Direct Phasing of Protein Crystals with Hybrid Difference Map Algorithms. [PDF]
He H, Liu Y, Su WP.
europepmc +1 more source
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova +4 more
wiley +1 more source
Course assessment model in vocational education based on BPNN optimized by genetic algorithm. [PDF]
Luo W, Zang L, Liang W, Ma Q, Chu J.
europepmc +1 more source
An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification
An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li +6 more
wiley +1 more source
Comparative optimization of overcurrent relay coordination in DG-integrated distribution networks: water cycle algorithm versus genetic algorithm and big bang-big crunch. [PDF]
Mohamed RE, Saleh SM, Ahmad AG.
europepmc +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Evaluating Bio-Inspired Metaheuristics for Dynamic Surgical Scheduling: A Resilient Three-Stage Flow Shop Model Under Stochastic Emergency Arrivals. [PDF]
Becerra-Rozas M +8 more
europepmc +1 more source
Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin +4 more
wiley +1 more source
Hybrid ML and metaheuristic optimization of slag-fly ash-gypsum modified solidified sludge for construction. [PDF]
Azarkhosh H, Chen Y, Elias S.
europepmc +1 more source
System identification and particle image velocimetry reveal how a modular robotic fish changes thrust physics across gaits. A traveling‐wave, fish‐like motion draws thrust from resistive drag, while a resonant standing‐wave motion is driven by reactive pressure.
Donghao Li +4 more
wiley +1 more source

