S1 File - by Vasanthi Avadhanula (259546)

Subjects:

Proportion of time spent in the Start Room or Avoidance Room or showing a behaviour (Stimulus Contact) presented across stimuli and separately for piglets and gilts. by Sara Hintze (3216885)

Subjects:

Table 1_Significance of host antimicrobial peptides in the pathogenesis and treatment of acne vulgaris.docx by Agata Lesiak (17951854)

A, Uncropped image of gel in Fig 1B. by Tomokazu Yamaguchi (8284989)

Subjects:

Cascade of care by HCV testing model. by Bao Vu Ngoc (14551955)

Subjects:

Factors associated with first-time HCV testing. by Bao Vu Ngoc (14551955)

Subjects:

Structure-Affinity-Pharmacokinetics Relationships of Novel ¹⁸F‑Labeled 1,4-Diazepane Derivatives for Orexin 1 Receptor Imaging by Yui Ishizaka (19922137)

Subjects:

Sex-based differences for combinations of brain regions and cell types, based on Mann-Whitney U-test. 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:

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

Subjects:

Clinical characteristics. by Clemens Plattner (21567706)

Subjects:

Principal Component Analysis (PCA) to illustrate the distribution of the significant lipid metabolites among the groups (NL, SS and MASH). by Laia Bertran (3685147)

Design of the D-trial. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Estimated mean values for light interception. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Raw data V-trial. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Raw data D-trial. by Torsten Schober (20485754)

“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m². …”

Detailed information of the observation datasets. by Weidong Ji (129916)

“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”

General technical specification for GW154/6700. by Weidong Ji (129916)

“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”