Doctor of Philosophy

dissertationThe present work focuses on developing a holistic understanding of flow and dispersion in urban environments. Toward this end, ideas are drawn from the fields of physical modeling, inverse modeling, and optimization in urban fluid dynamics. The physical modeling part of the dissertation investigates flow in the vicinity of tall buildings using wind tunnel two-dimensional particle image velocimetry (PIV) measurements. The data obtained have been used to evaluate and improve urban wind and dispersion models. In the inverse modeling part of the dissertation, an event reconstruction tool is developed to quickly and accurately characterize the source parameters of chemical / biological / radiological (CBR) agents released into the atmosphere in an urban domain. Event reconstruction is performed using concentration measurements obtained from a distributed sensor network in the city, where the spatial coordinates of the sensors are known a priori. Source characterization comprises retrieving several source parameters including the spatial coordinates of the source, the source strength, the wind speed, and wind direction at the source, etc. The Gaussian plume model is adopted as the forward model, and derivative-based optimization is chosen to take advantage of its simple analytical nature. The solution technique developed is independent of the forward model used and is comprised of stochastic search with regularized gradient optimization. The final part of the dissertation is comprised of urban form optimization. The problem of identification of urban forms that result in the best environmental conditions is referred to as the urban form optimization problem (UFOP). The decision variables optimized include the spatial locations and the physical dimensions of the buildings and the wind speed and wind direction over the domain of interest. For the UFOP, the quick urban and industrial complex (QUIC) dispersion model is used as the forward model. The UFOP is cast as a single optimization problem, and simulated annealing and genetic algorithms are used in the solution procedure

Role of Cell Type and Genetic Alterations in Driving Breast Cancer Pathogenesis

Breast cancer is the second most leading cause of death among women in the United States. Several environmental and genetic factors contribute to the pathogenesis of the disease. It is classified into different subtypes based on expression of certain markers as well as that of set of genes that define the disease progression and associated mortality. Identification of various subtypes namely: Luminal-like (Luminal-A, Luminal-B), ErbB2 over-expressing, Basal-like and Claudin low types, showed an association of survival outcomes with that of the corresponding gene expression signatures, thus paving a way for therapeutic intervention. It further emphasizes the importance of nature of gene expression changes characteristic of each subtype in regulating the disease outcome. Another important factor that determines disease phenotype is the nature of cell of origin. As part of my thesis research, I investigated the role of different combination of oncogenes/tumor–suppressor and the nature of cell type in contributing towards phenotypic and pathological differences in development of breast cancer. hTERT immortalized stem/progenitor cell lines K5+/K19- and K5+/K19+ when transformed by combination of triple oncogene/tumor-suppressor -mRas/mp53/wtErbB2 or mRas/mp53/wtEGFR gave rise to heterogeneous primary tumors as well as spontaneous lung metastasis in-vivo upon orthotopic transplantation in mammary glands of immunocompromised NSG mice. Important tumor characteristics such as latency and incidence of primary and metastatic tumors depend on both the nature of cell type and oncogene combination. K5+/K19- over-expressing mRas/mp53/wtEGFR had a significantly late tumor onset than all other tested cell lines. Transformed K5+/K19+ cells overall possess higher anchorage independent growth and metastasis forming ability than K5+/K19- cells. From microarray analysis, we observed that tumors from transformed K5+/K19- cells have a higher EMT gene signature, more so for K5+/K19- over-expressing mRas/mp53/wtErbB2. Tumors from K5+/K19+ cells over-expressing mRas/mp53/wtEGFR express known markers for metastasis in BC, accounting for higher metastasis ability from these tumors. We also observed complete in-vitro transformation and tumor formation from either cell lines following over-expression of mRas/mp53/mPI3K oncogene combination. K5+/K19- or K5+/K19+ cells show distinct EMT upon over-expression of mRas/mp53/mPI3K combination and overall K5+/K19- cells have a higher susceptibility to undergo EMT upon transformation as compared to K5+/K19+ cells

Role of myeloid cells specific PDK-1 in inflammation and obesity induced insulin resistance

Type 2 diabetes mellitus is a major disease affecting approximately 6% of the western population. Type 2 diabetes mellitus results from insulin resistance in organs such as liver, skeletal muscle and brain. Obesity is one of the underlying causes for increased insulin resistance and is associated with the development of type 2 diabetes mellitus. Obesity is also associated with a systemic chronic inflammatory state reflected by increased levels of inflammatory cytokines. Since macrophages are the major source for their secretion, we planned to determine the role of macrophages in the development of insulin resistance. Phosphoinositide-dependent kinase (PDK-1) is an important component of PI3 kinase pathway activated by the insulin receptor. Upon activation, PDK-1 phosphorylates and activates PKB (AKT) and p70 ribosomal protein S6 kinase. To mimic insulin resistance in macrophages at the level of this important signaling node, we generated mice with specific disruption of PDK-1 in macrophages. Here we show that deletion of PDK-1 specifically in myeloid cells (PDK-1delta myel) leads to increased expression and secretion of TLR4 induced inflammatory cytokines under Lipopolysaccharide (LPS) stimulation. In addition macrophages derived from PDK-1 deltamyel show increased phosphorylation of I kappa b alpha, negative regulator of NF-kappa B and increased translocation and activation of NF-kappa B in the nucleus. This enhanced phosphorylation of Ikappa b alpha is caused by the increased activation of the upstream IKK complex. Futher studies revealed that, this activation of IKK complex is caused by enhanced ubiquitination of signal transducer TRAF6. Thus PDK-1 in macrophages serves as a negative regulator of inflammatory signaling. When exposed to high fat diet (HFD) in order to induce obesity, PDK-1 delta myel mice gain significant body weight compared to its counterpart on normal chow diet (NCD), however there is no difference in the body weight between the control and PDK-1 delta myel mice. In addition, PDK-1 delta myel mice exhibit impaired glucose tolerance and decreased glucose infusion rate during euglycemic and hyperinsulinemic clamps. Taken together the disruption of PDK-1 in macrophages leads to exaggerated inflammation and impaired glucose homeostasis

Role of MHC antigens and Immunoregulation in Graft Survival in autoimmunity

Using a syngeneic islet transplantation model system we have showed that in autoimmune type 1 diabetes transplanted islets are destroyed by the host immune system unless the transplanted islets lack class I major histocompatibility complex (MHC) molecules. Alternatively, immunomodulation of the host by induction of regulatory T cells prevented the destruction of autologous islet graft. We conclude that these approaches will allow successful transplantation of autologous islets derived from the host by stem cell or other technology without immunosuppression to reverse autoimmune type 1 diabetes

Emergence of human immunoprofiling in health and disease

The human immune system is critical for maintaining health and providing protection from infectious diseases and cancer. Major advances in our understanding of the immune system have largely emerged from studies using animal models such as mice. However, this mouse-centric research has also limited our ability to comprehend the human immune system and how it changes with age and disease state. The fact that we have yet to define what constitutes a normal human immune system has hampered our ability to diagnose, treat, and prevent many human diseases. Immunoprofiling that measures the frequency of human immune cells based upon their functional biomarkers is critical for immunotherapy. With major advances in flow cytometry, mass cytometry, and imaging technology it is now possible to rapidly characterize many types of immune cells for immunotherapy and for monitoring disease. In this article, we discuss recent progress in immunoprofiling of the human immune system and how this system changes with age, chronic diseases, and autoimmunity. We also discuss this in the historical context as it relates to the emergence of human immunology. New knowledge generated by immunoprofiling studies will allow better understanding and monitoring of immune cells and their application in clinical medicine

Optimal processor assignment for pipeline computations

The availability of large scale multitasked parallel architectures introduces the following processor assignment problem for pipelined computations. Given a set of tasks and their precedence constraints, along with their experimentally determined individual responses times for different processor sizes, find an assignment of processor to tasks. Two objectives are of interest: minimal response given a throughput requirement, and maximal throughput given a response time requirement. These assignment problems differ considerably from the classical mapping problem in which several tasks share a processor; instead, it is assumed that a large number of processors are to be assigned to a relatively small number of tasks. Efficient assignment algorithms were developed for different classes of task structures. For a p processor system and a series parallel precedence graph with n constituent tasks, an O(np2) algorithm is provided that finds the optimal assignment for the response time optimization problem; it was found that the assignment optimizing the constrained throughput in O(np2log p) time. Special cases of linear, independent, and tree graphs are also considered

Effects of stretching on jump performance: A systematic review of literature

The purpose of this systematic review of literature was to agglomerate, summarize, and analyze the trial studies that investigate the effects of different types of stretching on the performance of different types of jumps. Only results of the studies examining the effects of stretching on jump performance were reported. The inclusion criteria were developed based on the systematic review guidelines and previous literature reviews. The search for the studies were conducted during late 2011 to early 2012 on databases such as SPORTDiscus, Web of Science, Academic Search Premier, and Medline. The studies testing the effects of the stretching on jump performance were gathered. Fifty-two studies were included in the review. The studies reviewed were determined to be of evidence level 1b as categorized by Center of Evidence-Based Practice. The static stretching, proprioceptive neuromuscular facilitation type of stretching and other stretching techniques that required the participants to hold the stretch over 20 s at a point of discomfort had a significant physiological effect - reduced H-reflex, that was counteractive to improved jump performance. The effect of dynamic stretching was similar to an active full range of motio

Who forms local institutions? Levels of household participation in India's joint forest management program

Participatory approaches aim at achieving representation of a broad segment of local communities, including poor and marginalized groups in natural resource management. Focusing on the case of Joint Forest Management (JFM) in India, this paper analyzes three levels of participation (attendance of decisive meetings, membership in executive committees, and influence on decisions taken) and their determinants. A conceptual model of the different levels of participation and their linkages is presented and tested through econometric analysis of data from 660 households within 55 JFM communities in Andhra Pradesh. Results indicate that participatory approaches have been somewhat successful in achieving representation of marginalized groups in executive committees and their attendance of meetings. Actual decisionmaking processes continue, however, to be dominated by community elites as well as forest department officials.Partizipative Ansätze haben zum Ziel, die Interessensvertretung lokaler Gemeinden, insbesondere auch armer und marginalisierter Gruppen, im Management von natürlichen Ressourcen zu fördern. Dieser Artikel analysiert drei Ebenen der Partizipation (Anwesenheit in maßgebenden Treffen, Mitgliedschaft in Vorstandsgremien und Einfluss auf getroffene Entscheidungen). Der Schwerpunkt des Artikels liegt dabei auf Joint Forest Management (JFM) in Indien. Ein konzeptionelles Modell der verschiedenen Partizipationsebenen mit ihren Verknüpfungen wird vorgestellt und durch eine ökonometrische Analyse mit Daten aus 660 Haushalten aus 55 JFM Gemeinden in Andhra Pradesh überprüft. Die Ergebnisse deuten darauf hin, dass die partizipativen Ansätze recht erfolgreich darin waren, die Vertretung marginalisierter Gruppen in Vorständen und ihre Teilnahme an Treffen zu erreichen. Eigentliche Entscheidungsprozesse werden jedoch weiterhin von Gemeindeeliten und Beamten des Forstamtes dominiert

Source characterization of atmospheric releases using quasi-random sampling and regularized gradient optimization

technical reportIn the present work, an inversion technique to solve the atmospheric source characterization problem is described. The inverse problem comprises characterizing the source (x, y and z coordinates and the source strength) and the meteorological conditions (wind speed and wind direction) at the source, given certain receptor locations and the concentration values at these receptor locations. A simple Gaussian plume dispersion model for continuous point releases has been adopted as the forward model. The solution methodology for this nonlinear inverse problem consists of Qausi-Monte Carlo (QMC) sampling of the model parameter space and the subsequent application of gradient optimization. The purpose of conducting QMC sampling is to provide the gradient scheme a good initial iterate to converge to the final solution. A new misfit functional that computes the L?-norm of the ratio of the observed and predicted data has been developed and was used in the QMC search stage. It has been demonstrated that the misfit functional developed, guides the inversion algorithm to the global minimum. Quasi-random sampling was performed using the Hammersley point-set in its original, scrambled and randomized form. Its performance was evaluated against the Mersenne-Twister uniform pseudo-random number generator in terms of the speed and quality of the initial iterate provided. Regularized Newton?s method with quadratic line-search was employed for gradient optimization. The standard Tikhonov stabilizing functional was used for regularization and the regularization parameter was updated adaptively during inversion. The proposed approach has been validated against both synthetic and field experiment data. Results obtained indicate that the proposed approach performs exceedingly well for inverse-source problems with the Gaussian dispersion equation as the forward operator. Also, the work presented highlights the advantages of using deterministic low-discrepancy sampling compared to the conventional pseudo-random sampling to solve the sourceinversion proble

Reciprocity in microbiome and immune system interactions and its implications in disease and health.

Adaptation of the whole microbial normal flora residing in a host to its natural habitat over an evolutionary period has resulted in peaceful coexistence with mutual benefits for both microbiota and host in steady state. This symbiotic relationship between host and microbiota has a significant impact on shaping the immune response in the host to achieve an immune tolerance to microbiota but retaining the ability to respond to invading pathogens. Perturbation of this balance by manipulation of microbial communities in the host can lead to immune dysregulation and susceptibility to diseases. By studying the host in the absence of microbiota or with alteration of microbiota the complexity of microbial impact on the immune system can be resolved. Conversely, the study of microbiota in the absence of immune system factors can show how the immune system contributes to preservation of the host-microbiota balance. The absence of molecules involved in innate or adaptive immunity in knockout models can perturb the balance between host and microbiota further adding to more immune dysregulation. A better understanding of Microbiome-immune system interaction provides a new opportunity to identify biomarkers and drug targets. This will allow the development of new therapeutic agents for modulating the immune system to improve health with little or no toxicity. The study of interplay between host and microbiota has a promising role in the design of therapeutic interventions for immunopathological diseases arising from imbalanced host and microbiota interactions