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

ECoG timescales decrease during spatial attention. by Isabel Raposo (21615517)

“…Bottom: timescales significantly decrease during covert attention relative to the attend-out condition (two locations: <i>p</i> = 0.0244; four locations: <i>p</i> < 0.0001; mean ± SEM; whiskers indicate maximum and minimum; dots correspond to individual electrodes). …”

Median SHAP values (calculated for CSCHF at age 5000 days) for binary features in the competing risks RSF model for different disease categories. The features are sorted in decreasing order by absolute value for the cancer outcomes. by Eric Wang (30587)

“…The features are sorted in decreasing order by absolute value for the cancer outcomes.…”

<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. …”

NSC population and proliferation decrease drastically during the second postnatal week of DG development. by Cristina Medina-Menéndez (21800157)

Mean ± SD values of unipedal stance parameters evaluated at the different time points of the postural training session. by Cristina Dolciotti (16317330)

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P values of Kruskal–Wallis test at 95% significance level. by Fahd Saeed Alakbari (10701871)

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

The (A) logistic regression model (LRM) and (B) random forest model (RFM) with only conservation scores as independent variables (orange, yellow) show decreased model fitting metri... by Bushra Haque (20513785)

The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. by Gui Araujo (22170819)

“…When they stop being introduced in further assembly events (i.e. introduced species do not carry any mutualistic interactions), their proportion slowly decreases with successive invasions. (B) Even though higher proportions of mutualism promote higher richness, introducing this type of interaction into already assembled large communities promotes a sudden drop in richness, while stopping mutualism promotes a slight boost in richness increase. …”

Class-wise performance on the test set. by Muhammad Zubair (728141)

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Association between the sum of health behaviors and decrease in physical health from before to during the pandemic.... by Elie Mulhem (22537863)

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Participant demographics. * P-values were determined using Fisher-Freeman-Halton test when contingency tables are larger than 2 × 2. by Elie Mulhem (22537863)

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Confusion Metrics: Presenting classification results on the test set. by Muhammad Zubair (728141)

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The MAE value of the model under raw data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

Three error values under raw data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

Image 7_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…Almost all the TAAbs applied for diagnosis are those elevated, however, there are still large numbers of autoantibodies detected to decrease in tumor serums, and their functions were rarely known. …”

Image 6_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…Almost all the TAAbs applied for diagnosis are those elevated, however, there are still large numbers of autoantibodies detected to decrease in tumor serums, and their functions were rarely known. …”

Image 3_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…Almost all the TAAbs applied for diagnosis are those elevated, however, there are still large numbers of autoantibodies detected to decrease in tumor serums, and their functions were rarely known. …”

Image 1_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…Almost all the TAAbs applied for diagnosis are those elevated, however, there are still large numbers of autoantibodies detected to decrease in tumor serums, and their functions were rarely known. …”