Results of the LMM analysis for GMS change. by Sayaka Kimura-Uchida (22793666)

“…The mean GMS was 2.46 ± 1.33 preoperatively, and decreased to 1.32 ± 1.31 at 3 months, and 1.60 ± 1.41 at 12 months postoperatively. …”

Mean parameter values for the selected crops. by Gourab Saha (8987405)

“…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”

Scaling of overall health burden with yearly expenditure growth. by Margherita Molaro (17803989)

Narrow- and broad-band spectral changes after hemispherotomy in an awake representative patient, displaying marked electroencephalography (EEG) slowing of the isolated cortex. by Michele Angelo Colombo (22446342)

Pathological changes in lung tissue of mice exposed to continuous inhalation of CS. by Yue He (385239)

Cross-sectional dependence results. by Ozlem Kutlu Furtuna (20308206)

“…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …”

Autocorrelation test results. by Ozlem Kutlu Furtuna (20308206)

“…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …”

Pesaran’s CADF test results for Model I. by Ozlem Kutlu Furtuna (20308206)

“…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …”

Descriptive statistics of related variables. by Ozlem Kutlu Furtuna (20308206)

“…Moreover, FDI and the non-linear form of FDI have no significant influence on ecological footprint. …”

AZ10606120 treatment significantly increased cytotoxicity and reduced cell number in a dose-dependent manner. by Matthew Drill (22258391)

“…Cell numbers were significantly decreased in cells after treatment with AZ10606120 (50µM) compared to both temozolomide (TMZ; 50µM) treatment and untreated controls. …”

Baseline characteristics of participants. by Mei Zhou (269746)

“…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …”

The framework diagram of this study. by Mei Zhou (269746)

“…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …”

Behaviour and significance of reservoir evaporation and seepage losses – an experience of four reservoirs in Damodar River Valley, India by Dipankar Chaudhuri (498103)

“…Annual pattern of both monthly (non-monsoon) and water-year mean seepage rates was similar. Frequency of seepage varied significantly with the season or month. …”

GWAS analysis using Cluster 2 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis using only Cluster 1 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis using Cluster 3 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis using Cluster 4 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis identifies several single nucleotide polymorphisms (SNPs) that are associated with the changes in viral copies. by Ke Li (106849)

GWAS analysis identifies several single nucleotide polymorphisms (SNPs) that are associated with the changes in viral copies. by Ke Li (106849)

Top predictive variables for KDIGO stage ≥ 3 identified by the final Random Forest model. by Julian Müller-Kühnle (22265248)