Flow chart of exclusions. by Kimberly J. Johnson (4281190)

“…We used the posterior predictive distribution to model differences between a predicted, uninterrupted process and the observed screening mammogram counts. …”

Detailed technical parameters of the test engine. by Mehmet Ferruh Kılınç (21567787)

“…Especially at a premixing ratio of 45%, an increase of 50% within heat release rate was observed. …”

Open chain representations of butanol isomers. by Mehmet Ferruh Kılınç (21567787)

“…Especially at a premixing ratio of 45%, an increase of 50% within heat release rate was observed. …”

Experimental Study Parameters. by Mehmet Ferruh Kılınç (21567787)

“…Especially at a premixing ratio of 45%, an increase of 50% within heat release rate was observed. …”

Diagram illustrating the experimental setup. by Mehmet Ferruh Kılınç (21567787)

“…Especially at a premixing ratio of 45%, an increase of 50% within heat release rate was observed. …”

Rp_0.30_Combustion_and_emissions_Dataset. by Mehmet Ferruh Kılınç (21567787)

“…Especially at a premixing ratio of 45%, an increase of 50% within heat release rate was observed. …”

Rp_0.30_Pressure_HRR_Temp_Dataset. by Mehmet Ferruh Kılınç (21567787)

“…Especially at a premixing ratio of 45%, an increase of 50% within heat release rate was observed. …”

Supplementary Material for: Levothyroxine Administration during Ramadan: A Prospective Randomized Controlled Trial by El-Kaissi S. (11254149)

“…For patients at the 50th percentile pre-Ramadan, no statically significant within-patient changes were found, though descriptively, increases in plasma TSH were observed for groups 2 and 3, while a decrease was observed in group 1. …”

Data for brain oscillations. by Thomas Jacquet (9960275)

“…During the cognitively demanding task, mental fatigue was evidenced by increased errors, missed trials, and decreased N100 amplitude over time. While no effect was reported on force steadiness, both tasks induced a decrease in MVC (<i>p</i> = .040), a force RFD-SF lower slope (<i>p</i> = .011), and a reduction in the coefficient of determination (<i>p</i> = .011). …”

Data for physical tasks. by Thomas Jacquet (9960275)

“…During the cognitively demanding task, mental fatigue was evidenced by increased errors, missed trials, and decreased N100 amplitude over time. While no effect was reported on force steadiness, both tasks induced a decrease in MVC (<i>p</i> = .040), a force RFD-SF lower slope (<i>p</i> = .011), and a reduction in the coefficient of determination (<i>p</i> = .011). …”

Subjective data. by Thomas Jacquet (9960275)

“…During the cognitively demanding task, mental fatigue was evidenced by increased errors, missed trials, and decreased N100 amplitude over time. While no effect was reported on force steadiness, both tasks induced a decrease in MVC (<i>p</i> = .040), a force RFD-SF lower slope (<i>p</i> = .011), and a reduction in the coefficient of determination (<i>p</i> = .011). …”

Bifurcation stability in the A branch model with Dirichlet cell boundary conditions. by Lowell T. Edgar (10099338)

Estimating germline maintenance. by Mareike Koppik (4489318)

POLDIP3 is a common substrate of different coronaviruses nsp5. by Yang Wu (66682)

“…(C and D) Overexpression of POLDIP3 decreased PEDV and TGEV infection by TCID₅₀ assay. …”

The age distribution of the patients. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Comparison experiments. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

External validation comparison results. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Patient characteristics. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Comparison with baseline methods. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

The details of the channel attention module. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”