1,176 research outputs found

    Generation of parabolic similaritons in tapered silicon photonic wires: comparison of pulse dynamics at telecom and mid-IR wavelengths

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    We study the generation of parabolic self-similar optical pulses in tapered Si photonic nanowires (Si-PhNWs) both at telecom (\lambda=1.55 \mu m) and mid-IR (\lambda=2.2 \mu m) wavelengths. Our computational study is based on a rigorous theoretical model, which fully describes the influence of linear and nonlinear optical effects on pulse propagation in Si-PhNWs with arbitrarily varying width. Numerical simulations demonstrate that, in the normal dispersion regime, optical pulses evolve naturally into parabolic pulses upon propagating in millimeter-long tapered Si-PhNWs, with the efficiency of this pulse reshaping process being strongly dependent on the spectral and pulse parameter regime in which the device operates, as well as the particular shape of the Si-PhNW.Comment: 4 pages, 5 figure

    Wavelength conversion and parametric amplification of optical pulses via quasi-phase-matched FWM in long-period Bragg silicon waveguides

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    We present a theoretical analysis supported by comprehensive numerical simulations of quasi phase-matched four-wave mixing (FWM) of ultrashort optical pulses that propagate in weakly width-modulated silicon photonic nanowire gratings. Our study reveals that, by properly designing the optical waveguide such that the interacting pulses co-propagate with the same group-velocity, a conversion efficiency enhancement of more than 15 dB, as compared to a uniform waveguide, can readily be achieved. We also analyze the dependence of the conversion efficiency and FWM gain on the pulse width, time delay, walk-off parameter, and grating modulation depth.Comment: 4 pages, 5 figure

    Exponential dichotomies of evolution operators in Banach spaces

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    This paper considers three dichotomy concepts (exponential dichotomy, uniform exponential dichotomy and strong exponential dichotomy) in the general context of non-invertible evolution operators in Banach spaces. Connections between these concepts are illustrated. Using the notion of Green function, we give necessary conditions and sufficient ones for strong exponential dichotomy. Some illustrative examples are presented to prove that the converse of some implication type theorems are not valid

    On the Benefits of Transparent Compression for Cost-Effective Cloud Data Storage

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    International audienceInfrastructure-as-a-Service (IaaS) cloud computing has revolutionized the way we think of acquiring computational resources: it allows users to deploy virtual machines (VMs) at large scale and pay only for the resources that were actually used throughout the runtime of the VMs. This new model raises new challenges in the design and development of IaaS middleware: excessive storage costs associated with both user data and VM images might make the cloud less attractive, especially for users that need to manipulate huge data sets and a large number of VM images. Storage costs result not only from storage space utilization, but also from bandwidth consumption: in typical deployments, a large number of data transfers between the VMs and the persistent storage are performed, all under high performance requirements. This paper evaluates the trade-off resulting from transparently applying data compression to conserve storage space and bandwidth at the cost of slight computational overhead. We aim at reducing the storage space and bandwidth needs with minimal impact on data access performance. Our solution builds on BlobSeer, a distributed data management service specifically designed to sustain a high throughput for concurrent accesses to huge data sequences that are distributed at large scale. Extensive experiments demonstrate that our approach achieves large reductions (at least 40%) of bandwidth and storage space utilization, while still attaining high performance levels that even surpass the original (no compression) performance levels in several data-intensive scenarios

    Epstein-Barr virus transcription factor Zta acts through distal regulatory elements to directly control cellular gene expression

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    Lytic replication of the human gamma herpes virus Epstein-Barr virus (EBV) is an essential prerequisite for the spread of the virus. Differential regulation of a limited number of cellular genes has been reported in B-cells during the viral lytic replication cycle. We asked whether a viral bZIP transcription factor, Zta (BZLF1, ZEBRA, EB1), drives some of these changes. Using genome-wide chromatin immunoprecipitation coupled to next-generation DNA sequencing (ChIP-seq) we established a map of Zta interactions across the human genome. Using sensitive transcriptome analyses we identified 2263 cellular genes whose expression is significantly changed during the EBV lytic replication cycle. Zta binds 278 of the regulated genes and the distribution of binding sites shows that Zta binds mostly to sites that are distal to transcription start sites. This differs from the prevailing view that Zta activates viral genes by binding exclusively at promoter elements. We show that a synthetic Zta binding element confers Zta regulation at a distance and that distal Zta binding sites from cellular genes can confer Zta-mediated regulation on a heterologous promoter. This leads us to propose that Zta directly reprograms the expression of cellular genes through distal elements

    Local maximum points of explicitly quasiconvex functions

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    This work concerns generalized convex real-valued functions defined on a nonempty convex subset of a real topological linear space. Its aim is twofold: first, to show that any local maximum point of an explicitly quasiconvex function is a global minimum point whenever it belongs to the intrinsic core of the function’s domain and second, to characterize strictly convex normed spaces by applying this property for a particular class of convex functions

    Riding out of the storm: How to deal with the complexity of grid and cloud management

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    Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management

    Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.

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    Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies of asthma in 5,416 individuals with asthma (cases) including individuals of European American, African American or African Caribbean, and Latino ancestry, with replication in an additional 12,649 individuals from the same ethnic groups. We identified five susceptibility loci. Four were at previously reported loci on 17q21, near IL1RL1, TSLP and IL33, but we report for the first time, to our knowledge, that these loci are associated with asthma risk in three ethnic groups. In addition, we identified a new asthma susceptibility locus at PYHIN1, with the association being specific to individuals of African descent (P = 3.9 × 10(-9)). These results suggest that some asthma susceptibility loci are robust to differences in ancestry when sufficiently large samples sizes are investigated, and that ancestry-specific associations also contribute to the complex genetic architecture of asthma

    Genome-Wide Functional Analysis of the Cotton Transcriptome by Creating an Integrated EST Database

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    A total of 28,432 unique contigs (25,371 in consensus contigs and 3,061 as singletons) were assembled from all 268,786 cotton ESTs currently available. Several in silico approaches [comparative genomics, Blast, Gene Ontology (GO) analysis, and pathway enrichment by Kyoto Encyclopedia of Genes and Genomes (KEGG)] were employed to investigate global functions of the cotton transcriptome. Cotton EST contigs were clustered into 5,461 groups with a maximum cluster size of 196 members. A total of 27,956 indel mutants and 149,616 single nucleotide polymorphisms (SNPs) were identified from consensus contigs. Interestingly, many contigs with significantly high frequencies of indels or SNPs encode transcription factors and protein kinases. In a comparison with six model plant species, cotton ESTs show the highest overall similarity to grape. A total of 87 cotton miRNAs were identified; 59 of these have not been reported previously from experimental or bioinformatics investigations. We also predicted 3,260 genes as miRNAs targets, which are associated with multiple biological functions, including stress response, metabolism, hormone signal transduction and fiber development. We identified 151 and 4,214 EST-simple sequence repeats (SSRs) from contigs and raw ESTs respectively. To make these data widely available, and to facilitate access to EST-related genetic information, we integrated our results into a comprehensive, fully downloadable web-based cotton EST database (www.leonxie.com)
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