Predicting uniaxial compressive strength of rocks using ANN models: Incorporating porosity, compressional wave velocity, and schmidt hammer data.

The unconfined compressive strength (UCS) of intact rocks is crucial for engineering applications, but traditional laboratory testing is often impractical, especially for historic buildings lacking sufficient core samples. Non-destructive tests like the Schmidt hammer rebound number and compressional wave velocity offer solutions, but correlating these with UCS requires complex mathematical models. This paper introduces a novel approach using an artificial neural network (ANN) to simultaneously correlate UCS with three non-destructive test indexes: Schmidt hammer rebound number, compressional wave velocity, and open-effective porosity.

Characteristics and Outcomes of Adult Patients in the PETHEMA Registry with Relapsed or Refractory -ITD Mutation-Positive Acute Myeloid Leukemia.

This retrospective study investigated outcomes of 404 patients with relapsed/refractory (R/R) FMS-like tyrosine kinase 3 (FLT3)-internal tandem duplication (ITD) acute myeloid leukemia (AML) enrolled in the PETHEMA registry, pre-approval of tyrosine kinase inhibitors. Most patients (63%) had received first-line intensive therapy with 3 + 7. Subsequently, patients received salvage with intensive therapy (n = 261), non-intensive therapy (n = 63) or supportive care only (n = 80).