Noble metal catalyst detection in rocks using machine-learning: The future to low-cost, green energy materials?

Carbon capture and catalytic conversion to methane is promising for carbon-neutral energy production. Precious metals catalysts are highly efficient; yet they have several significant drawbacks including high cost, scarcity, environmental impact from the mining and intense processing requirements. Previous experimental studies and the current analytical work show that refractory grade chromitites (chromium rich rocks with AlO > 20% and CrO + AlO > 60%) with certain noble metal concentrations (i.

Prognostic Prediction of Cancer Based on Radiomics Features of Diagnostic Imaging: The Performance of Machine Learning Strategies.

Tumor phenotypes can be characterized by radiomics features extracted from images. However, the prediction accuracy is challenged by difficulties such as small sample size and data imbalance. The purpose of the study was to evaluate the performance of machine learning strategies for the prediction of cancer prognosis.

Cell Cycle Arrest by a Natural Product via G2/M Checkpoint.

CKBM is a natural product that exhibits a novel anti-tumor activity through the induction of cell cycle arrest and apoptosis. We have investigated its effects on cell cycle regulation using a gastric cancer cell line, AGS. The effects of CKBM on cell proliferation, cell cycle regulation and apoptosis were analyzed using BrdU (5-bromo-2'-deoxyuridine) cell proliferation assay and flow cytometric analysis, respectively.