8,315 research outputs found
Phase Synchronization and Polarization Ordering of Globally-Coupled Oscillators
We introduce a prototype model for globally-coupled oscillators in which each
element is given an oscillation frequency and a preferential oscillation
direction (polarization), both randomly distributed. We found two collective
transitions: to phase synchronization and to polarization ordering. Introducing
a global-phase and a polarization order parameters, we show that the transition
to global-phase synchrony is found when the coupling overcomes a critical value
and that polarization order enhancement can not take place before global-phase
synchrony. We develop a self-consistent theory to determine both order
parameters in good agreement with numerical results
Pseudo-diffusive magnetotransport in graphene
Transport properties through wide and short ballistic graphene junctions are
studied in the presence of arbitrary dopings and magnetic fields. No dependence
on the magnetic field is observed at the Dirac point for any current cumulant,
just as in a classical diffusive system, both in normal-graphene-normal and
normal-graphene-superconductor junctions. This pseudo-diffusive regime is
however extremely fragile respect to doping at finite fields. We identify the
crossovers to a field-suppressed and a normal ballistic transport regime in the
magnetic field - doping parameter space, and provide a physical interpretation
of the phase diagram. Remarkably, pseudo-diffusive transport is recovered away
from the Dirac point in resonance with Landau levels at high magnetic fields.Comment: 4+ pages, 2 figures. Minor corrections. Published version
Geometric phases in semiconductor spin qubits: Manipulations and decoherence
We describe the effect of geometric phases induced by either classical or
quantum electric fields acting on single electron spins in quantum dots in the
presence of spin-orbit coupling. On one hand, applied electric fields can be
used to control the geometric phases, which allows performing quantum coherent
spin manipulations without using high-frequency magnetic fields. On the other
hand, fluctuating fields induce random geometric phases that lead to spin
relaxation and dephasing, thus limiting the use of such spins as qubits. We
estimate the decay rates due to piezoelectric phonons and conduction electrons
in the circuit, both representing dominant electric noise sources with
characteristically differing power spectra.Comment: 17 pages, 8 figures, published versio
Differentiation enhances Zika virus infection of neuronal brain cells.
Zika virus (ZIKV) is an emerging, mosquito-borne pathogen associated with a widespread 2015-2016 epidemic in the Western Hemisphere and a proven cause of microcephaly and other fetal brain defects in infants born to infected mothers. ZIKV infections have been also linked to other neurological illnesses in infected adults and children, including Guillain-Barré syndrome (GBS), acute flaccid paralysis (AFP) and meningoencephalitis, but the viral pathophysiology behind those conditions remains poorly understood. Here we investigated ZIKV infectivity in neuroblastoma SH-SY5Y cells, both undifferentiated and following differentiation with retinoic acid. We found that multiple ZIKV strains, representing both the prototype African and contemporary Asian epidemic lineages, were able to replicate in SH-SY5Y cells. Differentiation with resultant expression of mature neuron markers increased infectivity in these cells, and the extent of infectivity correlated with degree of differentiation. New viral particles in infected cells were visualized by electron microscopy and found to be primarily situated inside vesicles; overt damage to the Golgi apparatus was also observed. Enhanced ZIKV infectivity in a neural cell line following differentiation may contribute to viral neuropathogenesis in the developing or mature central nervous system
Generalized W-Class State and its Monogamy Relation
We generalize the W class of states from qubits to qudits and prove
that their entanglement is fully characterized by their partial entanglements
even for the case of the mixture that consists of a W-class state and a product
state .Comment: 12 pages, 1 figur
Algunas consideraciones acerca de fray Pedro Ponce de León y Juan Pablo Bonet
Separata del núm. extraordinario de "La Paraula", publicado con motivo del IV centenario del nacimiento de Fray P. Ponce de León y III de la publicación del libro "Reducción de las letras" de Joan. P. BonetCopia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2009-201
Compression algorithms for biomedical signals and nanopore sequencing data
The massive generation of biological digital information creates various computing
challenges such as its storage and transmission. For example, biomedical
signals, such as electroencephalograms (EEG), are recorded by multiple sensors over
long periods of time, resulting in large volumes of data. Another example is genome
DNA sequencing data, where the amount of data generated globally is seeing explosive
growth, leading to increasing needs for processing, storage, and transmission
resources. In this thesis we investigate the use of data compression techniques for
this problem, in two different scenarios where computational efficiency is crucial.
First we study the compression of multi-channel biomedical signals. We present
a new lossless data compressor for multi-channel signals, GSC, which achieves compression
performance similar to the state of the art, while being more computationally
efficient than other available alternatives. The compressor uses two novel
integer-based implementations of the predictive coding and expert advice schemes
for multi-channel signals. We also develop a version of GSC optimized for EEG
data. This version manages to significantly lower compression times while attaining
similar compression performance for that specic type of signal.
In a second scenario we study the compression of DNA sequencing data produced
by nanopore sequencing technologies. We present two novel lossless compression algorithms
specifically tailored to nanopore FASTQ files. ENANO is a reference-free
compressor, which mainly focuses on the compression of quality scores. It achieves
state of the art compression performance, while being fast and with low memory
consumption when compared to other popular FASTQ compression tools. On the
other hand, RENANO is a reference-based compressor, which improves on ENANO,
by providing a more efficient base call sequence compression component. For RENANO
two algorithms are introduced, corresponding to the following scenarios: a
reference genome is available without cost to both the compressor and the decompressor;
and the reference genome is available only on the compressor side, and a
compacted version of the reference is included in the compressed le. Both algorithms
of RENANO significantly improve the compression performance of ENANO,
with similar compression times, and higher memory requirements.La generación masiva de información digital biológica da lugar a múltiples desafíos informáticos, como su almacenamiento y transmisión. Por ejemplo, las señales biomédicas, como los electroencefalogramas (EEG), son generadas por múltiples sensores registrando medidas en simultaneo durante largos períodos de tiempo,
generando grandes volúmenes de datos. Otro ejemplo son los datos de secuenciación de ADN, en donde la cantidad de datos a nivel mundial esta creciendo de forma explosiva, lo que da lugar a una gran necesidad de recursos de procesamiento, almacenamiento y transmisión. En esta tesis investigamos como aplicar técnicas de compresión de datos para atacar este problema, en dos escenarios diferentes donde
la eficiencia computacional juega un rol importante.
Primero estudiamos la compresión de señales biomédicas multicanal. Comenzamos presentando un nuevo compresor de datos sin perdida para señales multicanal, GSC, que logra obtener niveles de compresión en el estado del arte y que al mismo tiempo es mas eficiente computacionalmente que otras alternativas disponibles. El compresor utiliza dos nuevas implementaciones de los esquemas de codificación predictiva
y de asesoramiento de expertos para señales multicanal, basadas en aritmética
de enteros. También presentamos una versión de GSC optimizada para datos de
EEG. Esta versión logra reducir significativamente los tiempos de compresión, sin
deteriorar significativamente los niveles de compresión para datos de EEG.
En un segundo escenario estudiamos la compresión de datos de secuenciación
de ADN generados por tecnologías de secuenciación por nanoporos. En este sentido,
presentamos dos nuevos algoritmos de compresión sin perdida, específicamente
diseñados para archivos FASTQ generados por tecnología de nanoporos. ENANO
es un compresor libre de referencia, enfocado principalmente en la compresión de
los valores de calidad de las bases. ENANO alcanza niveles de compresión en el
estado del arte, siendo a la vez mas eficiente computacionalmente que otras herramientas
populares de compresión de archivos FASTQ. Por otro lado, RENANO es
un compresor basado en la utilización de una referencia, que mejora el rendimiento
de ENANO, a partir de un nuevo esquema de compresión de las secuencias de bases.
Presentamos dos variantes de RENANO, correspondientes a los siguientes escenarios:
(i) se tiene a disposición un genoma de referencia, tanto del lado del compresor
como del descompresor, y (ii) se tiene un genoma de referencia disponible solo del
lado del compresor, y se incluye una versión compacta de la referencia en el archivo
comprimido. Ambas variantes de RENANO mejoran significativamente los niveles
compresión de ENANO, alcanzando tiempos de compresión similares y un mayor
consumo de memoria
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