Baseline patient characteristics. by Oscar F. C. van den Bosch (22184246)

“…While mean respiratory rate was not affected, midazolam resulted in a significant decrease in both VRR (ß = −0.071, 95% CI: −0.120 to −0.021) and VTV (ß = −0.117, 95% CI: −0.170 to −0.062). …”

The injectable contraceptives depot medroxyprogesterone acetate and norethisterone enanthate substantially and differentially decrease testosterone and sex hormone binding globulin... by Chanel Avenant (409756)

Data. by Aroon La-up (14095691)

“…However, no statistically significant changes were observed in groups with U-Cd levels above 2.0 μg/g creatinine. …”

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)

Study-related adverse events. by Benjamin R. Lewis (22279166)

“…In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Study flow chart. by Benjamin R. Lewis (22279166)

“…In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Study CONSORT diagram. by Benjamin R. Lewis (22279166)

“…In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Image 2_Changes in the gut microbiome due to diarrhea in neonatal Korean indigenous calves.jpeg by Ji-Yeong Ku (20832209)

“…However, Proteobacteria increased and Bacteroidetes and Actinobacteria decreased in calves with diarrhea. In addition, calves with diarrhea showed a significant decrease in the diversity of the gut microbiome, especially for anaerobic microorganisms Faecalibacterium prausnitzii, Gemmiger formicilis, and Collinsella aerofaciens. …”

Image 1_Changes in the gut microbiome due to diarrhea in neonatal Korean indigenous calves.jpeg by Ji-Yeong Ku (20832209)

“…However, Proteobacteria increased and Bacteroidetes and Actinobacteria decreased in calves with diarrhea. In addition, calves with diarrhea showed a significant decrease in the diversity of the gut microbiome, especially for anaerobic microorganisms Faecalibacterium prausnitzii, Gemmiger formicilis, and Collinsella aerofaciens. …”

Recruitment flow diagram of the current study. by Somayeh Momenyan (10111603)

“…Predictors of HRQoL included sociodemographic, psychological, medical, and trauma-related factors collected at baseline. We applied generalized additive mixed models to flexibly capture nonlinear changes in HRQoL over time, and piecewise latent growth curve model to analyze distinct linear phases of recovery across defined time intervals.…”

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

“…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. …”

Performance comparison of ML models. by Gourab Saha (8987405)

“…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. …”

Comparative data of different soil samples. by Gourab Saha (8987405)

“…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. …”

Confusion matrix of random forest model. by Gourab Saha (8987405)

“…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. …”

Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

“…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. …”

Evaluation metrics of selected ML models. by Gourab Saha (8987405)

“…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. …”

Block diagram of the proposed system. by Gourab Saha (8987405)

“…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. …”

Chart for applicable amount of fertilizers. by Gourab Saha (8987405)

“…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. …”

Cost analysis of irrigation controller unit. by Gourab Saha (8987405)

“…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. …”

Run times of two algorithms. by Gourab Saha (8987405)

“…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. …”