Biochemistry and mode of action of the Bacillus sphaericus toxins

Bacillus sphaericus produces at least two toxins which are highly toxic to mosquito larvae. The binary toxin, which is comprised of proteins of 51.4 and 41.9 kDa, is present in all highly insecticidal strains. The 100 kDa SSII-1 toxin is present in most highly insecticidal as well as the weakly insecticidal strains. The current status of studies on biochemistry and mode of action of these toxins is reviewed.

Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

Analyse des cannabinoïdes par spectrométrie de masse en mode tandem = Analysis of cannabinoids by tandem mass spectrometry

Depuis quelques années, la spectrométrie de masse en tandem (MS/MS) ne cesse de gagner du terrain comme méthode d'analyse en toxicologie forensique, notamment pour le dosage des cannabinoïdes. Couplée à la chromatographie liquide (LC) ou gazeuse (GC), elle permet l'identification fiable et le dosage rapide du THC, de son précurseur acide, et de ses principaux métabolites, y compris les glucuronides. Au cours de ces dix dernières années, un nombre significatif de publications sont parues sur ce sujet. L'objectif de cet article est de passer en revue les analyses par spectrométrie de masse en tandem des cannabinoïdes dans diverses matrices biologiques. In recent years, tandem mass spectrometry (MS/MS) is gaining ground as a reference method of analysis in clinical and forensic toxicology, especially for the determination of cannabinoids. Coupled to liquid chromatography (LC) or gas chromatography (GC), it allows the definitive identification and rapid determination of THC, its acid precursor, and its major metabolites, including the glucuronides. During the past decade, several methods of analysis of cannabinoids in different matrices have appeared on this subject. The aim of this paper is to review the analysis of cannabinoids by tandem mass spectrometry methods in various biological matrices

Mosquitocidal bacterial toxins: diversity, mode of action and resistance phenomena

Bacteria active against dipteran larvae (mosquitoes and black flies) include a wide variety of Bacillus thuringiensis and B. sphaericus strains, as well as isolates of Brevibacillus laterosporus and Clostridium bifermentans. All display different spectra and levels of activity correlated with the nature of the toxins, mainly produced during the sporulation process. This paper describes the structure and mode of action of the main mosquitocidal toxins, in relationship with their potential use in mosquito and/or black fly larvae control. Investigations with laboratory and field colonies of mosquitoes that have become highly resistant to the B. sphaericus Bin toxin have shown that several mechanisms of resistance are involved, some affecting the toxin/receptor binding step, others unknown.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Cinéma, machine à mondes : essai sur les films à univers multiples

Dans cet ouvrage, l'auteur propose une conceptualisation théorique de la coprésence en un même film de mondes multiples en abordant différents paramètres (hétérogénéité de la facture de l'image, pratiques du montage alterné, typologie des enchâssements, expansion sérielle, etc.) sur la base d'un corpus de films de fiction récents qui appartiennent pour la plupart au genre de la science-fiction (Matrix, Dark City, Avalon, Resident Evil, Avatar,...). Issue de la filmologie, la notion de « diégèse » y est développée à la fois dans le potentiel d'autonomisation dont témoigne la conception mondaine qui semble dominer aujourd'hui à l'ère des jeux vidéo, dans ses liens avec le récit et dans une perspective intermédiale. Les films discutés ont la particularité de mettre en scène des machines permettant aux personnages de passer d'un monde à l'autre : les modes de figuration de ces technologies sont investigués en lien avec les imaginaires du dispositif cinématographique et les potentialité du montage. La comparaison entre les films (Tron et son récent sequel, Totall Recall et son remake) et entre des oeuvres filmiques et littéraires (en particulier les nouvelles de Philip K. Dick et Simlacron 3 de Galouye) constitue un outil d'analyse permettant de saisir la contemporanéité de cette problématique, envisagée sur le plan esthétique dans le contexte de l'imagerie numérique.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Differentiation of blue ballpoint pen by positive and negative mode LDI-MS

Usually, the differentiation of inks on questioned documents is carried out by optical methods and thin layer chromatography (TLC). Therefore, spectrometric methods were also proposed in forensic literature for the analysis of dyes. Between these techniques, laser desorption/ionization mass spectrometry (LDI-MS) has demonstrated a great versatility thanks to its sensitivity to blue ballpoint ink dyes and minimal sample destruction. Previous researches concentrated mostly on the LDI-MS positive mode and have shown that this analytical tool offers higher discrimination power than high performance TLC (HPTLC) for the differentiation of blue ballpoint inks. Although LDI-MS negative mode has already been applied in numerous forensic domains like the studies of works of art, automotive paints or rollerball pens, its potential for the discrimination of ballpoint pens was never studied before. The aim of the present paper is therefore to evaluate its potential for the discrimination of blue ballpoint inks. After optimization of the method, ink entries from 33 blue ballpoint pens were analyzed directly on paper in both positive and negative modes by LDI-MS. Several cationic and anionic ink components were identified in inks; therefore, pens were classified and compared according to their formulations. Results show that additional information provided by anionic dyes and pigments significantly increases the discrimination power of positive mode. In fact, it was demonstrated that classifications obtained by the two modes were, to some extent, complementary (i.e., inks with specific cationic dyes not necessarily contained the same anionic components).