Showing 9,081 - 9,100 results of 49,000 for search '(( a ((step decrease) OR (mean decrease)) ) OR ( i ((largest decrease) OR (larger decrease)) ))', query time: 0.82s Refine Results
  1. 9081

    Influence of temperature on tire-pavement noise in hot climates: Qatar case by Okan, Sirin

    Published 2021
    “…There is an apparent trend of decreasing temperature coefficient with increasing mean texture depth of dense graded asphalt pavements. …”
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  2. 9082

    Alcohol and breast cancer risk: Middle-aged women’s logic and recommendations for reducing consumption in Australia by Samantha B. Meyer (555077)

    Published 2019
    “…We identified a low level of awareness of alcohol and breast cancer risk, and confusion related to alcohol as a risk for breast cancer, but not <i>always</i> causing breast cancer. …”
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    Gradients of timescales and predictability are consistent with an increase in recurrence in network models with correlated external input. by Lucas Rudelt (4059505)

    Published 2024
    “…In a given time step, units are either active or inactive, and, if active, can activate each connected neighbour with fixed probability <i>m</i>/<i>k</i> for the next time step. …”
  5. 9085

    S1 Dataset - by Mphatso Nancy Chisala (20477275)

    Published 2024
    “…Overall admissions declined but mortality remained around 23% [95%CI; 21, 25], and deaths occurred earlier (5.6 days [95%CI; 4.6, 6.9] in 2011 vs. 3.5 days [95%CI; 2.5, 4.7] in 2021; <i>p</i><0.001). Duration of hospitalization was shortened and readmissions surged from 4.9% [95%CI; 3.3, 7.4] in 2011 to 25% [95%CI; 18, 33] in 2021 (<i>p</i><0.001). …”
  6. 9086

    A novel approach for automatic visualization and activation detection of evoked potentials induced by epidural spinal cord stimulation in individuals with spinal cord injury by Samineh Mesbah (4506406)

    Published 2017
    “…The proposed method provides a fast and accurate five-step algorithms framework for activation detection and visualization of the results including: conversion of the EMG signal into its 2-D representation by overlaying the located signal building blocks; de-noising the 2-D image by applying the Generalized Gaussian Markov Random Field technique; detection of the occurrence of evoked potentials using a statistically optimal decision method through the comparison of the probability density functions of each segment to the background noise utilizing log-likelihood ratio; feature extraction of detected motor units such as peak-to-peak amplitude, latency, integrated EMG and Min-max time intervals; and finally visualization of the outputs as Colormap images. …”
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    Mean (± Standard Error) relative distribution (%) of the energy contained in the signal up to 200 Hz as a function of the frequency bands on the X-, Y- and Z-axis of the racket accelerometer (XR, YR and ZR, respectively) and X-axis of the wrist accelerometer (XW), for both decreased (V-) and increased (V+) velocity conditions (left), and for both lightly vibrant (RL) and highly vibrant (RH) rackets (right), with * for p≤0.05, ** for p ≤ 0.01, and *** for p ≤ 0.001. by Isabelle Rogowski (613715)

    Published 2015
    “…<p>Mean (± Standard Error) relative distribution (%) of the energy contained in the signal up to 200 Hz as a function of the frequency bands on the X-, Y- and Z-axis of the racket accelerometer (XR, YR and ZR, respectively) and X-axis of the wrist accelerometer (XW), for both decreased (V-) and increased (V+) velocity conditions (left), and for both lightly vibrant (RL) and highly vibrant (RH) rackets (right), with * for p≤0.05, ** for p ≤ 0.01, and *** for p ≤ 0.001.…”
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