Overview of the WeARTolerance program. by Ana Beato (20489933)

“…The quantitative results from Phase 1 demonstrated a decreasing trend in all primary outcomes. In phase 2, participants acknowledged the activities’ relevance, reported overall satisfaction with the program, and showed great enthusiasm and willingness to learn more. …”

Boxplot comparing Ct values for HD in flies and clothes. by Philippe Ndzomo (17706039)

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

<b>Aversive learning decreases aversive-reinforcer sensitivity</b><b> </b><b>in honey bees</b> by Martin GIURFA (8649351)

S1 Data. Bibliometric analysis. S2 Data. Estrogen level analysis. S3 Data. MicroCT quantification. S4 Data. Markers of bone metabolism. by Yan She (8639796)

The Table explains the "frame", i.e., the smallest time unit of 1/12 seconds. by Piotr Popik (292215)

Skin marks is the S1 Fig title. by Mercedes Soto-González (20422078)

Loss of MAP4K4 expression causes a decrease in the number of neutrophils. by Guihua Wang (286390)

Social change: No decrease in singing rate upon first-time social isolation in the same environment. by Anja T. Zai (9225852)

Mediation model illustrating the relationship between eGDR, diabetes, and frailty. by Wentao Yang (205781)

Youthful systemic milieu in young recipients decreased apoptosis and oxidative stress damage in allografts, and promoted proliferation. by Chengjun Yu (12136227)

The shortened version of the Edinburgh Handedness Inventory encompasses 4 items (e.g. writing) scored on a 5-point scale ranging from:” Always right; usually right; both equally; u... by Marcel F. Hinss (14675457)

Using Environmental Mixture Exposure-Triggered Biological Knowledge-Driven Machine Learning to Predict Early Pregnancy Loss by Mengyuan Ren (14724676)

“…The GO-integrated model, with an area under the curve (AUC) of 0.876, outperformed others (AUC = 0.819), even when the sample size decreased to 60% of the total. Additionally, this framework deciphered critical exposures (e.g., serum selenium and chromium) and biological perturbations (e.g., cell population proliferation and apoptotic nuclear changes), linking mixture exposure to EPL. …”

Passive sensing data. by Thierry Jean (20691795)

“…The CrossCheck dataset includes 6,364 mental state surveys using 4-point ordinal rating scales and 23,551 days of smartphone sensor data contributed by patients with schizophrenia. We trained 120 machine learning models to forecast 10 mental states (e.g., Calm, Depressed, Seeing things) from passive sensor data on 2 predictive tasks (ordinal regression, binary classification) with 2 learning algorithms (XGBoost, LSTM) over 3 forecast horizons (same day, next day, next week). …”

Surveys. by Thierry Jean (20691795)

“…The CrossCheck dataset includes 6,364 mental state surveys using 4-point ordinal rating scales and 23,551 days of smartphone sensor data contributed by patients with schizophrenia. We trained 120 machine learning models to forecast 10 mental states (e.g., Calm, Depressed, Seeing things) from passive sensor data on 2 predictive tasks (ordinal regression, binary classification) with 2 learning algorithms (XGBoost, LSTM) over 3 forecast horizons (same day, next day, next week). …”

Perceptual inference and learning of naturalistic images. by Kwangjun Lee (22226994)

Comparison of training and predicted values of compound water solubility for different machine learning models: (A) AdaBoost, (B) GBDT, (C) LGBM, (D) RF, (E) XGBoost, (F) RF, and (... by Bin Pan (742525)

Barbie audit data. by Cylie Williams (3446018)

Subjects:

The FEET system of barbie categorisation. by Cylie Williams (3446018)

Subjects:

Average mean decrease Gini across 100 partitions for the top 10 most important variables for binary mixed model and random forest. by Helal El-Zaatari (20442243)