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Deep generative design of RNA aptamers using structural predictions.

Nature computational science
RNAs represent a class of programmable biomolecules capable of performing diverse biological functions. Recent studies have developed accurate RNA three-dimensional structure prediction methods, which may enable new RNAs to be designed in a structure...

During haptic communication, the central nervous system compensates distinctly for delay and noise.

PLoS computational biology
Physically connected humans have been shown to exploit the exchange of haptic forces and tactile information to improve their performance in joint action tasks. As human interactions are increasingly mediated through robots and networks it is importa...

Global practical finite-time synchronization of disturbed inertial neural networks by delayed impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper delves into the practical finite-time synchronization (FTS) problem for inertial neural networks (INNs) with external disturbances. Firstly, based on Lyapunov theory, the local practical FTS of INNs with bounded external disturbances can b...

Enhancing MRI brain tumor classification: A comprehensive approach integrating real-life scenario simulation and augmentation techniques.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Brain cancer poses a significant global health challenge, with mortality rates showing a concerning surge over recent decades. The incidence of brain cancer-related mortality has risen from 140,000 to 250,000, accompanied by a doubling in new diagnos...

Optimization of grinding parameters in robotic-assisted preparation of cracked teeth based on fracture mechanics: FEA and experiment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: If left untreated, cracked teeth can lead to tooth loss, of which the incidence is 70%. Dental preparation is an effective treatment, but it is difficult to meet the clinical requirements when traditionally prepared by dent...

Data-sampled time-varying formation for singular multi-agent systems with multiple leaders.

Neural networks : the official journal of the International Neural Network Society
The time-varying formation problem of singular multi-agent systems under sampled data with multiple leaders is investigated in this paper. Firstly, a data-sampled time-varying formation control protocol is proposed in the current study where the comm...

Effective deep-learning brain MRI super resolution using simulated training data.

Computers in biology and medicine
BACKGROUND: In the field of medical imaging, high-resolution (HR) magnetic resonance imaging (MRI) is essential for accurate disease diagnosis and analysis. However, HR imaging is prone to artifacts and is not universally available. Consequently, low...

Differential Game-Based Control for Nonlinear Human-Robot Interaction System With Unknown Desired Trajectory.

IEEE transactions on cybernetics
Differential game is an effective technique to describe the negotiation between the humans and robots, which is widely used to realize the trajectory tracking tasks in the human-robot interaction (HRI). However, most existing works consider the contr...

Seizure Sources Can Be Imaged from Scalp EEG by Means of Biophysically Constrained Deep Neural Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Seizure localization is important for managing drug-resistant focal epilepsy. Here, the capability of a novel deep learning-based source imaging framework (DeepSIF) for imaging seizure activities from electroencephalogram (EEG) recordings in drug-res...

The state-of-the-art machine learning model for plasma protein binding prediction: Computational modeling with OCHEM and experimental validation.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Plasma protein binding (PPB) is closely related to pharmacokinetics, pharmacodynamics and drug toxicity. Existing models for predicting PPB often suffer from low prediction accuracy and poor interpretability, especially for high PPB compounds, and ar...