Simulated estimates of number of silicosis cases and annual tuberculosis (TB) cases at cumulative RCS distributions of increasing mean values. by Patrick Howlett (2612374)

“…In plot C, estimates of annual tuberculosis cases are estimated at distributions of increasing mean cumulative RCS (mg/m³-year), at HIV prevalence of 2%, 6% and 20%, the modelled association between HIV and TB is an OR of 2. …”

C-terminal tagging of NCAPH2 can either increase or decrease protein expression. by Gillian C. A. Taylor (3909568)

The contribution of each feature for the increase or decrease of the prediction target. by Raphael Souza de Oliveira (12647110)

WT1 and LANA expression correlate with decreased T cell infiltrates. by Ayana E. Morales (17756335)

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The time series depicts cases in which the period length remains relatively constant despite increasing reaction rates in the circadian clock model (A: reference set case, B: increased reaction rates case). by Shingo Gibo (21762920)

“…<p>Additionally, synchronization regions for these cases are presented (C: reference set case, D: increased reaction rates case). …”

WT1 siRNA decreases proliferation, pAKT, and Bcl2 expression. by Ayana E. Morales (17756335)

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MSE ratio of evaluated at , under cases A, B, and C for randomly missing case. by Ji Soo Kim (3609236)

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The contribution of each feature for the increase or decrease of the prediction target by alert level. by Raphael Souza de Oliveira (12647110)

Forecasts of cancer patients’ medical use (cancer type/cases). by Jinah Sim (15140709)

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Forecasts of cancer patients’ medical use (cancer type/cases). by Jinah Sim (15140709)

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Forecasts of cancer patients’ medical use (age/admission cases). by Jinah Sim (15140709)

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The proportion of lake area which exhibited decreases (blue bars) versus increases (green bars) in chl-a for the largest 18 lakes in the world. by Benjamin M. Kraemer (7526225)

Effect of parameter <i>a</i> on the model equations by increasing and decreasing value of <i>a</i> to 25%. by Shakoor Ahmad (168711)

“…<p><b>(a)</b> By increasing the value ‘<i>a</i>’ from 0.107 to 0.134. <b>(b)</b> By decreasing the value ‘<i>a</i>’ from 0.107 to 0.08.…”

Forecasts of cancer patients’ medical use and expenditure (income/admission cases). by Jinah Sim (15140709)

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Forecasts of cancer patients’ medical use and expenditure (income/outpatient cases). by Jinah Sim (15140709)

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Average values of the four covariates included in the best fit model. by Gina E. C. Charnley (11743650)

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The number of expected vaccinations decreases with the expected vaccination time, whereas the peak of infections increases. by Simon K. Schnyder (16632244)

“…Brighter colours indicate higher 〈<i>s</i>(<i>t</i>_<i>v</i>)〉. Note the nonlinear increase of <i>n</i> on the y-axis. C) Relatedly, we show the peak of infections max_<i>t</i>(<i>i</i>(<i>t</i>)) as a heat map as function of the expected vaccination time 〈<i>t</i>_<i>v</i>〉 for the same range of vaccine arrival distributions <i>p</i>_<i>n</i> as in B). …”

Average R values for 2018 and 2019 for all 37 Nigerian states. by Gina E. C. Charnley (11743650)

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Description of included cases in the study. by Kristina Lagerstedt-Robinson (3556532)

Active spread of mtDNAs in the network can increase and decrease cell-to-cell variability from cell divisions. by Robert C. Glastad (10692277)

“…The three columns for each panel give decreasing network heterogeneity, expressed via different seed numbers, 4, 16 and 64 (more seed points give a more homogeneous network). …”