Toward experiment-guided AlphaFold: Researchers overcome AI tool's single-conformation limitation

The AI-based program AlphaFold predicts a protein's 3D structure with remarkable accuracy. However, it tends to reduce heterogeneous structures to a single dominant conformation, or shape, and ...
PNAS

A general framework for interpretable neural learning based on local information-theoretic goal functions

Which learning goals must individual computational elements pursue to contribute to a network-level task solution? This local understanding is missing in both biological, but also artificial neural ...
C&EN

Latent Variable Machine Learning Framework for Catalysis: General Models, Transfer Learning, and Interpretability

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Machine learning has been successfully applied in recent years to screen materials for ...
Frontiers

Three-dimensional microstructure reconstruction for two-phase materials from three orthogonal surface maps

Introduction: A full three-dimensional (3D) microstructure characterization that captures the essential features of a given material is oftentimes desirable for determining critical mechanisms of ...
Frontiers

Artificial intelligence in cardiac magnetic resonance fingerprinting

Magnetic resonance fingerprinting (MRF) is a fast MRI-based technique that allows for multiparametric quantitative characterization of the tissues of interest in a single acquisition. In particular, ...
C&EN

A Review on Carbon Dioxide Minimization in Biogas Upgradation Technology by Chemical Absorption Processes

You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...
IEEE

Shaped-Beam Pattern Synthesis With Sidelobe Level Minimization via Nonuniformly-Spaced Sub-Array

Abstract: This article deals with the low-sidelobe shaped-beam pattern synthesis (SBPS) problem using two nonuniformly spaced subarray configurations, including amplitude and amplitude–phase subarray ...
Nature

On-the-fly closed-loop materials discovery via Bayesian active learning

Technologies drive the perpetual search for novel and improved functional materials, necessitating the exploration of increasingly complex multi-component materials 1. With each new component or ...
Scientific Research Publishing

Relating Optimization Problems to Systems of Inequalities and Equalities ()

Center on Stochastic Modeling, Optimization, and Statistics (COSMOS), The University of Texas at Arlington, Arlington, TX, USA. Quantitative decision analysis involves notions of comparison and ...
acm.org

Data-Driven Algorithm Design

The best algorithm for a computational problem generally depends on the “relevant inputs,” a concept that depends on the application domain and often defies formal articulation. Although there is a ...
PNAS

Collective behavior from surprise minimization

We introduce a model of collective behavior, proposing that individual members within a group, such as a school of fish or a flock of birds, act to minimize surprise. This active inference approach ...
Nature

DIC image reconstruction using an energy minimization framework to visualize optical path length distribution

The simplest of all optical microscopy techniques is the brightfield microscopy that was invented by Anton van Leeuwenhoek 1 in the 17 th century as an improved version of the modern microscope ...