(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. …”

Baseline characteristics. by Seung Min Lee (1644409)

“…Such a change was relevant to the improvement in BCVA, but not metamorphopsia.…”

Data file used in this study. by Seung Min Lee (1644409)

“…Such a change was relevant to the improvement in BCVA, but not metamorphopsia.…”

Changes in foveal location after surgery. by Seung Min Lee (1644409)

“…Such a change was relevant to the improvement in BCVA, but not metamorphopsia.…”

General participant characteristics. by Josephine Grandt (21512356)

“…GOBP analyses revealed an increase in pro-inflammatory and pro-fibrotic genes in NAFLD and cirrhosis, as well as a decrease in genes related to metabolism. Data were made browsable using two web-based apps. …”

Knockdown of <i>atg1</i> in DPM neurons causes memory loss. by Tong Yue (6033305)