Prediction of the effects of immobilization on the force-velocity relationship. by Frédéric Derbré (3157917)

Efficacy and safety of a single radiofrequency ablation of solid benign non-functioning thyroid nodules by Roberto Cesareo (4676131)

Optimal time points for a three-colonoscopy screening program in the US. by Viktor Zaika (18611072)

“…Selected model parameters were increased and decreased by up to 50%. Dashed lines indicate average optimal points obtained for nominal simulations. …”

Stimulation of murine <i>i</i>NKT cells, γδ T cells, or B cells in RPMI^suppl has no negative impact on cell viability. by Yusuf Cem Eskiocak (10789281)

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. …”

Ablation 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. …”

Pathological diagnosis. 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 ECRNet. 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. …”

Dynamics of CMV-specific CD8⁺ T-cells and CD8⁺ T_EM/EMRA cells in CMV+ and CMV- individuals. by Sara P. H. van den Berg (8703927)

<i>late</i>M cells provide better protection than <i>early</i>M cells following LCMV clone-13 infection. by Matthew D. Martin (803107)

OsNF-YAs suppress JA signaling. by Xiaoxiang Tan (12542842)

Mitochondrial morphologic changes in <i>A</i>. <i>lugdunensis</i>. by Min Seung Kang (9388806)

“…<p>After treatment with 50 μg/mL (B) of <i>T</i>. <i>nucifera</i>, structural damage and decreased wrinkling was observed compared with that in the control group (A). …”

Impact of Manganese Carbonate Precipitation on Uranium(VI) Fate in Conditions Relevant to Carbonate-Buffered Aquifers by Surya Sujathan (11355082)

“…Reactive modeling of Mn and DIC data exhibited a decrease in the surface area normalized rate constants of MnCO_3(s) precipitation from 5.9 to 3.3 × 10^–8 mol m^–2 h^–1 with an increase in initial U(VI) from 0 to 500 μM. …”

Impact of Manganese Carbonate Precipitation on Uranium(VI) Fate in Conditions Relevant to Carbonate-Buffered Aquifers by Surya Sujathan (11355082)

“…Reactive modeling of Mn and DIC data exhibited a decrease in the surface area normalized rate constants of MnCO_3(s) precipitation from 5.9 to 3.3 × 10^–8 mol m^–2 h^–1 with an increase in initial U(VI) from 0 to 500 μM. …”

Crowd forecasts and baseline shown in the application for a two week horizon. by Nikos I. Bosse (9756108)