1,334 research outputs found
Lost Light, Kayla Shaw, Spring 2020
Kayla Shaw was the first �freshman� to enroll in SIS Seminar. She is a pre�med major from Birmingham, Alabama
The Forgotten, Kayla Shaw, Spring 2020
Kayla Shaw was the first �freshman� to enroll in SIS Seminar. She is a pre�med major from Birmingham, Alabama
Episode 2: The African American Experience of World War I
The Department of History’s Kayla Campana sat down with Dr. John Morrow, Franklin Professor of History at the University of Georgia and author of several books including Only America Left Her Negro Troops Behind: The African American Military in the First World War. In the interview, Dr. Morrow talks with Kayla about the contributions of African American soldiers to World War I and he discusses how many Americans overlooked black soldiers’ efforts, and even feared that their achievements would disrupt segregated American society.https://stars.library.ucf.edu/knightshistorycast/1001/thumbnail.jp
General practice experiences for parents of children with intellectual disability : systematic review
Background Parents of children diagnosed with intellectual disability are at increased risk of mental and physical health difficulties compared with other parents. They are likely to regularly seek medical treatment for their health concerns from general practice as well as on behalf of their child with intellectual disability, yet there is limited evaluation of the role general practice plays for this patient group.
Aim To explore parents’ experiences of general practice support when caring for a child with intellectual disability.
Design & setting Systematic review of studies reporting experiences of general practice as described by parents who care for children with intellectual disability.
Method Databases were searched using a pre-defined search strategy. Studies were included based on detailed inclusion criteria, title, abstract, and full-text screening. Quality assessment was conducted using the Mixed Methods Appraisal Tool (MMAT). A narrative synthesis was conducted.
Results A total of nine studies were identified. There was a clear absence of data on parents' own health experience and consultation in general practice. Findings related to navigating general practice on behalf of their child’s health including accessibility of general practice and positive and negative experiences of GPs.
Conclusion Findings from this review highlight priority areas for research, including further exploration of parents’ perspectives on seeking support specifically for their own health concerns, while caring for a child with intellectual disability, to bring more awareness and understanding of the role general practice plays in supporting the health of this carer group. This review also considers implications for clinical services, including tailoring appointments for this patient group as a priority for continuity of care, which may result in improved experiences of general practice and encourage better communication
Supplemental Material, sj-pdf-2-ajh-10.1177_10499091211055900 - A Qualitative Study of the Role of Palliative Care During the COVID-19 Pandemic: Perceptions and Experiences Among Critical Care Clinicians, Hospital Leaders, and Spiritual Care Providers
Supplemental Material, sj-pdf-2-ajh-10.1177_10499091211055900 for A Qualitative Study of the Role of Palliative Care During the COVID-19 Pandemic: Perceptions and Experiences Among Critical Care Clinicians, Hospital Leaders, and Spiritual Care Providers by Tamara Vesel, Emma Ernst, Linda Vesel, Kayla McGowan and Thomas J. Stopka in American Journal of Hospice and Palliative Medicine®</p
Supplemental Material, sj-pdf-1-ajh-10.1177_10499091211055900 - A Qualitative Study of the Role of Palliative Care During the COVID-19 Pandemic: Perceptions and Experiences Among Critical Care Clinicians, Hospital Leaders, and Spiritual Care Providers
Supplemental Material, sj-pdf-1-ajh-10.1177_10499091211055900 for A Qualitative Study of the Role of Palliative Care During the COVID-19 Pandemic: Perceptions and Experiences Among Critical Care Clinicians, Hospital Leaders, and Spiritual Care Providers by Tamara Vesel, Emma Ernst, Linda Vesel, Kayla McGowan and Thomas J. Stopka in American Journal of Hospice and Palliative Medicine®</p
Absence of Aerosol Indirect Effect Dependence on Background Climate State in NCAR CESM2
This directory contains metadata utilized in [cication] Absence of Aerosol Indirect Effect Dependence on Background Climate State in CESM2.
Questions can be directed to the corresponding author at [email protected]
Structure of F (ATMOSPHERE-ONLY SIMULATION) file names:
[Variable].b.e21.F1850.f19.f19.mg17.001.mon.001-60.nc = 1850 SSTs with all forcings set at 1850 levels
[Variable].b.e21.F1850.f19.f19.mg17.001.aerosol2000.mon.001-60.nc = 1850 SSTs with all other forcings set at 1850 levels, and 2000 aerosol emissions
[Variable].b.e21.F2000.f19.f19.mg17.001.mon.001-60.nc = 2000 SSTs with all forcings set at 2000 levels
[Variable].b.e21.F2000.f19.f19.mg17.001.aerosol1850.mon.001-60.nc = 2000 SSTs with all other forcings set at 2000 levels, and 1850 aerosol emissions
[Variable].b.e21.F2000.f19.f19.mg17.001.aerosol1850.add4k.mon.001-60.nc = 2000+4K SSTs with all other forcings set at 2000 levels, and 1850 aerosol emissions
[Variable].b.e21.F2000.f19.f19.mg17.001.add4k.mon.001-60.nc = 2000+4K SSTs with all other forcings set at 2000 levels, and 2000 aerosol emissions
Files contain the monthly, 60-year time-series for a single variable. For analysis, the first 20 years are considered to be the model equilibrated period. Years 20-60 are used for the equilibrated signal.
Variables:
AODABSdn = 2D Aerosol absorption optical depth 550 nm, day night
AODVISdn = 2D Aerosol optical depth 550 nm, day night
AREL = 3D Average droplet effective radius
BURDENBCdn = 2D Black carbon aerosol burden, day night
BURDENDUSTdn = 2D Dust aerosol burden, day night
BURDENPOMdn = 2D POM aerosol burden, day night
BURDENSEASALTdn = 2D Seasalt aerosol burden, day night
BURDENSO4dn = 2D Sulfate aerosol burden, day night
BURDENSOAdn = 2D SOA aerosol burden, day night
CAPE = 2D Convectively available potential energy
CCN3 = 3D CCN concentration at S=0.1%
CDNUMC = 2D Vertically-integrated droplet concentration
CLDHGH = 2D Vertically-integrated high cloud
CLDLOW = 2D Vertically-integrated low cloud
CLDMED = 2D Vertically-integrated mid-level cloud
CLDTOT = 2D Vertically-integrated total cloud
CLOUD = 3D Cloud fraction
FLNT = 2D Net longwave flux at top of model
FLNTC = 2D Clearsky net longwave flux at top of model
FREQS = 3D Fractional occurrence of snow
FSDS = 2D Downwelling solar flux at surface
FSNS = 2D Net solar flux at surface
FSNT = 2D Net solar flux at top of model
FSNTC = 2D Clearsky net solar flux at top of model
FSUTOA = 2D Upwelling solar flux at top of atmosphere
ICEFRAC = 2D Fraction of sfc area covered by sea-ice
LHFLX = 2D Surface latent heat flux
LWCF = 2D Longwave cloud forcing
OMEGA = 3D Vertical velocity (pressure)
PRECC = 2D Convective precipitation rate (liq + ice)
PRECL = 2D Large-scale (stable) precipitation rate (liq + ice)
PRECSC = 2D Convective snow rate (water equivalent)
PRECSL = 2D Large-scale (stable) snow rate (water equivalent)
PS = 2D Surface pressure
Q = 3D Specific humidity
RELHUM = 3D Relative humidity
SHFLX = 2D Surface sensible heat flux
SSAVIS = 2D Aerosol single-scatter albedo, day only
SST = 2D Sea surface temperature
SWCF = 2D Shortwave cloud forcing
T = 3D Temperature
TGCLDCWP = 2D Total grid-box cloud water path (liquid and ice)
TGCLDIWP = 2D Total grid-box cloud ice water path
TGCLDLWP = 2D Total grid-box cloud liquid water path
TREFHT = 2D Reference height temperature
Z3 = 3D Geopotential Height (above sea level)
Background climate simulations with 2-dimensional variables are grouped by variable type and uploaded in a .tar file that contains all 4 background climate simulations for the given variable
Background climate simulations with 3-dimensional variables are uploaded individually due to size
de_la_Haye.Online_Supplement.FINAL – Supplemental material for Smoking Diffusion through Networks of Diverse, Urban American Adolescents over the High School Period
Supplemental material, de_la_Haye.Online_Supplement.FINAL for Smoking Diffusion through Networks of Diverse, Urban American Adolescents over the High School Period by Kayla de la Haye, Heesung Shin, George G. Vega Yon and Thomas W. Valente in Journal of Health and Social Behavior</p
When We Kneel, We Learn
When We Kneel, We Learn is an autobiographical work based on Kayla Dudley’s experience in a caregiving facility over the expanse of two years. The book touches on the relationships she cultivated with the elderly -- including those living with Alzheimer’s and dementia. The audience that the author hopes to reach are those that are interested in caring for the geriatric population, through the lens of Christianity. However, the lessons that are learned throughout the piece are so profoundly human, that they are accessible to anyone who wants to deepen their relationships and have a greater understanding of others. The memoir is shaped in such a way that it gives the reader insight into the personalities of our elders, including quotes and stories from individual persons, as well as ways that Kayla learned to approach caring for those enduring the effects of aging.Englis
Microdissected tissue vs tissue slices: a comparative study of tumor explant models cultured on-chip and off-chip
RÉSUMÉ: Cet ensemble de données contient les résultats expérimentaux bruts utilisés pour l'article : "Microdissected Tissue vs Tissue Slices—A Comparative Study of Tumor Explant Models Cultured On-Chip and Off-Chip" par Dina Dorrigiv, Kayla Simeone, Laudine Communal, Jennifer Kendall-Dupont, Amélie St-Georges-Robillard, Benjamin Péant, Euridice Carmona, Anne-Marie Mes-Masson et Thomas Gervais. Cet ensemble de données contient les résultats expérimentaux utilisés pour générer les figures 2 et 3. ABSTRACT: This data repository contains the raw experimental results used for the article: "Microdissected Tissue vs Tissue Slices—A Comparative Study of Tumor Explant Models Cultured On-Chip and Off-Chip" by Dina Dorrigiv, Kayla Simeone, Laudine Communal, Jennifer Kendall-Dupont, Amélie St-Georges-Robillard, Benjamin Péant, Euridice Carmona, Anne-Marie Mes-Masson, and Thomas Gervais. This dataset contains the experimental results used to generate figures 2 and 3
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