Decreasing fluconazole susceptibility of clinical South African <i>Cryptococcus neoformans</i> isolates over a decade حسب Serisha D. Naicker (8648370)

Flow chart of the study procedures. حسب Kazuhiko Ikeuchi (9234268)

"…Pre-treatment spontaneous decrease of RPR titer was associated with a slower decrease in post-treatment RPR titer.…"

E₅₀ values. حسب Junxia Zhou (14381598)

The fraction of predicted heterozygotes that are set to “No Call” by RHA decreases as the size of the heterozygote cluster increases. حسب Orna Mizrahi-Man (42539)

The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. حسب Gui Araujo (22170819)

"…<p>Using the invasion model, we investigate the effect of switching on and off (black vs grey) invasions with mutualisms halfway through the simulation (i.e. after 500 assembly events). …"

E₅₀ values of angle. حسب Junxia Zhou (14381598)

Curve fitting of E₅₀. حسب Junxia Zhou (14381598)

Fitting curves of E₅₀. حسب Junxia Zhou (14381598)

E₅₀ values of size. حسب Junxia Zhou (14381598)

E₅₀ fluctuation coefficient. حسب Junxia Zhou (14381598)

Fitting relationship of E₅₀. حسب Junxia Zhou (14381598)

Fitting curve of E₅₀. حسب Junxia Zhou (14381598)

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

Fitting curve of rock E₅₀. حسب Junxia Zhou (14381598)

Partial correlation of <i>ε</i>_max (left column) and IC₅₀ (right column) estimates at 10 days and 20 days (first and second bar of each color, respectively) o... حسب Hope Murphy (8843516)

Predicting pattern diversity decreases as a function of and . حسب Selim Haj Ali (21222613)

"…<p>For 50 Erdős-Rényi graphs with 30 nodes and 70 edges, we split the results into two columns according to the two initial degenerate unstable eigenmodes  +  : on the left, (if ), and on the right, (if ). …"

Tax expression is associated with decreased cellular motility. حسب Saumya Ramanayake (7879091)

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

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

Example of the process used to determine time dependence of <i>ε</i>_max and IC₅₀. حسب Hope Murphy (8843516)