Browsing by Author "Gelmi, Claudio A."

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    A probabilistic framework for microarray data analysis: Fundamental probability models and statistical inference
    (ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2010) Ogunnaike, Babatunde A.; Gelmi, Claudio A.; Edwards, Jeremy S.
    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. (C) 2010 Elsevier Ltd. All rights reserved.
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    An exploratory study of peat and sawdust as enhancers in the (bio)degradation of n-dodecane
    (2008) Saez-Navarrete, Cesar; Gelmi, Claudio A.; Reyes-Bozo, Lorenzo; Godoy-Faundez, Alex
    Current practice for dealing with oil spills involves the use of adsorbent materials to contain the pollution prior to bioremediation of the contaminated soil and adsorbent. This work presents a study of the effects of bioavailable carbon sources in the adsorbents peat and sawdust as organic nutrients for microorganisms specialized in degrading n-dodecane in soil and sawdust contaminated with hydrocarbon mixtures. An experimental bioremediation system was developed using n-dodecane, biomass adapted to n-dodecane, inorganic nutrients and the two adsorbents (sterilized). Bioreactors containing peat enhanced cell growth the most and also evolved more CO2. An advantage of peat is that its soluble carbon sources can sustain higher cell densities compared to sawdust, and this may prove decisive when cultivating endogenous microorganisms for the aerobic bioremediation of soils contaminated with hydrocarbons. However, at the end of the 68-day experiment slightly higher n-dodecane removal was identified in the system containing sawdust-n-dodecane (99.6%) than in that with peat-n-dodecane (98.5%), evidencing the higher hydrocarbon retention capacity of peat. Based on this study, the use of sawdust instead of peat is recommended when an adapted inoculum is available for aerobic bioremediation of organic contaminants, whereas the use of peat is advisable to boost cell densities in order to improve the probability of sustaining a viable biomass in unfavorable conditions.
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    Modeling temperature gradients in wine fermentation tanks
    (ELSEVIER SCI LTD, 2010) Zenteno, M. Isabel; Perez Correa, J. Ricardo; Gelmi, Claudio A.; Agosin, Eduardo
    Extreme temperatures are common in large wine fermentation tanks. If not controlled properly, they can lead to problematic fermentations. Thus, efficient cooling and automatic control systems must be designed. However, it is rather difficult to design and implement effective cooling and control systems without adequate models able to reproduce the complex dynamic behavior observed in large fermentors. Therefore, we developed a compartmental dynamic mass-and-energy-balance model able to simulate temperature and concentration gradients in large wine fermentation tanks. This paper presents the model, along with all its parameters. It discusses simulations of temperature, alcohol content, density, biomass, and sugar concentrations. Finally, it presents a sensitivity analysis of the must temperature dynamics. The model reproduced reasonably well the values of the observed variables, including the most critical one: must temperature (with an absolute mean error of 1.4 degrees C). After proper calibration, it can be used to design control strategies for cooling in large wine fermentation tanks. Our research efforts will be directed in designing such control strategies. (C) 2010 Elsevier Ltd. All rights reserved.
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    Simulation of a supercritical carbon dioxide extraction plant with three extraction vessels
    (PERGAMON-ELSEVIER SCIENCE LTD, 2011) Nunez, Gonzalo A.; Gelmi, Claudio A.; del Valle, Jose M.
    Although SuperCritical (SC) Fluid Extraction (SCFE) has been successfully applied commercially the last three decades, there is no systematic procedure or computational tool in the literature to scale-up and optimize it. This work proposes an algorithm to simulate dynamics in a multi-vessel (>= 3) high-pressure SCFE plant where extraction vessels operate in batches, and is thus forced to use simulated-countercurrent flow configuration to improve efficiency. The algorithm is applied to a three-vessel SCFE plant using a shrinking-core model to describe inner mass transfer in the substrate. As example, the extraction of oil from pre-pressed seeds using SC CO(2) at 313 K and 30 MPa is simulated. After three cycles the process reaches a pseudo-steady-state condition that simplifies the estimation of plant productivity. Use of a three-instead of two-vessel SCFE plant increases oil concentration in the stream exiting the plant and decreases CO(2) usage at the expense of increasing extraction time. (C) 2011 Published by Elsevier Ltd.