5,446 research outputs found

    Genetic characterization of Acipenser sturio L., 1758 in relation to other sturgeon species using satellite DNA

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    We obtained and characterized a satellite (st) DNA family named HindIII from the genomes of the Adriatic sturgeon Acipenser naccarii Bonaparte, 1836, Siberian sturgeon Acipenser baerii Brandt, 1869, and beluga sturgeon Huso huso (L., 1758). We did not find this stDNA in the genome of the Atlantic sturgeon Acipenser sturio L., 1758. The comparison of sturgeon species using the HindIII stDNA revealed the following: (1) A. naccarii and A. baerii are closely related; (2) H. huso appears to belong to the genus Acipenser and, probably, Huso is not a separate genus within the Acipenserinae; (3) A. sturio differs from the other three studied species by the absence of the HindIII stDNA and, most likely, it represents a separate evolutionary lineage within the Acipenseridae. The data on the HindIII stDNA can be successfully used for species identification of sturgeon specimens captured in different European regions.En este trabajo presentamos la caracterización del genoma de Acipenser sturio L., 1758 en relación con el genoma de Acipenser naccarii Bonaparte, 1836, Acipenser baerii Brandt, 1869 y Huso huso (L., 1758) utilizando una familia de ADN satélite (la familia HindIII). Nuestro análisis revela que: (1) A. naccarii y A. baerii son especies muy emparentadas; (2) H. huso aparece muy relacionada con las especies del género Acipenser y, probablemente, podría ser considerada como una especie perteneciente a dicho género, y (3) A. sturio difiere del resto de las especies analizadas, lo que sugiere que esta especie ha debido seguir una evolución independiente respecto a las otras especies. Estos datos pueden ser muy útiles, no sólo para establecer las relaciones filogenéticas entre A. sturio y las otras especies de Acipenseridae, sino también para la identificación de ejemplares de esturiones capturados en diferentes regiones europeas.Instituto Español de Oceanografí

    Three-body structure of low-lying 18Ne states

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    We investigate to what extent 18Ne can be descibed as a three-body system made of an inert 16O-core and two protons. We compare to experimental data and occasionally to shell model results. We obtain three-body wave functions with the hyperspherical adiabatic expansion method. We study the spectrum of 18Ne, the structure of the different states and the predominant transition strengths. Two 0+, two 2+, and one 4+ bound states are found where they are all known experimentally. Also one 3+ close to threshold is found and several negative parity states, 1-, 3-, 0-, 2-, most of them bound with respect to the 16O excited 3- state. The structures are extracted as partial wave components, as spatial sizes of matter and charge, and as probability distributions. Electromagnetic decay rates are calculated for these states. The dominating decay mode for the bound states is E2 and occasionally also M1.Comment: 17 pages, 5 figures (version to appear in EPJA

    An instrumental puzzle: the modular integration of AOLI

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    The Adaptive Optics Lucky Imager, AOLI, is an instrument developed to deliver the highest spatial resolution ever obtained in the visible, 20 mas, from ground-based telescopes. In AOLI a new philosophy of instrumental prototyping has been applied, based on the modularization of the subsystems. This modular concept offers maximum flexibility regarding the instrument, telescope or the addition of future developments.Comment: 10 pages, 8 figures, Proc. SPIE 9908, Ground-based and Airborne Instrumentation for Astronomy VI, 99082Z (August 9, 2016

    Gadget for anchovy 9a South: Model description and results to provide catch advice and reference points (WGHANSA-1 2021)

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    The model speci fications presented below correspond to those benchmarked in WKPELA 2018. The main difference is that results are presented now for the end of the second quarter of each year instead of being presented at the end of the fourth quarter. This responds to practical modi cations in the de nition of the assessment year, now it goes from July 1st to June 30th of the next year. Model speci fications for this year are presented in section 2.2 and ??, as well as estimated parameters after optimization in Table 2
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