N-acetilcysteine prevents the <i>A</i>. <i>simplex</i> CE-induced TEER decrease. by Noelia Carballeda-Sangiao (2889611)

Significant inter-relationships between baseline variables and MSCC or MCS. by Harshit Arora (22008280)

JNJ26993135 + BML-111 decreases permeability and enhances ZO-1 and claudin-1 induced by PAF but does not change TEER. by Kameljit K. Kalsi (16496511)

Transepithelial electrical resistance (TEER) (N = 6). by Shirko Marcel Shokr (19173337)

“…<p><b>(A)</b> During the cultivation of SMC and ALI we observed significantly differences on day 18 (SMC: 9.61 kΩ*cm²; ALI: 7.73 kΩ*cm²; p<0.05) and day 25 (SMC: 8.19 kΩ*cm²; ALI: 6.44 kΩ*cm²; p<0.05) ALI cultures showed significantly decreased values compared to SMC. …”

RMSE. by Pengfei Wu (3200082)

Inter-assay parameters correlations. by Ekaterina M. Koltsova (5464523)

The RMSE of point to point movement results. by John David Prieto Prada (11883577)

RMSE results. by YueSheng Jiang (19267984)

Point range comparisons of RMSE. by Steven M. Pawley (18265087)

The inter-regional Gini coefficient in CCD of HER and DIC. by Ying Xie (50016)

Differences in inter-regional synergy of HER and DIC in China. by Ying Xie (50016)

Performance through MAE, MSE and RMSE. by Ghulam Mustafa (458105)

“…Artificial Intelligence (AI) has increased the yield accuracy significantly. The existing Machine Learning (ML) methods are using statistical measures as regression, correlation and chi square test for predicting crop yield, all such model’s leads to low accuracy when the number of factors (variables) such as the weather and soil conditions, the wind, fertilizer quantity, and the seed quality and climate are increased. …”

Intra- and inter-day precision and accuracy. by Ewa Paszkowska (21246702)

“…<div><p>Purpose</p><p>Statins are the most commonly used drugs worldwide. Besides a significant decrease in cardiovascular diseases (CVDs) risk, the use of statins is also connected with a broad beneficial pleiotropic effect. …”

Transepithelial resistance of NHBE decreases significantly after PAA exposure. by Ellie S. Burns (21246537)

RMSE metrics for different models at varying input sizes. by Xiangyue Zhang (9251306)

RMSE after embedding the CP module into different models. by Xiangyue Zhang (9251306)

Inter-operator reliability^b'*'. by Lotte van Dam (17347733)

“…The coefficient of variance significantly decreased with increasing knee flexion (2.27% at 0°, 1.65% at 45° and 1.20% at 90°, p<0.001). …”

GXM decreases the trans-endothelial electrical resistance (TEER) and transmigration of <i>C</i>. <i>neoformans</i> through HBECs in a blood brain barrier (BBB) model. by Hiu Ham Lee (15374677)

RMSE versus learning rate. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

RMSE versus training parameters. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”