5,560 research outputs found

    Accounting for accountability

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    Why communism failed: the philosophical lessons.

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    A skeptical appreciation of natural law theory

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    An Analysis of Learning Styles Among Young-Old Adults (Age 65-74) and Old-Old Adults (Age 75-99) and the Affect on Aging

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    This dominant/less dominant design uses two methods (phenomenological and quantitative) to study, describe, examine, and analyze the learning style of two groups of older adults. The first group consists of Young-Old adults, who are between the ages of 65 and 74. The second group consists of Old-Old adults, who are between the ages of 75 and 99. The researcher used the Kolb Learning Style Inventory Version 3 to determine the preferred learning style of each participant within each group. The results of the inventory for each participant was analyzed and compared between the two age groups. The analysis includes a within-case analysis and a cross-case analysis identifying differences and similarities among the members of each group and between the two groups. The researcher used an audio-recorded interview of each participant. Each participant was asked 12 questions about how stages of maturity affected perceived learning styles. Each participant described awareness and perceived problems of aging applicable to learning. The responses to questions of perceived problems of learning of new information were compared with the results of the Kolb Learning Style Inventory (LSI-3). The predominant learning styles among older adults are assimilating and diverging and five of ten participants demonstrated use of more than one learning style. There was corroboration between the LSI-3 and self-perceived learning style. There were no differences between age groups and learning style, and learning style appeared stable. Because learning new knowledge, information, and skills can occur after 65, it is important that studies be conducted that contribute to the understanding of learning in older adults

    Data management study, volume 5. Appendix J - Contractor data package procurement and contracting /PC/ Final report

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    Contractor data package for administration of procurement and contracting of Voyager spacecraft system

    Heart of glass anchors Rasip1 at endothelial cell-cell junctions to support vascular integrity.

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    Heart of Glass (HEG1), a transmembrane receptor, and Rasip1, an endothelial-specific Rap1-binding protein, are both essential for cardiovascular development. Here we performed a proteomic screen for novel HEG1 interactors and report that HEG1 binds directly to Rasip1. Rasip1 localizes to forming endothelial cell (EC) cell-cell junctions and silencing HEG1 prevents this localization. Conversely, mitochondria-targeted HEG1 relocalizes Rasip1 to mitochondria in cells. The Rasip1-binding site in HEG1 contains a 9 residue sequence, deletion of which abrogates HEG1's ability to recruit Rasip1. HEG1 binds to a central region of Rasip1 and deletion of this domain eliminates Rasip1's ability to bind HEG1, to translocate to EC junctions, to inhibit ROCK activity, and to maintain EC junctional integrity. These studies establish that the binding of HEG1 to Rasip1 mediates Rap1-dependent recruitment of Rasip1 to and stabilization of EC cell-cell junctions

    Distribution and Abundance of Host-seeking Culex Species at Three Proximate Locations with Different Levels of West Nile Virus Activity

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    Culex species were monitored at three proximate sites with historically different West Nile virus (WNV) activities. The site with human WNV transmission (epidemic) had the lowest abundance of the putative bridge vectors, Culex pipiens and Cx. salinarius. The site with horse cases but not human cases (epizootic) had the highest percent composition of Cx. salinarius, whereas the site with WNV-positive birds only (enzootic) had the highest Cx. pipiens abundance and percent composition. A total of 29 WNV-positive Culex pools were collected at the enzootic site, 17 at the epidemic site, and 14 at the epizootic site. Published models of human risk using Cx. pipiens and Cx. salinarius as the primary bridge vectors did not explain WNV activity at our sites. Other variables, such as additional vector species, environmental components, and socioeconomic factors, need to be examined to explain the observed patterns of WNV epidemic activity
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