S2 File - Factors influencing effective decrease of controlled attenuation parameters in metabolic-associated steatotic liver disease: A multilevel linear regression analysis at Va... by Sonsawan Sangprasert (22772538)

Summary of sites of activity of genes encoded by SNPs observed to be associated in our study in the NO signaling pathway downstream of Cit. by Dai Nogimura (21445649)

Subjects:

A prepubertal CD decreases hepatic DNA methylation and increases hydroxymethylation in adulthood despite a chronic HFD in Sprague-Dawley male rats. by Ana Aguilar-Lozano (20614619)

EGF is decreased in individual donor milk, but not pooled donor milk. by Christian Tamar (21100605)

RcbA and RcbB co-operatively decrease motility independent of CaCl₂ concentration. by Shobnom Mustaree (21728815)

Deep crypt secretory (DCS) cells are predominantly distributed in the proximal colon, with a progressive decrease towards the distal colon. by Daisuke Sugahara (2047696)

PAP I point mutations lead to a decrease in pYV PCN, plasmid stability, and T3SS activity. by Katherine Schubert (5452712)

The performance of eigenvectors of the covariance matrix in a model with more complex population structure. by Joshua G. Schraiber (8027060)

Mean case duration before and after intervention (t-statistic = -3.35, p <i>< </i>0.001), indicating a statistically significant difference in means. by Mohammad Bakhtiari (11838264)

Pan-cancer analyses of ACADM expression and its prognostic significance in the TCGA database. by Yu Zhang (12946)

ATGL-1 levels increase and lipid droplets decrease in response to <i>N. parisii</i> infection. by Hala Tamim El Jarkass (16625309)

Shematic representation for the mechanism of the swelling pressure: (a)soil without added fiber; (b)soil with added fiber. by Yonggang Huang (223155)

Decreased expression of tight junction proteins and disruption of intestinal barrier integrity in DSS-induced colitis mouse model. by Mariam Wed Eladham (21439745)

Generated spline library. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Correlation coefficient matrix. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus learning rate. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus training parameters. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Assembly process of machine recognition form. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Process of steel truss incremental launching. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

CGAN and AutoML stacking device. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”