Intensification of summer rainfall variability in the southeastern United States during recent decades

The variability of summer precipitation in the southeastern United States is examined in this study using 60-yr (1948-2007) rainfall data. The Southeast summer rainfalls exhibited higher interannual variability with more intense summer droughts and anomalous wetness in the recent 30 years (1978-2007) than in the prior 30 years (1948-77). Such intensification of summer rainfall variability was consistent with a decrease of light (0.1-1 mm day-1) and medium (1-10 mm day-1) rainfall events during extremely dry summers and an increase of heavy (.10 mm day-1) rainfall events in extremely wet summers. Changes in rainfall variability were also accompanied by a southward shift of the region of maximum zonal wind variability at the jet stream level in the latter period. The covariability between the Southeast summer precipitation and sea surface temperatures (SSTs) is also analyzed using the singular value decomposition (SVD) method. It is shown that the increase of Southeast summer precipitation variability is primarily associated with a higher SST variability across the equatorial Atlantic and also SST warming in the Atlantic. © 2010 American Meteorological Society.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Magnetic Resonance Imaging Biomarkers of Renal Structure and Function

The kidney's major role in filtration depends on its high blood flow, concentrating mechanisms, and biochemical activation. The kidney's greatest strengths also lead to vulnerability for drug-induced nephrotoxicity and other renal injuries. The current standard to diagnose renal injuries is with a percutaneous renal biopsy, which can be biased and insufficient. In one particular case, biopsy of a kidney with renal cell carcinoma can actually initiate metastasis. Tools that are sensitive and specific to detect renal disease early are essential, especially noninvasive diagnostic imaging. While other imaging modalities (ultrasound and x-ray/CT) have their unique advantages and disadvantages, MRI has superb soft tissue contrast without ionizing radiation. More importantly, there is a richness of contrast mechanisms in MRI that has yet to be explored and applied to study renal disease.

The focus of this work is to advance preclinical imaging tools to study the structure and function of the renal system. Studies were conducted in normal and disease models to understand general renal physiology as well as pathophysiology. This dissertation is separated into two parts--the first is the identification of renal architecture with ex vivo MRI; the second is the characterization of renal dynamics and function with in vivo MRI. High resolution ex vivo imaging provided several opportunities including: 1) identification of fine renal structures, 2) implementation of different contrast mechanisms with several pulse sequences and reconstruction methods, 3) development of image-processing tools to extract regions and structures, and 4) understanding of the nephron structures that create MR contrast and that are important for renal physiology. The ex vivo studies allowed for understanding and translation to in vivo studies. While the structure of this dissertation is organized by individual projects, the goal is singular: to develop magnetic resonance imaging biomarkers for renal system.

The work presented here includes three ex vivo studies and two in vivo studies:

1) Magnetic resonance histology of age-related nephropathy in sprague dawley.

2) Quantitative susceptibility mapping of kidney inflammation and fibrosis in type 1 angiotensin receptor-deficient mice.

3) Susceptibility tensor imaging of the kidney and its microstructural underpinnings.

4) 4D MRI of renal function in the developing mouse.

5) 4D MRI of polycystic kidneys in rapamycin treated Glis3-deficient mice.

Of Trustees and Offsprings: A Diasporic Trail of Parsi “Crisis” from Bombay to Hong Kong

This thesis examines the discourse(s) of crisis in the Parsi diaspora. Treating crisis as a common variable, rather than a singular and unique event across various Parsi communities, I investigate the dimensions of crisis that bind separated Parsi communities in anxiety through a shared language, cultural experience, and historical memory. Turning first to India and then Hong Kong as my case studies, I analyze “crisis,” that has often been identified in terms of demographic decay or postcolonial decline, in the context of more subtle debates around racial purity and trust funds. Crisis, for the Parsi diaspora, while indicating a critical moment in the present, also serves to reveal the underlying and pre-existing socio-economic and cultural tensions in the communities. Relying largely on life-story interviews, online blogs and articles, and archival work, I portray the crisis not as a unique and sporadic event, but rather as one of continuity and complexity, albeit manifesting each time in different and unique guises, that continues to disrupt as well as unite the Parsi diaspora today.