Bioinformatic characterization of the extracellular lipases from Kluyveromyces marxianus

Lipases are hydrolytic enzymes that break the ester bonds of triglycerides, generating free fatty acids and glycerol. Extracellular lipase activity has been reported for the nonconventional yeast Kluyveromyces marxianus, grown in olive oil as a substrate, and the presence of at least eight putative lipases has been detected in its genome. However, to date, there is no experimental evidence on the physiological role of the putative lipases nor their structural and catalytic properties. In this study, a bioinformatic analysis of the genes of the putative lipases from K. marxianus L-2029 was performed, particularly identifying and characterizing the extracellular expected enzymes, due to their biotechnological relevance. The amino acid sequence of 10 putative lipases, obtained by in silico translation, ranged between 389 and 773 amino acids. Two of the analysed putative proteins showed a signal peptide, 25 and 33 amino acids long for KmYJR107Wp and KmLIP3p, and a molecular weight of 44.53 and 58.23 kDa, respectively. The amino acid alignment of KmLIP3p and KmYJR107Wp with the crystallized lipases from a patatin and the YlLip2 lipase from Yarrowia lipolytica, respectively, revealed the presence of the hydrolase characteristic motifs. From the 3D models of putative extracellular K. marxianus L-2029 lipases, the conserved pentapeptide of each was determined, being GTSMG for KmLIP3p and GHSLG for KmYJR107Wp; besides, the genes of these two enzymes (LIP3 and YJR107W) are apparently regulated by oleate response elements. The phylogenetic analysis of all K. marxianus lipases revealed evolutionary affinities with lipases from abH15.03, abH23.01, and abH23.02 families.     

Tribological behaviour of a 3Y-TZP/Ta ceramic-metal biocomposite against ultrahigh molecular weight polyethylene (UHMWPE)

This study aims to evaluate the tribological behaviour of 3Y-TZP/Ta (20 vol%) ceramic-metal composites and 3Y-TZP monolithic ceramic prepared by spark plasma sintering (SPS) against ultrahigh molecular weight polyethylene (UHMWPE). According to the results of pin (UHMWPE)-on-flat wear test under dry conditions, the UHMWPE – 3Y-TZP/Ta system exhibited lower volume loss and friction coefficient than the UHMWPE – monolithic ceramic combination due to the presence of an autolubricating layer that provides sufficient lubrication for reducing the friction. Owing to the lubrication of the liquid media, under wet conditions obtained using simulated body fluid (SBF), similar behaviour is observed in both cases. Additionally, the ceramic and biocomposite materials were subjected to a low temperature degradation (LTD) process (often referred to as “ageing”) to evaluate the changes in the tribological behaviour after this treatment. In this particular case, the wear properties of the UHMWPE-biocomposite system were found to be less influenced by ageing in contrast to the case of the UHMWPE-zirconia monolithic material. In addition to their exceptional mechanical performance, 3Y-TZP/Ta composites also showed high resistance to low temperature degradation and good tribological properties, making them promising candidates for biomedical applications, especially for orthopaedic implants.     

Bibliometric analysis of the evolution of biochar research trends and scientific production

Clean Technologies and Environmental Policy - Biochar has caught great attention over the last decade, yielding a large number of publications in a broad range of disciplines. This scientometric...     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis.

This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision-based algorithm is used to extract relevant three-dimensional (3-D) features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3-D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3-D information previously extracted, an accurate distance computation is performed.     

Velocity selective filters recursively implemented in the spatiotemporal domain.

Energy-based methods for motion estimation in image sequences process the input data either in the spatiotemporal or in the frequency domain. In both cases, the algorithms already described in the literature often require a huge number of elementary operations. In this paper, we describe a class of velocity selective filters which yield an accurate detection of the edges moving in the sequence. We first present a filtering scheme based on a convolution operation computed on a finite size neighborhood and describe its properties in the spatiotemporal and frequency domains. Then, we show that filters with similar properties can be implemented recursively, i.e., as convolutions computed on infinite-size neighborhoods. As an example, we finally show the filters' responses in the case of two superimposed translational motions.     

L’optimisation des réseaux cellulaires assistée par ordinateur: le logiciel RNO (Radio Network Optimisation)

Quality of service has become today a major concern for operators of mobile communication networks. The massive development of networks and strong competition between operators has lead to the necessary and daily follow-up of network quality of service, a key factor for its subscriber’s fidelity. This article aims at presenting the optimization methodology and proposes its illustration with a case of RNO (Radio Network Optimisation) software usage, one of the Alcatel optimization toolchain component. After a short presentation of cellular network, the optimization basic principles are described. RNO software and its main functionnalities are then detailed before a last part dedicated to a real case of optimization done with RNO software.