A direct discretization recurrent neurodynamics method for time-variant nonlinear optimization with redundant robot manipulators.

Discrete time-variant nonlinear optimization (DTVNO) problems are commonly encountered in various scientific researches and engineering application fields. Nowadays, many discrete-time recurrent neurodynamics (DTRN) methods have been proposed for solving the DTVNO problems. However, these traditional DTRN methods currently employ an indirect technical route in which the discrete-time derivation process requires to interconvert with continuous-time derivation process.

Systematic coronary physiology improves level of agreement in diagnostic coronary angiography.

Objective: The training of interventional cardiologists (ICs), non-interventional cardiologists (NICs) and cardiac surgeons (CSs) differs, and this may be reflected in their interpretation of invasive coronary angiography (ICA) and management plan. Availability of systematic coronary physiology might result in more homogeneous interpretation and management strategy compared with ICA alone.

Methods: 150 coronary angiograms from patients with stable chest pain were presented independently to three NICs, three ICs and three CSs.

High-density electroanatomic activation mapping to guide slow pathway modification in patients with persistent left superior vena cava.

Background: Slow pathway (SP) mapping and modification can be challenging in patients with persistent left superior vena cava (PLSVC) due to anatomic variance of the Koch triangle (KT) and coronary sinus (CS) dilation. Studies using detailed 3-dimensional (3D) electroanatomic mapping (EAM) to investigate conduction characteristics and guide ablation targets in this condition are lacking.

Objectives: The purpose of this study was to describe a novel technique of SP mapping and ablation in sinus rhythm using 3D EAM in patients with PLSVC after validation in a cohort with normal CS anatomy.

Novel Discrete-Time Recurrent Neural Networks Handling Discrete-Form Time-Variant Multi-Augmented Sylvester Matrix Problems and Manipulator Application.

In this article, the discrete-form time-variant multi-augmented Sylvester matrix problems, including discrete-form time-variant multi-augmented Sylvester matrix equation (MASME) and discrete-form time-variant multi-augmented Sylvester matrix inequality (MASMI), are formulated first. In order to solve the above-mentioned problems, in continuous time-variant environment, aided with the Kronecker product and vectorization techniques, the multi-augmented Sylvester matrix problems are transformed into simple linear matrix problems, which can be solved by using the proposed discrete-time recurrent neural network (RNN) models. Second, the theoretical analyses and comparisons on the computational performance of the recently developed discretization formulas are presented.

UK multicenter retrospective comparison of novel active versus conventional passive fixation coronary sinus leads.

Background: A novel active fixation coronary sinus (CS) lead, Attain Stability (AS), has been released aiming to improve targeted lead positioning. Rather than being wedged into the distal vessel, it relies on a side helix for fixation. We aimed to compare implant procedure parameters and electromechanical stability of the AS lead with passive CS leads.