Assessing Biomaterial‐Induced Stem Cell Lineage Fate by Machine Learning‐Based Artificial Intelligence (Adv. Mater. 19/2023)

T-cell lineage fate: Instructed by receptor signals?

Mechanisms of lineage choice represent a challenging problem in developmental biology. Recent studies have shown that different T-cell receptor signals can affect CD4 or CD8 lineage choice. Thus, all the ingredients for instructive mechanisms of lineage fate are in place but other mechanisms cannot be completely ruled out.

Metamaterials: Snapping Mechanical Metamaterials under Tension (Adv. Mater. 39/2015).

By exploiting snap-through instabilities, D. Pasini and co-workers design a damage-tolerant mechanical metamaterial that snaps sequentially under tension, thereby accommodating a very large deformation up to 150%. On page 5931, they describe how the nonlinear mechanical response of the metamaterial can be robustly programmed by tuning the architecture of its unit cell.

Artificial Intelligence in Brain-Machine Interface

This paper reviews research in the field of Brain-Machine Interfaces (BMIs) and the existing Artificial Intelligence (AI) in Neuroprosthetics to the purpose of examining the future for BMI in particular regard to AI. The conclusive remarks are that this research is expanding a lot at the moment and the potential for this field can result in rapid improvements in the lives of humans in need of p...

Next Generation Artificial Intelligence and Machine Learning

Machine learning - an artificial intelligence approach

Imagine that you get such certain awesome experience and knowledge by only reading a book. How can? It seems to be greater when a book can be the best thing to discover. Books now will appear in printed and soft file collection. One of them is this book machine learning an artificial intelligence approach. It is so usual with the printed books. However, many people sometimes have no space to br...