Suicide is one of the most tragic issues in mental health. Suicide has traditionally been studied as an outcome of specific psychiatric disorders. The goal of this study was to consider whether there might be underlying dimensions across psychiatric disorders that are related to suicidality. This study proposed a transdiagnostic model of suicidality. Psychiatric symptoms were hypothesized to load onto three factors: Negative Mood, Impulsivity, and Arousal. Factors were then examined as predictors of suicidal ideation and suicide attempts. Data were drawn from the National Comorbidity Survey-Replication Study (NCS-R). Structured interviews were conducted in two parts using the Composite International Diagnostic Interview (CIDI). All survey respondents (N = 9,282) were administered the core diagnostic assessment. Those who met criteria for a psychiatric disorder, met subthreshold lifetime criteria and sought treatment at some time in their life, or ever in their life made a plan to commit or attempt suicide were administered Part II of the interview and are the sample of interest in this study (N = 5,692). The sample was representative of non-institutionalized civilian adults ages 18 or older whose primary language was English. Factor analyses revealed three modified factors: a Negative Mood/Emotional Arousal factor, a Negative Thinking factor, and a Recurrent Substance Use factor. Negative Mood/Emotional Arousal was a strong predictor of suicidal ideation. Suicidal ideation mediated the relationship between Negative Mood/Emotional Arousal and suicide attempts, controlling for Negative Thinking. Negative Thinking, Recurrent Substance Use, and suicidal ideation predicted suicide attempts. When number of suicide attempts was examined as the dependent variable, the model did not fit the data, suggesting that these factors were not as helpful in predicting highly recurrent suicide attempts. Recurrent Substance Use moderated the relationship between Negative Mood/Emotional Arousal and suicide attempts, demonstrating that, as negative mood increases, people with high levels of recurrent substance use are more likely to make a suicide attempt compared to people with mean or low levels of recurrent substance use. In sum, results of this study support two distinct pathways to making a suicide attempt: a direct relationship between negative thinking and suicide attempts, as well as an interaction between negative mood/emotional arousal and recurrent substance use. Several limitations including issues of sampling, the cross-sectional nature of the data, self-report bias, and the structure of the CIDI instrument, were taken into account in interpreting the results. Clinical implications and future directions for research are discussed.

A three dimensional numerical model for a micro proton exchange membrane fuel cell was developed to simulate the concentration distribution of the fuel gas, and analyze the flow field and current field in the fuel cell. Finite control volume scheme with SIMPLEC algorithm was employed in the numerical method. Various operating conditions on the performance of the fuel cell were studied. It was shown that the concentration of oxygen at the cathode can strongly influence the cell performance. Increase the operating temperature and the pressure of the inlet gas can improve the performance of the fuel cell.

This dissertation describes the preparation of a novel inorganic membrane for hydrogen permeation and its application in a membrane reactor for the study of the methane steam reforming reaction. The investigations include both experimental studies of the membrane permeation mechanism and theoretical modeling of mass transfer through the membrane and simulation of the membrane reactor with 1-D and 2-D models. A hydrothermally stable and hydrogen selective membrane composed of silica and alumina was successfully prepared on a macroporous alumina support by chemical vapor deposition in an inert atmosphere at high temperature. Before the deposition of the silica-alumina composite, multiple graded layers of alumina were coated on the alumina support with a mean pore size of 100 nm by the sequential application of three boehmite sols with gradually decreasing sol particle sizes of 630, 200 and 40 nm, respectively. The resulting supported composite alumina-silica membrane had high permeability for hydrogen in the order of 10-7 mol m-2 s-1 Pa-1 at 873 K with a H2 /CH4 selectivity of 940 and exhibited much higher stability to water vapor at the high temperature of 873 K. In addition, the same unusual permeance order of Heï¼ H2ï¼ Ne previously observed for the pure silica membrane was also observed for the alumina-silica membrane, indicating that the silica structure did not change much after introduction of the alumina. The permeation of hydrogen and helium through vitreous glass and silica membranes was modeled using ab initio density functional calculations. Comparison of the calculated activation energies to those reported for vitreous glass (20—40 kJ mol -1) indicated the presence of 5- and 6-membered siloxane rings, consistent with the accepted structure of glass as a disordered form of cristobalite. The experimental studies of the steam reforming of methane were examined at various temperatures (773-923 K) and pressures (1-20 atm) with a commercial Ni/MgAl2O4 catalyst in a hydrogen selective silica-alumina membrane reactor and compared with a packed bed reactor. One-dimensional and two-dimensional modeling of the membrane rector and the packed bed reactor were performed at the same conditions and their performances were compared with the values obtained in the experimental study. Improved methane conversions and hydrogen yields were obtained in the membrane reactor compared to the packed bed reactor at all temperatures and pressures. From the two modeling studies, it was also found out that the two-dimensional model performed better in the membrane reactor case especially at higher pressures. / Ph. D.

<p>Nowadays, business intelligence techniques are applied more and more often in different settings including corporations and organizations both in the private and public sector. It is really a broad field which can assist business people to realize the state of their organization and make profitable decisions.</p><p>In this thesis, I will focus on one of its components, data warehouse, by proposing activity theory as the method to solve the dimension identification problem in data warehouse. Under the background of project IMIS and the involved personnel, who determine the dimension, firstly I study how to use the ER method, “bottom up” method, and activity theory method to identify the dimension in data warehouse, and some relevant knowledge about the three methods. Then, we apply the three methods to identify the dimension. After that, I evaluate the dimension identification results of the three methods according to the feedback from the healthcare organization to get their veracity and integrality. Finally, based on the results of my efforts, I arrive to the conclusion that the activity theory method can be applied to identify the dimension in data warehouse, and with the comparison to the other two traditional methods (ER model and “bottom up”), the activity theory method is more easy and natural to identify the dimension of a dimensional model.</p>

The process of fish migration within rivers and streams is important, especially during the spawning season which often coincides with peak spring discharges in Manitoba. Current environmental regulations for fish passage through culverts require that the average velocity be limited to the prolonged swimming speed of the fish species present. In order to examine the validity of this approach, physical model results were used to calibrate and test a commercially available Computational Fluid Dynamics (CFD) model. Detailed analysis showed that CFD models and the empirical equations used were both able to give a better representation of the flow field than the average velocity. However, the empirical equations were able to provide a more accurate velocity distribution within the fully developed region. A relationship was then developed, to estimate the cumulative percent area less than a threshold velocity within CSP culverts, to be used as a guideline during the design phase.

The process of fish migration within rivers and streams is important, especially during the spawning season which often coincides with peak spring discharges in Manitoba. Current environmental regulations for fish passage through culverts require that the average velocity be limited to the prolonged swimming speed of the fish species present. In order to examine the validity of this approach, physical model results were used to calibrate and test a commercially available Computational Fluid Dynamics (CFD) model. Detailed analysis showed that CFD models and the empirical equations used were both able to give a better representation of the flow field than the average velocity. However, the empirical equations were able to provide a more accurate velocity distribution within the fully developed region. A relationship was then developed, to estimate the cumulative percent area less than a threshold velocity within CSP culverts, to be used as a guideline during the design phase.

Nowadays, business intelligence techniques are applied more and more often in different settings including corporations and organizations both in the private and public sector. It is really a broad field which can assist business people to realize the state of their organization and make profitable decisions. In this thesis, I will focus on one of its components, data warehouse, by proposing activity theory as the method to solve the dimension identification problem in data warehouse. Under the background of project IMIS and the involved personnel, who determine the dimension, firstly I study how to use the ER method, “bottom up” method, and activity theory method to identify the dimension in data warehouse, and some relevant knowledge about the three methods. Then, we apply the three methods to identify the dimension. After that, I evaluate the dimension identification results of the three methods according to the feedback from the healthcare organization to get their veracity and integrality. Finally, based on the results of my efforts, I arrive to the conclusion that the activity theory method can be applied to identify the dimension in data warehouse, and with the comparison to the other two traditional methods (ER model and “bottom up”), the activity theory method is more easy and natural to identify the dimension of a dimensional model.

The geometry and mineralization features of small left-lateral strike-slip faults and associated fractures in Lake Edison Granodiorite of the central Sierra Nevada, California, were examined in order to model the three-dimensional structure of strike-slip faults. These faults, which are reactivated joints, were also examined to determine fault sizes, starting joint size, and evidence for fluid flow. The associated secondary fractures are usually found in the dilational quadrants of fault-tip regions. The longest fault-segment trace is 32.14 m; the longest joint trace is 22 m. The joint population length (l) is represented by a power-law distribution (l-n) and it is l-1.22. The fault-segment distributions are l-0.23~0.79, and the compiled fault-segment distribution is l-1.18. The data on fracture and fault spacing, along with the joint power-law distribution, will aid in the simulation and analysis of fault evolution. The splay-fracture traced in the faults are linear at depth and the average splay-fracture angle is 39° ± 13°. The dihedral angle of the splay plane and fault plane ranges from 20° to 65°. There is a high concentration of splay fractures near the fault. As distance increases perpendicular form the fault, the splay-fracture spacing increases and splay-fracture frequency decreases. The splay tracelength distributions have a high short tracelength concentration with a rapid decrease of long tracelengths. The maximum tracelength of multiple splay-fracture groups is restricted by their distance orthogonal to the fault trace. The three-dimensional relationship between the splay-fracture plane and fault plane can be inferred from these data. When present, mineralized quartz appears largely as lenses and few as single continuous veins along the faults. No consistent pattern exists between fault displacement and the locations and dimensions of quartz cavities. There is no visible damage zone near the fault termination or around the faults. Microstructures in the fault zone consist of cataclasites and patchy gouges, and zones of dynamically recrystallized fault walls. The three-dimensional geometry, along with quartz cavity distribution and thin section analysis, has led to the conclusion that fluid migrates vertically among the faults and fractures.

To assess the long-term performance of a solar thermal system, mathematical models that accurately capture the effects of heat transfer within and interactions between individual components are required. For solar domestic hot water systems, the components can include the solar collectors, storage tanks, heat exchangers, pumps, and associated piping. In addition, weather data and demand profiles are also required. Simplified models for each component are needed to reduce the computational time required to run long-term simulations. The simplified models, however, must also be sufficiently accurate in order to provide meaningful system-level results. Accurate prediction of the temperature profiles in the storage tanks of these systems is important since the temperature within the tank has a large impact on the efficiency of the entire system. TRNSYS, which is a commercial code commonly used for such simulations, contains a variety of different one-dimensional storage tank models. Previous research has indicated that these models have deficiencies in predicting experimental data. Therefore, this thesis is focussed on the analysis of the tank modelling used in TRNSYS. Results of this thesis show that the poor predictions are a result of numerical diffusion due to insufficient grid resolution. The correct theoretical profiles could be obtained by using a large number of nodes. However, this would lead to a significant increase in computational time. Alternative modelling strategies were also developed using analytical techniques to more accurately predict the temperature profiles within a storage tank while keeping a relatively low computational cost. Different models were created which considered the different mixing mechanisms present in a storage tank, such as increasing inlet temperatures with time, heat losses to the surroundings, tank wall heat conduction, and inlet jet mixing. / Thesis / Master of Applied Science (MASc)

A comercialização de produtos agropecuários tem grande importância para o Brasil, sendo responsável por altos índices de produção e financeiro. E como para todo grande segmento, o acesso à informação tem se tornado essencial para manter a competitividade no ambiente globalizado. Apesar de o agronegócio possuir um grande volume de informações, as mesmas muitas vezes estão inconsistentes ou inacessíveis. Nesse contexto, ainda se observam a necessidade de ampliação de pesquisas que busquem minimizar essa falta de dados que podem auxiliar produtores, agentes de mercado e principalmente pesquisadores para que desenvolvam análises para o mercado agropecuário para servir de apoio para as tomadas de decisões sobre a comercialização diária desses produtos. A técnica usada por diversos segmentos que visam a melhorar e a permitir acesso a dados para tomada de decisão é conhecida como Data Warehouse, pois provê um ambiente propício para análises e acesso a informações consolidadas e históricas. O objetivo do estudo foi demonstrar o processo de análise efetuado por pesquisadores para obtenção de dados, e aplicar dois estudos de casos usando técnicas de Data Warehouse, sendo para dados de comercialização de pecuária e para dados de grãos (soja e milho), gerando assim o modelo dimensional, a matriz de barramento e aplicação da ferramenta de processamento analítico online. O resultado do estudo de pecuária permitiu gerar os modelos iniciais para a cadeia, e podem ser expandidos com a inclusão de novos produtos, bem como auxiliar o pesquisador na geração de análises com a utilização das ferramentas para acesso ao Data Mart. Assim como foi possível gerar análises de comercialização de grãos a partir de dados armazenados no Data Mart. Portanto, pode-se afirmar que a aplicação e expansão da técnica de Data Warehouse é viável para outras cadeias do agronegócio possibilitando a ampliação e a melhoria da oferta de informações. / The agricultural and livestock markets in Brazil play important roles both for the production and the financial sectors. However, like other business, information is essential to maintain the competitiveness in the global market. Although the agribusiness sector processes high amount of information on a daily basis, it is almost always inconsistent or inaccessible. Moreover, there is little research aimed at minimizing the lack of agribusiness information available for the producers, market agents and researchers in order to develop data analyses on agribusiness, to help in the decision process. The technique commonly used in other segments, such as industries, is called Data Warehouse, which provides an environment to provide access to data and consistent information. The goals of this research were to present what researchers what they can do to perform agribusiness analysis, how to apply Data Warehouse modeling and the application of the tool to this process. To reach these goals, we evaluated two case studies. The first study used data from the livestock market, as it allowed to generate initial data for the chain and because it can be applied to other products, as well as to help the researcher to analyze using the OLAP tool. At the same line, the study about grain market was developed, and models and OLAP tools were developed to help with the particular points for this chain. Concluding, the research shows that it is viable to use Data Warehouse techniques to create an agribusiness data environment, consistent and organized, which can be expanded to new agricultural products.