Baseline patient characteristics. حسب 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). …"

Cohort characteristics. حسب Fernanda Talarico (807333)

"…</p><p>Results</p><p>The analysis reveals a significant decrease in all health services utilization from 2016 to 2019, followed by an increase until 2022. …"

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

Study-related adverse events. حسب 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. حسب 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. حسب 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). …"

Geometric manifold comparison visualization حسب Eloy Geenjaar (21533195)

"…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …"

Hyperparameter ranges حسب Eloy Geenjaar (21533195)

"…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …"

Convolutional vs RNN context encoder حسب Eloy Geenjaar (21533195)

"…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …"

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

"…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. حسب Torsten Schober (20485754)

"…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. حسب Torsten Schober (20485754)

"…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. حسب Torsten Schober (20485754)

"…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. …"

Primer sequences used for RT-PCR. حسب Jingjing Chen (293564)

"…Notably, SIRT1 levels decrease with age in both mice and during cellular senescence, highlighting its significance in anti-aging processes. …"

Correlation in site-level DNA methylation estimates between TMS and RRBS data after permutation. حسب Amy Longtin (21409957)

Scores vs Skip ratios on single-agent task. حسب Hongjie Zhang (136127)

"…Inspired by human decision-making patterns, which involve reasoning only on critical states in continuous decision-making tasks without considering all states, we introduce the <i>LazyAct</i> algorithm. This algorithm significantly reduces the number of inferences while preserving the quality of the policy. …"

Time(s) and GFLOPs savings of single-agent tasks. حسب Hongjie Zhang (136127)

"…Inspired by human decision-making patterns, which involve reasoning only on critical states in continuous decision-making tasks without considering all states, we introduce the <i>LazyAct</i> algorithm. This algorithm significantly reduces the number of inferences while preserving the quality of the policy. …"

The source code of LazyAct. حسب Hongjie Zhang (136127)

"…Inspired by human decision-making patterns, which involve reasoning only on critical states in continuous decision-making tasks without considering all states, we introduce the <i>LazyAct</i> algorithm. This algorithm significantly reduces the number of inferences while preserving the quality of the policy. …"

Win rate vs Skip ratios on multi-agents tasks. حسب Hongjie Zhang (136127)

"…Inspired by human decision-making patterns, which involve reasoning only on critical states in continuous decision-making tasks without considering all states, we introduce the <i>LazyAct</i> algorithm. This algorithm significantly reduces the number of inferences while preserving the quality of the policy. …"

Visualization on SMAC-25m based on <i>LazyAct</i>. حسب Hongjie Zhang (136127)

"…Inspired by human decision-making patterns, which involve reasoning only on critical states in continuous decision-making tasks without considering all states, we introduce the <i>LazyAct</i> algorithm. This algorithm significantly reduces the number of inferences while preserving the quality of the policy. …"