Determinación de nitratos por espectrofotometría UV-visible en productos cárnicos

La presencia de aditivos se ha tornado algo común en la industrialización de alimentos. Resulta positivo entonces, que existan herramientas que permitan su cuantificación y de esa manera poder controlar, por comparación con la legislación vigente, si los elaboradores respetan los valores máximos establecidos. En el caso particular de los nitratos, además de su control como algo legislado, importa desde el punto de vista de la salud de las personas, por cuanto este anión combinado con aminas forma compuestos de reconocida naturaleza cancerígena. El presente trabajo tiene como finalidad poner a punto la técnica espectrofotométrica UV-Visible para determinar la concentración de nitratos en productos derivados de origen animal. Posteriormente se realizará la validación de la misma a fin de confirmar si el procedimiento descrito es útil y confiable para el objetivo propuesto. Previo al tratamiento de la muestra se realizó la curva de calibrado partiendo de un patrón de concentración conocida (nitrato de sodio proanálisis), donde se relacionan diferentes valores de concentración con valores de absorbancia obtenidos en distintas lecturas brindadas por el equipo. El ensayo consiste en la desproteinización de la muestra, filtrado, agregado de salicilato de sodio y evaporación en baño María. La muestra desecada se acidifica, se agrega el reactivo revelador tomando coloración amarilla en función de la concentración del anión en estudio, para finalmente leer valores de absorción por espectrofotometría a 415 nm de longitud de onda. Para la validación del método propuesto se realizaron las siguientes pruebas: linealidad, sensibilidad, exactitud, precisión, límites de detección y cuantificación. En función del análisis estadístico pudo comprobarse que para el rango de concentraciones estudiado, la técnica es confiable para cuantificar este aditivo en productos cárnicos.The presence of additives has become common in the industrialization of food. It is positive then, that there are tools that allow quantification and thus be able to control, by comparison with current legislation, whether the processors respect the maximum established values. In the particular case of nitrates, in addition to their control as something legislated, it matters from the point of view of people`s health, because this anion combined with amines forms compounds of recognized carcinogenic nature. The purpose of this work is to develop the UV-Visible spectrophotometric technique to determine the concentration of nitrates in derived products of animal origin. Subsequently, it will be validated in order to confirm whether the procedure described is useful and reliable for the proposed purpose. Prior to the treatment of the sample, the calibration curve was carried out based on a pattern of known concentration (sodium nitrate proanalysis), where different concentration values are related to absorbance values obtained in different readings provided by the team. The test consists in the deproteinization of the sample, filtering, sodium salicylate aggregate and evaporation in a water bath. The dried sample is acidified, the developer reagent is added taking yellow coloration depending on the concentration of the anion under study, to finally read absorption values by spectrophotometry at 415 nm wavelength. For the validation of the proposed method, the following tests were performed: linearity, sensitivity, accuracy, precision, detection limits and quantification. Based on the statistical analysis, it was found that for the range of concentrations studied, the technique is reliable to quantify this additive in meat products.Fil: Villegas, Gabriel Oscar. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias

La UBA y la cultura

Fil: García, Oscar Gabriel. Universidad de Buenos Aires. Extensión Universitaria y Bienestar Estudiantil; Argentin

Okara: A nutritionally valuable by-product able to stabilize lactobacillus plantarum during freeze-drying, spray-drying, and storage

Okara is a nutritionally valuable by-product produced in large quantities as result of soymilk elaboration. This work proposes its use as both culture and dehydration medium during freeze-drying, spray-drying, and storage of Lactobacillus plantarum CIDCA 83114. Whole and defatted okara were employed as culture media for L. plantarum CIDCA 83114. The growth kinetics were followed by plate counting and compared with those of bacteria grown in MRS broth (control). No significant differences in plate counting were observed in the three media. The fatty acid composition of bacteria grown in whole and defatted okara showed a noticeable increase in the unsaturated/saturated (U/S) fatty acid ratio, with regard to bacteria grown in MRS. This change was mainly due to the increase in polyunsaturated fatty acids, namely C18:2. For dehydration assays, cultures in the stationary phase were neutralized and freeze-dried (with or without the addition of 250 mM sucrose) or spray-dried. Bacteria were plate counted immediately after freeze-drying or spray-drying and during storage at 4°C for 90 days. Freeze-drying in whole okara conducted to the highest bacterial recovery. Regarding storage, spray-dried bacteria previously grown in whole and defatted okara showed higher plate counts than those grown in MRS. On the contrary, freeze-dried bacteria previously grown in all the three culture media were those with the lowest plate counts. The addition of sucrose to the dehydration media improved their recovery. The higher recovery of microorganisms grown in okara after freeze-drying and spray-drying processes and during storage was ascribed to both the presence of fiber and proteins in the dehydration media, and the increase in U/S fatty acids ratio in bacterial membranes. The obtained results support for the first time the use of okara as an innovative matrix to deliver L. plantarum. Considering that okara is an agro-waste obtained in large quantities, these results represent an innovative strategy to add it value, providing a symbiotic ingredient with promising industrial applications in the development of novel functional foods and feeds.Fil: Quintana, Gabriel Sebastian. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; ArgentinaFil: Gerbino, Oscar Esteban. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; ArgentinaFil: Gomez Zavaglia, Andrea. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; Argentin

Analysis of drawbacks and constraints of classification algorithms for three-phase voltage dips

Voltage events are one of the most common and harmful disturbances of power electric systems. Voltage dips, swells and interruptions are included under this heading. Given the economic cost that these disturbances represent for electrical power transmission and distribution companies and the industry, it becomes imperative to detect and classify them properly. Several classification criteria and algorithms have been proposed in the literature as analysis tools to differentiate voltage events by their characteristics and, if possible, to determine their causes and consequences. Even though some of these approaches make a correct classification of the voltage events, there are certain operation conditions that are common in real electrical grids, in which the classification criteria, and their corresponding algorithms, make a wrong classification. These particular conditions, together with the lack of a fair comparison in a common scenario, have not been addressed in the specific field literature. This work explores in detail all these aspects by evaluating the symmetrical components criterion and ABC classification criterion, and rigorously analyzes three specific algorithms: the Symmetrical Components Algorithm, the Six Phases Algorithm and the Space Vector Algorithm. Drawbacks arise from both classification criteria and algorithms. The causes of the classification errors are described and discussed in detail in order to better understand the problem, and evidence the constraints of these classification methods.Fil: Strack, Jorge Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Carugati, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Orallo, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Donato, Patricio Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Maestri, Sebastian Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Carrica, Daniel Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; Argentin

Regularity theory and high order numerical methods for the (1D)-fractional Laplacian

This paper presents regularity results and associated high-order numerical methods for one-dimensional Fractional-Laplacian boundary-value problems. On the basis of a factorization of solutions as a product of a certain edge-singular weight $w$ times a ``regular´´ unknown, a characterization of the regularity of solutions is obtained in terms of the smoothness of the corresponding right-hand sides. In particular, for right-hand sides which are analytic in a Bernstein Ellipse, analyticity in the same Bernstein Ellipse is obtained for the ``regular´´ unknown. Moreover, a sharp Sobolev regularity result is presented which completely characterizes the co-domain of the Fractional-Laplacian operator in terms of certain weighted Sobolev spaces introduced in (Babu{s}ka and Guo, SIAM J. Numer. Anal. 2002). The present theoretical treatment relies on a full eigendecomposition for a certain weighted integral operator in terms of the Gegenbauer polynomial basis. The proposed Gegenbauer-based Nystr"om numerical method for the Fractional-Laplacian Dirichlet problem, further, is significantly more accurate and efficient than other algorithms considered previously. The sharp error estimates presented in this paper indicate that the proposed algorithm is spectrally accurate, with convergence rates that only depend on the smoothness of the right-hand side. In particular, convergence is exponentially fast (resp. faster than any power of the mesh-size) for analytic (resp. infinitely smooth) right-hand sides. The properties of the algorithm are illustrated with a variety of numerical results.Fil: Acosta, Gabriel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; ArgentinaFil: Borthagaray, Juan Pablo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; ArgentinaFil: Bruno, Oscar Ricardo. California Institute Of Technology; Estados UnidosFil: Maas, Martín Daniel. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentin

Nuevos Modelos de Aprendizaje Híbrido para Clasificación y Ordenamiento Multi-Etiqueta

En la última década, el aprendizaje multi-etiqueta se ha convertido en una importante tarea de investigación, debido en gran parte al creciente número de problemas reales que contienen datos multi-etiqueta. En esta tesis se estudiaron dos problemas sobre datos multi-etiqueta, la mejora del rendimiento de los algoritmos en datos multi-etiqueta complejos y la mejora del rendimiento de los algoritmos a partir de datos no etiquetados. El primer problema fue tratado mediante métodos de estimación de atributos. Se evaluó la efectividad de los métodos de estimación de atributos propuestos en la mejora del rendimiento de los algoritmos de vecindad, mediante la parametrización de las funciones de distancias empleadas para recuperar los ejemplos más cercanos. Además, se demostró la efectividad de los métodos de estimación en la tarea de selección de atributos. Por otra parte, se desarrolló un algoritmo de vecindad inspirado en el enfoque de clasifcación basada en gravitación de datos. Este algoritmo garantiza un balance adecuado entre eficiencia y efectividad en su solución ante datos multi-etiqueta complejos. El segundo problema fue resuelto mediante técnicas de aprendizaje activo, lo cual permite reducir los costos del etiquetado de datos y del entrenamiento de un mejor modelo. Se propusieron dos estrategias de aprendizaje activo. La primer estrategia resuelve el problema de aprendizaje activo multi-etiqueta de una manera efectiva y eficiente, para ello se combinaron dos medidas que representan la utilidad de un ejemplo no etiquetado. La segunda estrategia propuesta se enfocó en la resolución del problema de aprendizaje activo multi-etiqueta en modo de lotes, para ello se formuló un problema multi-objetivo donde se optimizan tres medidas, y el problema de optimización planteado se resolvió mediante un algoritmo evolutivo. Como resultados complementarios derivados de esta tesis, se desarrolló una herramienta computacional que favorece la implementación de métodos de aprendizaje activo y la experimentación en esta tarea de estudio. Además, se propusieron dos aproximaciones que permiten evaluar el rendimiento de las técnicas de aprendizaje activo de una manera más adecuada y robusta que la empleada comunmente en la literatura. Todos los métodos propuestos en esta tesis han sido evaluados en un marco experimental adecuado, se utilizaron numerosos conjuntos de datos y se compararon los rendimientos de los algoritmos frente a otros métodos del estado del arte. Los resultados obtenidos, los cuales fueron verificados mediante la aplicación de test estadísticos no paramétricos, demuestran la efectividad de los métodos propuestos y de esta manera comprueban las hipótesis planteadas en esta tesis.In the last decade, multi-label learning has become an important area of research due to the large number of real-world problems that contain multi-label data. This doctoral thesis is focused on the multi-label learning paradigm. Two problems were studied, rstly, improving the performance of the algorithms on complex multi-label data, and secondly, improving the performance through unlabeled data. The rst problem was solved by means of feature estimation methods. The e ectiveness of the feature estimation methods proposed was evaluated by improving the performance of multi-label lazy algorithms. The parametrization of the distance functions with a weight vector allowed to recover examples with relevant label sets for classi cation. It was also demonstrated the e ectiveness of the feature estimation methods in the feature selection task. On the other hand, a lazy algorithm based on a data gravitation model was proposed. This lazy algorithm has a good trade-o between e ectiveness and e ciency in the resolution of the multi-label lazy learning. The second problem was solved by means of active learning techniques. The active learning methods allowed to reduce the costs of the data labeling process and training an accurate model. Two active learning strategies were proposed. The rst strategy e ectively solves the multi-label active learning problem. In this strategy, two measures that represent the utility of an unlabeled example were de ned and combined. On the other hand, the second active learning strategy proposed resolves the batch-mode active learning problem, where the aim is to select a batch of unlabeled examples that are informative and the information redundancy is minimal. The batch-mode active learning was formulated as a multi-objective problem, where three measures were optimized. The multi-objective problem was solved through an evolutionary algorithm. This thesis also derived in the creation of a computational framework to develop any active learning method and to favor the experimentation process in the active learning area. On the other hand, a methodology based on non-parametric tests that allows a more adequate evaluation of active learning performance was proposed. All methods proposed were evaluated by means of extensive and adequate experimental studies. Several multi-label datasets from di erent domains were used, and the methods were compared to the most signi cant state-of-the-art algorithms. The results were validated using non-parametric statistical tests. The evidence showed the e ectiveness of the methods proposed, proving the hypotheses formulated at the beginning of this thesis

Dynamic Coefficients of Finite Length Journal Bearing. Evaluation Using a Regular Perturbation Method

A set of simple expressions is deduced for static and dynamic parameters associated to hydrodynamic journal bearings (JB). The behavior of this system is governed by two dimensionless numbers, the aspect ratio, L/D, and the eccentricity ratio, η. In a previous work, we presented a regular perturbation method that extended the Ocvirk solution and successfully described isothermal JBs up to L/D and η of ∼1/2. Presently, we extend that methodology, modified using a smaller perturbation parameter, to obtain analytical expressions of the dynamic coefficients, as well as static variables like friction factor, load carrying capacity, lubricant flow rate and phase angle. The deduced expressions successfully describe the static and dynamic behavior of JBs up to L/D and η of ∼3/4.Fil: Merelli, Claudio Ernesto. Universidad Nacional de la Patagonia "San Juan Bosco"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Química; ArgentinaFil: Barilá, Daniel Oscar. Universidad Nacional de la Patagonia "San Juan Bosco"; ArgentinaFil: Vignolo, Gustavo Gabriel. Universidad Nacional de la Patagonia "San Juan Bosco"; ArgentinaFil: Quinzani, Lidia Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

Global existence and exponential decay for hyperbolic dissipative relativistic fluid theories

We consider dissipative relativistic fluid theories on a fixed flat, compact, globally hyperbolic, Lorentzian manifold. We prove that for all initial data in a small enough neighborhood of the equilibrium states (in an appropriate Sobolev norm), the solutions evolve smoothly in time forever and decay exponentially to some, in general undetermined, equilibrium state. To prove this, three conditions are imposed on these theories. The first condition requires the system of equations to be symmetric hyperbolic, a fundamental requisite to have a well posed and physically consistent initial value formulation. The second condition is a generic consequence of the entropy law, and is imposed on the non principal part of the equations. The third condition is imposed on the principal part of the equations and it implies that the dissipation affects all the fields of the theory. With these requirements we prove that all the eigenvalues of the symbol associated to the system of equations of the fluid theory have strictly negative real parts, which in fact, is an alternative characterization for the theory to be totally dissipative. Once this result has been obtained, a straight forward application of a general stability theorem due to Kreiss, Ortiz, and Reula, implies the results above mentioned.Comment: 10 pages, Late