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...     

Kinetic,thermodynamic parameters and in vitro digestion of tannase from Aspergillus tamarii URM 7115

Tannase is an enzyme used in various industries and produced by a large number of microorganisms. The aim of this study was to evaluate tannase production to determine the biochemical, kinetic, and thermodynamic properties and to simulate tannase in vitro digestion. The tannase-producing fungal strain was isolated from “jamun” leaves and identified as Aspergillus tamarii. Temperature at 26°C for 67?h was the best combination for maximum tannase activity (6.35-fold; initial activity in Plackett–Burman design—15.53?U/mL and average final activity in Doehlert design—98.68?U/mL). The crude extract of tannase was optimally active at 40°C, pH 5.5 and 6.5. Moreover, tannase was stimulated by Na⁺, Ca²⁺, Mg²⁺, and Mn²⁺. The half-life at 40°C lasted 247.55?min. The free energy of Gibbs, enthalpy, and entropy, at 40°C, was 81.47, 16.85, and ?0.21?kJ/mol?·?K, respectively. After total digestion, 123.95% of the original activity was retained. Results suggested that tannase from A. tamarii URM 7115 is an enzyme of interest for industrial applications, such as gallic acid production, additive for feed industry, and for beverage manufacturing, due to its catalytic and thermodynamic properties.     

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...     

Java multimedia telecollaboration

Using Java-based tools in multimedia collaborative environments accessed over the Internet can increase an application's client base. Most operating systems support Java, and its "compile once-run everywhere" architecture is easy to maintain and update. The Java-based tools presented here let users share Internet resources, including resources originally designed for single use.     

A New Hand-Held Microsystem Architecture for Biological Analysis

This paper presents a hand-held microsystem based on new fully integrated magnetoresistive biochips for biomolecular recognition (DNA hybridization, antibody antigen interaction, etc.). Magnetoresistive chip surfaces are chemically treated, enabling the immobilization of probe biomolecules such as DNA or antibodies. Fluid handling is also integrated in the biochip. The proposed microsystem not only integrates the biochip, which is an array of 16times16 magnetoresistive sensors, but it also provides all the electronic circuitry for addressing and reading out each transducer. The proposed architecture and circuits were specifically designed for achieving a compact, programmable and portable microsystem. The microsystem also integrates a hand-held analyzer connected through a wireless channel. A prototype of the system was already developed and detection of magnetic nanoparticles was obtained. This indicates that the system may be used for magnetic label based bioassays     

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.