Revision of a Liquid Fuel Airblast Atomizer and Installation of a Laser Extinction System for Measurement of Soot Produced During Liquid Fuel Combustion

Studying liquid fuel combustion is necessary to better design combustion systems. Through more efficient combustors and alternative fuels, it is possible to reduce greenhouse gases and harmful emissions. In particular, coal-derived and Fischer-Tropsch liquid fuels are of interest because, in addition to producing fewer emissions, they have the potential to drastically reduce the United States' dependence on foreign oil. Major academic research institutions like the Pennsylvania State University perform cutting-edge research in many areas of combustion. The Combustion Research Laboratory (CRL) at Bucknell University is striving to develop the necessary equipment to be capable of both independent and collaborative research efforts with Penn State and in the process, advance the CRL to the forefront of combustion studies. The focus of this thesis is to advance the capabilities of the Combustion Research Lab at Bucknell. Specifically, this was accomplished through a revision to a previously designed liquid fuel injector, and through the design and installation of a laser extinction system for the measurement of soot produced during combustion. The previous liquid fuel injector with a 0.005" hole did not behave as expected. Through spray testing the 0.005" injector with water, it was determined that experimental errors were made in the original pressure testing of the injector. Using data from the spray testing experiment, new theoretical hole sizes of the injector were calculated. New injectors with 0.007" and 0.0085" orifices were fabricated and subsequently tested to qualitatively validate their behavior. The injectors were installed in the combustion rig in the CRL and hot-fire tested with liquid heptane. The 0.0085" injector yielded a manageable fuel pressure and produced a broad flame. A laser extinction system was designed and installed in the CRL. This involved the fabrication of a number of custom-designed parts and the specification of laser extinction equipment for purchase. A standard operating procedure for the laser extinction system was developed to provide a consistent, safe method for measuring soot formation during combustion.

Good efficacy of drug-eluting balloons in a mixed population of patients with coronary artery disease

Drug-coated balloons (DCB) are being increasingly used in interventional cardiology and are established for the treatment of in-stent restenosis (ISR). It is unclear how effective they are in patients with de novo lesions.

Inhibition of indoleamine 2,3-dioxygenase in mixed lymphocyte reaction affects glucose influx and enzymes involved in aerobic glycolysis and glutaminolysis in alloreactive T-cells

Indoleamine 2,3-dioxygenase (IDO) suppresses adaptive immunity. T-cell proliferation and differentiation to effector cells require increased glucose consumption, aerobic glycolysis and glutaminolysis. The effect of IDO on the above metabolic pathways was evaluated in alloreactive T-cells. Mixed lymphocyte reaction (MLR) in the presence or not of the IDO inhibitor, 1-DL-methyl-tryptophane (1-MT), was used. In MLRs, 1-MT decreased tryptophan consumption, increased cell proliferation, glucose influx and lactate production, whereas it decreased tricarboxylic acid cycle activity. In T-cells, from the two pathways that could sense tryptophan depletion, i.e. general control nonrepressed 2 (GCN2) kinase and mammalian target of rapamycin complex 1, 1-MT reduced only the activity of the GCN2 kinase. Additionally 1-MT treatment of MLRs altered the expression and/or the phosphorylation state of glucose transporter-1 and of key enzymes involved in glucose metabolism and glutaminolysis in alloreactive T-cells in a way that favors glucose influx, aerobic glycolysis and glutaminolysis. Thus in alloreactive T-cells, IDO through activation of the GCN2 kinase, decreases glucose influx and alters key enzymes involved in metabolism, decreasing aerobic glycolysis and glutaminolysis. Acting in such a way, IDO could be considered as a constraining factor for alloreactive T-cell proliferation and differentiation to effector T-cell subtypes.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

A Diagnostic Test for the Mixing Distribution in a Generalised Linear Mixed Model

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.