987 resultados para hybrid identification


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This paper reports on the development of specific slicing techniques for functional programs and their use for the identification of possible coherent components from monolithic code. An associated tool is also introduced. This piece of research is part of a broader project on program understanding and re-engineering of legacy code supported by formal methods

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The genus Heliconia is not much studied and the number of existing species in this genus is still uncertain. It is known that this number relies between 150 to 250 species. In Brazil, about 40 species are native and known by many different names. The objective of this paper was to characterize morphometrically and to identify the NOR (active nucleolus organizer regions) by Ag-NOR banding of chromosomes of Heliconia bihai (L) L. Root meristems were submitted to blocking treatment in an amiprofos-methyl (APM) solution, fixed in methanol-acetic acid solution for 24 hours, at least. The meristems were washed in distilled water and submitted to enzymatic digestion with pectinase enzyme. The slides were prepared by dissociation of the root meristem, dried in the air and also on hot plate at 50°C. Subsequently, some slides were submitted to 5% Giemsa stain for karyotype construction and to a solution of silver nitrate (AgNO3) 50% for Ag-NOR banding. The species H. bihai has 2n = 22 chromosomes, 4 pairs of submetacentric chromosomes and 7 pairs of metacentric chromosomes, and graded medium to short (3.96 to 0.67 μM), with the presence of active NOR in pairs 1 and 2 and interphase cells with 2 nucleoli. These are the features of a diploid species.

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Polyembryonic seeds are characterized by the development of over one embryo in the same seed, which can be zygotic and nucellar. The objective of this work was to identify the genetic origin, whether zygotic or nucellar, of seedlings of polyembryonic seeds of 'Ubá' mango tree using ISSR markers, and relating them with the vigor of the seedlings. Thus, mangos were harvested in Visconde do Rio Branco (accession 102) and Ubá (accessions 112, 138, 152 and 159), whose seeds were germinated in plastic trays filled with washed sand. Fifty days after sowing, seedlings from five seeds of each one of the accessions 102, 112, 138, 159 and from 10 seeds of the accession 152, were analyzed. These sseedlings were characterized and evaluated for plant height, stem circumference and mass of fresh aerial part and the most vigorous seedling was the one displaying at least two of these traits higher than the other seedlings from seed. Leaves were collected for genomic DNA extraction, which was amplified using seven ISSR primers previously selected based on the amplification profile and considering the number and resolution of fragments. Zygotic seedlings were found in 18 seeds, which were the most vigorous in six seeds. The results evidenced the existence of genetic variability in orchards using seedlings grown from seeds, because the farmer usually uses the most vigorous ones, assuming that this is of nucellar origin. These results also indicate that the most vigorous seedling are not always nucellar, inasmuch as of 20% of the total seeds evaluated, the zygotic seedling was the most vigorous.

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ABSTRACTSocially oriented ventures have provided livelihoods and social recognition to disadvantaged communities in different corners of the world. In some cases, these ventures are the result of Corporate Social Responsibility (CSR) programs. In Latin America, this type of undertaking has responded positively to unmet social needs. The social cause drives these organizations and their human resources and they give high value to organizational cause-fit. This paper presents empirical evidence of the effects of perceived cause-fit on several worker attitudes and behaviors. Psychological contract theory was adopted as theoretical background. Employees working in a hybrid (for-profit/socially oriented) Colombian organization created by a CSR program participated in the survey. Data provided by 218 employees were analyzed using PLS structural equation modeling. The results suggest the ideological components of the employee-employer relationship predict positive attitudes and cooperative organizational behaviors towards hybrid organizations.

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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

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The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

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In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

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Preliminary version

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OBJECTIVE: To evaluate the microbiological quality of pasteurized milk commercialized in Rio de Janeiro, Brazil, and determine serologically enteropathogenic Escherichia coli (EPEC) strains in E. coli isolates obtained from milk samples. METHODS: Ninety samples of pasteurized milk -- types B and C -- of three different commercial brands, purchased in supermarkets and bakeries in Rio de Janeiro, were examined. The amount of total and fecal coliform bacteria was estimated using the Most Probable Number technique. Mesophilic, psychrotrophic, and thermoduric microorganism counts were determined by the Standard Plate Count technique. Isolation and identification of E. coli were carried out using conventional physiological tests. Commercial antisera were used for serological characterization of EPEC. RESULTS: The three milk brands analyzed revealed bacterial counts above the regulated values of the Brazilian government. It was found that among 208 strains of E. coli isolated, 46 (22.1%) were serologically classified as EPEC. The most common EPEC serogroup was O55 (15.2%). CONCLUSIONS: Though recent studies on virulence factors indicate that not all strains serologically classified as EPEC are able to attaching/effacing lesion, it is believed that the isolation of EPEC serogroups from pasteurized milk represent a potential risk for children, as well as an indicative of the presence of other enteropathogens.

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In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

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A doença de Machado-Joseph (DMJ) ou ataxia espinocerebelosa do tipo 3 (SCA3), conhecida por ser a mais comum das ataxias hereditárias dominantes em todo o mundo, é uma doença neurodegenerativa autossómica dominante que leva a uma grande incapacidade motora, embora sem alterar o intelecto, culminando com a morte do doente. Atualmente não existe nenhum tratamento eficaz para esta doença. A DMJ é resultado de uma alteração genética causada pela expansão de uma sequência poliglutamínica (poliQ), na região C-terminal do gene que codifica a proteína ataxina-3 (ATXN3). Os mecanismos celulares das doenças de poliglutaminas que provocam toxicidade, bem como a função da ATXN3, não são ainda totalmente conhecidos. Neste trabalho, usamos, pela sua simplicidade e potencial genético, um pequeno animal invertebrado, o nemátode C. elegans, com o objetivo de identificar fármacos eficazes para o combate contra a patogénese da DMJ, analisando simultaneamente o seu efeito na agregação da ATXN3 mutante nas células neuronais in vivo e o seu impacto no comportamento motor dos animais. Este pequeno invertebrado proporciona grandes vantagens no estudo dos efeitos tóxicos de proteínas poliQ nos neurónios, uma vez que a transparência das suas 959 células (das quais 302 são neurónios) facilita a deteção de proteínas fluorescentes in vivo. Para além disso, esta espécie tem um ciclo de vida curto, é económica e de fácil manutenção. Neste trabalho testámos no nosso modelo transgénico da DMJ com 130Qs em C.elegans dois compostos potencialmente moduladores da agregação da ATXN3 mutante e da resultante disfunção neurológica, atuando pela via da autofagia. De modo a validar a possível importância terapêutica da ativação da autofagia os compostos candidatos escolhidos foram o Litío e o análogo da Rapamicina CCI-779, testados independentemente e em combinação. A neuroproteção conferida pelo Litío e pelo CCI-779 independentemente sugere que o uso destes fármacos possa ser considerado uma boa estratégia como terapia para a DMJ, a testar em organismos evolutivamente mais próximos do humano. A manipulação da autofagia, segundo vários autores, parece ser benéfica e pode ser a chave para o desenvolvimento de novos tratamentos para várias doenças relacionadas com a agregação proteica e o envelhecimento.

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A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

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In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.