Linking NrfD/PsrC-like architecture to energy conservation: Functional residues in the quinone reactive QrcABCD complex of sulfate-reducing bacteria. [PDF]
Manteigas G +4 more
europepmc +1 more source
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez +10 more
wiley +1 more source
Unraveling the Dynamics of Oxytocin in Hypothalamic Neurons. [PDF]
Aznar-Escolano B +6 more
europepmc +1 more source
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source
The Global Status of Microplastic Pollution in Respiratory Health. [PDF]
Bayo J +5 more
europepmc +1 more source
Engineering a Correlated Narrow‐Gap Semiconductor: Effects of Ga Substitution in EuZn2P2
ABSTRACT The effect of Ga substitution on the electronic, magnetic, and low‐energy responses of the Zintl phase EuZn2P2${\rm EuZn}_2 {\rm P}_2$ is investigated by electrical transport, electron spin resonance (ESR), and terahertz time‐domain spectroscopy (THz‐TDS). Incorporating Ga into EuZn2P2${\rm EuZn}_2 {\rm P}_2$ (EuZn1.8Ga0.2P2${\rm EuZn}_{1.8} {\
Mateus Dutra +13 more
wiley +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
A Large Scale Multi‐Modal Workflow for Battery Characterization: From Concept to Implementation
Isolated characterization techniques produce independent datasets and single‐property insights. However, progressively more holistic interpretations of battery‐material behavior is needed in the future. Here we demonstrate a coordinated multimodal workflow enabling the correlation of heterogeneous datasets and the construction of multidimensional ...
François Cadiou +34 more
wiley +1 more source
ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary ...
Beatriz Corchuelo Martínez‐Azúa +1 more
wiley +1 more source
Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira +13 more
wiley +1 more source

