Table 4_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.xlsx by Chao-Chao Chen (21090215)

“…<p>The global prevalence of metabolic diseases, including hypertension, type 2 diabetes mellitus (T2DM), gout, and obesity, has significantly increased over the past two decades. The brain plays a central role in regulating both human behavior and metabolism. …”

Table 5_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.xlsx by Chao-Chao Chen (21090215)

“…<p>The global prevalence of metabolic diseases, including hypertension, type 2 diabetes mellitus (T2DM), gout, and obesity, has significantly increased over the past two decades. The brain plays a central role in regulating both human behavior and metabolism. …”

The number of male–male agonistic interactions in relation to females with maximal swelling. by Heungjin Ryu (10747673)

“…<b>(D)</b> Visualization of the interdependency between the number of males and females with maximal swelling on the male aggression rate (significant interaction in LM-2E) shows that when there were a greater number of males in the party, e.g., Mean + 1SD (9.6 males in D), the male aggression rate decreased as the number of females with maximal swelling increased. …”

Downregulation of ATM1 affects iron-sulfur cluster proteins in <i>Toxoplasma</i> and iron levels in <i>Plasmodium</i>. by Deepti Shrivastava (17715780)

“…The number of significantly increased and decreased proteins is given and the NEET protein CDGSH1 is indicated. …”

Population structure impacts the relationship between the amount of environmental DNA particles and organism abundance by Toshiaki S. Jo (15869182)

“…On the other hand, under the allometric eDNA production, the <i>R</i>^<em>2</em> values decreased for the populations with broader population size range and broader/heterogeneous mass distribution by using biomass, which was not statistically significant by using ASM.…”

S1 Data - by Yumeng Zhang (3115050)

“…The results of this study suggest that the level of well-being as a whole, as well as in the eastern, central and western regions increased significantly over the period, with an “east-to-west decreasing” distribution in China. …”

Index system for well-being level. by Yumeng Zhang (3115050)

“…The results of this study suggest that the level of well-being as a whole, as well as in the eastern, central and western regions increased significantly over the period, with an “east-to-west decreasing” distribution in China. …”

DataSheet1_Association between amoxicillin administration and outcomes in critically ill patients with acute kidney injury.PDF by Xinyao Luo (12084194)

“…A dose‒response relationship was evident, with higher doses (>875 mg) further decreasing mortality rates. …”

Generated spline library. 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. …”

Correlation coefficient matrix. 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. …”

Actual measurement of shape errors. 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. …”

RMSE versus learning rate. 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. …”

RMSE versus training parameters. 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. …”

Assembly process of machine recognition form. 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. …”

Process of steel truss incremental launching. 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. …”

CGAN and AutoML stacking device. 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. …”

Comprehensive prediction process of shape errors. 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. …”

Shape error manual calculation process. 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. …”

U-wave estimates versus R-matrix noise variance. 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. …”

Sliding window process. 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. …”