Showing 101 - 120 results of 103,321 for search '(( 1 mm decrease ) OR ( 5 ((step decrease) OR (((we decrease) OR (a decrease)))) ))', query time: 1.65s Refine Results
  1. 101

    Supplementary Material for: Longitudinal Decrease in Left Ventricular Size with Age: Impact on Mortality and Cardiovascular Hospitalization by figshare admin karger (2628495)

    Published 2025
    “…Participants were categorized by LVEDD change from baseline: No Change (<5 mm), Decreased (≥5 mm), and Increased (≥5 mm). …”
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    Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by Malena Sibaja Leyton (18400983)

    Published 2025
    “…</p><p><br></p><p dir="ltr">#METADATA</p><p dir="ltr">#'data.frame': 472 obs. of 28 variables:</p><p dir="ltr"> #$ ID: Factor variable; a unique identity for the response to the survey</p><p dir="ltr"> #$ Year: Factor variable; six factors available (2016, 2017, 2018, 2019, 2020, 2021) representing the year for the response to the survey</p><p dir="ltr"> #$ N_dead_annual: Numeric variable; representing the number of colonies annually lost</p><p dir="ltr">#$ N_alive_annual: Numeric variable; representing the number of colonies annually alive</p><p dir="ltr"> #$ N_dead_dry: Numeric variable; representing the number of colonies lost during the dry season</p><p dir="ltr">#$ N_alive_dry: Numeric variable; representing the number of colonies alive during the dry season</p><p dir="ltr"> #$ N_dead_rainy: Numeric variable; representing the number of colonies lost during the rainy season</p><p dir="ltr">#$ N_alive_rainy: Numeric variable; representing the number of colonies alive during the rainy season</p><p dir="ltr"> #$ Education: Factor variable; four factors are available ("Self-taught","Learned from another melip","Intro training","Formal tech training"), representing the training level in meliponiculture</p><p dir="ltr"> #$ Operation_Size: Numeric variable; representing the number of colonies managed by the participant (in n)</p><p dir="ltr"> #$ propAgri: Numeric variable; representing the percentage of agricultural area surrounding the meliponary (in %)</p><p dir="ltr"> #$ propForest: Numeric variable; representing the percentage of forested area surrounding the meliponary (in %)</p><p dir="ltr">#$ temp.avg_annual: Numeric variable; representing the average annual temperature (in ºC)</p><p dir="ltr">#$ precip_annual_sum: Numeric variable; representing the total accumulated precipitation (in mm)</p><p dir="ltr">#$ precip_Oct_March_sum: Numeric variable; representing the total accumulated precipitation between October to March (in mm)</p><p dir="ltr">#$ precip_Apri_Sept_sum: Numeric variable; representing the total accumulated precipitation between April to September (in mm)</p><p dir="ltr">#$ temp.avg_Oct_March: Numeric variable; representing the total accumulated precipitation between October to March (in ºC)</p><p dir="ltr">#$ temp.avg_Apri_Sept: Numeric variable; representing the total accumulated precipitation between April to September (in ºC)</p><p dir="ltr"> #$ Importance_dead: Factor variable; three factors are available Normal","High","Very high"), representing the perception of the significance of annual colony losses</p><p dir="ltr"> #$ Climatic_environmental: Binary variable; representing if the participant considered climatic and environmental problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Contamination: Binary variable; representing if the participant considered contamination problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Nutritional: Binary variable; representing if the participant considered nutritional problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Sanitary: Binary variable; representing if the participant considered sanitary problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Queen: Binary variable; representing if the participant considered queen problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Time: Binary variable; representing if the participant considered time problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Economic: Binary variable; representing if the participant considered economic problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Attacks: Binary variable; representing if the participant considered time attacks as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Swarming: Binary variable; representing if the participant considered swarming problems as a potential driver (1) or not (0) of their annual colony losses</p><p><br></p>…”
  4. 104

    Changes in V<sub>T</sub> and FRC during decreasing PEEP. by Marcus J. Kitchen (444759)

    Published 2014
    “…<p>The increase in tidal volume (V<sub>T</sub>) and decrease in functional residual capacity (FRC) when positive end-expiratory pressure (PEEP) is decreased in 5 cmH<sub>2</sub>O stepwise decrements (10-5-0PEEP), large steps (10-0PEEP) and from a small step (5-0PEEP) in the ventilated lung. …”
  5. 105

    The Immunologic Effects of Mesalamine in Treated HIV-Infected Individuals with Incomplete CD4+ T Cell Recovery: A Randomized Crossover Trial by Ma Somsouk (283498)

    Published 2014
    “…The effect of mesalamine in HIV-infected individuals, who exhibit abnormal mucosal immune activation and microbial translocation (MT), has not been established in a placebo-controlled trial. We randomized 33 HIV-infected subjects with CD4 counts <350 cells/mm<sup>3</sup> and plasma HIV RNA levels <40 copies/ml on antiretroviral therapy (ART) to add mesalamine vs. placebo to their existing regimen for 12 weeks followed by a 12 week crossover to the other arm. …”
  6. 106

    Data_Sheet_1_Chemical Similarity of Co-occurring Trees Decreases With Precipitation and Temperature in North American Forests.CSV by Brian E. Sedio (10875330)

    Published 2021
    “…We used untargeted metabolomics methods based on data generated with liquid chromatography-tandem mass spectrometry to identify, classify, and compare 13,480 unique foliar metabolites and to quantify the metabolomic similarity of species in each community with respect to the whole metabolome and each of five broad classes of metabolites. …”
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