A Fast Algorithm for Estimating Two-Dimensional Sample Entropy Based on an Upper Confidence Bound and Monte Carlo Sampling.

The two-dimensional sample entropy marks a significant advance in evaluating the regularity and predictability of images in the information domain. Unlike the direct computation of sample entropy, which incurs a time complexity of O(N2) for the series with length, the Monte Carlo-based algorithm for computing one-dimensional sample entropy (MCSampEn) markedly reduces computational costs by minimizing the dependence on . This paper extends MCSampEn to two dimensions, referred to as MCSampEn2D.

Gas-modulating microcapsules for spatiotemporal control of hypoxia.

Oxygen is a vital molecule involved in regulating development, homeostasis, and disease. The oxygen levels in tissue vary from 1 to 14% with deviations from homeostasis impacting regulation of various physiological processes. In this work, we developed an approach to encapsulate enzymes at high loading capacity, which precisely controls the oxygen content in cell culture.