The linearly decreasing convergence factor a. by Junhao Wei (6816803)

<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

“…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". The following acronyms included in the CSV file are defined as follows: Hbt is total hemoglobin, Art is artery region, DV is draining vein region, WV is whisker vein region, SEM is standard error mean, TS is time series, max peak is maximum peak, min peak is minima, AUC is area under the curve, WT is wild-type, AD is Alzheimer's disease, ATH is atherosclerosis and MIX is mixed AD/atherosclerosis. …”

Obstacle uniform linear motion scenarios. by Long Di (9977453)

“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”

Based on our time series data(first from the left), the visualizations of linear residual predictions under different decimation rates (next three) show that as the decimation rate decreases, the range of residual variations also becomes smaller. by Hua Huo (1818133)

“…<p>Based on our time series data(first from the left), the visualizations of linear residual predictions under different decimation rates (next three) show that as the decimation rate decreases, the range of residual variations also becomes smaller.…”

Association between the sum of health behaviors and decrease in physical health from before to during the pandemic. Results are from linear model analysis adjusted for age, gender and additional covariates.... by Elie Mulhem (22537863)

“…Results are from linear model analysis adjusted for age, gender and additional covariates. …”

nsP4-C483Y or Q192L mutations decrease sensitivity to 4′-FlU. by Peiqi Yin (6533747)

STL Linear Combination Forecast Graph. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

Innovation and night light in large and small cities. by Saul Estrin (8629173)

Linear regressions of consumer stable carbon and nitrogen isotope values and collection date. by Nathan D. McTigue (10706460)

The flowchart of the large model for font style transfer. by Weijia Zhu (65481)

Subjects:

Predicted distance (km) needed to achieve a correlation coefficient of at least r =  0.50 using the median-based linear regression models. by Claire Stevens (11127729)

Association of each health behavior and the reported decrease in psychological well-being during the pandemic between individuals who often/very often compared to rarely/never engaged in health behaviors.... by Elie Mulhem (22537863)

“…<p>Association of each health behavior and the reported decrease in psychological well-being during the pandemic between individuals who often/very often compared to rarely/never engaged in health behaviors. …”

Effect of each health behavior on the reported decrease in physical health during the pandemic between individuals who often/very often compared to rarely/never engaged in health behaviors.... by Elie Mulhem (22537863)

“…<p>Effect of each health behavior on the reported decrease in physical health during the pandemic between individuals who often/very often compared to rarely/never engaged in health behaviors. …”

Linear regressions of pPOM and sPOM stable carbon and nitrogen isotope values versus collection date. by Nathan D. McTigue (10706460)

Few-Shot Symbol Detection in Engineering Drawings by Laura Jamieson (19759235)

Subjects:

Baseline patient characteristics. by Oscar F. C. van den Bosch (22184246)

Subjects:

Deep learning-based locomotive syndrome prediction method. by Junichi Kushioka (12236447)

Subjects:

Results from linear regression analysis for δ¹³C or δ¹⁵N and collection date. by Nathan D. McTigue (10706460)

Linear regression. by Myriam Aïche (22290591)

Linear regressions of the distance between buoys (km) and the Pearson correlation coefficient for each pairwise buoy combination for 2021 (blue) and 2022 (gray). by Claire Stevens (11127729)