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 $n$ qubits to $n$ 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 $\ket{0}^{\otimes n}$.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