Partial differential equations (PDEs) are among the most universal and parsimonious
descriptions of natural physical laws, capturing a rich variety of phenomenology and …

Lithium-ion batteries can last many years but sometimes exhibit rapid, nonlinear
degradation that severely limits battery lifetime. In this work, we review prior work on" knees" …

The energy and water sectors are intrinsically linked to meet several consumer needs. A
holistic analysis is required to quantify the technoeconomic and environmental benefits and …

Quantifying movement is critical for understanding animal behavior. Advances in computer
vision now enable markerless tracking from 2D video, but most animals move in 3D. Here …

The sparse identification of nonlinear dynamics (SINDy) is a regression framework for the
discovery of parsimonious dynamic models and governing equations from time-series data …

The Koopman operator has become an essential tool for data-driven approximation of
dynamical (control) systems, eg, via extended dynamic mode decomposition. Despite its …

Discovering governing equations of complex dynamical systems directly from data is a
central problem in scientific machine learning. In recent years, the sparse identification of …

Sparse system identification is the data-driven process of obtaining parsimonious differential
equations that describe the evolution of a dynamical system, balancing model complexity …

Time-delay embedding and dimensionality reduction are powerful techniques for
discovering effective coordinate systems to represent the dynamics of physical systems …

In this paper we propose, and demonstrate through a prototype, a completely novel device
able to harvest mechanical energy from the multidirectional vibrations in a wind turbine, and …