Communication in quantum networks of logical bus topology

Perfect state transfer (PST) is discussed in the context of passive quantum networks with logical bus topology, where many logical nodes communicate using the same shared media, without any external control. The conditions under which, a number of point-to-point PST links may serve as building blocks for the design of such multi-node networks are investigated. The implications of our results are discussed in the context of various Hamiltonians that act on the entire network, and are capable of providing PST between the logical nodes of a prescribed set in a deterministic manner.Comment: 9 pages, 1 figur

A possible case of serum sickness after ocrelizumab infusion – Commentary

Serum sickness is a type III delayed hypersensitivity reaction which causes deposition of immune-complexes in the tissues. It has been reported with rituximab, and in this issue of the journal, there is a case report of a patient with relapsing remitting multiple sclerosis who developed a possible serum sickness after the third infusion of ocrelizumab. In this commentary, we discuss the current literature on serum sickness, and how to diagnose and manage it. We provide our opinion on this particular case, and encourage neurologists and patients to remain vigilant of such a possibility

Neurophysiological Vocal Source Modeling for Biomarkers of Disease

Speech is potentially a rich source of biomarkers for detecting and monitoring neuropsychological disorders. Current biomarkers typically comprise acoustic descriptors extracted from behavioral measures of source, filter, prosodic and linguistic cues. In contrast, in this paper, we extract vocal features based on a neurocomputational model of speech production, reflecting latent or internal motor control parameters that may be more sensitive to individual variation under neuropsychological disease. These features, which are constrained by neurophysiology, may be resilient to artifacts and provide an articulatory complement to acoustic features. Our features represent a mapping from a low-dimensional acoustics-based feature space to a high-dimensional space that captures the underlying neural process including articulatory commands and auditory and somatosensory feedback errors. In particular, we demonstrate a neurophysiological vocal source model that generates biomarkers of disease by modeling vocal source control. By using the fundamental frequency contour and a biophysical representation of the vocal source, we infer two neuromuscular time series whose coordination provides vocal features that are applied to depression and Parkinson’s disease as examples. These vocal source coordination features alone, on a single held vowel, outperform or are comparable to other features sets and reflect a significant compression of the feature space.United States. Air Force (Contract No. FA8721-05-C-0002)United States. Air Force (Contract No. FA8702-15- D-0001

Flame propagation across an obstacle: OH-PLIF and 2-D simulations with detailed chemistry

Flame propagation across a single obstacle inside a closed square channel is studied experimentally and numerically using a stoichiometric H_2/O_2 mixture at initial conditions 15 kPa and 300 K. The 50% blockage obstacle consists of a pair of fence-type obstacles mounted on the top and bottom walls of the channel. Direct optical visualization was performed using single-image measurement of the planar laser-induced fluorescence of the OH radical (OH-PLIF) and simultaneous high-speed schlieren video to study the flame topology and the flame tip velocity along the channel streamwise axis, respectively. The OH-PLIF images provide a novel level of detail and permit a thorough evaluation of the simulation accuracy. The flame tip accelerates to a peak velocity of 590 m/s just downstream of the obstacle followed by a deceleration and subsequent re-acceleration. The unburnt gas flow ahead of the flame is subsonic at all times. The flame does not show any signs of diffusive-thermal instability. Vortex–flame interactions in the recirculation zones downstream of the obstacle wrinkle the flame. The numerical simulations, based on solving the 2-D compressible reactive Navier–Stokes equations with detailed chemistry, predict the flame tip velocity accurately. However, differences in flame topology are observed, specifically, wrinkling is over-estimated. The over-prediction of flame wrinkling suggests a lower dissipation rate in the numerical simulations than in reality, which could be a consequence of neglecting the third channel dimension. Conditional means of the fuel consumption rate are similar to the consumption rates of 1-D unstretched laminar flames at all times. The increase in pressure during flame propagation causes an increase in fuel consumption rate which needs to be accounted for in simplified modeling approaches

Overview of the Low Complexity Enhancement Video Coding (LCEVC) Standard

The Low Complexity Enhancement Video Coding (LCEVC) specification is a recent standard approved by the ISO/IEC JTC 1/SC 29/WG04 (MPEG) Video Coding. The main goal of LCEVC is to provide a standalone toolset for the enhancement of any other existing codec. It works on top of other coding schemes, resulting in a multi-layer video coding technology, but unlike existing scalable video codecs, adds enhancement layers completely independent from the base video. The LCEVC technology takes as input the decoded video at lower resolution and adds up to two enhancement sub-layers of residuals encoded with specialized low-complexity coding tools, such as simple temporal prediction, frequency transform, quantization, and entropy encoding. This paper provides an overview of the main features of the LCEVC standard: high compression efficiency, low complexity, minimized requirements of memory and processing power

Linking immune-mediated damage to neurodegeneration in multiple sclerosis: could network-based MRI help?

Inflammatory demyelination characterizes the initial stages of multiple sclerosis, while progressive axonal and neuronal loss are coexisting and significantly contribute to the long-term physical and cognitive impairment. There is an unmet need for a conceptual shift from a dualistic view of multiple sclerosis pathology, involving either inflammatory demyelination or neurodegeneration, to integrative dynamic models of brain reorganization, where, glia-neuron interactions, synaptic alterations and grey matter pathology are longitudinally envisaged at the whole-brain level. Functional and structural MRI can delineate network hallmarks for relapses, remissions or disease progression, which can be linked to the pathophysiology behind inflammatory attacks, repair and neurodegeneration. Here, we aim to unify recent findings of grey matter circuits dynamics in multiple sclerosis within the framework of molecular and pathophysiological hallmarks combined with disease-related network reorganization, while highlighting advances from animal models (in vivo and ex vivo) and human clinical data (imaging and histological). We propose that MRI-based brain networks characterization is essential for better delineating ongoing pathology and elaboration of particular mechanisms that may serve for accurate modelling and prediction of disease courses throughout disease stages