Schematic figure of the promoter probe vectors. by Gábor Patyi (11846776)

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. …”

Secondary structure profile analysis for the SP domain of native PC and its mutant structures over 200 ns MD simulation times. by Mahvash Farajzadeh-Dehkordi (17468232)

Domains and position of high-risk missense SNPs within the human PC. by Mahvash Farajzadeh-Dehkordi (17468232)

Amount of antimicrobial consumption in food producing animals by antimicrobial class (2017–2019) (mg/PCU_Thailand). by Angkana Lekagul (7180856)

Modelled and observed shoot mortality for ash trees of different level of dieback. by Benoit Marçais (14632379)

Free energy landscape (FEL) analysis for the SP domain of native PC and its mutant structures over 200 ns MD simulation times. by Mahvash Farajzadeh-Dehkordi (17468232)

The tree decision analysis to predict DOMS responders. by Einat Kodesh (13132997)

Raw data for figures and tables in the paper. by Runhai Jiang (19871068)

“…<i>rwandensis</i> could promote the transformation of Pb fractions and a functional change in the soil bacterial community, ultimately decreasing Pb accumulation in the biomass and promoting the development of maize.…”

Power spectra changes related to the seizure onset zone and increased adaptation. by Brian Nils Lundstrom (14659973)

Artificial enhancer constructs reveal a tandem-<i>like</i> structure. by Maximilian Haeussler (86348)

“…(F) Introduction of spacer regions of 25/50/75/150 bp between the two D1(ab) fragments strongly decreased the activity of the tandem constructs. …”

<i>Hnrnph1</i> Is A Quantitative Trait Gene for Methamphetamine Sensitivity by Neema Yazdani (835533)

“…We used interval-specific congenic mouse lines carrying various segments of chromosome 11 from the DBA/2J strain on an isogenic C57BL/6J background to positionally clone a 206 kb QTL (50,185,512–50,391,845 bp) that was causally associated with a reduction in the locomotor stimulant response to methamphetamine (2 mg/kg, i.p.; DBA/2J < C57BL/6J)—a non-contingent, drug-induced behavior that is associated with stimulation of the dopaminergic reward circuitry. …”