Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

Subjects:

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

Subjects:

Temporal profiles of the key BO-NN features. by Julia Berezutskaya (9080269)

“…<p><b>(a)</b> Autocorrelation profiles of 53 key BO-NN features. Per feature, a black line shows the time point where the autocorrelation drops below .5. …”

Detailed meta–analyses in untreated hypothyroid patients compared with controls for each HRV parameters: RR intervals, SDNN, RMSSD, pNN50, TP, LF, HF, LF/HF. by Valentin Brusseau (12769704)

Global Land Use Change Impacts on Soil Nitrogen Availability and Environmental Losses by Jing Wang (6206297)

“…By compiling a global data set of 1,782 paired observations from 185 publications, we show that land use conversion from natural to managed ecosystems significantly reduced NNM by 7.5% (−11.5, −2.8%) and increased NN by 150% (86, 194%), indicating decreasing N availability while increasing potential N loss through denitrification and nitrate leaching. …”

Variable importance plot (mean decrease accuracy and mean decrease Gini). by Fernando Martinez-Taboada (8655132)

Fig 5 - by Dennis Ochola (11626912)

Subjects:

GXM decreases the trans-endothelial electrical resistance (TEER) and transmigration of <i>C</i>. <i>neoformans</i> through HBECs in a blood brain barrier (BBB) model. by Hiu Ham Lee (15374677)

Fig 9 - by Dennis Ochola (11626912)

Subjects:

Fig 7 - by Dennis Ochola (11626912)

Subjects:

Fig 4 - by Dennis Ochola (11626912)

Subjects:

Comparison of mean differences in temperature decreases. by Hans-Jörg Gillmann (8460585)

Numbers of all fractures, arranged in order of decreasing mean age and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age. by Camilla Bergh (9904522)

“…<p>Numbers of all fractures, arranged in order of decreasing mean age and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age.…”

Expression of ApoB-50 decreased lipid accumulation and inhibited HCV production. by Bei Wang (116772)

Numbers of all fractures occurring in men, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age. by Camilla Bergh (9904522)

“…<p>Numbers of all fractures occurring in men, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age.…”

Numbers of all fractures occurring in women, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age. by Camilla Bergh (9904522)

“…<p>Numbers of all fractures occurring in women, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age.…”

Identification of Gut Microbiota Biomarker Genera Distinguishing Wild and Captive Animals (A) Top 50 discriminative genera selected by random forest classifier, ranked by mean decrease accuracy. by Lin Xu (94491)

Dose- and time-dependent effect of IFN-γ and TNF-α on benzamil-sensitive <i>I</i>_sc and TEER in HBECs. by Anusree Sasidharan (19226521)

First and second mean values and intraclass correlation coefficients (ICCs) of each parameter in pattern electroretinogram. by Soo Ji Jeon (3364214)

Lubrication Behavior of Fullerene-Coated Nanoparticles on Rough Surfaces by Guangchao Han (1453198)