Projected incremental cost to the India national TB programme between 2022 and 2030, from implementation of a pan-TB regimen, for different assumed values for the regimen cost (x-axis). by Nimalan Arinaminpathy (88497)

Positively selected sites of Hume’s pheasant MHCIIB exon 2 sequences from implementing neutral (M1a, M7) and selection (M2a, M8) models in CODEML [26]. by Weicai Chen (687044)

“…<p>Positively selected sites of Hume’s pheasant MHCIIB exon 2 sequences from implementing neutral (M1a, M7) and selection (M2a, M8) models in CODEML [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116499#pone.0116499.ref026" target="_blank">26</a>].…”

Comparison of estimates of <i>Z</i>, and estimates of the elements of and , obtained from implementation of the three methods presented in this paper, for 100 different simplex-truncated multivariate normal distributions of dimension <i>n</i> = 4. by Matthew P. Adams (7339883)

Comparison of estimates of <i>Z</i>, and estimates of the elements of and , obtained from implementation of the three methods presented in this paper, for 100 different simplex-truncated multivariate normal distributions of dimension <i>n</i> = 5. by Matthew P. Adams (7339883)

The mode and 95% confidence interval for <i>N_C</i>, <i>N_H</i> and <i>T</i> (in number of generations) for the demographic models implemented in DIYABC for the scenario with the highest probability (population bottleneck). by Nicolas Dussex (696163)

“…<p>The mode and 95% confidence interval for <i>N_C</i>, <i>N_H</i> and <i>T</i> (in number of generations) for the demographic models implemented in DIYABC for the scenario with the highest probability (population bottleneck).…”

Configuration details of the object detection models implemented in MMDetection. Here, FPN = Feature Pyramid Network, AHs = Attention Heads, TLs = Transformer Layers, SGD = Stochastic Gradient Descent.... by Parminder Kaur (719846)

“…<p>Configuration details of the object detection models implemented in MMDetection. Here, FPN = Feature Pyramid Network, AHs = Attention Heads, TLs = Transformer Layers, SGD = Stochastic Gradient Descent. …”

The Bayes Factor (BF) of each model, mode and 90% highest posterior density (in parentheses) for <i>N_C</i>, <i>N_H</i> and <i>T</i> for the demographic models implemented in MSVAR. by Nicolas Dussex (696163)

“…<p>The Bayes Factor (BF) of each model, mode and 90% highest posterior density (in parentheses) for <i>N_C</i>, <i>N_H</i> and <i>T</i> for the demographic models implemented in MSVAR.</p>…”

Critical transitions in networked spin-shift model implementation with 2000 nodes in groups of 400 with link degrees <i>deg</i> ∈ {3, 4, 5, 6, 7} respectively, and driven over 20000 iterations into an assortativity of 0.99. by Manfred Füllsack (4691716)

Challenges and solutions when implementing genetics and parasite data into models. by Doug Butterworth (10005953)

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Hyperspectral reflectance data, plants traits and weights for trained model implemented in: "Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel." https://doi.org/10.1002/ppj2.20106 by Michael C. Tross (12090261)

A process suggested for model implementation (1 –delegating the task to ISec experts; 2 –performing an assessment; 3 –data analysis according to the model design; 4 –presentation of the results and identification of gaps in the ISec performance; 5 –implementation of corrective measures). by Kaja Prislan (3131103)

“…<p>A process suggested for model implementation (1 –delegating the task to ISec experts; 2 –performing an assessment; 3 –data analysis according to the model design; 4 –presentation of the results and identification of gaps in the ISec performance; 5 –implementation of corrective measures).…”

Appropriate models. by James M. Osborne (163443)

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Table of parameters specific to the morphogen-dependent proliferation simulations. by James M. Osborne (163443)

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Simulations of monoclonal conversion in the colonic crypt. by James M. Osborne (163443)

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Table of parameters specific to the lateral inhibition simulations. by James M. Osborne (163443)

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Comparison of clonal population dynamics and cell velocity across crypt simulations for varying levels of contact inhibition. by James M. Osborne (163443)

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Table of parameters specific to the colonic crypt simulations. by James M. Osborne (163443)

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Number of cells in the crypt for varying contact inhibition. by James M. Osborne (163443)

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Effect of perturbations on cell sorting. by James M. Osborne (163443)

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Comparison of cell fate patterning, and cell compression across lateral inhibition simulations. by James M. Osborne (163443)

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