Sangaletti-Gerhard N.,University of Sao Paulo |
Cea M.,University of the Frontier |
Risco V.,University of the Frontier |
Navia R.,University of the Frontier |
Navia R.,Center for Biotechnology and Bioengineering
Bioresource Technology | Year: 2015
This study proposes to select the most appropriate sewage sludge (greasy, primary and secondary) for in situ transesterification and to compare the technical, economic and energetic performance of an enzymatic catalyst (Novozym®435) with sulfuric acid. Greasy sludge was selected as feedstock for biodiesel production due to its high lipid content (44.4%) and low unsaponifiable matter. Maximum methyl esters yield (61%) was reached when processing the wet sludge using sulfuric acid as catalyst and n-hexane, followed by dried-greasy sludge catalyzed by Novozym®435 (57% methyl esters). Considering the economic point of view, the process using acid catalyst was more favorable compared to Novozym®435 catalyst due to the high cost of lipase. In general, greasy sludge (wet or dried) showed high potential to produce biodiesel. However, further technical adjustments are needed to make biodiesel production by in situ transesterification using acid and enzymatic catalyst feasible. © 2014 Elsevier Ltd.
Contador C.A.,Center for Biotechnology and Bioengineering |
Contador C.A.,University of Chile |
Shene C.,Center for Biotechnology and Bioengineering |
Shene C.,University of the Frontier |
And 9 more authors.
Metabolic Engineering Communications | Year: 2015
Macroalgae have high potential to be an efficient, and sustainable feedstock for the production of biofuels and other more valuable chemicals. Attempts have been made to enable the co-fermentation of alginate and mannitol by Saccharomyces cerevisiae to unlock the full potential of this marine biomass. However, the efficient use of the sugars derived from macroalgae depends on the equilibrium of cofactors derived from the alginate and mannitol catabolic pathways. There are a number of strong metabolic limitations that have to be tackled before this bioconversion can be carried out efficiently by engineered yeast cells. An analysis of the redox balance during ethanol fermentation from alginate and mannitol by Saccharomyces cerevisiae using metabolic engineering tools was carried out. To represent the strain designed for conversion of macroalgae carbohydrates to ethanol, a context-specific model was derived from the available yeast genome-scale metabolic reconstructions. Flux balance analysis and dynamic simulations were used to determine the flux distributions. The model indicates that ethanol production is determined by the activity of 4-deoxy-l-erythro-5-hexoseulose uronate (DEHU) reductase (DehR) and its preferences for NADH or NADPH which influences strongly the flow of cellular resources. Different scenarios were explored to determine the equilibrium between NAD(H) and NADP(H) that will lead to increased ethanol yields on mannitol and DEHU under anaerobic conditions. When rates of mannitol dehydrogenase and DehRNADH tend to be close to a ratio in the range 1-1.6, high growth rates and ethanol yields were predicted. The analysis shows a number of metabolic limitations that are not easily identified through experimental procedures such as quantifying the impact of the cofactor preference by DEHU reductase in the system, the low flux into the alginate catabolic pathway, and a detailed analysis of the redox balance. These results show that production of ethanol and other chemicals can be optimized if a redox balance is achieved. A possible methodology to achieve this balance is presented. This paper shows how metabolic engineering tools are essential to comprehend and overcome this limitation. © 2015 Published by Elsevier B.V.
Rojas O.,University of Santiago de Chile |
Rojas O.,Center for Biotechnology and Bioengineering |
Gil-Costa V.,University of Santiago de Chile |
Gil-Costa V.,Center for Biotechnology and Bioengineering |
And 2 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016
Large scale Web search engines have to process thousands of queries per second and each query has to be solved within a fraction of a second. To achieve this goal, search engines rely on sophisticated services capable of processing large amounts of data. One of these services is the search service (or index service) which is in charge of computing the top-k document results for user queries. Predicting in advance the response time of queries has practical applications in efficient administration of hardware resources assigned to query processing. In this paper, we propose and evaluate a query running time prediction algorithm that is based on a discrete Fourier transform which models the index as a collection of signals to obtain patterns. Results show that our approach performs at least as effectively as well-known prediction algorithms in the literature, while significantly improving computational efficiency. © Springer International Publishing Switzerland 2016.