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

E₅₀ values. by 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. by Orna Mizrahi-Man (42539)

E₅₀ values of angle. by Junxia Zhou (14381598)

Curve fitting of E₅₀. by Junxia Zhou (14381598)

Fitting curves of E₅₀. by Junxia Zhou (14381598)

E₅₀ values of size. by Junxia Zhou (14381598)

E₅₀ fluctuation coefficient. by Junxia Zhou (14381598)

Fitting relationship of E₅₀. by Junxia Zhou (14381598)

Fitting curve of E₅₀. by Junxia Zhou (14381598)

Fitting curve of rock E₅₀. by 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... by Hope Murphy (8843516)

Predicting pattern diversity decreases as a function of and . by 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 ). …”

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

Effectiveness of interventions to decrease hesitancy. by Maximilian Nicolaus Burger (12969212)

Distribution Coefficients of the REEs, Sr, Y, Ba, Th, and U between α‑HIBA and AG50W-X8 Resin by Haoyu Li (1672648)

“…For all 19 elements, the distribution coefficients decrease with increasing acid concentration. For the REEs, a linear relationship is observed in log–log space between <i>K</i>_d values and α-HIBA molarity. …”

IC₅₀ of indole alkaloid against lipase [23]. by Atikarn Janthongkaw (17020498)

Supplemental Material for MSG L-00273-2023R1;Hemopexin Reverses Activation of Lung eIF2a and Decreases Mitochondrial Injury in Chlorine Exposed Mice by Sadis Matalon (13571353)

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)

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)