing traditional techniques. The preliminary experimental results demonstrate the usability of the proposed approach.

Towards user profiling for web recommendation

Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.

Sviluppo e Applicazione di Metodologie per l'Ottimizzazione di Sistemi Energetici

La riduzione dei consumi di combustibili fossili e lo sviluppo di tecnologie per il risparmio energetico sono una questione di centrale importanza sia per l’industria che per la ricerca, a causa dei drastici effetti che le emissioni di inquinanti antropogenici stanno avendo sull’ambiente. Mentre un crescente numero di normative e regolamenti vengono emessi per far fronte a questi problemi, la necessità di sviluppare tecnologie a basse emissioni sta guidando la ricerca in numerosi settori industriali. Nonostante la realizzazione di fonti energetiche rinnovabili sia vista come la soluzione più promettente nel lungo periodo, un’efficace e completa integrazione di tali tecnologie risulta ad oggi impraticabile, a causa sia di vincoli tecnici che della vastità della quota di energia prodotta, attualmente soddisfatta da fonti fossili, che le tecnologie alternative dovrebbero andare a coprire. L’ottimizzazione della produzione e della gestione energetica d’altra parte, associata allo sviluppo di tecnologie per la riduzione dei consumi energetici, rappresenta una soluzione adeguata al problema, che può al contempo essere integrata all’interno di orizzonti temporali più brevi. L’obiettivo della presente tesi è quello di investigare, sviluppare ed applicare un insieme di strumenti numerici per ottimizzare la progettazione e la gestione di processi energetici che possa essere usato per ottenere una riduzione dei consumi di combustibile ed un’ottimizzazione dell’efficienza energetica. La metodologia sviluppata si appoggia su un approccio basato sulla modellazione numerica dei sistemi, che sfrutta le capacità predittive, derivanti da una rappresentazione matematica dei processi, per sviluppare delle strategie di ottimizzazione degli stessi, a fronte di condizioni di impiego realistiche. Nello sviluppo di queste procedure, particolare enfasi viene data alla necessità di derivare delle corrette strategie di gestione, che tengano conto delle dinamiche degli impianti analizzati, per poter ottenere le migliori prestazioni durante l’effettiva fase operativa. Durante lo sviluppo della tesi il problema dell’ottimizzazione energetica è stato affrontato in riferimento a tre diverse applicazioni tecnologiche. Nella prima di queste è stato considerato un impianto multi-fonte per la soddisfazione della domanda energetica di un edificio ad uso commerciale. Poiché tale sistema utilizza una serie di molteplici tecnologie per la produzione dell’energia termica ed elettrica richiesta dalle utenze, è necessario identificare la corretta strategia di ripartizione dei carichi, in grado di garantire la massima efficienza energetica dell’impianto. Basandosi su un modello semplificato dell’impianto, il problema è stato risolto applicando un algoritmo di Programmazione Dinamica deterministico, e i risultati ottenuti sono stati comparati con quelli derivanti dall’adozione di una più semplice strategia a regole, provando in tal modo i vantaggi connessi all’adozione di una strategia di controllo ottimale. Nella seconda applicazione è stata investigata la progettazione di una soluzione ibrida per il recupero energetico da uno scavatore idraulico. Poiché diversi layout tecnologici per implementare questa soluzione possono essere concepiti e l’introduzione di componenti aggiuntivi necessita di un corretto dimensionamento, è necessario lo sviluppo di una metodologia che permetta di valutare le massime prestazioni ottenibili da ognuna di tali soluzioni alternative. Il confronto fra i diversi layout è stato perciò condotto sulla base delle prestazioni energetiche del macchinario durante un ciclo di scavo standardizzato, stimate grazie all’ausilio di un dettagliato modello dell’impianto. Poiché l’aggiunta di dispositivi per il recupero energetico introduce gradi di libertà addizionali nel sistema, è stato inoltre necessario determinare la strategia di controllo ottimale dei medesimi, al fine di poter valutare le massime prestazioni ottenibili da ciascun layout. Tale problema è stato di nuovo risolto grazie all’ausilio di un algoritmo di Programmazione Dinamica, che sfrutta un modello semplificato del sistema, ideato per lo scopo. Una volta che le prestazioni ottimali per ogni soluzione progettuale sono state determinate, è stato possibile effettuare un equo confronto fra le diverse alternative. Nella terza ed ultima applicazione è stato analizzato un impianto a ciclo Rankine organico (ORC) per il recupero di cascami termici dai gas di scarico di autovetture. Nonostante gli impianti ORC siano potenzialmente in grado di produrre rilevanti incrementi nel risparmio di combustibile di un veicolo, è necessario per il loro corretto funzionamento lo sviluppo di complesse strategie di controllo, che siano in grado di far fronte alla variabilità della fonte di calore per il processo; inoltre, contemporaneamente alla massimizzazione dei risparmi di combustibile, il sistema deve essere mantenuto in condizioni di funzionamento sicure. Per far fronte al problema, un robusto ed efficace modello dell’impianto è stato realizzato, basandosi sulla Moving Boundary Methodology, per la simulazione delle dinamiche di cambio di fase del fluido organico e la stima delle prestazioni dell’impianto. Tale modello è stato in seguito utilizzato per progettare un controllore predittivo (MPC) in grado di stimare i parametri di controllo ottimali per la gestione del sistema durante il funzionamento transitorio. Per la soluzione del corrispondente problema di ottimizzazione dinamica non lineare, un algoritmo basato sulla Particle Swarm Optimization è stato sviluppato. I risultati ottenuti con l’adozione di tale controllore sono stati confrontati con quelli ottenibili da un classico controllore proporzionale integrale (PI), mostrando nuovamente i vantaggi, da un punto di vista energetico, derivanti dall’adozione di una strategia di controllo ottima.

Valutazione del rischio ecologico e sviluppo di strategie innovative per il monitoraggio della qualita’ dei corpi idrici: applicazione di un nuovo approccio integrato in un bacino pilota.

Freshwater is extremely precious; but even more precious than freshwater is clean freshwater. From the time that 2/3 of our planet is covered in water, we have contaminated our globe with chemicals that have been used by industrial activities over the last century in a unprecedented way causing harm to humans and wildlife. We have to adopt a new scientific mindset in order to face this problem so to protect this important resource. The Water Framework Directive (European Parliament and the Council, 2000) is a milestone legislative document that transformed the way that water quality monitoring is undertaken across all Member States by introducing the Ecological and Chemical Status. A “good or higher” Ecological Status is expected to be achieved for all waterbodies in Europe by 2015. Yet, most of the European waterbodies, which are determined to be at risk, or of moderate to bad quality, further information will be required so that adequate remediation strategies can be implemented. To date, water quality evaluation is based on five biological components (phytoplankton, macrophytes and benthic algae, macroinvertebrates and fishes) and various hydromorphological and physicochemical elements. The evaluation of the chemical status is principally based on 33 priority substances and on 12 xenobiotics, considered as dangerous for the environment. This approach takes into account only a part of the numerous xenobiotics that can be present in surface waters and could not evidence all the possible causes of ecotoxicological stress that can act in a water section. The mixtures of toxic chemicals may constitute an ecological risk not predictable on the basis of the single component concentration. To improve water quality, sources of contamination and causes of ecological alterations need to be identified. On the other hand, the analysis of the community structure, which is the result of multiple processes, including hydrological constrains and physico-chemical stress, give back only a “photograph” of the actual status of a site without revealing causes and sources of the perturbation. A multidisciplinary approach, able to integrate the information obtained by different methods, such as community structure analysis and eco-genotoxicological studies, could help overcome some of the difficulties in properly identifying the different causes of stress in risk assessment. In synthesis, the river ecological status is the result of a combination of multiple pressures that, for management purposes and quality improvement, have to be disentangled from each other. To reduce actual uncertainty in risk assessment, methods that establish quantitative links between levels of contamination and community alterations are needed. The analysis of macrobenthic invertebrate community structure has been widely used to identify sites subjected to perturbation. Trait-based descriptors of community structure constitute a useful method in ecological risk assessment. The diagnostic capacity of freshwater biomonitoring could be improved by chronic sublethal toxicity testing of water and sediment samples. Requiring an exposure time that covers most of the species’ life cycle, chronic toxicity tests are able to reveal negative effects on life-history traits at contaminant concentrations well below the acute toxicity level. Furthermore, the responses of high-level endpoints (growth, fecundity, mortality) can be integrated in order to evaluate the impact on population’s dynamics, a highly relevant endpoint from the ecological point of view. To gain more accurate information about potential causes and consequences of environmental contamination, the evaluation of adverse effects at physiological, biochemical and genetic level is also needed. The use of different biomarkers and toxicity tests can give information about the sub-lethal and toxic load of environmental compartments. Biomarkers give essential information about the exposure to toxicants, such as endocrine disruptor compounds and genotoxic substances whose negative effects cannot be evidenced by using only high-level toxicological endpoints. The increasing presence of genotoxic pollutants in the environment has caused concern regarding the potential harmful effects of xenobiotics on human health, and interest on the development of new and more sensitive methods for the assessment of mutagenic and cancerogenic risk. Within the WFD, biomarkers and bioassays are regarded as important tools to gain lines of evidence for cause-effect relationship in ecological quality assessment. Despite the scientific community clearly addresses the advantages and necessity of an ecotoxicological approach within the ecological quality assessment, a recent review reports that, more than one decade after the publication of the WFD, only few studies have attempted to integrate ecological water status assessment and biological methods (namely biomarkers or bioassays). None of the fifteen reviewed studies included both biomarkers and bioassays. The integrated approach developed in this PhD Thesis comprises a set of laboratory bioassays (Daphnia magna acute and chronic toxicity tests, Comet Assay and FPG-Comet) newly-developed, modified tacking a cue from standardized existing protocols or applied for freshwater quality testing (ecotoxicological, genotoxicological and toxicogenomic assays), coupled with field investigations on macrobenthic community structures (SPEAR and EBI indexes). Together with the development of new bioassays with Daphnia magna, the feasibility of eco-genotoxicological testing of freshwater and sediment quality with Heterocypris incongruens was evaluated (Comet Assay and a protocol for chronic toxicity). However, the Comet Assay, although standardized, was not applied to freshwater samples due to the lack of sensitivity of this species observed after 24h of exposure to relatively high (and not environmentally relevant) concentrations of reference genotoxicants. Furthermore, this species demonstrated to be unsuitable also for chronic toxicity testing due to the difficult evaluation of fecundity as sub-lethal endpoint of exposure and complications due to its biology and behaviour. The study was applied to a pilot hydrographic sub-Basin, by selecting section subjected to different levels of anthropogenic pressure: this allowed us to establish the reference conditions, to select the most significant endpoints and to evaluate the coherence of the responses of the different lines of evidence (alteration of community structure, eco-genotoxicological responses, alteration of gene expression profiles) and, finally, the diagnostic capacity of the monitoring strategy. Significant correlations were found between the genotoxicological parameter Tail Intensity % (TI%) and macrobenthic community descriptors SPEAR (p<0.001) and EBI (p<0.05), between the genotoxicological parameter describing DNA oxidative stress (ΔTI%) and mean levels of nitrates (p<0.01) and between reproductive impairment (Failed Development % from D. magna chronic bioassays) and TI% (p<0.001) as well as EBI (p<0.001). While correlation among parameters demonstrates a general coherence in the response to increasing impacts, the concomitant ability of each single endpoint to be responsive to specific sources of stress is at the basis of the diagnostic capacity of the integrated approach as demonstrated by stations presenting a mismatch among the different lines of evidence. The chosen set of bioassays, as well as the selected endpoints, are not providing redundant indications on the water quality status but, on the contrary, are contributing with complementary pieces of information about the several stressors that insist simultaneously on a waterbody section providing this monitoring strategy with a solid diagnostic capacity. Our approach should provide opportunities for the integration of biological effects into monitoring programmes for surface water, especially in investigative monitoring. Moreover, it should provide a more realistic assessment of impact and exposure of aquatic organisms to contaminants. Finally this approach should provide an evaluation of drivers of change in biodiversity and its causalities on ecosystem function/services provision, that is the direct and indirect contributions to human well-being.

AKTive Food:semantic web based knowledge conduits for the organic food industry

We present a vision and a proposal for using Semantic Web technologies in the organic food industry. This is a very knowledge intensive industry at every step from the producer, to the caterer or restauranteur, through to the consumer. There is a crucial need for a concept of environmental audit which would allow the various stake holders to know the full environmental impact of their economic choices. This is a di?erent and parallel form of knowledge to that of price. Semantic Web technologies can be used e?ectively for the calculation and transfer of this type of knowledge (together with other forms of multimedia data) which could contribute considerably to the commercial and educational impact of the organic food industry. We outline how this could be achieved as our essential ob jective is to show how advanced technologies could be used to both reduce ecological impact and increase public awareness.