103 research outputs found

    Efecto de la lluvia en el momento de la cosecha (lavado) sobre características físicas, químicas y reológicas del grano de trigo Triticum aestivum L.

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    p.1-6Se simularon lluvias artificiales de magnitud creciente en un lote de trigo en condiciones de ser cosechado mecánicamente (humedad menor al 11,2 por ciento). Estas lluvias disminuyeron el Peso Hectolítrico y la densidad del grano, encontrándose una correlación curvilínea altamente significativa (r igual a -0,986 y r igual a -0,981, respectivamente) entre los dos parámetros y la magnitud de las lluvias. Se ideó una escala visual que se encontró estrechamente correlacionada con ambos (r igual a 0,88 y r igual a -0,83 en igual orden) posibilitando su uso como estimador rápido del lavado en experimentos en el futuro. Otros parámetros del grano no fueron afectados como tampoco lo fue la calidad industrial

    The INFN-grid testbed

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    The Italian INFN-Grid Project is committed to set-up, run and manage an unprecedented nation-wide Grid infrastructure. The implementation and use of this INFN-Grid Testbed is presented and discussed. Particular care and attention are devoted to those activities, relevant for the management of the Testbed, carried out by the INFN within international Grid Projects

    Prevention of benzene-induced myelotoxicity by nonsteroidal anti-inflammatory drugs.

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    Benzene affects hematopoietic progenitor cells leading to bone marrow depression and genotoxic effects such as micronucleus formation. Progenitor cell proliferation and differentiation are inhibited by prostaglandins produced by macrophages. Administration of benzene to DBA/2 or C57BL/6 mice caused a dose-dependent bone marrow depression and a significant increase in marrow prostaglandin E level and both were prevented by the coadministration of indomethacin and other inhibitors of the cyclooxygenase component of prostaglandin H synthase. Levels of benzene that decreased bone marrow cellularity also caused genotoxic effects measured as increased micronucleated polychromatic erythrocytes in peripheral blood, which was also prevented by the coadministration of indomethacin. These results suggest a possible role for prostaglandin synthase in benzene myelotoxicity; a mechanism by which this might occur is presented

    INDIGO-DataCloud: a Platform to Facilitate Seamless Access to E-Infrastructures

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    [EN] This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications.INDIGO-Datacloud has been funded by the European Commision H2020 research and innovation program under grant agreement RIA 653549.Salomoni, D.; Campos, I.; Gaido, L.; Marco, J.; Solagna, P.; Gomes, J.; Matyska, L.... (2018). INDIGO-DataCloud: a Platform to Facilitate Seamless Access to E-Infrastructures. Journal of Grid Computing. 16(3):381-408. https://doi.org/10.1007/s10723-018-9453-3S381408163García, A.L., Castillo, E.F.-d., Puel, M.: Identity federation with VOMS in cloud infrastructures. In: 2013 IEEE 5Th International Conference on Cloud Computing Technology and Science, pp 42–48 (2013)Chadwick, D.W., Siu, K., Lee, C., Fouillat, Y., Germonville, D.: Adding federated identity management to OpenStack. Journal of Grid Computing 12(1), 3–27 (2014)Craig, A.L.: A design space review for general federation management using keystone. In: Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, pp 720–725. IEEE Computer Society (2014)Pustchi, N., Krishnan, R., Sandhu, R.: Authorization federation in iaas multi cloud. In: Proceedings of the 3rd International Workshop on Security in Cloud Computing, pp 63–71. ACM (2015)Lee, C.A., Desai, N., Brethorst, A.: A Keystone-Based Virtual Organization Management System. In: 2014 IEEE 6Th International Conference On Cloud Computing Technology and Science (Cloudcom), pp 727–730. IEEE (2014)Castillo, E.F.-d., Scardaci, D., García, A.L.: The EGI Federated Cloud e-Infrastructure. Procedia Computer Science 68, 196–205 (2015)AARC project: AARC Blueprint Architecture, see https://aarc-project.eu/architecture . Technical report (2016)Oesterle, F., Ostermann, S., Prodan, R., Mayr, G.J.: Experiences with distributed computing for meteorological applications: grid computing and cloud computing. Geosci. Model Dev. 8(7), 2067–2078 (2015)Plasencia, I.C., Castillo, E.F.-d., Heinemeyer, S., García, A.L., Pahlen, F., Borges, G.: Phenomenology tools on cloud infrastructures using OpenStack. The European Physical Journal C 73(4), 2375 (2013)Boettiger, C.: An introduction to docker for reproducible research. ACM SIGOPS Operating Systems Review 49(1), 71–79 (2015)Docker: http://www.docker.com (2013)Gomes, J., Campos, I., Bagnaschi, E., David, M., Alves, L., Martins, J., Pina, J., Alvaro, L.-G., Orviz, P.: Enabling rootless linux containers in multi-user environments: the udocker tool. Computing Physics Communications. https://doi.org/10.1016/j.cpc.2018.05.021 (2018)Zhang, Z., Chuan, W., Cheung, D.W.L.: A survey on cloud interoperability taxonomies, standards, and practice. SIGMETRICS perform. Eval. Rev. 40(4), 13–22 (2013)Lorido-Botran, T., Miguel-Alonso, J., Lozano, J.A.: A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments. Journal of Grid Computing 12(4), 559–592 (2014)Nyrén, R., Metsch, T., Edmonds, A., Papaspyrou, A.: Open Cloud Computing Interface–Core. Technical report, Open Grid Forum (2010)Metsch, T., Edmonds, A.: Open Cloud Computing Interface-Infrastructure. Technical report, Open Grid Forum (2010)Metsch, T., Edmonds, A.: Open Cloud Computing Interface-RESTful HTTP Rendering. Technical report, Open Grid Forum (2011)(Ca Technologies) Lipton, P., (Ibm) Moser, S., (Vnomic) Palma, D., (Ibm) Spatzier, T.: Topology and Orchestration Specification for Cloud Applications. Technical report, OASIS Standard (2013)Teckelmann, R., Reich, C., Sulistio, A.: Mapping of cloud standards to the taxonomy of interoperability in IaaS. In: Proceedings - 2011 3rd IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2011, pp 522–526 (2011)García, A.L., Castillo, E.F.-d., Fernández, P.O.: Standards for enabling heterogeneous IaaS cloud federations. Computer Standards & Interfaces 47, 19–23 (2016)Caballer, M., Zala, S., García, A.L., Montó, G., Fernández, P.O., Velten, M.: Orchestrating complex application architectures in heterogeneous clouds. Journal of Grid Computing 16 (1), 3–18 (2018)Hardt, M., Jejkal, T., Plasencia, I.C., Castillo, E.F.-d., Jackson, A., Weiland, M., Palak, B., Plociennik, M., Nielsson, D.: Transparent Access to Scientific and Commercial Clouds from the Kepler Workflow Engine. Computing and Informatics 31(1), 119 (2012)Fakhfakh, F., Kacem, H.H., Kacem, A.H.: Workflow Scheduling in Cloud Computing a Survey. In: IEEE 18Th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations (EDOCW), 2014, Vol. 71, pp. 372–378. Springer, New York (2014)Stockton, D.B., Santamaria, F.: Automating NEURON simulation deployment in cloud resources. Neuroinformatics 15(1), 51–70 (2017)Plóciennik, M., Fiore, S., Donvito, G., Owsiak, M., Fargetta, M., Barbera, R., Bruno, R., Giorgio, E., Williams, D.N., Aloisio, G.: Two-level Dynamic Workflow Orchestration in the INDIGO DataCloud for Large-scale, Climate Change Data Analytics Experiments. Procedia Computer Science 80, 722–733 (2016)Moreno-Vozmediano, R., Montero, R.S., Llorente, I.M.: Multicloud deployment of computing clusters for loosely coupled mtc applications. IEEE transactions on parallel and distributed systems 22(6), 924–930 (2011)Katsaros, G., Menzel, M., Lenk, A.: Cloud Service Orchestration with TOSCA, Chef and Openstack. In: Ic2e (2014)Garcia, A.L., Zangrando, L., Sgaravatto, M., Llorens, V., Vallero, S., Zaccolo, V., Bagnasco, S., Taneja, S., Dal Pra, S., Salomoni, D., Donvito, G.: Improved Cloud resource allocation: how INDIGO-DataCloud is overcoming the current limitations in Cloud schedulers. J. Phys. Conf. Ser. 898(9), 92010 (2017)Singh, S., Chana, I.: A survey on resource scheduling in cloud computing issues and challenges. Journal of Grid Computing, pp. 1–48 (2016)García, A.L., Castillo, E.F.-d., Fernández, P.O., Plasencia, I.C., de Lucas, J.M.: Resource provisioning in Science Clouds: Requirements and challenges. Software: Practice and Experience 48(3), 486–498 (2018)Chauhan, M.A., Babar, M.A., Benatallah, B.: Architecting cloud-enabled systems: a systematic survey of challenges and solutions. Software - Practice and Experience 47(4), 599–644 (2017)Somasundaram, T.S., Govindarajan, K.: CLOUDRB A Framework for scheduling and managing High-Performance Computing (HPC) applications in science cloud. Futur. Gener. Comput. Syst. 34, 47–65 (2014)Sotomayor, B., Keahey, K., Foster, I.: Overhead Matters: A Model for Virtual Resource Management. In: Proceedings of the 2nd International Workshop on Virtualization Technology in Distributed Computing SE - VTDC ’06, p 5. IEEE Computer Society, Washington (2006)SS, S.S., Shyam, G.K., Shyam, G.K.: Resource management for Infrastructure as a Service (IaaS) in cloud computing SS Manvi A survey. J. Netw. Comput. Appl. 41, 424–440 (2014)INDIGO-DataCloud consortium: Initial requirements from research communities - d2.1, see https://www.indigo-datacloud.eu/documents/initial-requirements-research-communities-d21 https://www.indigo-datacloud.eu/documents/initial-requirements-research-communities-d21 https://www.indigo-datacloud.eu/documents/initial-requirements-research-communities-d21 . Technical report (2015)Europen open science cloud: https://ec.europa.eu/research/openscience (2015)Proot: https://proot-me.github.io/ (2014)Runc: https://github.com/opencontainers/runc (2016)Fakechroot: https://github.com/dex4er/fakechroot (2015)Pérez, A., Moltó, G., Caballer, M., Calatrava, A.: Serverless computing for container-based architectures Future Generation Computer Systems (2018)de Vries, K.J.: Global fits of supersymmetric models after LHC run 1. Phd thesis Imperial College London (2015)Openstack: https://www.openstack.org/ (2015)See http://argus-documentation.readthedocs.io/en/stable/argus_introduction.html (2017)See https://en.wikipedia.org/wiki/xacml (2013)See http://www.simplecloud.info (2014)Opennebula: http://opennebula.org/ (2018)Redhat openshift: http://www.opencityplatform.eu (2011)The cloud foundry foundation: https://www.cloudfoundry.org/ (2015)Caballer, M., Blanquer, I., Moltó, G., de Alfonso, C.: Dynamic management of virtual infrastructures. Journal of Grid Computing 13(1), 53–70 (2015)See http://www.infoq.com/articles/scaling-docker-with-kubernetes http://www.infoq.com/articles/scaling-docker-with-kubernetes (2014)Prisma project: http://www.ponsmartcities-prisma.it/ (2010)Opencitiy platform: http://www.opencityplatform.eu (2014)Onedata: https://onedata.org/ (2018)Dynafed: http://lcgdm.web.cern.ch/dynafed-dynamic-federation-project http://lcgdm.web.cern.ch/dynafed-dynamic-federation-project (2011)Fts3: https://svnweb.cern.ch/trac/fts3 (2011)Fernández, P.O., García, A.L., Duma, D.C., Donvito, G., David, M., Gomes, J.: A set of common software quality assurance baseline criteria for research projects, see http://hdl.handle.net/10261/160086 . Technical reportHttermann, M.: Devops for developers Apress (2012)EOSC-Hub: ”Integrating and managing services for the European Open Science Cloud” Funded by H2020 research and innovation pr ogramme under grant agreement No. 777536. See http://eosc-hub.eu (2018)Apache License: author = https://www.apache.org/licenses/LICENSE-2.0 (2004)INDIGO Package Repo: http://repo.indigo-datacloud.eu/ (2017)INDIGO DockerHub: https://hub.docker.com/u/indigodatacloud/ https://hub.docker.com/u/indigodatacloud/ (2015)Indigo gitbook: https://indigo-dc.gitbooks.io/indigo-datacloud-releases https://indigo-dc.gitbooks.io/indigo-datacloud-releases (2017)Van Zundert, G.C., Bonvin, A.M.: Disvis: quantifying and visualizing the accessible interaction space of distance restrained biomolecular complexes. Bioinformatics 31(19), 3222–3224 (2015)Van Zundert, G.C., Bonvin, A.M.: Fast and sensitive rigid–body fitting into cryo–em density maps with powerfit. AIMS Biophys. 2(0273), 73–87 (2015

    Proposed Role for COUP-TFII in Regulating Fetal Leydig Cell Steroidogenesis, Perturbation of Which Leads to Masculinization Disorders in Rodents

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    Reproductive disorders that are common/increasing in prevalence in human males may arise because of deficient androgen production/action during a fetal ‘masculinization programming window’. We identify a potentially important role for Chicken Ovalbumin Upstream Promoter-Transcription Factor II (COUP-TFII) in Leydig cell (LC) steroidogenesis that may partly explain this. In rats, fetal LC size and intratesticular testosterone (ITT) increased ∼3-fold between e15.5-e21.5 which associated with a progressive decrease in the percentage of LC expressing COUP-TFII. Exposure of fetuses to dibutyl phthalate (DBP), which induces masculinization disorders, dose-dependently prevented the age-related decrease in LC COUP-TFII expression and the normal increases in LC size and ITT. We show that nuclear COUP-TFII expression in fetal rat LC relates inversely to LC expression of steroidogenic factor-1 (SF-1)-dependent genes (StAR, Cyp11a1, Cyp17a1) with overlapping binding sites for SF-1 and COUP-TFII in their promoter regions, but does not affect an SF-1 dependent LC gene (3β-HSD) without overlapping sites. We also show that once COUP-TFII expression in LC has switched off, it is re-induced by DBP exposure, coincident with suppression of ITT. Furthermore, other treatments that reduce fetal ITT in rats (dexamethasone, diethylstilbestrol (DES)) also maintain/induce LC nuclear expression of COUP-TFII. In contrast to rats, in mice DBP neither causes persistence of fetal LC COUP-TFII nor reduces ITT, whereas DES-exposure of mice maintains COUP-TFII expression in fetal LC and decreases ITT, as in rats. These findings suggest that lifting of repression by COUP-TFII may be an important mechanism that promotes increased testosterone production by fetal LC to drive masculinization. As we also show an age-related decline in expression of COUP-TFII in human fetal LC, this mechanism may also be functional in humans, and its susceptibility to disruption by environmental chemicals, stress and pregnancy hormones could explain the origin of some human male reproductive disorders

    The ALICE experiment at the CERN LHC

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    ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008
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