scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta +3 more
wiley +1 more source
Hybrid Harris Hawks optimization with eagle strategy particle swarm optimization for stability and disturbance rejection in tethered UAV systems. [PDF]
Ismael AK, Kurnaz S, Basil N.
europepmc +1 more source
A Critical Assessment of Bonding Descriptors for Predicting Materials Properties
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik +6 more
wiley +1 more source
Active disturbance rejection control based on soft computing techniques for electric power steering to improve system performance. [PDF]
Nguyen TA.
europepmc +1 more source
A triple-step controller with linear active disturbance rejection control for a lower limb rehabilitation robot. [PDF]
Peng H, Zhou J, Song R.
europepmc +1 more source
In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley +1 more source
A Robust Disturbance Rejection Whole-Body Control Framework for Bipedal Robots Using a Momentum-Based Observer. [PDF]
Heng S +7 more
europepmc +1 more source
Active Disturbance Rejection Control in Magnetic Bearing Rotor Systems with Redundant Structures. [PDF]
Cheng B +6 more
europepmc +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Active Disturbance Rejection Control via Neural Networks for a Lower-Limb Exoskeleton. [PDF]
Espinosa-Espejel KI +4 more
europepmc +1 more source

