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. …”

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

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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. …”

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.…”

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

Assessment values of machine learning models. by Bin Pan (742525)

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

“…<div><p>Ensuring that a robot employing demonstration learning models can simultaneously achieve accurate trajectory tracking of demonstrated paths and effective avoidance of moving obstacles in dynamic environments remains a critical research challenge. …”

Performance evaluation of models based on various indicators in 2008 and 2023. by Abdolhossein Boali (19996390)

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

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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)

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

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Decrease in loss during the training process. by Muhammad Idrees (92773)

Model and learning rule. by Janis Keck (21587252)

“…The right column has the same pre- and postsynaptic activities as the left column, only in reverse order. In <b>(C)</b>, the learning rule with parameters is used, while in <b>(D)</b> Only in the latter the synaptic weight changes are preserved (in reverse order), while in <b>(C)</b>, postsynaptic activity before presynaptic activity leads to a net weight decrease. …”

Spatio-temporal data mining modeling for wind erosion risk assessment. by Abdolhossein Boali (19996390)

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Performance evaluation of ensemble model based on various indicators in 2008 and 2023. by Abdolhossein Boali (19996390)

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The maps illustrating wind erosion in northeastern Iran for 2008 and 2023, generated using various models from the SDM package. by Abdolhossein Boali (19996390)

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Performance comparison of machine learning models across accuracy, AUC, MCC, and F1 score on GMSC dataset. by Seongil Han (20490232)

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Performance comparison of machine learning models across accuracy, AUC, MCC, and F1 score on GMSC dataset. by Seongil Han (20490232)

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

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