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The aim of this work was to report the current state of the art, and recommend future development of fracture mechanics-based analytical tools for modeling subcritical fatigue crack growth in structures. Of special interest is the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. The authors conducted a survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

We developed a new statistical feature to represent tumor subtypes using one hundred RNA-Seq measured genes using sparse logistic regression. Our method, subtype-simulation, and a visualization tool were implemented in an R package. We used two breast cancer datasets, METABRIC and TCGA, to show the differences in subtype predictions, including the association between the four subtypes and patient outcomes and time to relapse (TTR). Subtype-simulation enables simulation of unseen samples to provide insights into the reliability of the subtypes and in the study of subtype association with oncogenes and clinical outcomes. Simulation enabled us to draw inferences about the reliability of each subtype using limited data from rare subtypes. We also showed that our method achieves good performance in the study of subtype associations.

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