Results 61 to 70 of about 1,412,360 (277)
Biophysical characterisation shows that NanX, a membrane transport protein from the major facilitator superfamily (MFS), forms both monomers and dimers after purification. AlphaFold modelling and substrate docking provide information on residues likely involved in substrate recognition for NanX and another MFS member, NanT.
Michael C. Newton‐Vesty +13 more
wiley +1 more source
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec +6 more
wiley +1 more source
СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY [PDF]
The paper deals with the basic principles of signals representation in optical coherence tomography with the usage of dynamic systems theory formalism.
Maxim A. Volynsky +3 more
doaj
Monte Carlo algorithms simulates some prescribed number of samples, taking some random real time to complete the computations necessary. This work considers the converse: to impose a real-time budget on the computation, which results in the number of ...
Lawrence M. Murray +2 more
doaj +1 more source
A Sequential Monte Carlo Method for Motif Discovery [PDF]
Publication in the conference proceedings of EUSIPCO, Florence, Italy ...
Kuo-ching Liang +2 more
openaire +5 more sources
ABSTRACT Introduction Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) have demonstrated significant weight‐reducing effects and may offer benefits in idiopathic intracranial hypertension (IIH); however, recent concerns about the risk of non‐arteritic anterior ischemic optic neuropathy (NAION) have emerged.
Faisal A. Al‐Harbi +9 more
wiley +1 more source
Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane +10 more
wiley +1 more source
Auto-Encoding Sequential Monte Carlo
We build on auto-encoding sequential Monte Carlo (AESMC): a method for model and proposal learning based on maximizing the lower bound to the log marginal likelihood in a broad family of structured probabilistic models. Our approach relies on the efficiency of sequential Monte Carlo (SMC) for performing inference in structured probabilistic models and ...
Le, T +4 more
openaire +4 more sources
Sequential Monte Carlo Sampling for DSGE Models [PDF]
We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples--an artificial state-space model, the Smets and Wouters (2007) model, and Schmitt-Grohe and Uribe ...
Edward P. Herbst, Frank Schorfheide
openaire +4 more sources
Neural Adaptive Sequential Monte Carlo
Sequential Monte Carlo (SMC), or particle filtering, is a popular class of methods for sampling from an intractable target distribution using a sequence of simpler intermediate distributions. Like other importance sampling-based methods, performance is critically dependent on the proposal distribution: a bad proposal can lead to arbitrarily inaccurate ...
Gu, Shixiang +2 more
openaire +4 more sources

