159 research outputs found

    Teaching Awareness of Ambiguity in Data

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    The widespread and growing use of analytics has highlighted the need for more data savvy students. One recently identified aspect of data literacy is the awareness of the ambiguity. This paper outlines a method and initial results for raising awareness of data ambiguity in a short, one lesson, active learning format suitable for business or computer science courses. The paper also includes a summary prior research on ambiguity, data literacy taxonomies, implications, and suggestions for further research

    A Fresh Catch of Massive Binaries in the Cygnus OB2 Association

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    Massive binary stars may constitute a substantial fraction of progenitors to supernovae and gamma-ray bursts, and the distribution of their orbital characteristics holds clues to the formation process of massive stars. As a contribution to securing statistics on OB-type binaries, we report the discovery and orbital parameters for five new systems as part of the Cygnus OB2 Radial Velocity Survey. Four of the new systems (MT070, MT174, MT267, and MT734 (a.k.a. VI Cygni #11) are single-lined spectroscopic binaries while one (MT103) is a double-lined system (B1V+B2V). MT070 is noteworthy as the longest period system yet measured in Cyg OB2, with P=6.2 yr. The other four systems have periods ranging between 4 and 73 days. MT174 is noteworthy for having a probable mass ratio q<0.1, making it a candidate progenitor to a low-mass X-ray binary. These measurements bring the total number of massive binaries in Cyg OB2 to 25, the most currently known in any single cluster or association.Comment: Accepted for publication in the Astrophysical Journa

    Introduction to Human Development (GHC)

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    This Grants Collection for Introduction to Human Development was created under a Round Nine ALG Textbook Transformation Grant. Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process. Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials: Linked Syllabus Initial Proposal Final Reporthttps://oer.galileo.usg.edu/psychology-collections/1023/thumbnail.jp

    Real-time motion analytics during brain MRI improve data quality and reduce costs

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    Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more

    Applying refinement to the use of mice and rats in rheumatoid arthritis research

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    Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

    STOX1 deficiency is associated with renin-mediated gestational hypertension and placental defects

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    The pathogenesis of preeclampsia and other hypertensive disorders of pregnancy remains poorly defined despite the substantial burden of maternal and neonatal morbidity associated with these conditions. In particular, the role of genetic variants as determinants of disease susceptibility is understudied. Storkhead-box protein 1 (STOX1) was first identified as a preeclampsia risk gene through family-based genetic linkage studies in which loss-of-function variants were proposed to underlie increased preeclampsia susceptibility. We generated a genetic Stox1 loss-of-function mouse model (Stox1 KO) to evaluate whether STOX1 regulates blood pressure in pregnancy. Pregnant Stox1-KO mice developed gestational hypertension evidenced by a significant increase in blood pressure compared with WT by E17.5. While severe renal, placental, or fetal growth abnormalities were not observed, the Stox1-KO phenotype was associated with placental vascular and extracellular matrix abnormalities. Mechanistically, we found that gestational hypertension in Stox1-KO mice resulted from activation of the uteroplacental renin-angiotensin system. This mechanism was supported by showing that treatment of pregnant Stox1-KO mice with an angiotensin II receptor blocker rescued the phenotype. Our study demonstrates the utility of genetic mouse models for uncovering links between genetic variants and effector pathways implicated in the pathogenesis of hypertensive disorders of pregnancy
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