941 resultados para Intention-based models
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Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis disease of cotton, is widespread in Brazil and can cause severe yield loss. Because weather conditions greatly affect disease development, the objective of this work was to develop weather-based models to assess disease favorability. Latent period, incidence, and severity of ramulosis symptoms were evaluated in controlled environment experiments using factorial combinations of temperature (15, 20, 25, 30, and 35 degrees C) and leaf wetness duration (0, 4, 8, 16, 32, and 64 h after inoculation). Severity was modeled as an exponential function of leaf wetness duration and temperature. At the optimum temperature of disease development, 27 degrees C, average latent period was 10 days. Maximum ramulosis severity occurred from 20 to 30 degrees C, with sharp decreases at lower and higher temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. In field experiments at Piracicaba, Sao Paulo State, Brazil, cotton plots were inoculated (10(5) conidia ml(-1)) and ramulosis severity was evaluated weekly. The model obtained from the controlled environment study was used to generate a disease favorability index for comparison with disease progress rate in the field. Hourly measurements of solar radiation, temperature, relative humidity, leaf wetness duration, rainfall, and wind speed were also evaluated as possible explanatory variables. Both the disease favorability model and a model based on rainfall explained ramulosis growth rate well, with R(2) of 0.89 and 0.91, respectively. They are proposed as models of ramulosis development rate on cotton in Brazil, and weather-disease relationships revealed by this work can form the basis of a warning system for ramulosis development.
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Specific leaf area (SLA; m(leaf)(2) kg(leaf)(-1)) is a key ecophysiological parameter influencing leaf physiology, photosynthesis, and whole plant carbon gain. Both individual tree-based models and other forest process-based models are generally highly sensitive to this parameter, but information on its temporal or within-stand variability is still scarce. In a 2-4-year-old Eucalyptus plantation in Congo, prone to seasonal drought, the within-stand and seasonal variability in SLA were investigated by means of destructive sampling carried out at 2-month intervals, over a 2-year period. Within-crown vertical gradients of SLA were small. Highly significant relationships were found between tree-average SLA (SLA(t)) and tree size (tree height, H(t), or diameter at breast height, DBH): SLA(t) ranged from about 9 m(2) kg(-1) for dominant trees to about 14-15 m(2) kg(-1) for the smallest trees. The decrease in SLA(t) with increasing tree size was accurately predicted from DBH using power functions. Stand-average SLA varied by about 20% during the year, with lowest values at the end of the 5-month dry season, and highest values about 2-3 months after the onset of the wet season. Variability in leaf water status according to tree size and season is discussed as a possible determinant of both the within-stand and seasonal variations in SM. (C) 2009 Elsevier B.V. All rights reserved.
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This study aims to evaluate the feasibility of using simple techniques - pollen abortion rates, passive diffusive tubes (NO(2)) and trace element accumulation in tree barks - when determining the area of influence of pollution emissions produced in a traffic corridor. Measurements were performed at 0, 60 and 120 meters from a major road with high vehicular traffic, taking advantage of a sharp gradient that exists between the road and a cemetery. NO(2) values and trace elements measured at 0 meters were significantly higher than those measured at more distant points. Al, S. Cl, V. Fe, Cu, and Zn exhibited a higher concentration in tree barks at the vicinity of the traffic corridor. The same pattern was observed for the pollen abortion rates measured at the three different sites. Our data suggests that simple techniques may be applied either to validate dispersion land-based models in an urban settings or, alternatively, to provide better spatial resolution to air pollution exposure when high-resolution pollution monitoring data are not available. (C) 2011 Elsevier B.V. All rights reserved.
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A series of aluminum-10 wt pet silicon castings were produced in sand molds to investigate the effect of modification on porosity formation. Modification with individual additions of either strontium or sodium resulted in a statistically significant increase in the level of porosity compared to unmodified castings. The increase in porosity with modification is due to the presence of numerous dispersed pores, which were absent in the unmodified casting. It is proposed that these pores form as a result of differences in size of the aluminum-silicon eutectic grains between unmodified and modified alloys. A geometric model is developed to show how the size of eutectic grains can influence the amount and distribution of porosity. Unlike traditional feeding-based models, which incorporate the effect: of microstructure on permeability, this model considers what happens when liquid is isolated from the riser and can no longer flow. This simple isolation model complements rather than contradicts existing theories on modification-related porosity formation and should be considered in the development of future comprehensive models.
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Mutations in PKD2 are responsible for approximately 15% of the autosomal dominant polycystic kidney disease cases. This gene encodes polycystin-2, a calcium-permeable cation channel whose C-terminal intracytosolic tail (PC2t) plays an important role in its interaction with a number of different proteins. In the present study, we have comprehensively evaluated the macromolecular assembly of PC2t homooligomer using a series of biophysical and biochemical analyses. Our studies, based on a new delimitation of PC2t, have revealed that it is capable of assembling as a homotetramer independently of any other portion of the molecule. Our data support this tetrameric arrangement in the presence and absence of calcium. Molecular dynamics simulations performed with a modified all-atoms structure-based model supported the PC2t tetrameric assembly, as well as how different populations are disposed in solution. The simulations demonstrated, indeed, that the best-scored structures are the ones compatible with a fourfold oligomeric state. These findings clarify the structural properties of PC2t domain and strongly support a homotetramer assembly of PC2.
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Aripiprazole is an atypical antipsychotic that acts as a partial agonist at the dopamine D-2 receptor. It has been mainly investigated in dopamine-based models of schizophrenia, while its effects on glutamate-based paradigms have remained to be further characterized. Due to its unique mechanism of action, aripiprazole has also been considered as a replacement medication for psychostimulant abuse. Thus, in the present study we tested the hypothesis that aripiprazole would prevent the motor hyperactivity induced by psychostimulant and psychotomimetic drugs that act either by dopaminergic or glutamatergic mechanisms. Male Swiss mice received injections of aripiprazole (0.1-1 mg/kg) followed by drugs that enhance the dopamine-mediated neurotransmission, amphetamine (3 mg/kg) or cocaine (5 mg/kg), or by glutamate NMDA-receptor antagonists, ketamine (60 mg/kg) or MK-801 (0.4 mg/kg). Independent groups also received aripiprazole (0.1-1 mg/kg) or haloperidol (0.5 mg/kg) and were tested for catalepsy. All doses of aripiprazole were effective in preventing the motor stimulant effects of amphetamine and cocaine. Moreover, the higher dose also prevented the effects of ketamine and MK-801. The present study reports the effects of aripiprazole in dopaminergic and glutamatergic models predictive of antipsychotic activity, suggesting that both may be useful for screening novel partial agonists with antipsychotic activity. It also shows that aripiprazole may prevent the acute effects of psychostimulant drugs without significant motor impairment. C) 2007 Elsevier B.V. All rights reserved.
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A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.
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This paper reviews the current knowledge and understanding of martensitic transformations in ceramics - the tetragonal to monoclinic transformation in zirconia in particular. This martensitic transformation is the key to transformation toughening in zirconia ceramics. A very considerable body of experimental data on the characteristics of this transformation is now available. In addition, theoretical predictions can be made using the phenomenological theory of martensitic transformations. As the paper will illustrate, the phenomenological theory is capable of explaining all the reported microstructural and crystallographic features of the transformation in zirconia and in some other ceramic systems. Hence the theory, supported by experiment, can be used with considerable confidence to provide the quantitative data that is essential for developing a credible, comprehensive understanding of the transformation toughening process. A critical feature in transformation toughening is the shape strain that accompanies the transformation. This shape strain, or nucleation strain, determines whether or not the stress-induced martensitic transformation can occur at the tip of a potentially dangerous crack. If transformation does take place, then it is the net transformation strain left behind in the transformed region that provides toughening by hindering crack growth. The fracture mechanics based models for transformation toughening, therefore, depend on having a full understanding of the characteristics of the martensitic transformation and, in particular, on being able to specify both these strains. A review of the development of the models for transformation toughening shows that their refinement and improvement over the last couple of decades has been largely a result of the inclusion of more of the characteristics of the stress-induced martensitic transformation. The paper advances an improved model for the stress-induced martensitic transformation and the strains resulting from the transformation. This model, which separates the nucleation strain from the subsequent net transformation strain, is shown to be superior to any of the constitutive models currently available. (C) 2002 Elsevier Science Ltd. All rights reserved.
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O presente trabalho investigou o problema da modelagem da dispersão de compostos odorantes em presença de obstáculos (cúbicos e com forma complexa) sob condição de estabilidade atmosférica neutra. Foi empregada modelagem numérica baseada nas equações de transporte (CFD1) bem como em modelos algébricos baseados na pluma Gausseana (AERMOD2, CALPUFF3 e FPM4). Para a validação dos resultados dos modelos e a avaliação do seu desempenho foram empregados dados de experimentos em túnel de vento e em campo. A fim de incluir os efeitos da turbulência atmosférica na dispersão, dois diferentes modelos de sub-malha associados à Simulação das Grandes Escalas (LES5) foram investigados (Smagorinsky dinâmico e WALE6) e, para a inclusão dos efeitos de obstáculos na dispersão nos modelos Gausseanos, foi empregado o modelo PRIME7. O uso do PRIME também foi proposto para o FPM como uma inovação. De forma geral, os resultados indicam que o uso de CFD/LES é uma ferramenta útil para a investigação da dispersão e o impacto de compostos odorantes em presença de obstáculos e também para desenvolvimento dos modelos Gausseanos. Os resultados também indicam que o modelo FPM proposto, com a inclusão dos efeitos do obstáculo baseado no PRIME também é uma ferramenta muito útil em modelagem da dispersão de odores devido à sua simplicidade e fácil configuração quando comparado a modelos mais complexos como CFD e mesmo os modelos regulatórios AERMOD e CALPUFF. A grande vantagem do FPM é a possibilidade de estimar-se o fator de intermitência e a relação pico-média (P/M), parâmetros úteis para a avaliação do impacto de odores. Os resultados obtidos no presente trabalho indicam que a determinação dos parâmetros de dispersão para os segmentos de pluma, bem como os parâmetros de tempo longo nas proximidades da fonte e do obstáculo no modelo FPM pode ser melhorada e simulações CFD podem ser usadas como uma ferramenta de desenvolvimento para este propósito. Palavras chave: controle de odor, dispersão, fluidodinâmica computacional, modelagem matemática, modelagem gaussiana de pluma flutuante, simulação de grandes vórtices (LES).
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Solubility measurements of quinizarin. (1,4-dihydroxyanthraquinone), disperse red 9 (1-(methylamino) anthraquinone), and disperse blue 14 (1,4-bis(methylamino)anthraquinone) in supercritical carbon dioxide (SC CO2) were carried out in a flow type apparatus, at a temperature range from (333.2 to 393.2) K and at pressures from (12.0 to 40.0) MPa. Mole fraction solubility of the three dyes decreases in the order quinizarin (2.9 x 10(-6) to 2.9.10(-4)), red 9 (1.4 x 10(-6) to 3.2 x 10(-4)), and blue 14 (7.8 x 10(-8) to 2.2 x 10(-5)). Four semiempirical density based models were used to correlatethe solubility of the dyes in the SC CO2. From the correlation results, the total heat of reaction, heat of vaporization plus the heat of solvation of the solute, were calculated and compared with the results presented in the literature. The solubilities of the three dyes were correlated also applying the Soave-Redlich-Kwong cubic equation of state (SRK CEoS) with classical mixing rules, and the physical properties required for the modeling were estimated and reported.
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Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.
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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes
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Mestrado em Contabilidade
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The solubilities of two C-tetraalkylcalix[4]resorcinarenes, namely C-tetramethylcalix[4]resorcinarene and C-tetrapentylcalix[4]resorcinarene, in supercritical carbon dioxide (SCCO2) were measured in a flow-type apparatus at a temperature range from (313.2 to 333.2) K and at pressures from (12.0 to 35.0) MPa. The C-tetraalkylcalix[4]resorcinarenes were synthesized applying our optimized procedure and fully characterized by means of gel permeation chromatography, infrared and nuclear magnetic resonance spectroscopy. The solubilities of the C-tetraalkylcalix[4]resorcinarenes in SCCO2 were determined by analysis of the extracts obtained by HPLC with ultraviolet (UV) detection methodology adapted by our team. Four semiempirical density-based models, and the SoaveRedlichKwong cubic equation of state (SRK CEoS) with classical mixing rules, were applied to correlate the solubility of the calix[4]resorcinarenes in the SC CO2. The physical properties required for the modeling were estimated and reported.
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Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.