Viral variation of the bovine immunodeficiency-like virus

The bovine immunodeficiency-like virus (BIV) is a lentivirus that causes a persistent viral infection in cattle. This thesis describes new isolates of BIV, tools, and general knowledge of the natural viral variation to look at the pathogenesis of this virus;A BIV infected dairy herd from Florida was identified, and samples were taken for attempting virus isolation using fetal bovine lung and spleen cells. Two cultures, FL112 and FL491,were identified as being infected based on syncytia production and were confirmed as BIV infected with a polymerase chain reaction (PCR) test to the reverse transcriptase (RT) gene and protein immunoblot tests with cell culture supernatant as antigen with BIV positive and negative reference serum. The PCR product from both isolates were sequenced and found to have high sequence homology with R29-derived BIV isolates. The new isolates were each experimentally inoculated into two calves. Both calves had an increase in their mononuclear cell numbers early in infection, with the calves infected with the FL112 isolate having the largest response. All four calves had an antibody response typical of calves infected with BIV;A nested PCR test was developed to detect BIV infection in experimentally infected cattle. This technique was compared to virus isolation and protein immunoblot tests for sensitivity in detecting BIV infection. Nested PCR was more sensitive than the other techniques especially early in infection. Later in infection both experimentally infected calves had a decrease in antibodies to the p26 gag protein based on protein immunoblot, but the nested PCR test continued to identify infected cattle;The surface envelope gene (SU) and a region of the reverse transcriptase gene (RT) were sequenced and compared from a number of BIV isolates. The SU gene had much higher sequence diversity than the RT gene, with up to 50% amino acid sequence differences. Seven hypervariable and six conserved regions of the SU gene were identified. The V2 region had large size differences when comparing the different isolates. The R29-derived isolates had the smallest SU gene sequenced and the uncultured OK20 isolate had the largest SU gene sequenced

El mercadeo para comerciantes y microempresas

En la actualidad, la finalidad e interpretación del mercadeo en el sector comercial y micro empresarial se percibe como un gasto en el proceso de desarrollo, minimizando las ganancias esperadas por los socios o dueños, sin darse cuenta, que el mercadeo es una herramienta catalizadora que bien aplicada no representa una inversión muy alta, y si, tiene como finalidad construir relaciones redituables con los clientes actuales y futuros. Pero la realidad muestra que el mercadeo es una herramienta básica para el emprendimiento en el sector real y la aplicación de este no requiere invertir grandes cantidades de dinero en el desarrollo de las dichas actividades, en este documento encontrará los pasos y la manera de aplicación del marketing en una manera fácil y práctica de aplicar mezclando los cinco pasos fundamentales del mercadeo desde la idea del negocio hasta la manera en que puede posicionarse en el mercado, dejando como inquietud asta donde está dispuesto a llegar en la aplicación de la herramient

Neutrino oscillations within the induced gravitational collapse paradigm of long gamma-ray bursts

The specific class of binary-driven hypernovae within the induced gravitational collapse scenario for the explanation of the long Gamma-Ray Bursts indicates as progenitor a binary system composed of a carbon-oxygen core and a neutron star in a tight orbit. The supernova explosion of the core triggers a hypercritical (highly super-Eddington) accretion process onto the NS companion, making it reach the critical mass with consequent formation of a Kerr black hole. Recent numerical simulations of the above system show that a part of the ejecta keeps bound to the newborn Kerr black hole with enough angular momentum to generate a new process of hypercritical accretion, i.e. an accretion disk. Throughout this entire process, we focus on two contexts of neutrino emission leading to two different systems in which an analysis of neutrino flavour oscillations (or flavour transformations) not only constitutes a novel extension of the induced gravitational collapse paradigm literature but also can have an impact on a wide range of astrophysical phenomena: from $e^{-}e^{+}$ plasma production in the vicinity of neutron stars or black holes in GRB models, to r-process nucleosynthesis in disk winds and characterization of astrophysical MeV neutrino sources. In particular, we study neutrino oscillations in: egin{enumerate} - extit{Spherical accretion onto a neutron star:} During this process, copious amounts of neutrino--anti-neutrino pairs ($uar{ u}$) are emitted at the neutron star surface. The neutrino emission can reach luminosities of up to $10^{57}$~MeV~s$^{-1}$, mean neutrino energies 20~MeV, and neutrino densities $10^{31}$~cm$^{-3}$. Along their path from the vicinity of the NS surface outward, such neutrinos experience flavour transformations dictated by the neutrino to electron density ratio. We determine the neutrino and electron on the accretion zone and use them to compute the neutrino flavour evolution. For normal and inverted neutrino-mass hierarchies and within the two-flavour formalism ($u_{e} u_{x}$), we estimate the final electronic and non-electronic neutrino content after two oscillation processes: (1) neutrino collective effects due to neutrino self-interactions where the neutrino density dominates and, (2) the Mikheyev-Smirnov-Wolfenstein effect, where the electron density dominates. We find that the final neutrino content is composed by $sim$55% ($sim$62%) of electronic neutrinos, i.e. $u_{e}+ar{ u}_{e}$, for the normal (inverted) neutrino-mass hierarchy. - extit{Neutrino-cooled disks around a Kerr black hole:} In this phase of the binary-driven hypernovae, given the extreme conditions of high density (up to $10^{12}$~g~cm$^{-3}$) and temperatures (up to tens of MeV) inside this disk, neutrinos can reach densities of $10^{33}$~cm$^{-3}$ and energies of $50$~MeV. Although the geometry of the disk is significantly different from that of spherical accretion, these conditions provide an environment that allows neutrino flavour transformations. We estimate the evolution of the electronic and non-electronic neutrino content within the two-flavour formalism ($u_{e} u_{x}$) under the action of neutrino collective effects by neutrino self-interactions. We find that neutrino oscillations inside the disk can have frequencies between $sim (10^{5}$--$10^{9})$~s$^{-1}$, leading the disk to achieve flavour equipartition. This implies that the energy deposition rate by neutrino annihilation ($u + ar{ u} o e^{-} + e^{+}$) in the vicinity of the Kerr black hole is smaller than previous estimates in the literature not accounting by flavour oscillations inside the disk. The exact value of the reduction factor depends on the $u_{e}$ and $u_{x}$ optical depths but it can be as high as $sim 5$. This work has allowed us to identify key theoretical and numerical features involved in the study of neutrino oscillations and our results are a first step toward the analysis of neutrino oscillations in unique astrophysical settings other than core-collapse supernovae. As such, they deserve further attention

Distributed and parallel sparse convex optimization for radio interferometry with PURIFY

Next generation radio interferometric telescopes are entering an era of big data with extremely large data sets. While these telescopes can observe the sky in higher sensitivity and resolution than before, computational challenges in image reconstruction need to be overcome to realize the potential of forthcoming telescopes. New methods in sparse image reconstruction and convex optimization techniques (cf. compressive sensing) have shown to produce higher fidelity reconstructions of simulations and real observations than traditional methods. This article presents distributed and parallel algorithms and implementations to perform sparse image reconstruction, with significant practical considerations that are important for implementing these algorithms for Big Data. We benchmark the algorithms presented, showing that they are considerably faster than their serial equivalents. We then pre-sample gridding kernels to scale the distributed algorithms to larger data sizes, showing application times for 1 Gb to 2.4 Tb data sets over 25 to 100 nodes for up to 50 billion visibilities, and find that the run-times for the distributed algorithms range from 100 milliseconds to 3 minutes per iteration. This work presents an important step in working towards computationally scalable and efficient algorithms and implementations that are needed to image observations of both extended and compact sources from next generation radio interferometers such as the SKA. The algorithms are implemented in the latest versions of the SOPT (https://github.com/astro-informatics/sopt) and PURIFY (https://github.com/astro-informatics/purify) software packages {(Versions 3.1.0)}, which have been released alongside of this article.Comment: 25 pages, 5 figure

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest. The learning machine leverages big data to find examples that maximize the training value of its interaction with the teacher. When the teacher is restricted to labeling examples selected by the machine, this problem is an instance of active learning. When the teacher can provide additional information to the machine (e.g., suggestions on what examples or predictive features should be used) as the learning task progresses, then the problem becomes one of interactive learning. To accommodate the two-way communication channel needed for efficient interactive learning, the teacher and the machine need an environment that supports an interaction language. The machine can access, process, and summarize more examples than the teacher can see in a lifetime. Based on the machine's output, the teacher can revise the definition of the task or make it more precise. Both the teacher and the machine continuously learn and benefit from the interaction. We have built a platform to (1) produce valuable and deployable models and (2) support research on both the machine learning and user interface challenges of the interactive learning problem. The platform relies on a dedicated, low-latency, distributed, in-memory architecture that allows us to construct web-scale learning machines with quick interaction speed. The purpose of this paper is to describe this architecture and demonstrate how it supports our research efforts. Preliminary results are presented as illustrations of the architecture but are not the primary focus of the paper

Geometry of subduction and depth of the seismogenic zone in the Guerrero gap, Mexico

L'étude sismique de la zone côtière de Guerrero (Mexique) permet d'interpréter la géométrie de la subduction dans cette régio