Origin of <i>Neisseria meningitidis</i> clonal complex 4821. [PDF]
Tan Z+9 more
europepmc +1 more source
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar+3 more
wiley +1 more source
Laser Stripe Centerline Extraction Method for Deep-Hole Inner Surfaces Based on Line-Structured Light Vision Sensing. [PDF]
Du H, Yu D, Zhao X, Zhou Z.
europepmc +1 more source
Multistable Composite Laminate Grids as a Design Tool for Soft Reconfigurable Multirotors
Flexible, lightweight, stable: the reconfigurable multirotor combines stable flight in multiple shapes with low‐energy reconfiguration. Utilizing optimized multistable composites, it achieves self‐locking in open and folded configurations, cutting width‐span by 48% and allowing for safe gap traversal.
Luca Girardi+4 more
wiley +1 more source
Characterization of the Diversity in Host Range of an Extensively Drug-Resistant (XDR) Type IV Secretion System-Encoding Plasmid in <i>Acinetobacter</i>. [PDF]
Martz K+4 more
europepmc +1 more source
Advancements in Machine Learning for Microrobotics in Biomedicine
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi+6 more
wiley +1 more source
Whole-genome analysis of escherichia coli isolated from captive giant pandas (ailuropoda melanoleuca) at the Dujiangyan base of the China conservation and research center for the giant panda, Sichuan, China. [PDF]
Yu H+11 more
europepmc +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park+8 more
wiley +1 more source
Genetic structure and haplotype analysis of predominant genetic group of Bemisia tabaci Asia II 1 from Asia and India. [PDF]
Ramesh KB+4 more
europepmc +1 more source