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DataSheet_1_Changes in Urologic Operative Practice at the Beginning of the COVID-19 Pandemic in a Large, National Cohort.docx
Published 2021“…Northeastern (β = -5.66, 95% confidence interval [CI]: -10.2 to -1.18, p = 0.013) and Midwestern hospitals (β = -4.17, 95% CI: -7.89 to -0.45, p = 0.027; both with South as reference region), and those with an increasing percentage of patients insured by Medicaid (β= -0.17 per percentage point, 95% CI: -0.33 to -0.01, p = 0.04) experienced a significantly larger decrease in volume.</p>Conclusions<p>There was a 20% decline in urologic operative volume in March 2020, compared with baseline, that preferentially affected hospitals serving Medicaid patients, and those in Northeast and Midwest. …”
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The number of Brn3a-expressing cells in retino-collicular co-cultures decreases between DIV4 and DIV12.
Published 2013“…(B, C) The density of cells immunoreactive for Brn3a undergoes a reduction of ∼68% between DIV4 and DIV7, and a further decrease of ∼22% between DIV 7 and DIV12. …”
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Estimation of a Floquet multiplier (FM) using linear regression.
Published 2015“…Though the length of the two cases are the same (1000), the stitched time series has significantly larger bias than a single time series. All of these results remain similar when the noise comes from a uniform or lognormal distribution; the estimation of FM using linear regression shows similar bias in the presence of noise from a uniform distribution (E), or an asymmetric lognormal distribution (F).…”
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Coupled Dynamics of Droplet Impact on a Flexible, Hydrophilic Cantilever Beam
Published 2023“…As expected, increasing the droplet viscosity dampens the magnitude of droplet spreading and displacement of the cantilever’s tip due to a larger dissipation of kinetic energy in the bulk of the droplet. …”
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Data_Sheet_1_Linear fine-tuning: a linear transformation based transfer strategy for deep MRI reconstruction.PDF
Published 2023“…Accordingly, we propose a novel transfer strategy, linear fine-tuning (LFT), which introduces scaling and shifting (SS) factors into the pre-trained model. …”
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