Effect of the POM cycles on selected metabolites. by Bonnie A. McNeil (22331601)

Assembly error angle of a single spline. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”

Data_Sheet_1_Effects of a 30-min rest with a nap chair on task performance, sleepiness, and neurophysiological measures in men with suspected brain fatigue: a randomized controlled... by Minoru Fujino (12742196)

“…The Karolinska Sleepiness score significantly decreased after the nap-chair rest, and the between-treatment difference in the decrease was highly significant (P = 0.0004). …”

Antibodies information. by Xin Zhang (35492)

“…It has been reported that GsMTx-4, a specific blocker of the mechanosensitive ion channels Piezo1, can protect the integrity of the neuromuscular junction and promote nerve regeneration, and thus has the potential as a therapeutic agent for SCI. …”

Transient suppression of autophagy in neurons impairs ITM. by Tong Yue (6033305)

(a)Raw soil; (b) The grain size distribution. by Chenhao Li (822769)

“…Although increasing SHMP content improved the early strength, it led to a decrease in later strength, with the maximum late strength observed at 2% SHMP. …”

(a) The impact of changing the epoch at which the proximity factor for infection clusters is activated on the validation infection coverage and <i>F</i>₁ measure. by Ibrahim Almakky (22530341)

Data from: Quantifying seed rain patterns in a remnant and a chronosequence of restored tallgrass prairies in north central Missouri by Katherine Wynne (22078346)

“…We further found that decreases in seed rain quantity across the chronosequence did not correspond with increases in seed mass, suggesting a lack of tradeoffs between these metrics. …”

Inhibition of lysosomal activity causes memory impairment. by Tong Yue (6033305)

“…<p><b>(A)</b>Heatmap of significantly down-regulated genes associated with the lysosomal signaling pathway between ND and HFD. …”

HFD impairs autophagic activity in fly brains. by Tong Yue (6033305)

Experimental design of this study. by Renya Kawakami (20469088)

“…However, only a few studies that investigated influences of male aging as well as male mating experience on their post-copulatory sexual selection. …”

All relevant data of this study. by Renya Kawakami (20469088)

“…However, only a few studies that investigated influences of male aging as well as male mating experience on their post-copulatory sexual selection. …”

Supplementary Material for: Off-label Use of Mycophenolate Mofetil in Immunoglobulin A Nephropathy: A Systematic Review and Meta-analysis by Feng L. (5056958)

“…Introduction: Mycophenolate mofetil (MMF) is widely used off-label in patients with immunoglobulin A nephropathy (IgAN), although the literature does not consistently agree on its efficacy and safety. …”

Preference for the EIA – conjoint results. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample attribute table. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Subgroup analysis – Political affiliation. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample scenario description. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

AMCEs – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Methodological flowchart. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Preference for the EIA vs. ETA across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”