Results 71 to 80 of about 6,889,850 (329)
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu +10 more
wiley +1 more source
COMPASS is a fixed-target experiment at CERN SPS which focused on light-quark hadron spectroscopy during the data taking in 2008 and 2009. A world-leading data set was collected with a 190GeV/c hadron beam impinging on a liquid hydrogen target in order ...
Austregesilo, A.
core +2 more sources
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source
Enhanced monopulse radar tracking using empirical mode decomposition [PDF]
Monopulse radar processors are used to track targets that appear in the look direction beamwidth. The target tracking information (range, azimuth angle, and elevation angle) are affected when manmade high power interference (jamming) is introduced to the
Elgamel, Sherif A.E.H., Soraghan, J.J.
core
In radar polarimetry, incoherent target decomposition techniques help extract scattering information from polarimetric synthetic aperture radar (SAR) data.
S. Dey +4 more
semanticscholar +1 more source
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
Current Tracking Adaptive Control of Brushless DC Motors
In this paper, the current tracking for Brushless Direct Current motors is approached considering uncertainty in the parameters of the motor's model. An adaptive control scheme to compensate electrical parameters uncertainty is proposed without requiring any knowledge of the mechanical parameters.
Fernanda Ramos‐García +3 more
wiley +1 more source
Unique Information via Dependency Constraints
The partial information decomposition (PID) is perhaps the leading proposal for resolving information shared between a set of sources and a target into redundant, synergistic, and unique constituents. Unfortunately, the PID framework has been hindered by
Crutchfield, James P. +2 more
core
Engineering Stable Discrete-Time Quantum Dynamics via a Canonical QR Decomposition
We analyze the asymptotic behavior of discrete-time, Markovian quantum systems with respect to a subspace of interest. Global asymptotic stability of subspaces is relevant to quantum information processing, in particular for initializing the system in ...
Bolognani, Saverio, Ticozzi, Francesco
core +2 more sources

