2,492 research outputs found

    Lift EVERY Voice and Sing: An Intersectional Qualitative Study Examining the Experiences of Lesbian, Gay, Bisexual, and Queer Faculty and Administrators at Historically Black Colleges and Universities

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    While there is minimal literature that address the experiences of lesbian, gay, bisexual, and trans* identified students at Historically Black Colleges and Universities (HBCUs), the experiences of Black, queer faculty and administrators at HBCUs has not been studied. This intersectional qualitative research study focused on the experiences of lesbian, gay, bisexual, and queer identified faculty and administrators who work at HBCUs. By investigating the intersections of religion, race, gender, and sexuality within a predominantly Black institution, this study aims to enhance diversity, equity, and inclusion efforts at HBCUs by sharing the experiences of the LGBQ faculty and administrators that previously or currently work at an HBCU as a full-time employee. The research questions that guided this study were 1) How have LGBQ faculty and staff negotiated/navigated their careers at HBCUs? and 2) How do LGBQ faculty and staff at HBCUs influence cultural (relating to LGBQ inclusion) change at the organizational level? The main theoretical framework used was intersectionality and it shaped the chosen methodology and methods. The Politics of Respectability was the second theoretical framework used to describe the intra-racial tensions within the Black/African American community. The study included 60-120 minute interviews with 12 participants. Using intersectionality as a guide, the data were coded and utilized for thematic analysis. Then, an ethnodramatic performance engages readers. The goals of this study were to encourage policy changes, promote inclusivity for LGBQ employees at HBCUs, and provide an expansion to the body of literature in the field pertaining to the experiences of LGBQ faculty and administrators in higher education

    Modeling the Progression of Discrete Paired Longitudinal Data.

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    It is our intention to derive a methodology for which to model discrete paired longitudinal data. Through the use of transition matrices and maximum likelihood estimation techniques by means of software, we develop a way to model the progression of such data. We provide an example by applying this method to the Wisconsin Epidemiological Study of Diabetic Retinopathy data set. The data set is comprised of individuals, all diabetics, who have had their eyes examined for diabetic retinopathy. The eyes are treated as paired data, and we have the results of the examination at the four unequally spaced time points spanning over a fourteen year duration

    Using Reading CBM to Predict Performance on Smarter Balanced Assessment

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    This study examined the relationship between AIMSweb oral reading fluency (R-CBM) and reading comprehension (MAZE) curriculum-based measures and performance on the English language arts/literacy (ELA/L) component of the Smarter Balanced Assessment (SBA) using a sample of students in third through fifth grade (N = 499). Pearson correlations between R-CBM, MAZE, and SBA were moderate to high, with R-CBM generally demonstrating the strongest relationships with coefficients ranging from .73 to .75. Results from hierarchical multiple regression models indicated that R-CBM provided strong predictive validity for SBA performance among third grade students (63.4% variance explained, p\u3c.001), while the addition of MAZE to the equation was negligible (1.4% additional variance explained, p\u3c.001). Similar findings resulted from the fourth and fifth grade multiple regression models. The predictive value of R-CBM and MAZE each decreased as grade level increased. Results support continued use of CBM to predict success on the Smarter Balanced Assessment, although CBM using cloze passages explained little variance in high-stakes test scores beyond that of oral reading fluency alone

    Evaporite karst geohazards in the Delaware Basin, Texas: review of traditional karst studies coupled with geophysical and remote sensing characterization

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    Evaporite karst throughout the Gypsum Plain of west Texas is complex and extensive, including manifestations ranging from intrastratal brecciation and hypogene caves to epigene features and suffosion caves. Recent advances in hydrocarbon exploration and extraction has resulted in increased infrastructure development and utilization in the area; as a result, delineation and characterization of potential karst geohazards throughout the region have become a greater concern. While traditional karst surveys are essential for delineating the subsurface extent and morphology of individual caves for speleogenetic interpretation, these methods tend to underestimate the total extent of karst development and require surficial manifestation of karst phenomena. Therefore, this study utilizes a composite suite of remote sensing and traditional field studies for improved karst delineation and detection of potential karst geohazards within gypsum karst. Color InfraRed (CIR) imagery were utilized for delineation of lineaments associated with fractures, while Normalized Density Vegetation Index (NDVI) analyses were used to delineate regions of increased moisture flux and probable zones of shallow karst development. Digital Elevation Models (DEM) constructed from high-resolution LiDAR (Light Detection and Ranging) data were used to spatially interpret sinkholes, while analyses of LiDAR intensity data were used in a novel way to categorize local variations in surface geology. Resistivity data, including both direct current (DC) and capacitively coupled (CC) resistivity analyses, were acquired and interpreted throughout the study area to delineate potential shallow karst geohazards specifically associated with roadways of geohazard concern; however, detailed knowledge of the surrounding geology and local karst development proved essential for proper interpretation of resistivity inversions. The composite suite of traditional field investigations and remotely sensed karst delineations used in this study illustrate how complex gypsum karst terrains can be characterized with greater detail through the utilization of rapidly advancing technologies, especially in arid environments with low vegetation densities

    Neuregulin-1 attenuates experimental cerebral malaria (ECM) pathogenesis by regulating ErbB4/AKT/STAT3 signaling.

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    BACKGROUND:Human cerebral malaria (HCM) is a severe form of malaria characterized by sequestration of infected erythrocytes (IRBCs) in brain microvessels, increased levels of circulating free heme and pro-inflammatory cytokines and chemokines, brain swelling, vascular dysfunction, coma, and increased mortality. Neuregulin-1β (NRG-1) encoded by the gene NRG1, is a member of a family of polypeptide growth factors required for normal development of the nervous system and the heart. Utilizing an experimental cerebral malaria (ECM) model (Plasmodium berghei ANKA in C57BL/6), we reported that NRG-1 played a cytoprotective role in ECM and that circulating levels were inversely correlated with ECM severity. Intravenous infusion of NRG-1 reduced ECM mortality in mice by promoting a robust anti-inflammatory response coupled with reduction in accumulation of IRBCs in microvessels and reduced tissue damage. METHODS:In the current study, we examined how NRG-1 treatment attenuates pathogenesis and mortality associated with ECM. We examined whether NRG-1 protects against CXCL10- and heme-induced apoptosis using human brain microvascular endothelial (hCMEC/D3) cells and M059K neuroglial cells. hCMEC/D3 cells grown in a monolayer and a co-culture system with 30 μM heme and NRG-1 (100 ng/ml) were used to examine the role of NRG-1 on blood brain barrier (BBB) integrity. Using the in vivo ECM model, we examined whether the reduction of mortality was associated with the activation of ErbB4 and AKT and inactivation of STAT3 signaling pathways. For data analysis, unpaired t test or one-way ANOVA with Dunnett's or Bonferroni's post test was applied. RESULTS:We determined that NRG-1 protects against cell death/apoptosis of human brain microvascular endothelial cells and neroglial cells, the two major components of BBB. NRG-1 treatment improved heme-induced disruption of the in vitro BBB model consisting of hCMEC/D3 and human M059K cells. In the ECM murine model, NRG-1 treatment stimulated ErbB4 phosphorylation (pErbB4) followed by activation of AKT and inactivation of STAT3, which attenuated ECM mortality. CONCLUSIONS:Our results indicate a potential pathway by which NRG-1 treatment maintains BBB integrity in vitro, attenuates ECM-induced tissue injury, and reduces mortality. Furthermore, we postulate that augmenting NRG-1 during ECM therapy may be an effective adjunctive therapy to reduce CNS tissue injury and potentially increase the effectiveness of current anti-malaria therapy against human cerebral malaria (HCM)

    Thermal Insulation System Analysis Tool (TISTool) User's Manual. Version 1.0.0

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    The Thermal Insulation System Analysis Tool (TISTool) was developed starting in 2004 by Jonathan Demko and James Fesmire. The first edition was written in Excel and Visual BasIc as macros. It included the basic shapes such as a flat plate, cylinder, dished head, and sphere. The data was from several KSC tests that were already in the public literature realm as well as data from NIST and other highly respectable sources. More recently, the tool has been updated with more test data from the Cryogenics Test Laboratory and the tank shape was added. Additionally, the tool was converted to FORTRAN 95 to allow for easier distribution of the material and tool. This document reviews the user instructions for the operation of this system

    Automated rapid artefact surface area measurement from imagery with computer vision

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    Automated surface area measurements have been of interest to archaeologists since digital imagery began allowing researchers to remotely collect artefact metrics. We present a method of automatically measuring 2D surface area from artefact planform images employing computer vision in Python. The Python script, provided as a .py file in supplementary data, creates boundaries around regions of relatively homogeneous pixels (artefacts) in the image. These bounded regions are called contours. A count of the number of pixels within each contour provides a surface area in pixels. A circular reference object provides a conversion factor for the contours, as well as a point of reference for geometric accuracy of outputs.  Measurements of 2D artefact surface area can be used in combination with measurements of length, width, thickness, and mass, or in some cases, replace such measurements. As presented, this technique provides utility to archaeology with applications to new documentation of artefacts, archived artefact images containing a scale, as well as landscape geoarchaeology and sedimentary contexts. Limitations of this type of surface area measurement include the requirement of the image background being of a solid colour heavily contrasting the artefacts being measured. Effectively, the background requirement limits deployment supporting collection of rapid field measurements from in-situ surface scatters without modification to the script or manipulation of the artefacts. Analytical applications utilizing this technique include studies of relative artefact abundance, shape and size class characterizations in artefact scatters, and redistribution of artefacts by geomorphological processes

    Neuregulin-1 attenuates mortality associated with experimental cerebral malaria.

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    BackgroundCerebral Malaria (CM) is a diffuse encephalopathy caused by Plasmodium falciparum infection. Despite availability of antimalarial drugs, CM-associated mortality remains high at approximately 30% and a subset of survivors develop neurological and cognitive disabilities. While antimalarials are effective at clearing Plasmodium parasites they do little to protect against CM pathophysiology and parasite-induced brain inflammation that leads to seizures, coma and long-term neurological sequelae in CM patients. Thus, there is urgent need to explore therapeutics that can reduce or prevent CM pathogenesis and associated brain inflammation to improve survival. Neuregulin-1 (NRG-1) is a neurotrophic growth factor shown to protect against brain injury associated with acute ischemic stroke (AIS) and neurotoxin exposure. However, this drug has not been tested against CM-associated brain injury. Since CM-associated brain injuries and AIS share similar pathophysiological features, we hypothesized that NRG-1 will reduce or prevent neuroinflammation and brain damage as well as improve survival in mice with late-stage experimental cerebral malaria (ECM).MethodsWe tested the effects of NRG-1 on ECM-associated brain inflammation and mortality in P. berghei ANKA (PbA)-infected mice and compared to artemether (ARM) treatment; an antimalarial currently used in various combination therapies against malaria.ResultsTreatment with ARM (25 mg/kg/day) effectively cleared parasites and reduced mortality in PbA-infected mice by 82%. Remarkably, NRG-1 therapy (1.25 ng/kg/day) significantly improved survival against ECM by 73% despite increase in parasite burden within NRG-1-treated mice. Additionally, NRG-1 therapy reduced systemic and brain pro-inflammatory factors TNFalpha, IL-6, IL-1alpha and CXCL10 and enhanced anti-inflammatory factors, IL-5 and IL-13 while decreasing leukocyte accumulation in brain microvessels.ConclusionsThis study suggests that NRG-1 attenuates ECM-associated brain inflammation and injuries and may represent a novel supportive therapy for the management of CM
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