225 research outputs found

    Truth be Told: Utilizing Music to (Re)define the Narrative of Black Women Educators’ Lived Experiences

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    The experiences of Black women in the academy are unique and extremely nuanced. In this track, we utilize Black feminist thought (BFT) to explore how music can be used to [re]define Black women educators’ lived experiences. We meaningfully and symbolically explore song lyrics from notable Black women artists to uncover how racism, sexism, and other interlocking systems of oppression and privilege manifest in and create barriers for Black women to thrive and sustain in educational environments. By utilizing pop cultural analysis methodologies, we engage in storytelling as cultural productions, to not only highlight authentic counternarratives but also challenge dominant narratives that may perpetuate harmful stereotypes or overlook the unique struggles faced by Black women in academia. Produced with the principle of recognizing that Black women educators have the agency, autonomy, and power to self-define and self-affirm our lived experiences

    Music Appreciation (Clayton State)

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    This Grants Collection for Music Appreciation was created under a Round Four 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/arts-collections/1002/thumbnail.jp

    Policy Recommendations for Meeting the Grand Challenge to Advance Long and Productive Lives

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    This brief was created forSocial Innovation for America’s Renewal, a policy conference organized by the Center for Social Development in collaboration with the American Academy of Social Work & Social Welfare, which is leading theGrand Challenges for Social Work initiative to champion social progress. The conference site includes links to speeches, presentations, and a full list of the policy briefs

    Towards a framework for the analysis of CSCL (computer supported co-operative learning) discourse

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    The thesis aims to develop a possible description of electronic discourse in CSCL\ud through a data-driven description of the linguistic behaviour and discourse strategies of 4\ud groups of postgraduate students engaged in an asynchronous CSCL task during-February\ud 2000 and February 2001.\ud The study develops an analytic framework for the coding of the messages. The\ud framework consists of three levels, with a default inheritance relationship between these\ud levels. The top level concerns the aim of the messages, identified within the broad\ud context of Levinson's Activity Type. The mid-level consists of the traditional\ud conversational analysis categories, with some minor adaptations to the CMC medium.\ud The third level is based on a neo-Gricean approach to utterance interpretation, with\ud special attention to Levinson's (2000) theory of generalised conversational implicature.\ud The analysis was conducted through intensive reading of the coded data to identify\ud categories of speaker behaviour. The categories were then collated to address the research\ud question. 19 categories were identified, covering 4 aspects of discourse behaviour.\ud As an additional test of the discourse analysis framework, the coded output was used as\ud data for a separate theory-driven question. The question was to seek evidence of\ud behaviour typical of the iterative dialogue that characterises Laurillard's (2002) model of\ud learning through conversational dialogue.\ud The research study found that the majority of the discourse categories identified by the\ud framework are valid, although some need to be refined. In particular, 4 basic message\ud structure types, and distinctive patterns in the use of indirect and direct forms of\ud expression are clearly identified in this data. There are also clear indicators of strategies\ud used to maintain cohesion and coherence. In the test case, the coded data was used to\ud identify six types of critical learning behaviour that are broadly consistent with\ud Laurillard's model of learning

    Leveraging Snow Plow Dashboards Cams and Connected Vehicle Speed Data to Improve Winter Operations Performance Measures

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    Recent developments in mobile phone applications for polling traffic and roadway condition data from the public have led to new data sources that complement traditional Intelligent Transportation System (ITS) sensors, weather stations, and automatic vehicle location (AVL) on fleet vehicles. This study compared qualitative assessments by different users of snow plow dashboard images with interstate connected vehicle speeds. The data set was composed of 1,119 geotagged images collected during a snowstorm on February 2-3, 2016, on Interstate 80. The images were classified by three users into one of seven categories to describe the road conditions. The classification of images saw the greatest deviation when road conditions were “wet,” “dry,” or “icy,” suggesting some variation in the interpretation of these categories by the users. Connected vehicle speed data was used to validate conditions and analyze speeds at GPS locations of each image for a two-hour window around when the image was taken to identify any potential impacts the plows have made. The Kolmogorov-Smirnov test was used for all before and after combinations to determine which comparisons were the most significant between minutes before and after the plow, and found that speed data taken between 17 to 12 minutes before the plow had the greatest maximum distance improvement on the speed distributions 25 to 35 minutes after the plow has gone through. Longer term, these techniques will provide a framework for agencies to dynamically monitor changing road conditions and respond to changing weather conditions

    Uzungwa Scarp Nature Forest Reserve: a unique hotspot for reptiles in Tanzania

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    While knowledge of African vertebrate biodiversity has increased dramatically in recent years, the field of herpetology which encompasses many threatened and endemic species, has lagged behind, and many areas have not been adequately explored. Intensive field work was conducted during the rainy season from December 2017 to April 2018 to assess reptile occurrence mostly in previously unexplored areas of the Uzungwa Scarp Nature Forest Reserve (USNFR) which is part of the Udzungwa Mountain ranges in the Eastern Arc Mountains (EAM), and adjacent agricultural areas. Bucket pitfall traps, funnel traps, night transects and opportunistic search methods were used to sample reptiles across four zones: in lowland, submontane and montane forests of the USNFR, and in neighboring farmlands. Forty-five reptile species across 14 families were recorded, mostly concentrated on the lowland and submontane forests. The number of endemic and threatened species in the USNFR reaches 20 and 14 respectively, and most are found in the submontane forest. Nineteen species were new records for the USNFR, five of them representing range extensions. Reptile species richness, abundance and diversity differed significantly across the four zones, except between montane and farmland zones and between lowland and submontane. However, farmland zone was discordant from other zones in terms of species composition. This study adds to the importance of the EAM not only in harbouring large numbers of species but also as an important hotspot for endemic and threatened reptiles. It also calls for proper land-use practices in farms adjacent to protected areas for sustainable conservation of biodiversity

    CSF Cytokines in Aging, Multiple Sclerosis, and Dementia

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    Inflammation is a common process involved in aging, multiple sclerosis (MS), and age-related neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD), but there is limited evidence for the effects of aging on inflammation in the central nervous system. We collected cerebrospinal fluid (CSF) from 105 healthy control subjects representing a wide age range (23–86), and analyzed levels of cytokines associated innate immunity (TNF-α) and different T-helper subtypes: interferon–gamma induced protein 10 (IP-10) for Th1, interleukin-10 (IL-10) for Th2, and interleukin 8 (IL-8/CXCL8) for Th17. We show that CSF levels of TNF-α, IP-10, and IL-8 all increased linearly with age, but levels of IL-10 demonstrated a U-shaped relationship with age. We further found greater age-related increases in TNF-α, IL-10, and IL-8 relative to increases in IP-10 levels, consistent with a shift from Th1 to other inflammatory phenotypes. Finally, when we analyzed the same four cytokines in people with neurological disorders, we found that MS and AD, but not PD or dementia with Lewy bodies, further accentuated the age-related shift from Th1- to non-Th1-related cytokines. We propose that CSF cytokine levels represent powerful surrogates of brain inflammation and aging, and some, but not all, neurological disorders accelerate the shift away from Th1 phenotypes

    Evolution by Any Other Name: Antibiotic Resistance and Avoidance of the E-Word

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    The word "evolution" is rarely used in papers from medical journals describing antimicrobial resistance, which may directly impact public perception of the importance of evolutionary biology in our everyday lives
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