832 resultados para MONGE, CARLOS FRANCISCO,


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Lasioderma serricorne (Coleoptera: Anobiidae); Oryzaephillus surinamensis (Coleoptera: Silvanidae);Cryptolestes ferrugineus (Coleoptera: Cucujidae); Ephestia kuehniella (Lepidoptera: Pyralidae). Expurgo de sementes: tempo de liberação da fosfina (horas); tempo de exposição das sementes a fosfina (horas);

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O capim-elefante tem contribuído para alimentação animal em sistemas de produção leiteira. Entretanto, o manejo das cultivares de porte normal constitui uma das dificuldades, devido ao rápido alongamento do colmo. A cultivar anã BRS Kurumi foi recentemente lançada com o objetivo de facilitar o manejo do capim-elefante. O BRS Kurumi se destacou pela maior densidade volumétrica de folhas, elevada digestibilidade, baixo teor de fibra e maior facilidade de manejo, devido ao baixo alongamento de colmos, sendo boa opção para intensificação da produção animal a pasto.

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Este trabalho está inserido no Projeto Especial Plano Estratégico de Atuação da Embrapa na Região do Matopiba, financiado pela Embrapa (Projeto SEG/IDEARE 05.13.25.009.00.00), e tem como objetivo avaliar a aptidão agrícola das terras do Matopiba, na escala 1:500.000, com base em informações pedoclimáticas disponíveis consubstanciadas por verificação in situ por meio de campanhas de campo para validação das interpretações de aptidão agrícola.

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O objetivo deste trabalho foi analisar as estatísticas disponíveis para aferir a evolução, nos últimos 5 anos (2010-2014), das exportações das frutas de maior importância econômica para o Submédio do Vale do São Francisco, enfocando tanto o comportamento agregado quanto o mercado europeu e o americano. A base de dados usada foi a do sistema Aliceweb2, do Ministério do Desenvolvimento, Indústria e Comércio Exterior, (MDIC).

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Background: the impact of early postnatal androgen exposure on female laryngeal tissue may depend on certain characteristics of this exposure. We assessed the impact of the dose, duration, and timing of early androgen exposure on the vocal development of female subjects who had been treated for adrenocortical tumor (ACT) in childhood.Methods: the long-term effects of androgen exposure on the fundamental vocal frequency (F0), vocal pitch, and final height and the presence of virilizing signs were examined in 9 adult (age, 18.4 to 33.5 years) and 10 adolescent (13.6 to 17.8 years) female ACT patients. We also compared the current values with values obtained 0.9 years to 7.4 years after these subjects had undergone ACT surgery, a period during which they had shown normal androgen levels.Results: of the 19 subjects, 17 (89%) had been diagnosed with ACT before 4 years of age, 1 (5%) at 8.16 years, and 1 (5%) at 10.75 years. Androgen exposure (2 to 30 months) was sufficiently strong to cause pubic hair growth in all subjects and clitoromegaly in 74% (14/19) of the subjects, but did not reduce their height from the target value. Although androgen exposure induced a remarkable reduction in F0 (132 Hz) and moderate pitch virilization in 1 subject and partial F0 virilization, resulting in F0 of 165 and 169 Hz, in 2 subjects, the majority had normal F0 ranging from 189 to 245 Hz.Conclusions: Female laryngeal tissue is less sensitive to androgen exposure between birth and adrenarche than during other periods. Differential larynx sensitivity to androgen exposure in childhood and F0 irreversibility in adulthood are age-, concentration-, duration-, and timing-dependent events that may also be affected by exposure to inhibitory or stimulatory hormones. Further studies are required to better characterize each of these factors.

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Plakhov, A.Y., (2004) 'Precise solutions of the one-dimensional Monge-Kantorovich problem', Sbornik: Mathematics 195(9) pp.1291-1307 RAE2008

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This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

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In the first part of this paper we reviewed the fingerprint classification literature from two different perspectives: the feature extraction and the classifier learning. Aiming at answering the question of which among the reviewed methods would perform better in a real implementation we end up in a discussion which showed the difficulty in answering this question. No previous comparison exists in the literature and comparisons among papers are done with different experimental frameworks. Moreover, the difficulty in implementing published methods was stated due to the lack of details in their description, parameters and the fact that no source code is shared. For this reason, in this paper we will go through a deep experimental study following the proposed double perspective. In order to do so, we have carefully implemented some of the most relevant feature extraction methods according to the explanations found in the corresponding papers and we have tested their performance with different classifiers, including those specific proposals made by the authors. Our aim is to develop an objective experimental study in a common framework, which has not been done before and which can serve as a baseline for future works on the topic. This way, we will not only test their quality, but their reusability by other researchers and will be able to indicate which proposals could be considered for future developments. Furthermore, we will show that combining different feature extraction models in an ensemble can lead to a superior performance, significantly increasing the results obtained by individual models.