Variations In Desiccation Tolerance In Seeds Of Eugenia Pyriformis: Dispersal At Different Stages Of Maturation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Eugenia pyriformis Cambess., known locally as uvaieira, a species of fruit-bearing tree with both pharmacological and gastronomic potential, has seeds which are sensitive to desiccation. The aim of this study was to analyse whether the degree of tolerance to desiccation of uvaieira seeds depends on the stage of maturation of the seeds at shedding. This, in turn, depends on the environmental conditions in which the seeds develop, including the accumulation of degree-days and rainfall in the period. Seeds were collected from the ripe fruit of parent plants located in the states of São Paulo and Minas Gerais, Brazil, submitted to drying and analysed for water content and germination. A completely randomised design was used in a 20 × 3 factorial scheme (source of material x level of drying). The degree of desiccation tolerance differs between region and period of collection, even for the same parent plant when the seeds are collected in different years. The water and thermal conditions of the environment during seed development modify the maturation cycle, the physiological quality and the acquisition of desiccation tolerance. In uvaieira seeds, desiccation tolerance depends on the physiological maturity of the seeds at the time of dispersal, which is associated with the environmental conditions.471118126CAPES, Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Valores de aminoácidos digestíveis de alimentos para aves

O experimento foi conduzido para determinar os coeficientes de digestibilidade verdadeira dos aminoácidos utilizando-se o método de alimentação forçada com galos adultos cecectomizados. Os alimentos estudados foram: quirera de arroz; farelo de arroz integral; milho; sorgo; farelo de trigo; farelo de soja; farelo de algodão 28% e farelo de algodão 38%; levedura 43%; levedura 40%. Os valores médios dos coeficientes de digestibilidade verdadeira dos aminoácidos essenciais e não-essenciais foram, respectivamente: 77,53 e 67,21% para a quirera de arroz; 73,33 e 52,54% para o farelo de arroz integral; 73,33 e 52,54% para o milho; 84,48 e 67,21% para o sorgo; 70,75 e 48,55% para o farelo de trigo; 89,37 e 85,22% para o farelo de soja; 74,85 e 74,13 para o farelo de algodão 28%; 77,50 e 72,46% para o farelo de algodão 38%; 49,16 e 48,63% para a levedura 43%; e 46,03 e 38,88% para a levedura 40%. Os valores obtidos dos coeficientes de digestibilidade verdadeira de aminoácidos essenciais e não-essenciais dos alimentos estudados permitem elaborar rações mais eficientes para aves.This experiment was carried out to determine the values of the real digestibility coefficients of amino acids by using the method of "forced feed" with cecectomized roosters. The studied food were the following: rice bran, whole rice meal, corn, sorghum, wheat bran, soybean meal, cotton meal 28%, cotton meal 38%, yeast sugar cane 43% and yeast sugar cane 40%. The mean values of real digestibility coefficients of essential and non-essential amino acids were, in percentage, the following: for rice bran, 77.53 and 67.21; for rice meal, 73.33 and 52.54; for corn, 84.65 and 74.42; for sorghum, 84.48 and 67.29; for wheat bran, 70.75 and 48.55; for soybean meal, 89.37 and 85.22; for cotton meal 28%, 74.85 and 74.13; for cotton meal 38%, 77.50 and 72.46; for yeast sugar cane 43%, 49.16 and 48.63; and yeast sugar cane 40%, 46.03 and 38.88. The values of the coefficients of real digestibility of essential and nonessential amino acids of feedstuffs studied allow to formulate more efficient rations for birds

Boosting background suppression in the NEXT experiment through Richardson-Lucy deconvolution

Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.The NEXT Collaboration acknowledges support from the following agencies and institutions: the European Research Council (ERC) under the Advanced Grant 339787-NEXT; the European Union's Framework Programme for Research and Innovation Horizon 2020 (2014-2020) under the Grant Agreements No. 674896, 690575 and 740055; the Ministerio de Economia y Competitividad and the Ministerio de Ciencia, Innovacion y Universidades of Spain under grants FIS2014-53371-C04, RTI2018-095979, the Severo Ochoa Program grants SEV-2014-0398 and CEX2018-000867-S, and the Maria de Maeztu Program MDM-2016-0692; the Generalitat Valenciana under grants PROMETEO/2016/120 and SEJI/2017/011; the Portuguese FCT under project PTDC/FIS-NUC/2525/2014 and under projects UID/04559/2020 to fund the activities of LIBPhys-UC; the U.S. Department of Energy under contracts No. DE-AC02-06CH11357 (Argonne National Laboratory), DE-AC02-07CH11359 (Fermi National Accelerator Laboratory), DE-FG02-13ER42020 (Texas A&M) and DE-SC0019223/DE-SC0019054 (University of Texas at Arlington); the University of Texas at Arlington (U.S.A.); and the Pazy Foundation (Israel) under grants 877040 and 877041. DGD acknowledges Ramon y Cajal program (Spain) under contract number RYC-2015-18820. JM-A acknowledges support from Fundacion Bancaria "la Caixa" (ID 100010434), grant code LCF/BQ/PI19/11690012. AS acknowledges support from the Kreitman School of Advanced Graduate Studies at Ben-Gurion University. Documen