Feature Selection of Post-Graduation Income of College Students in the United States

This study investigated the most important attributes of the 6-year post-graduation income of college graduates who used financial aid during their time at college in the United States. The latest data released by the United States Department of Education was used. Specifically, 1,429 cohorts of graduates from three years (2001, 2003, and 2005) were included in the data analysis. Three attribute selection methods, including filter methods, forward selection, and Genetic Algorithm, were applied to the attribute selection from 30 relevant attributes. Five groups of machine learning algorithms were applied to the dataset for classification using the best selected attribute subsets. Based on our findings, we discuss the role of neighborhood professional degree attainment, parental income, SAT scores, and family college education in post-graduation incomes and the implications for social stratification.Comment: 14 pages, 6 tables, 3 figure

Bayesian Gaussian Copula Factor Models for Mixed Data.

Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa

SAVER: Surface Autonomous Vehicle for Emergency Rescue

The design, fabrication, and testing of an unmanned surface vehicle for the NASA Micro-G NExT SAVER challenge. This device features a radio direction finding phase array to autonomously navigate to an emergency distress beacon to deliver emergency supplies

Risk attitudes and informal employment in a developing economy

© 2012 Bennett et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.We model an urban labour market in a developing economy, incorporating workers’ risk attitudes. Trade-offs between risk aversion and ability determine worker allocation across formal and informal wage employment, and voluntary and involuntary self employment. Greater risk of informal wage non-payment can raise or lower informal wage employment, depending on the source of risk. Informal wage employment can be reduced by increasing detection efforts or by strengthening contract enforcement for informal wage payment. As the average ability of workers rises, informal wage employment first rises, then falls. Greater demand for formal production may lead to more involuntary self employment

Chandra observations of Cygnus OB2

Cygnus OB2 is the nearest example of a massive star forming region, containing over 50 O-type stars and hundreds of B-type stars. We have analyzed two Chandra pointings in Cyg OB2, detecting ~1700 X-ray sources, of which ~1450 are thought to be members of the association. Optical and near-IR photometry has been obtained for ~90% of these sources from recent deep Galactic plane surveys. We have performed isochrone fits to the near-IR color-magnitude diagram, deriving ages of 3.5(+0.75,-1.0) and 5.25(+1.5,-1.0) Myrs for sources in the two fields, both with considerable spreads around the pre-MS isochrones. The presence of a second population in the region, somewhat older than the present-day O-type stars, has been suggested by other authors and fits with the ages derived here. The fraction of sources with inner circumstellar disks (as traced by the K-band excess) is found to be very low, but appropriate for a population of age ~5 Myrs. We measure the stellar mass functions and find a power-law slope of Gamma = -1.09 +/- 0.13, in good agreement with the global mean value estimated by Kroupa. A steepening of the mass function at high masses is observed and we suggest this is due to the presence of the previous generation of stars that have lost their most massive members. Finally, combining our mass function and an estimate of the radial density profile of the association suggests a total mass of Cyg OB2 of ~30,000 Msun, similar to that of many of our Galaxy's most massive star forming regions.Comment: 6 pages, 4 figures, conference proceedings for JENAM 2010: Star Clusters in the Era of Large Surveys, Editors: A.Moitinho and J. Alve

Multilocus sequence typing (MLST) analysis of Vibrio cholerae O1 El Tor isolates from Mozambique that harbour the classical CTX prophage.

Vibrio cholerae O1 isolates belonging to the Ogawa serotype, El Tor biotype, harbouring the classical CTX prophage were first isolated in Mozambique in 2004. Multilocus sequence typing (MLST) analysis using nine genetic loci showed that the Mozambique isolates have the same sequence type (ST) as O1 El Tor N16961, a representative of the current seventh cholera pandemic. Analysis of the CTX prophage in the Mozambique isolates indicated that there is one type of rstR in these isolates: the classical CTX prophage. It was also found that the ctxB-rstR-rstA-rstB-phs-cep fragment was PCR-amplified from these isolates, which indicates the presence of a tandem repeat of the classical CTX prophage in the genome of the Mozambique isolates. The possible origin of these isolates and the presence of the tandem repeat of the classical prophage in them implicate the presence of the classical CTX phage

Pittsburgh Center for Artificial Intelligence Innovation in Medical Imaging

We propose to create a medical imaging artificial intelligence (AI) center (name: Pittsburgh Center for Artificial Intelligence Innovation in Medical Imaging). AI is the new revolutionary technique for medical research and is reshaping tomorrow’s clinical practice in medical imaging (radiology and pathology). Our long-term vision is to build a center for innovative AI in clinical translational medical imaging by combining computational expertise and clinical resources across Pitt, UPMC, and CMU. The Center concept is a formalization of a group of researchers and clinicians that are united by the common theme: “building advanced and trustworthy imaging AI for clinical applications.” Our short-term plan is to assemble dedicated members from the School of Medicine, the School of Engineering, and the School of Computing and Information. We seek a Scaling grant from the Momentum Funds to foster collaborative activities of the Center between these three Pitt schools to provide the essential components of a competitive P41 (Biomedical Technology Resource Centers) center grant in 2 years. The National Institute of Biomedical Imaging and Bioengineering (NIBIB) P41 mechanism aligns with the overall vision of this initiative to develop specific AI imaging tools and to support the dissemination and commercialization pathways that are essential to bringing AI imaging tools to clinical practice. These projects will include key components: 1) Clinical need-driven medical imaging AI development and evaluation of tools, models, systems, and informatics, 2) Core imaging AI theory, methodology, and algorithm investigation, and 3) Linking imaging phenotypes to the biological (genomics and proteomics) underpinnings. To date, we have already 35 members for the Center. The Pitt Momentum Funds will provide critical scaling support to promote communication between the three Pitt schools to develop a competitive P41 grant application and a sustainable framework to ensure the clinical impact of these AI imaging tools

Deletion of Fibroblast Growth Factor Receptor 2 from the Peri-Wolffian Duct Stroma Leads to Ureteric Induction Abnormalities and Vesicoureteral Reflux

Purpose: Pax3cre-mediated deletion of fibroblast growth factor receptor 2 (Fgfr2) broadly in renal and urinary tract mesenchyme led to ureteric bud (UB) induction defects and vesicoureteral reflux (VUR), although the mechanisms were unclear. Here, we investigated whether Fgfr2 acts specifically in peri-Wolffian duct stroma (ST) to regulate UB induction and development of VUR and the mechanisms of Fgfr2 activity. Methods: We conditionally deleted Fgfr2 in ST (Fgfr2 ST-/- ) using Tbx18cre mice. To look for ureteric bud induction defects in young embryos, we assessed length and apoptosis of common nephric ducts (CNDs). We performed 3D reconstructions and histological analyses of urinary tracts of embryos and postnatal mice and cystograms in postnatal mice to test for VUR. We performed in situ hybridization and real-time PCR in young embryos to determine mechanisms underlying UB induction defects. Results: We confirmed that Fgfr2 is expressed in ST and that Fgfr2 was efficiently deleted in this tissue in Fgfr2 ST-/- mice at embryonic day (E) 10.5. E11.5 Fgfr2 ST-/- mice had randomized UB induction sites with approximately 1/3 arising too high and 1/3 too low from the Wolffian duct; however, apoptosis was unaltered in E12.5 mutant CNDs. While ureters were histologically normal, E15.5 Fgfr2 ST-/- mice exhibit improper ureteral insertion sites into the bladder, consistent with the ureteric induction defects. While ureter and bladder histology appeared normal, postnatal day (P) 1 mutants had high rates of VUR versus controls (75% versus 3%, p = 0.001) and occasionally other defects including renal hypoplasia and duplex systems. P1 mutant mice also had improper ureteral bladder insertion sites and shortened intravesicular tunnel lengths that correlated with VUR. E10.5 Fgfr2 ST-/- mice had decreases in Bmp4 mRNA in stromal tissues, suggesting a mechanism underlying the ureteric induction and VUR phenotypes. Conclusion: Mutations in FGFR2 could possibly cause VUR in humans. © 2013 Walker et al

Latent Factor Analysis to Discover Pathway-Associated Putative Segmental Aneuploidies in Human Cancers

Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of “trans”-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1α protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage

A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent