2,650 research outputs found
Hispanic Children Least Likely to Have Health Insurance: Citizenship, Ethnicity, and Language Barriers to Coverage
This policy brief examines health insurance coverage of Hispanic children and its relationship to their citizenship status, their parents’ citizenship status, parents’ insurance coverage, language spoken at home, and their state’s Medicaid expansion policies. Using the most recent data from the U.S. Census Bureau’s American Community Survey collected in 2014, authors Michael Staley and Jessica Carson report that Hispanic children are less likely to have health insurance than black or white children, a gap that is explained by differences in citizenship status between Hispanic and non-Hispanic children. Noncitizen Hispanic children are nearly three times more likely to be uninsured than Hispanic citizen children living with citizen parents and more than three times more likely to be uninsured than citizen children living with noncitizen parents. Hispanic children who do not have an insured parent are seven times more likely to be uninsured than Hispanic children with at least one insured parent. In conclusion, they suggest policy considerations that might incrementally reduce the number of uninsured children
Health Insurance Among Young Adults Rebounds Post Recession: More Become Dependents on a Parent\u27s Plan After ACA Extends Coverage to Adult Children
While much of the existing research explores young adults\u27 insurance only in the post-recession period (that is, 2010 to present), authors Michael Staley and Jessica Carson assess young adults\u27 rates of coverage within and beyond the context of the recession by examining changes across the entire 2007 to 2012 period
Book Review: Why We Do What We Do
Review of Behave: The Biology of Humans at Our Best and Worst by Robert M. Sapolsky. (New York: Penguin Random House, 2017)
Discovering meaning from biological sequences: focus on predicting misannotated proteins, binding patterns, and G4-quadruplex secondary
Proteins are the principal catalytic agents, structural elements, signal transmitters, transporters, and molecular machines in cells. Experimental determination of protein function is expensive in time and resources compared to computational methods. Hence, assigning proteins function, predicting protein binding patterns, and understanding protein regulation are important problems in functional genomics and key challenges in bioinformatics. This dissertation comprises of three studies. In the first two papers, we apply machine-learning methods to (1) identify misannotated sequences and (2) predict the binding patterns of proteins. The third paper is (3) a genome-wide analysis of G4-quadruplex sequences in the maize genome. The first two papers are based on two-stage classification methods. The first stage uses machine-learning approaches that combine composition-based and sequence-based features. We use either a decision trees (HDTree) or support vector machines (SVM) as second-stage classifiers and show that classification performance reaches or outperforms more computationally expensive approaches. For study (1) our method identified potential misannotated sequences within a well-characterized set of proteins in a popular bioinformatics database. We identified misannotated proteins and show the proteins have contradicting AmiGO and UniProt annotations. For study (2), we developed a three-phase approach: Phase I classifies whether a protein binds with another protein. Phase II determines whether a protein-binding protein is a hub. Phase III classifies hub proteins based on the number of binding sites and the number of concurrent binding partners. For study (3), we carried out a computational genome-wide screen to identify non-telomeric G4-quadruplex (G4Q) elements in maize to explore their potential role in gene regulation for flowering plants. Analysis of G4Q-containing genes uncovered a striking tendency for their enrichment in genes of networks and pathways associated with electron transport, sugar degradation, and hypoxia responsiveness. The maize G4Q elements may play a previously unrecognized role in coordinating global regulation of gene expression in response to hypoxia to control carbohydrate metabolism for anaerobic metabolism. We demonstrated that our three studies have the ability to predict and provide new insights in classifying misannotated proteins, understanding protein binding patterns, and identifying a potentially new model for gene regulation
Forecasts Of Earnings: Empirical Studies Of Effects On Investment Analysts And Incidence In Canadian Annual Reports
Long day's journey into night by Eugene O'Neill; directed by Michael R. Carson (production book)
Thesis (M.F.A.)--Boston University. Boston University School of Fine and Applied Arts Graduate thesis production book submitted as partial fulfillment of the requirements for the degree Master of Fine Arts, 1961
A Nested Logit Model of Recreational Fishing Demand in Alaska
Travel cost analysis, bioeconomic modeling, Public Economics, Research Methods/ Statistical Methods, Q26, Q22, C35,
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