Etude par capteur optique du dépôt formé lors de la filtration d'une suspension de bentonite sur fibre creuse

Lors de la filtration sur fibres creuses de suspensions de bentonite, il a été mis en évidence que le facteur limitant est la formation d'un dépôt à la surface de la fibre.Parlant de ces considérations, un dispositif optique a été mis au point pour suivre l'évolution spatio-temporelle du dépôt en cours de filtration sur fibre creuse à peau externe.Ainsi, il a pu être mis en évidence que l'influence de la vitesse d'écoulement n'est sensible qu'après un certain temps de filtration ou un certain volume filtré.Dans le domaine testé des faibles vitesses d'écoulement, il existe une période initiale où la loi de filtration sur gâteau est applicable.Dans le cas de fibres creuses à peau externe, l'optimum technique (productivité maximale) ou économique (coût minimal du m3 traité) serait donc plus à rechercher dans une optimisation de la séquence filtration-lavage que dans une augmentation de la vitesse d'écoulement.L'efficacité du réentraînement du dépôt lors du lavage peut être suivie grâce à l'équipement et au capteur développés.Use of membranes (MF or UF) for water treatment is now developed at an industrial scale. This approach is considered as a good solution to deal with the periodic strong increases in suspended solids contents which occur in karstic aquifers.Under these conditions, the main contribution to the growth of hydraulic resistance is related to the formation of a deposit on the membrane surface.Thus, an experimental study was performed at the laboratory scale in order to perform on line characterization of deposit formation during the filtration of a bentonite suspension through a hollow fiber.The filtration module is transparent and contains only one hollow fiber with its external skin.An optical device formerly developed was used as a sensor : a horizontal laser beam is focussed at the surface of the hollow fiber which is held perpendicular to the beam and can be moved step by step in the micrometric range.Experiments were performed with a bentonite suspension (concentration 0.375 kg/m3) and under different operating conditions :- dead end filtration and crossflow filtration with velocities up to 0,30 m/s in the annular space (which means Re ≈ 2000, velocity gradient ≈ 1000 S-1, shear stress ≈ 1 Pa) ;-transmembrane pressure between 85 and 185 Kpa.One of the main conclusions of this study is that influence of the velocity appears only after an initial period during which the growth of the deposit and the filtrate flowrate variation with time are in agreement with the equations of dead end filtration at constant pressure.Thus a combination of dead end filtration and periodic backwash for removing the deposit might be the best solution for getting the highest productivity with minimal energy consumption.These optimal conditions may be simulated using the equations of dead end filtration at constant pressure and making the assumption that the backwashing is fully efficicent.The experimental study of backwashing, using the optical sensor for measuring the diameter of the fiber after each backwashing, proves that this assumption is correct and that it is possible to get a steady mean filtrate flux by periodic backwashing.From the theoretical study, the optimal duration of the filtration period is rather short (about 10 minutes) but the decline after the maximum is very malt, which means that the fiitration period may be longer without significative variation of the productivity.Thus the method presented here is able, if applied to actual raw water, to give technical and economical elements of comparison between dead end filtration with periodic backwashing and crossflow filtration

Implicit reconstruction by zooming

This paper presents a new method to infer 3D information using a static camera equipped with a zoom-lens. The modelling algorithm does not required any explicit calibration model and the computations involved are straightforward. This approach uses several images of accurate regular grids placed on a micrometric table, as calibration process . The basic idea is to compute a local transformation that allows to establish a relationship between a distorted grid detected on the CCD matrix and the real one located in front of the camera . This relationship takes automatically into account all distortion phenomena and allows to obtain reconstruction results much more accurate than previous works in the same field . A complete experiment on real data is provided and shows that it is possible to compute 3D information from a zooming image set even if data are close to the optical axis .Cet article présente une nouvelle méthode permettant d'inférer des informations tridimensionnelles à l'aide d'une caméra statique munie d'un zoom. L'algorithme de modélisation ne nécessite aucun modèle explicite de calibrage et met en oeuvre plusieurs images de grilles régulières et précises formant un espace métrique particulier. Une transformation locale permet d'établir une relation entre l'image distordue d'une grille détectée sur la matrice CCD et une grille réelle située devant la caméra. Cette relation prend automatiquement en compte les phénomènes de distorsion optique et permet d'obtenir des résultats de reconstruction bien meilleurs que ceux obtenus jusqu'à présent en reconstruction axiale par zoom. De plus, la méthode présentée permet de calibrer l'objectif sur une gamme importante de distances focales sans changer d'objet de calibrage. Une expérimentation complète sur des données réelles est présentée et montre qu'il est possible de reconstruire des objets 3D à partir d'une séquence d'images de zoom même si ces données sont proches de l'axe optique

Guía de Práctica Clínica para el diagnóstico de compromiso orgánico en amiloidosis: parte 3/3 año 2020

Métodos: Se generó un listado de preguntas con el formato PICO centradas en la especificidad y sensibilidad de las pruebas diagnósticas en amiloidosis. Se realizó la búsqueda en PubMed durante julio-agosto del 2019, en inglés y español. Los niveles de evidencia y los grados de recomendación se basan en el sistema GRADE (http://www.gradeworkinggroup.org/index.htm). Las recomendaciones se graduaron según su dirección (a favor o en contra) y según fuerza (fuertes y débiles). Las recomendaciones finales fueron evaluadas con la herramienta GLIA para barreras y facilitadores en la implementación de éstas. Interpretación de recomendaciones: Las recomendaciones fuertes indican alta confianza, ya sea a favor o en contra, de una intervención. En esta guía se utiliza el lenguaje “se recomienda” cuando se define una recomendación fuerte. Las recomendaciones débiles indican que los resultados para una intervención, favorable o desfavorable, son dudosos. En este caso, se utiliza el lenguaje “se sugiere”, cuando se define una recomendación débil. Cómo utilizar estas pautas: Las recomendaciones deben ser interpretadas en el contexto de la atención especializada, con estudios diagnósticos validados y realizados por médicos entrenados. Se asume que el médico tratante tiene alto nivel de sospecha de amiloidosis. No asume condiciones coexistentes que modifican el curso de la enfermedad. Asume que los estudios diagnósticos son realizados por médicos entrenados con métodos validados y estandarizados. Esta guía es relevante para los profesionales de la salud y los involucrados en las políticas sanitarias, para ayudar a asegurar que existan los acuerdos necesarios para brindar la atención adecuada

Pediatric Hospitalizations Associated with 2009 Pandemic Influenza A (H1N1) in Argentina

Fil: Libster, Romina. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Bugna, Jimena. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Coviello, Silvina. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Hijano, Diego R. Hospital De Niños Sor María Ludovica, La Plata; Argentina.Fil: Dunaiewsky, Mariana. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Reynoso, Natalia. Hospital Municipal Materno Infantil de San Isidro; Argentina.Fil: Cavalieri, Maria L. Hospital Eva Perón, Benito Juárez, Buenos Aires; ArgentinaFil: Guglielmo, Maria C. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Areso, M. Soledad. Hospital Eva Perón, Benito Juárez, Buenos Aires; ArgentinaFil: Gilligan, Tomas. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Santucho, Fernanda. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Cabral, Graciela. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Gregorio, Gabriela L. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Moreno, Rina. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Lutz, Maria I. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Panigasi, Alicia L. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Saligari, Liliana. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Caballero, Mauricio T. Hospital De Niños Sor María Ludovica, La Plata; Argentina.Fil: Egües Almeida, Rodrigo M. Hospital De Niños Sor María Ludovica, La Plata; Argentina.Fil: Gutierrez Meyer, Maria E. Hospital De Niños Sor María Ludovica, La Plata; Argentina.Fil: Neder, Maria D. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Davenport, Maria C. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Del Valle, Maria P. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Santidrian, Valeria S. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Mosca, Guillermina. Ministerio de Ciencia, Técnica e Innovación. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Alvarez, Liliana. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Landa, Patricia. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Pota, Ana. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Boloñati, Norma. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Dalamon, Ricardo. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Sanchez Mercol, Victoria I. Hospital Eva Perón, Benito Juárez, Buenos Aires; Argentina.Fil: Espinoza, Marco. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Peuchot, Juan Carlos. Hospital Eva Perón, Benito Juárez, Buenos Aires; Argentina.Fil: Karolinski, Ariel. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Bruno, Miriam. Hospital General de Agudos Carlos G. Durand, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Borsa, Ana. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Ferrero, Fernando. Hospital General de Niños Pedro de Elizalde, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Bonina, Angel. Hospital De Niños Sor María Ludovica, La Plata; Argentina.Fil: Ramonet, Margarita. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Albano, Lidia C. Hospital Nacional Profesor Alejandro Posadas, El Palomar, Buenos Aires; Argentina.Fil: Luedicke, Nora. Ministerio de Ciencia, Técnica e Innovación. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Alterman, Elias. Fundación Infant, Ciudad Autónoma de Buenos Aires; Argentina.Fil: Savy, Vilma L. ANLIS Dr.C.G.Malbrán. Instituto de Enfermedades Infecciosas; Argentina.Fil: Baumeister, Elsa. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas. Departamento de Virología. Servicio de Virosis Respiratoria; Argentina.Fil: Chappell, James D. Vanderbilt University. Pathology, Nashville, Tennessee; Estados Unidos.Fil: Edwards, Kathryn M. Vanderbilt University. Departments of Pediatrics, Nashville, Tennessee; Estados Unidos.Fil: Melendi, Guillermina A. Vanderbilt University. Departments of Pediatrics, Nashville, Tennessee; Estados Unidos.Fil: Polack, Fernando P. Vanderbilt University. Departments of Pediatrics, Nashville, Tennessee; Estados Unidos.Background: While the Northern Hemisphere experiences the effects of the 2009 pandemic influenza A (H1N1) virus, data from the recent influenza season in the Southern Hemisphere can provide important information on the burden of disease in children. Methods: We conducted a retrospective case series involving children with acute infection of the lower respiratory tract or fever in whom 2009 H1N1 influenza was diagnosed on reverse-transcriptase polymerase-chain-reaction assay and who were admitted to one of six pediatric hospitals serving a catchment area of 1.2 million children. We compared rates of admission and death with those among age-matched children who had been infected with seasonal influenza strains in previous years. Results: Between May and July 2009, a total of 251 children were hospitalized with 2009 H1N1 influenza. Rates of hospitalization were double those for seasonal influenza in 2008. Of the children who were hospitalized, 47 (19%) were admitted to an intensive care unit, 42 (17%) required mechanical ventilation, and 13 (5%) died. The overall rate of death was 1.1 per 100,000 children, as compared with 0.1 per 100,000 children for seasonal influenza in 2007. (No pediatric deaths associated with seasonal influenza were reported in 2008.) Most deaths were caused by refractory hypoxemia in infants under 1 year of age (death rate, 7.6 per 100,000). Conclusions: Pandemic 2009 H1N1 influenza was associated with pediatric death rates that were 10 times the rates for seasonal influenza in previous years

Modélisation d'un bioréacteur à membrane vraie grandeur avec le modèle boues activées ASM1 : défis et solutions

International audienceA full-scale membrane bioreactor (1600 m3.d-1) was monitored for modelling purposes during the summer of 2006. A complete calibration of the ASM1 model is presented, in which the key points were the wastewater characterisation, the oxygen transfer and the biomass kinetics. Total BOD tests were not able to correctly estimate the biodegradable fraction of the wastewater. Therefore the wastewater fractionation was identified by adjusting the simulated sludge production rate to the measured value. MLVSS and MLSS were accurately predicted during both calibration and validation periods (20 and 30 days). Because the membranes were immerged in the aeration tank, the coarse bubble and fine bubble diffusion systems coexisted in the same tank. This allowed five different aeration combinations, depending whether the 2 systems were operating separately or simultaneously, and at low speed or high speed. The aeration control maintained low DO concentrations, allowing simultaneous nitrification and denitrification. This made it difficult to calibrate the oxygen transfer. The nitrogen removal kinetics were determined using maximum nitrification rate tests and an 8-hour intensive sampling campaign. Despite the challenges encountered, a calibrated set of parameters was identified for ASM1 that gave very satisfactory results for the calibration period. Matching simulated and measured data became more difficult during the validation period, mainly because the dominant aeration configuration had changed. However, the merit of this study is to be the first effort to simulate a full-scale MBR plant

Extraction and purification of high added value compounds from by-products of the winemaking chain using alternative/nonconventional processes/technologies

Grape byproducts are today considered as a cheap source of valuable compounds since existent technologies allow the recovery of target compounds and their recycling. The goal of the current article is to explore the different recovery stages used by both conventional and alternative techniques and processes. Alternative pre-treatments techniques reviewed are: ultrasounds, pulsed electric fields and high voltage discharges. In addition, nonconventional solvent extraction under high pressure, specifically, supercritical fluid extraction and subcritical water extraction are discussed. Finally alternative purification technologies, for example membrane processing were also examined. The intent is to describe the mechanisms involved by these alternative technologies and to summarize the work done on the improvement of the extraction process of phenolic compounds from winery by-products. With a focus on the developmental stage of each technology, highlighting the research need and challenges to be overcome for an industrial implementation of these unitary operations in the overall extraction process. A critical comparison of conventional and alternative techniques will be reviewed for ethe pre-treatment of raw material, the diffusion of polyphenols and the purification of these high added value compounds. This review intends to give the reader some key answers (costs, advantages, drawbacks) to help in the choice of alternative technologies for extraction purposes

Comparison of the effect of pulsed electric field or high voltage electrical discharge for the control of sweet white must fermentation process with the conventional addition of sulfur dioxide

International audienceThe present work discusses the efficiency of pulsed electrical treatments for the inactivation of yeasts. The application of pulsed electric fields (PEFs) and high voltage electrical discharges (HVEDs) as alternatives to sulfites, which are used as anti-microbial to stop the fermentation of sweet white wine, was investigated. The influence of sulfite concentration (from 0 mg.L-1 to 500 mg.L-1), PEF (from 4 kV.cm(-1) to 20 kV.cm(-1); from 0.25 ms to 6 ms) and HVED (40 kV/cm; 1 ms or 4 ms) treatments on the inactivation of total yeasts and non-Saccharomyces yeasts was determined. The addition of SO2 (250 mg.L-1) resulted in 8 log total yeast reduction. The maximum yeast inactivation obtained with PEF and HVED was respectively 3 and 4 logs. The use of SO2, HVED and PEF allows decreasing the non-Saccharomyces yeast level by 7, 5 and 4 logs respectively. However, the wine browning was less pronounced for the samples treated by PEF in comparison with HVED and SO2 treatments. PEF seems to be the most suitable alternative technique to sulfite addition