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This investigation is supported by an experimental program covering tests of smooth and notched specimens to derive monotonic and elastoplastic cyclic/fatigue data under a diversity of multiaxial stress conditions.
An inverse finite element (FE) optimisation algorithm was developed and used, in conjunction with quasi-static and dynamic tests performed to five cadaveric heel specimens, to derive specimen-specific and mean hyper-viscoelastic material models able to predict accurately the response of the tissue at compressive loading of strain rates up to 150 s−150
For meta-analyses, we chose ten data sets with pathological annotation of ER status based on IHC, EIA or both, incorporating a total of 1975 breast cancer specimens to derive and validate the classifiers for ER status (Table 1).
For each taxon, we calculated the rank of the relative abundance across all specimens to derive a new rank vector Ri = (ri1, …, riK).
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The resulting 4,975 specimens were split randomly, while retaining proportionality of each class, into a training set of 3,982 specimens used to derive the classifier, and a test set of 993 specimens that was not used except to evaluate the final classifier.
Blood specimens used to derive lipids and HbA1c were processed by Quest Diagnostics Laboratories.
3D finite element analyses have been carried out to simulate the FOD impact on the LSPed aerofoil specimen and to derive an effective stress intensity factor range, considering both the 3D residual stress fields due to LSP and FOD and crack closure due to the compressive residual stresses.
In particular, from the time evolution of thermo-elastic effects it is possible to get information useful to establish the time interval the impactor remains in contact with the specimen surface and to derive information about bending and deformation of the surface under the impactor pushing force.
Four-point bending tests on notched specimens were carried out to derive the first crack strength and the ductility indexes.
As the cellular composition of a tumor biopsy can differ depending on the tissue sampling method used [ 58], we sought to compare the metagene score distributions between the surgically acquired tumor specimens that we previously used to derive the metagenes (n = 1,954 tumor samples) [ 36] and the confirmed FNA biopsy samples that comprise the majority of the current study (n = 482 tumor samples).
Furthermore, our results suggest that EVA can be applied to other ridge-based biometrics such as ballprint to derive a specimen's image quality despite being trained and optimised on fingermarks.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com