Learning is traditionally studied in biological or computational systems. The power of
learning frameworks in solving hard inverse problems provides an appealing case for the …

Mechanical metamaterials are a class of artificial materials whose geometry is engineered to
have peculiar mechanical properties or programmed responses that are difficult to find in …

Allosteric regulation plays an important role in many biological processes, such as signal
transduction, transcriptional regulation, and metabolism. Allostery is rooted in the …

Evolution in time-varying environments naturally leads to adaptable biological systems that
can easily switch functionalities. Advances in the synthesis of environmentally responsive …

Here we review recent studies of mechanical metamaterials originating from or closely
related to marginally jammed solids. Unlike previous approaches mainly focusing on the …

Interacting many-body physical systems ranging from neural networks in the brain to folding
proteins to self-modifying electrical circuits can learn to perform diverse tasks. This learning …

Allostery is central to many cellular processes, by up-or down-regulating target function.
However, what determines the allosteric type remains elusive and currently it is impossible …

While the pervasiveness of allostery in proteins is commonly accepted, we further show the
generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel …

Designing materials with tailored structural or functional properties is a fundamental goal of
materials science and engineering. A vast research activity is currently devoted to achieving …

Mechanical metamaterial actuators achieve pre-determined input–output operations
exploiting architectural features encoded within a single 3D printed element, thus removing …