Typical time history curves of voltage under three-dimensional high static load and frequent dynamic disturbance (confining pressure of 20 MPa, axial compression of 120 MPa). by Chun Wang (337817)

Failure mode of deep serpentinite under different preload axial pressures (confining pressure of 20 MPa). by Chun Wang (337817)

Change relations between the dynamic deformation modulus and accumulative impact times under a confining pressure of 20 MPa. by Chun Wang (337817)

Change relations between the dynamic peak strain and accumulative number of impacts under a confining pressure of 20 MPa (1—<i>P</i>_<i>as</i> = 100 MPa; 2—<i>P</i><sub><... by Chun Wang (337817)

Change relations between the maximum strain and accumulative number of impacts under a confining pressure of 20 MPa (1—<i>P</i>_<i>as</i> = 100 MPa; 2—<i>P</i><sub><i>as<... by Chun Wang (337817)

Change relations of accumulative impact times with the ratio of confining pressure to axial pressure (1—<i>P</i>_<i>ws</i> = 15 MPa; 2—<i>P</i>_<i>ws</i> = 20 M... by Chun Wang (337817)

Change relations of dynamic average strength with the ratio of confining pressure to axial pressure (1—<i>P</i>_<i>ws</i> = 15 MPa; 2—<i>P</i>_<i>ws</i> = 20 MP... by Chun Wang (337817)

Change relations between accumulative impact times and axial compression with certain confining pressure (1—<i>P</i>_<i>ws</i> = 30 MPa; 2—<i>P</i>_<i>ws</i> =... by Chun Wang (337817)

Stability scores with refinement and no USM decreases. by Jedediah M. Singer (10331212)

“…<p>Effects of guided and random substitutions within expert-designed proteins, when guided substitutions are not permitted to decrease USM EC₅₀ predictions.</p> <p>(EPS)</p>…”

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)

Failure mode of deep serpentinite under different preloaded confining pressures (axial compression of 140 MPa). by Chun Wang (337817)

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:

Change relations between the dynamic peak stress and accumulative impact times under a confining pressure of 15 MPa. by Chun Wang (337817)

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

All-cause gastroenteritis hospitalisations of children decreased after the introduction of rotavirus vaccine in Stockholm by Selma Olsson-Åkefeldt (11500789)

EB (Ethyl Butyrate) as a Cosolvent of Electrolyte Tuning an Ultrathin CEI Membrane for Improving the Ultralow-Temperature Behaviors of LiNi_0.8Co_0.1Mn<sub>0.1<... by Lucheng Li (13753395)

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

“…In contrast, reversing managed to natural ecosystems significantly increased NNM by 20% (9.7, 25.4%) and decreased NN by 89% (−125, −46%), indicating increasing N availability while decreasing potential N loss. …”

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

Prevalence and anatomic level of stenosis ≥ 50% in either limb. by O. Stivalet (6890189)