Hydrodynamic induced deformation of and orientation of a microscopic elastic filament

We describe simulations of an elastic filament immersed in a fluid and subjected to a body force. The coupling between the fluid flow and the friction that the filament experiences induces bending and alignment perpendicular to the force. With increasing force there are four shape regimes, ranging from slight distortion to an unsteady tumbling motion. We also find marginally stable structures. The instability of these shapes and the alignment are explained by induced bending and nonlocal hydrodynamic interactions. These effects are experimentally relevant for stiff microfilaments.

Self-organized criticality and synchronization in a coupled map lattice model of integrate-and-fire oscillators

We introduce two coupled map lattice models with nonconservative interactions and a continuous nonlinear driving. Depending on both the degree of conservation and the convexity of the driving we find different behaviors, ranging from self-organized criticality, in the sense that the distribution of events (avalanches) obeys a power law, to a macroscopic synchronization of the population of oscillators, with avalanches of the size of the system.

The neonatal progeroid syndrome (Wiedemann-Rautenstrauch) and its relationship to Pelizaeus-Merzbacher's disease.

The neuropathology of a clinically well-documented case of the neonatal progeroid syndrome Wiedemann-Rautenstrauch is described. The most striking feature was a nearly complete absence of mature myelin in the brain. When immunohistochemistry for myelin basic protein was applied, some subcortical nerve fibres were accompanied by immature myelin sheaths. The neuropathology corresponds exactly to that of Pelizaeus-Merzbacher disease (Seitelberger type). Furthermore, this morphology, with the presence of myelin basic protein in the absence of mature myelin sheaths is reminiscent of the early stages of myelination in the newborn. From a brief review of the literature on Wiedemann-Rautenstrauch syndrome, we conclude, that the neuropathology of the syndrome is heterogeneous, and that there is relationship between the progeroid aspect and pathological myelination.

On the spinning axis representation

A new spinning axis representation is introduced. It allows us to calculate the evolution operator of a system with slowly varying time dependent Hamiltonian with the desired degree of approximation in the parameter used for describing its dynamical evolution. The procedure is compared with a previously existing one and applied to a simple example.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Traveling waves and nonequilibrium stationary patterns in two-component reactive Langmuir monolayers

A simple kinetic model of a two-component phase-separating Langmuir monolayer with a chemical reaction is proposed. Its analysis and numerical simulations show that nonequilibrium periodic stationary structures and patterns of traveling stripes can spontaneously develop. The nonequilibrium phase diagram of this system is constructed and the properties of the patterns are discussed.

Plastid genome characterisation in Brassica and Brassicaceae using a new set of nine SSRs.

We report a new set of nine primer pairs specifically developed for amplification of Brassica plastid SSR markers. The wide utility of these markers is demonstrated for haplotype identification and detection of polymorphism in B. napus, B. nigra, B. oleracea, B. rapa and in related genera Arabidopsis, Camelina, Raphanus and Sinapis. Eleven gene regions (ndhB-rps7 spacer, rbcL-accD spacer, rpl16 intron, rps16 intron, atpB-rbcL spacer, trnE-trnT spacer, trnL intron, trnL-trnF spacer, trnM-atpE spacer, trnR-rpoC2 spacer, ycf3-psaA spacer) were sequenced from a range of Brassica and related genera for SSR detection and primer design. Other sequences were obtained from GenBank/EMBL. Eight out of nine selected SSR loci showed polymorphism when amplified using the new primers and a combined analysis detected variation within and between Brassica species, with the number of alleles detected per locus ranging from 5 (loci MF-6, MF-1) to 11 (locus MF-7). The combined SSR data were used in a neighbour-joining analysis (SMM, D (DM) distances) to group the samples based on the presence and absence of alleles. The analysis was generally able to separate plastid types into taxon-specific groups. Multi-allelic haplotypes were plotted onto the neighbour joining tree. A total number of 28 haplotypes were detected and these differentiated 22 of the 41 accessions screened from all other accessions. None of these haplotypes was shared by more than one species and some were not characteristic of their predicted type. We interpret our results with respect to taxon differentiation, hybridisation and introgression patterns relating to the 'Triangle of U'.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

A fully validated method for the determination of arsenic species in rice and infant cereal products

A full validation of inorganic arsenic (iAs), methylarsonic acid (MA), and dimethyl arsinic acid (DMA) in several types of rice and rice-based infant cereals is reported. The analytical method was developed and validated in two laboratories. The extraction of the As species was performed using nitric acid 0.2 % and hydrogen peroxide 1 %, and the coupled system liquid chromatography-inductively coupled plasma-mass spectrometry (LCICP-MS) was used for speciation measurements. Detection limit (DL), quantification limit, linearity, precision, trueness, accuracy, selectivity, as well as expanded uncertainty for iAs, MA, and DMA were established. The certified reference materials (CRMs) (NMIJ 7503a, NCS ZC73008, NIST SRM 1568a) were used to check the accuracy. The method was shown to be satisfactory in two proficiency tests (PTs). The broad applicability of the method is shown from the results of analysis of 29 samples including several types of rice, rice products, and infant cereal products. Total As ranged from 40.1 to 323.7 μg As kg1. From the speciation results, iAs was predominant, and DMA was detected in some samples while MA was not detected in any sample.

Review: Contact sport-related chronic traumatic encephalopathy in the elderly: clinical expression and structural substrates.

A. Costanza, K. Weber, S. Gandy, C. Bouras, P. R. Hof, P. Giannakopoulos and A. Canuto (2011) Neuropathology and Applied Neurobiology37, 570-584 Contact sport-related chronic traumatic encephalopathy in the elderly: clinical expression and structural substrates Professional boxers and other contact sport athletes are exposed to repetitive brain trauma that may affect motor functions, cognitive performance, emotional regulation and social awareness. The term of chronic traumatic encephalopathy (CTE) was recently introduced to regroup a wide spectrum of symptoms such as cerebellar, pyramidal and extrapyramidal syndromes, impairments in orientation, memory, language, attention, information processing and frontal executive functions, as well as personality changes and behavioural and psychiatric symptoms. Magnetic resonance imaging usually reveals hippocampal and vermis atrophy, a cavum septum pellucidum, signs of diffuse axonal injury, pituitary gland atrophy, dilated perivascular spaces and periventricular white matter disease. Given the partial overlapping of the clinical expression, epidemiology and pathogenesis of CTE and Alzheimer's disease (AD), as well as the close association between traumatic brain injuries (TBIs) and neurofibrillary tangle formation, a mixed pathology promoted by pathogenetic cascades resulting in either CTE or AD has been postulated. Molecular studies suggested that TBIs increase the neurotoxicity of the TAR DNA-binding protein 43 (TDP-43) that is a key pathological marker of ubiquitin-positive forms of frontotemporal dementia (FTLD-TDP) associated or not with motor neurone disease/amyotrophic lateral sclerosis (ALS). Similar patterns of immunoreactivity for TDP-43 in CTE, FTLD-TDP and ALS as well as epidemiological correlations support the presence of common pathogenetic mechanisms. The present review provides a critical update of the evolution of the concept of CTE with reference to its neuropathological definition together with an in-depth discussion of the differential diagnosis between this entity, AD and frontotemporal dementia.

A forensic science perspective on the role of images in crime investigation and reconstruction

This article presents a global vision of images in forensic science. The proliferation of perspectives on the use of images throughout criminal investigations and the increasing demand for research on this topic seem to demand a forensic science-based analysis. In this study, the definitions of and concepts related to material traces are revisited and applied to images, and a structured approach is used to persuade the scientific community to extend and improve the use of images as traces in criminal investigations. Current research efforts focus on technical issues and evidence assessment. This article provides a sound foundation for rationalising and explaining the processes involved in the production of clues from trace images. For example, the mechanisms through which these visual traces become clues of presence or action are described. An extensive literature review of forensic image analysis emphasises the existing guidelines and knowledge available for answering investigative questions (who, what, where, when and how). However, complementary developments are still necessary to demystify many aspects of image analysis in forensic science, including how to review and select images or use them to reconstruct an event or assist intelligence efforts. The hypothetico-deductive reasoning pathway used to discover unknown elements of an event or crime can also help scientists understand the underlying processes involved in their decision making. An analysis of a single image in an investigative or probative context is used to demonstrate the highly informative potential of images as traces and/or clues. Research efforts should be directed toward formalising the extraction and combination of clues from images. An appropriate methodology is key to expanding the use of images in forensic science.

Sensitive gene expression profiling of human T cell subsets reveals parallel post-thymic differentiation for CD4+ and CD8+ lineages.

The differentiation of CD4(+) or CD8(+) T cells following priming of naive cells is central in the establishment of the immune response against pathogens or tumors. However, our understanding of this complex process and the significance of the multiple subsets of differentiation remains controversial. Gene expression profiling has opened new directions of investigation in immunobiology. Nonetheless, the need for substantial amount of biological material often limits its application range. In this study, we have developed procedures to perform microarray analysis on amplified cDNA from low numbers of cells, including primary T lymphocytes, and applied this technology to the study of CD4 and CD8 lineage differentiation. Gene expression profiling was performed on samples of 1000 cells from 10 different subpopulations, defining the major stages of post-thymic CD4(+) or CD8(+) T cell differentiation. Surprisingly, our data revealed that while CD4(+) and CD8(+) T cell gene expression programs diverge at early stages of differentiation, they become increasingly similar as cells reach a late differentiation stage. This suggests that functional heterogeneity between Ag experienced CD4(+) and CD8(+) T cells is more likely to be located early during post-thymic differentiation, and that late stages of differentiation may represent a common end in the development of T-lymphocytes.