Enzyme activity and partial characterization of proteases obtained from Bromelia karatas fruit and compared with Bromelia pinguin proteases

Food Science and Biotechnology - The enzymatic activity and partial characterization of proteases from Bromelia karatas fruits were evaluated and compared with Bromelia pinguin proteases. The...     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Dielectric relaxation of vegetable-based polyurethane

Vegetable-based polyurethane (PU) was prepared in the thin film form by spin coating. This polymer is synthesised from castor oil, which can be extracted from the seeds of a native plant in Brazil called mamona. This polymer is biocompatible and is being used as material for artificial bone. The PU was characterised by dielectric spectroscopy in a wide range of frequency (10^–5 Hz to 10⁵ Hz) and by thermally stimulated discharge current (TSDC) measurements. The glass transition temperature (T _g = 39°C) was determined and using the initial rise method the activation energy was found to be 1.58 eV.     

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.     

Dealumination–aging pattern of REUSY zeolites contained in fluid cracking catalysts

The evolution of the properties of a REUSY zeolite contained in a fluid cracking catalyst was investigated under laboratory steam deactivation procedures and in age fractions of the corresponding equilibrium catalyst (Ecat). The aging pattern, defined by the evolution of the zeolite surface area (ZSA) related to the decrease of the unit cell size (UCS), was similar between lab-steamed zeolites and Ecat fractions. A sharp drop in ZSA occurred at ca. 2.430 nm UCS. A study done by FT-IR spectroscopy suggested that zeolite dealumination initially took place more extensively on the sodalite cages and double six-member rings (D6R) of the structure and that the final collapse of the zeolite framework occurred through destruction of the 12-member rings (12M). This can be explained by a crystal fracture and break down process and disassembling of the sodalite cages in the faujasite structure. NH₃ microcalorimetry showed that strong acid sites in faujasites are destroyed by steam aging, but this effect does not lead to a reduction in the cracking activity of the Ecat form. The microactivity test (MAT) showed that the specific activity declined sharply at 2.430 nm UCS. Differences in product selectivity were related to the extent of damage of the zeolite, extra-framework alumina and mesoporosity. While further aging canceled the effect attributed to extra-framework alumina differences attributed to mesoporosity increased.     

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.     

Josef Maria Bro?ek (1913-2004).

Presents an obituary and information about the life and accomplishments of Josef Maria Bro?ek. Born August 14, 1913, in the ancient town of Melnik, in central Bohemia, today the Czech Republic, Josef spent his childhood in Poland (Warsaw, 1913- 1915) and in Siberia (1915-1920). His education in Czechoslovakia culminated with a thesis on "Memory, Its Measurement and Structure" and a PhD awarded in June 1937. In the history of psychology, his lifetime project bore the title "Historiography of Psychology Around the World," and it covered about 20 geographical areas. Extensive attention was devoted to institutional and organizational developments as journals, academic settings, archives, museums, research groups, conferences, and institutes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

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.