Internal loading potential of phosphorus in reservoirs along a semiarid watershed by Diana Souza Moura (8743428)

“…Reservoir R#6 showed the predominance of PFeAl and PCa fractions on points A and B, respectively, showing that the characteristics of the sediments may vary in the same reservoir. …”

Spiking neuron network model with spike frequency adaptation (SFA) and synaptic depression (STD). by Brian Nils Lundstrom (14659973)

Investigating Eye Temperature as a Potential Biomarker for Emotion in Thoroughbred Horses by Ella Baird (22459603)

“…<p dir="ltr">This study investigated whether differences in eye temperature could be detected in Thoroughbred horses exposed to two different training conditions: either high or low probability of receiving a food reward. Twenty-three horses were trained to complete a simple industry relevant task. …”

CTCF is responsible for upregulation of PRMT5 under hypoxia in breast cancer cells. by Srinivas Abhishek Mutnuru (22513457)

“…<b>K)</b> Immunoblot showing decrease in PRMT5 expression upon transfection with dCAS9-DNMT3A sgCTCFbs vs. sgControl. …”

Drift and diffusion in the short-term BMI dynamics of individuals in a human population. by John C. Lang (1402759)

“…The red curves (triangles) show that the standard deviation of annual BMI changes, which results from natural short-term fluctuations in an individual’s BMI that may be due to variations in diet or physical activity, increases approximately linearly as a function of BMI. These results establish that BMI dynamics feature a <i>drift</i> towards a set point, and a <i>diffusion</i> that is proportional to the BMI. …”

Data obtained from monitoring patients. by Ana Gabriela Gomes Ferrari Strang (17068913)

“…Three decreasing values of immunoglobulin G were a security parameter for stopping the child’s medication in the exposed group (50/61). …”

General characteristics and statistical analysis. by Ana Gabriela Gomes Ferrari Strang (17068913)

“…Three decreasing values of immunoglobulin G were a security parameter for stopping the child’s medication in the exposed group (50/61). …”

Fig 1 - by Guansheng Han (15338907)

S2 File - by Young Chang (3666829)

Postmortem confirmation of tetrode placement. by Alice Berners-Lee (15354255)

The RNAi efficiency of <i>Met</i>, <i>EcR</i>, and <i>AaERR</i> genes in <i>Ae</i>. <i>aegypti</i>. by Dan-Qian Geng (18137370)

Wind Reversals During Morning and Evening Transitions in a Small Valley by Rui Zhang (20177106)

“…The outmost domain covers an area of 500×500 km with a horizontal grid spacing of 3 km. The horizontal grid spacing decreases to 1 km for d02 and 0.33 km for d03, while d02 and d03 cover an area of 100×100 km and 10×10 km, respectively. …”

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. …”