Showing 1 - 20 results of 291 for search '(((( 59 ((_ decrease) OR (mean decrease)) ) OR ( 10 nn decrease ))) OR ( 50 n decrease ))*', query time: 0.17s Refine Results
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    Biocorrosion behavior of biodegradable nanocomposite fibers coated layer-by-layer on AM50 magnesium implant by Abdal-hay, Abdalla

    Published 2016
    “…The results showed that the AJS 3D membrane fiber layers, particularly the hybrid membrane layers containing a small amount of nHA (3wt.%), induce a higher biocorrosion resistance and effectively decrease the initial degradation rate compared with the neat AM50 coupon samples. …”
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    Adaptive thermal comfort in the different buildings of Darjeeling Hills in eastern India – Effect of difference in elevation by Thapa, Samar

    Published 2018
    “…Whereas, the mean comfort temperature decreased with the elevation of the location and this difference was also statistically significant, t = −92.34 (df = 2607, p < 0.001). …”
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    Study of performance, combustion, and emissions parameters of DI-diesel engine fueled with algae biodiesel/diesel/n-pentane blends by Elkelawy, Medhat

    Published 2021
    “…Through performance tests, it was found that 15 ml of n-pentane per liter was the best addition as it caused an increase in the brake thermal efficiency of 7.1% and a decrease in brake specific fuel consumption of 6.4% compared to the elegant B50. …”
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    The Structure of the Free Volume in Poly(styrene-co-acrylonitrile) from Positron Lifetime and Pressure Volume Temperature (PVT) Experiments by Dlubek, Gunter

    Published 2004
    “…The mean hole volume, vh, varies in PS between 105 Å3 (27 °C) and 220 Å3 (190 °C), and shows a systematic decrease with increasing AN content, at Tg from 121 Å3 for PS to 102 (±2) Å3 for SAN50. …”
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    Limiting the Rise in Core Temperature During a Rugby Sevens Warm-up With an Ice Vest. by Taylor, Lee

    Published 2019
    “…Athletes in VEST demonstrated a decrease in ΔTS (-1.59; ±0.72) and ΔTC (-1.63; ±0.73) pre- to post-warm-up, with a lower RPE post warm-up (-1.01; ±0.46), compared to CONTROL. …”
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    Estimating blood pressure from the photoplethysmogram signal and demographic features using machine learning techniques by Chowdhury, Moajjem H.

    Published 2020
    “…Gaussian process regression (GPR) along with the ReliefF feature selection algorithm outperforms other algorithms in estimating SBP and DBP with a root mean square error (RMSE) of 6.74 and 3.59, respectively. …”
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