Optimización de la producción de biomasa usando glicerol crudo, de una cepa mutante de Yarrowia lipolytica con actividad incrementada de lipasa

218-225The yeast Yarrowia lipolytica accumulates oils and is able to produce extracellular lipases when growing in different carbon sources including glycerol, the principal by-product of the biodiesel industry. In this study, biomass production of a novel mutant strain of Y. lipolytica was statistically optimized by Response Surface Methodology in media containing biodiesel-derived glycerol as main carbon source. This strain exhibited distinctive morphological and fatty acid profile characteristics, and showed an increased extracellular lipase activity. An organic source of nitrogen and the addition of 1.0 g/l olive oil were necessary for significant lipase production. Plackett-Burman and Central Composite Statistical Designs were employed for screening and optimization of fermentation in shaken flasks cultures, and the maximum values obtained were 16.1 g/l for biomass and 12.2 Units/ml for lipase, respectively. Optimized batch bioprocess was thereafter scaled in aerated bioreactors and the values reached for lipase specific activity after 95 percent of the glycerol had been consumed, were three-fold higher than those obtained in shaken flasks cultures. A sustainable bioprocess to obtain biomass and extracellular lipase activity was attained by maximizing the use of the by-products of biodiesel industry

Noise-induced perturbations of dispersion-managed solitons

We study noise-induced perturbations of dispersion-managed solitons by developing soliton perturbation theory for the dispersion-managed nonlinear Schroedinger (DMNLS) equation, which governs the long-term behavior of optical fiber transmission systems and certain kinds of femtosecond lasers. We show that the eigenmodes and generalized eigenmodes of the linearized DMNLS equation around traveling-wave solutions can be generated from the invariances of the DMNLS equations, we quantify the perturbation-induced parameter changes of the solution in terms of the eigenmodes and the adjoint eigenmodes, and we obtain evolution equations for the solution parameters. We then apply these results to guide importance-sampled Monte-Carlo simulations and reconstruct the probability density functions of the solution parameters under the effect of noise.Comment: 12 pages, 6 figure

Logical Linked Data Compression

Linked data has experienced accelerated growth in recent years. With the continuing proliferation of structured data, demand for RDF compression is becoming increasingly important. In this study, we introduce a novel lossless compression technique for RDF datasets, called Rule Based Compression (RB Compression) that compresses datasets by generating a set of new logical rules from the dataset and removing triples that can be inferred from these rules. Unlike other compression techniques, our approach not only takes advantage of syntactic verbosity and data redundancy but also utilizes semantic associations present in the RDF graph. Depending on the nature of the dataset, our system is able to prune more than 50% of the original triples without affecting data integrity

The muscle spindle as a feedback element in muscle control

The muscle spindle, the feedback element in the myotatic (stretch) reflex, is a major contributor to muscular control. Therefore, an accurate description of behavior of the muscle spindle during active contraction of the muscle, as well as during passive stretch, is essential to the understanding of muscle control. Animal experiments were performed in order to obtain the data necessary to model the muscle spindle. Spectral density functions were used to identify a linear approximation of the two types of nerve endings from the spindle. A model reference adaptive control system was used on a hybrid computer to optimize the anatomically defined lumped parameter estimate of the spindle. The derived nonlinear model accurately predicts the behavior of the muscle spindle both during active discharge and during its silent period. This model is used to determine the mechanism employed to control muscle movement

The dispersion-managed Ginzburg-Landau equation and its application to femtosecond lasers

The complex Ginzburg-Landau equation has been used extensively to describe various non-equilibrium phenomena. In the context of lasers, it models the dynamics of a pulse by averaging over the effects that take place inside the cavity. Ti:sapphire femtosecond lasers, however, produce pulses that undergo significant changes in different parts of the cavity during each round-trip. The dynamics of such pulses is therefore not adequately described by an average model that does not take such changes into account. The purpose of this work is severalfold. First we introduce the dispersion-managed Ginzburg-Landau equation (DMGLE) as an average model that describes the long-term dynamics of systems characterized by rapid variations of dispersion, nonlinearity and gain in a general setting, and we study the properties of the equation. We then explain how in particular the DMGLE arises for Ti:sapphire femtosecond lasers and we characterize its solutions. In particular, we show that, for moderate values of the gain/loss parameters, the solutions of the DMGLE are well approximated by those of the dispersion-managed nonlinear Schrodinger equation (DMNLSE), and the main effect of gain and loss dynamics is simply to select one among the one-parameter family of solutions of the DMNLSE.Comment: 22 pages, 4 figures, to appear in Nonlinearit

Scale-Free model for governing universe dynamics

We investigate the effects of scale-free model on cosmology, providing, in this way, a statistical background in the framework of general relativity. In order to discuss properties and time evolution of some relevant universe dynamical parameters (cosmographic parameters), such as $H(t)$ (Hubble parameter), $q(t)$ (deceleration parameter), $j(t)$ (jerk parameter) and $s(t)$ (snap parameter), which are well re-defined in the framework of scale-free model, we analyze a comparison between WMAP data. Hence the basic purpose of the work is to consider this statistical interpretation of mass distribution of universe, in order to have a mass density $\rho$ dynamics, not inferred from Friedmann equations, via scale factor $a(t)$. This model, indeed, has been used also to explain a possible origin and a viable explanation of cosmological constant, which assumes a statistical interpretation without the presence of extended theories of gravity; hence the problem of dark energy could be revisited in the context of a classical probability distribution of mass, which is, in particular, for the scale-free model, $P(k)\sim k^{-\gamma}$, with $2<\gamma<3$. The $\Lambda$CDM model becomes, with these considerations, a consequence of the particular statistics together with the use of general relativity.Comment: 7 pages, 4 figure

Universal OWL Axiom Enrichment for Large Knowledge Bases

Abstract. The Semantic Web has seen a rise in the availability and usage of knowledge bases over the past years, in particular in the Linked Open Data initiative. Despite this growth, there is still a lack of knowl-edge bases that consist of high quality schema information and instance data adhering to this schema. Several knowledge bases only consist of schema information, while others are, to a large extent, a mere collec-tion of facts without a clear structure. The combination of rich schema and instance data would allow powerful reasoning, consistency check-ing, and improved querying possibilities as well as provide more generic ways to interact with the underlying data. In this article, we present a light-weight method to enrich knowledge bases accessible via SPARQL endpoints with almost all types of OWL 2 axioms. This allows to semi-automatically create schemata, which we evaluate and discuss using DB-pedia.