7th Drug hypersensitivity meeting: part two

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Software For Modeling Multiple Emissions In A River

This work presents a software based on a three-dimensional model for the dispersion of effluents in rivers using CFD techniques. There are several models can be found in the literature, some of which even analyze complex flows. They are however restricted to small river sections. The main contribution of this work is that it proposes a new software capable of predicting the dispersion of effluents in very large open channels using Computational Fluid Dynamics. The model is very fast, an unusual feature of CFD models. Due to this, it is possible to predict the dispersion of substances in long sections of rivers with some kilometers in extension. Moreover, multiple emissions can be analysed by the model, allowing its use as a predictive tool to analyze and guide management decisions on future industrial installations near rivers. Results for the dispersion of an inert emission in a river near Campinas were used to validate the model. This software is Windows 98/NT/2000 based, and it was developed using Visual Fortran, Visual Basic and Matlab.Chow, V.T., (1959) Open-channel hydraulics, , McGraw-Hill Book CompanyFischer, H.B., The Mechanics of Dispersion in Natural Streams (1967) J. Hydr. Div, 93 (6), pp. 187-216Modenesi, K., Furlan, L.T., Tomaz, E., Guirardello, R., Nunhez, J.R., A CFD Model for Pollutant Dispersion in Rivers (2004) Brazilian Journal of Chemical Engineering, 21 (4), pp. 556-568. , October-DecemberNokes, R.I., Hughes, G.O., Turbulent mixing in uniform channels of irregular cross-section (1994) Journal of Hydraulic Research, 32 (1)Rodi, W., (1984), Turbulence models and their applications in hydraulics, a state of the art reviewSpalding, D.B., A Single Formula for the Law of the Wall, Journal of Applied Mechanics, 28, pp. 455-457, 1961White, F., (1992) Viscous Fluid Flow, , Mc Graw Hill, 2nd editionTominaga, A., Nezu, I., Turbulent Structure in Compound Open-Channel Flows (1991) Journal of Hydraulic Engineering, 117 (1). , Januar

A New Computational Fluid Dynamic (cfd) Model For The Estimation Of Effluent Dispersion In Rivers Sections

This work presents a new three-dimensional model for the prediction of the dispersion of effluents in rivers with the use of Computational Fluid Dynamics (CFD) techniques. Even though several models based on CFD have already been reported in the literature (some of them analyzing complex flows), they are restricted to small river sections, since CFD commercial software demand large computational resources for problems of that kind. The main contribution of this work is that it proposes a new model which is able to predict the dispersion of effluents in several kilometers long channels using CFD. The model is very fast, what is an unusual feature for CFD models. The model is capable of predicting multiple emissions on the same river section, what makes it an important tool to analyze and guide management decisions on future industrial installations in river regions already receiving many discharges. Results for the dispersion of an inert emission in a river near Campinas, Brazil, were used for the model validation

Software For Modeling Effluent Emissions In Rivers [software Para Modelagem De Dispersão De Efluentes Em Rios]

This work presents a three-dimensional model for the dispersion of effluents in rivers using Computational Fluid Dynamics (CFD) techniques. There are several models in the literature, some of which even analyze complex flows. They are however restricted to small river sections. The main contribution of this work is that it proposes a new software capable of predicting the dispersion of effluents in very large open channels. The model is very fast, an unusual feature of CFD models. Due to this, it is possible to predict the dispersion of substances in long sections of rivers with some kilometers in extension. Moreover, multiple emissions can be analyzed by the model, allowing its use as a predictive tool to analyze and guide management decisions on future industrial installations near rivers. Results for the dispersion of an inert emission in a river near Campinas (Brazil) were used to validate the model.133291297COX, B.A., A review of currently available in-stream water-quality models and their applicability for simulating dissolved oxygen in lowland rivers (2003) The Science of the Total Environment, 314-316, pp. 335-377COX, B.A., A review of dissolved oxygen modeling techniques for lowland rivers (2003) The Science of the Total Environment, 314-316, pp. 303-334MACHADO, M.B., Modelagem Tridimensional da Dispersão de Poluentes em Rios (2006) Tese (doutorado em Engenharia Química), pp. 147 f. , Universidade Estadual de Campinas, UNICAMP, Campinas, SPMODENESI, K., A CFD model por pollutant dispersion in rivers (2004) Brazilian Journal of Chemical Engineering, 21 (4), pp. 557-568. , out./dezRODI, W., Turbulence Models and their Application in Hydraulics (1993) IAHR Monograph Series, , 3a EdiçãoSPALDING, D.B., A single formula for the law of the wall (1991) Journal of Applied Mechanics, 28 (3). , Setembr

Caracterização química de extratos hidrossolúveis desidratados de arroz e soja Chemical characterization of dehydrated rice and soybean water-soluble extracts

O presente trabalho teve por objetivo caracterizar quimicamente os extratos hidrossolúveis desidratados de arroz (Oryza sativa L.) e de soja (Glycine max (L.) Merrill). Os processos utilizados para a obtenção dos extratos hidrossolúveis foram: maceração do arroz e da soja, desintegração, centrifugação, adição de ácido cítrico, fervura e secagem por atomização. A caracterização química foi realizada através das seguintes determinações: composição centesimal aproximada, composição de minerais e atividade do inibidor de tripsina. Com o aumento das proporções de soja (0 a 50%), os extratos hidrossolúveis desidratados tiveram aumento nos teores de proteína, extrato etéreo, cinzas e fibra crua, porém diminuição no teor de carboidratos. Os teores de P, K, Mg, Cu e Co foram altos em alguns extratos hidrossolúveis desidratados estudados, os quais foram semelhantes à indicação diária na "Recommended Dietary Allowances", enquanto os demais minerais se mostraram em pequenas quantidades ou apenas traços. Não foi detectada atividade do inibidor de tripsina.<br>The objective of the present study was to evaluate the chemical characteristics of dehydrated water-soluble extracts of rice (Oryza sativa L.) and soybean (Glycine max (L.) Merrill). The preparation included soaking of the rice and soybean, desintegration, centrifugation, addition of citric acid, boiling and spray drying. Dehydrated water-soluble extracts were analysed for their proximate composition, minerals content and trypsin inhibitor activity. Results indicated that an increase in the proportion of soybean (0 to 50%) resulted in an increase in the content of proteins, oil, ash, crude fiber, as well as a decrease in the percentage of carbohydrates. The content of P, K, Mg, Cu and Co in some of the extracts were particularly high and were comparable with those of the Recommended Dietary Allowances. Other minerals were detected in low or trace amounts. No trypsin inhibitor activity was detected

Equação de predição da exigência de proteína bruta para aves reprodutoras pesadas na fase de produção Prediction equation of crude protein requirements for broiler breeders hens

O objetivo do presente trabalho foi determinar as exigências de proteína para aves reprodutoras pesadas através do método fatorial. A exigência de proteína bruta para mantença (PBm) foi determinada por intermédio da técnica do balanço de nitrogênio por meio de ensaio de metabolismo com aves submetidas a quatro dietas com níveis decrescentes de proteína, proporcionando balanço positivo, próximo a zero e negativo. Para determinar a exigência de proteína bruta para o ganho de peso (PBg) dois experimentos foram conduzidos, sendo que em um, determinou-se as exigências líquidas de nitrogênio e no outro, a eficiência de utilização do nitrogênio para o ganho, por meio de abates semanais de aves no período de 26 a 33 semanas de idade. A exigência de proteína bruta para produção de ovos (PBo) foi determinada através de análises semanais de proteína bruta dos ovos coletados, no período de 31 a 37 semanas de idade, considerando a eficiência de deposição da proteína no ovo. A exigência e eficiência de utilização da proteína para mantença foram 2.282 mg PB/kg0,75/dia e 60,79%; respectivamente. As exigências de PBg e PBo determinadas foram: 356 mg PB/g e 262 mg PB/g, respectivamente, e as eficiências de utilização do nitrogênio, 40 e 46,80%, respectivamente. A equação de predição elaborada para aves reprodutoras pesadas na fase de produção foi: PB=2,282.P0,75+0,356.G+0,262.MO, onde PB é a exigência de proteína bruta (g/ave/dia), P o peso corporal (kg), G o ganho de peso (g/dia) e MO a massa de ovos (g/dia).<br>The objective of this study was to determine the protein requirement for broiler breeder hens using factorial method. The requirement of crude protein for maintenance (CPm) was determined using nitrogen balance technique in metabolism assay. The birds were fed with four protein levels in order to get a positive, a close to zero and a negative nitrogen balance. To determine the crude protein weight gain requirement (CPg), two experiments were carried out. The first was calculate to determine the net nitrogen requirement and the other to determine nitrogen use efficiency for body deposition, from 26 to 33 weeks old. The crude protein requirement for egg production (CPe) was determined by content of crude protein of eggs measured in birds from 31 to 37 weeks old. The protein requirement for maintenance was 2,282 mg CP/kg0.75/day and the protein efficiency 60.79%. The nitrogen requirement for weight gain and egg production were: 356 mgCP/g and 262 mg of CP/g, respectively, and the protein efficiency utilization were: 40 and 46.80% for weight gain and egg production, respectively. The prediction equation for broiler breeder hens was : CP = 2,282W0.75 + 0.356G + 0.262 EM, where CP is crude protein requirement (g/bird/day), W is body weight (kg), G is weight gain (g/day) and EM is egg mass (g/day)