The minimal data set 21. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 18. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 20. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 5. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 17. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 19. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 4. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 13. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

The minimal data set 7. by Esete Habtemariam Fenta (9727779)

“…The most significant service delivery changes included repurposing health centers and prolonged prescriptions (multi-month medication dispensing). …”

(Related to Fig 6): NPF in LNd and NPFR in LPN are not required to high-temperature-induced evening sleep decrease. by Xin Yuan (174619)

Testing set error. 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. …”

S1 Data - by Miki Doi (15347878)

Subjects:

Contains R code utilized in the analyses. by Arttu Autio-Kimura (20454681)

Subjects:

Sex-based differences for combinations of brain regions and cell types, based on Mann-Whitney U-test. by Arttu Autio-Kimura (20454681)

Subjects:

Bootstrapped spearman correlations from a randomly selected subset of male sample donor originating samples (n = 493). by Arttu Autio-Kimura (20454681)

Subjects:

Spearman correlations between the age of the sample donor (20–70 years) and estimated proportions of neuronal, glial, and endothelial cells. by Arttu Autio-Kimura (20454681)

Subjects:

Box plots for subsets of female originating samples, displaying the distributions of the proportions of neuronal, glial, and endothelial cells. by Arttu Autio-Kimura (20454681)

Subjects:

Box plots for subsets of male originating samples, displaying the distributions of the proportions of neuronal, glial, and endothelial cells. by Arttu Autio-Kimura (20454681)

Subjects:

Box plot displaying the distributions of the deconvolution derived proportions of cell types. by Arttu Autio-Kimura (20454681)

Subjects:

Spearman correlation of age with proportions of cell types in men, for each brain region. by Arttu Autio-Kimura (20454681)

Subjects: