Application of Monte Carlo calculation and OEDIPE software for virtual calibration of an in vivo counting system

OEDIPE (a French acronym standing for 'Tool for Personalized Internal Dose Assessment'), developed by IRSN, is used to perform virtual calibration of a real in vivo counting system. The system, installed recently at Le Vésinet, consists of four Broad Energy germanium detectors. CT images of Livermore torso phantom are used to create a voxel phantom after segmentation using Dosigray software. Virtual calibration using the voxel phantom was validated by the comparison of peak efficiencies between Monte Carlo calculation and phantom experiments using lung sources 152Eu and 241Am at different chest wall thickness (CWT = 19, 25, 30, 43 mm). The comparison between virtual calibration and physical phantom experiments shows that the relative deviations are within +/- 10% in the energy range of 59.5-1408 keV, and within +/- 30% for 17.5 keV photons.     

Potential of modern technologies for improving internal exposure monitoring

Internal dosimetry is the science of assessing the amount and distribution of radionuclides in the body, and calculating resulting radiation doses to internal organs or tissues over specific time periods. Because the ionizing radiation energy deposited in a particular organ from radionuclides incorporated in the body cannot be measured directly, internal doses are estimated or inferred principally from in vivo or in vitro bioassay. As a matter of fact, in an effort to implement effective programmes in internal dosimetry, since internal dosimetry programmes exist, the internal dosimetry laboratories have always tried to develop new capabilities for these techniques or achieve the harmonisation in individual monitoring for occupational exposures. The primary goal of this paper is to categorise the principal trends made in recent developments in these fields regarding their potential and eligibility for the routine monitoring community and discuss the main aspects, which aims at a comprehensive assessment of these techniques. Secondly, starting from these data, their potential improvements are compared to the currently employed monitoring techniques used in routines.     

Isotope Studies of the CMR Compounds La1−xCaxMnO3+δ

Oxygen isotope effect studies of the ferromagnetic Curie temperature T _c of La_1?x Ca _x MnO₃ are presented. The isotope exponent α₀=?ΔlnT _c/Δlnm ₀ changes from 0.4 to 0.14 in the range 0.2<x<0.43. The isotope exponent decreases strongly with increasing tolerance factor, or decreasing lattice distortion. Above Tc the conductivity is characteristic of small polarons. Raman scattering shows a prominent peak at 230 cm?1. The peak width could be related to site-dependent Jahn–Teller distortions above T _c, becoming significantly smaller at and below T _c. IR reflectivity data show a much larger zero frequency IR conductivity than dc conductivity. The IR peaks are independent of temperature between 150 and 295 K.     

Computer animation of human walking: a survey

This paper surveys the set of techniques developed in computer graphics for animating human walking. First we focus on the evolution from purely kinematic ‘knowledge‐based’ methods to approaches that incorporate dynamic constraints or use dynamic simulations to generate motion. Then we review the recent advances in motion editing that enable the control of complex animations by interactively blending and tuning synthetic or captured motions. Copyright © 1999 John Wiley & Sons, Ltd.     

Fast and robust method for the determination of microstructure and composition in butadiene, styrene-butadiene, and isoprene rubber by near-infrared spectroscopy

In the tire industry, synthetic styrene-butadiene rubber (SBR), butadiene rubber (BR), and isoprene rubber (IR) elastomers are essential for conferring to the product its properties of grip and rolling resistance. Their physical properties depend on their chemical composition, i. e., their microstructure and styrene content, which must be accurately controlled. This paper describes a fast, robust, and highly reproducible near-infrared analytical method for the quantitative determination of the microstructure and styrene content. The quantitative models are calculated with the help of pure spectral profiles estimated from a partial least squares (PLS) regression, using (13)C nuclear magnetic resonance (NMR) as the reference method. This versatile approach allows the models to be applied over a large range of compositions, from a single BR to an SBR-IR blend. The resulting quantitative predictions are independent of the sample path length. As a consequence, the sample preparation is solvent free and simplified with a very fast (five minutes) hot filming step of a bulk polymer piece. No precise thickness control is required. Thus, the operator effect becomes negligible and the method is easily transferable. The root mean square error of prediction, depending on the rubber composition, is between 0.7% and 1.3%. The reproducibility standard error is less than 0.2% in every case.     

Hierarchically structured transparent hybrid membranes by in situ growth of mesostructured organosilica in host polymer

The elaborate performances characterizing natural materials result from functional hierarchical constructions at scales ranging from nanometres to millimetres, each construction allowing the material to fit the physical or chemical demands occurring at these different levels. Hierarchically structured materials start to demonstrate a high input in numerous promising applied domains such as sensors, catalysis, optics, fuel cells, smart biologic and cosmetic vectors. In particular, hierarchical hybrid materials permit the accommodation of a maximum of elementary functions in a small volume, thereby optimizing complementary possibilities and properties between inorganic and organic components. The reported strategies combine sol-gel chemistry, self-assembly routes using templates that tune the material's architecture and texture with the use of larger inorganic, organic or biological templates such as latex, organogelator-derived fibres, nanolithographic techniques or controlled phase separation. We propose an approach to forming transparent hierarchical hybrid functionalized membranes using in situ generation of mesostructured hybrid phases inside a non-porogenic hydrophobic polymeric host matrix. We demonstrate that the control of the multiple affinities existing between organic and inorganic components allows us to design the length-scale partitioning of hybrid nanomaterials with tuned functionalities and desirable size organization from ?ngstr?m to centimetre. After functionalization of the mesoporous hybrid silica component, the resulting membranes have good ionic conductivity offering interesting perspectives for the design of solid electrolytes, fuel cells and other ion-transport microdevices.     

Effect of pH on glucose and starch fermentation in batch and sequenced-batch mode with a recently isolated strain of hydrogen-producing Clostridium butyricum CWBI1009

This paper reports investigations carried out to determine the optimum culture conditions for the production of hydrogen with a recently isolated strain Clostridium butyricum CWBI1009. The production rates and yields were investigated at 30 °C in a 2.3 L bioreactor operated in batch and sequenced-batch mode using glucose and starch as substrates. In order to study the precise effect of a stable pH on hydrogen production, and the metabolite pathway involved, cultures were conducted with pH controlled at different levels ranging from 4.7 to 7.3 (maximum range of 0.15 pH unit around the pH level). For glucose the maximum yield (1.7 mol H₂ mol⁻¹ glucose) was measured when the pH was maintained at 5.2. The acetate and butyrate yields were 0.35 mol acetate mol⁻¹ glucose and 0.6 mol butyrate mol⁻¹ glucose. For starch a maximum yield of 2.0 mol H₂ mol⁻¹ hexose, and a maximum production rate of 15 mol H₂ mol⁻¹ hexose h⁻¹ were obtained at pH 5.6 when the acetate and butyrate yields were 0.47 mol acetate mol⁻¹ hexose and 0.67 mol butyrate mol⁻¹ hexose.     

Tokamak D-T neutron source models for different plasma physics confinement modes

Neutronic studies of European demonstration fusion power plant (DEMO) have been so far based on plasma physics low confinement mode (L-mode). Future tokamaks, nevertheless, may likely use alternative confinement modes such as high or advanced confinement modes (H&A-mode). Based on analytical formulae used in plasma physics, H&A-modes D-T neutron sources formulae are proposed in this paper. For that purpose, a tokamak random neutron source generator, TRANSGEN, has been built generating bidimensional (radial and poloidal) neutron source maps to be used as input for neutronics Monte-Carlo codes (TRIPOLI-4 and MCNP5). The impact of such a source on the neutronic behavior of the European DEMO-2007 Helium-cooled lithium–lead reactor concept has been assessed and compared with previous results obtained using a L-mode neutron source. An A-mode neutron source map from TRANSGEN has been used with the code TRIPOLI-4. Assuming the same fusion power, results show that main reactor global neutronic parameters, e.g. tritium breeding ratio and neutron multiplication factor, evolved slightly when compared to present uncertainties margin. However, local parameters, such as the neutron wall loading (NWL), change significantly compared to L-mode shape: from ?22% to +11% for NWL.     

A Condition‐Based Deterioration Model for the Stochastic Dependency of Corrosion Rate and Crack Propagation in Corroded Concrete Structures

Physics‐based models are intensively studied in mechanical and civil engineering but their constant increase in complexity makes them harder to use in a maintenance context, especially when degradation model can/should be updated from new inspection data. On the other hand, Markovian cumulative damage approaches such as Gamma processes seem promising; however, they suffer from lack of acceptability by the civil engineering community due to poor physics considerations. In this article, we want to promote an approach for modeling the degradation of structures and infrastructures for maintenance purposes which can be seen as an intermediate approach between physical models and probabilistic models. A new statistical, data‐driven state‐dependent model is proposed. The construction of the degradation model will be discussed within an application to the cracking of concrete due to chloride‐induced corrosion. Numerical experiments will later be conducted to identify preliminary properties of the model in terms of statistical inferences. An estimation algorithm is proposed to estimate the parameters of the model in cases where databases suffer from irregularities.