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)

Analysis of the difference in overall bacterial community structure in each group. by Shudan Liu (7049483)

VEGF immunoperoxidase in kidneys of 17-GD LP progeny compared to NP offspring. by Julia Seva Gomes (15411772)

HIF-1α immunoperoxidase in kidneys of 17-GD LP progeny compared to NP offspring. by Julia Seva Gomes (15411772)

Mitochondrial function of memory CD8 T cells increases with time after infection. by Matthew D. Martin (803107)

“…Error bars represent the standard error of the mean.</p>…”

Serum levels of anti-CsAWA IgG and IgE in <i>Cs</i>- and <i>Cs</i>+ individuals with different genders. by Shuo Kan (13766867)

Serum levels of antibodies and cytokines in <i>Cs</i>- and <i>Cs</i>+ individuals excluding co-infection with soil-transmitted helminths. by Shuo Kan (13766867)

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. …”