Potential influence of microorganisms on the corrosion of carbon steel in the French high- and intermediate-level long-lived radioactive waste disposal context

In the context of the high-level radioactive waste disposal CIGEO, the corrosion rate due to microbially influenced corrosion (MIC) has to be evaluated. In France, it is envisaged to dispose of high- and intermediate-level long-lived radioactive waste at a depth of 500 m in a deep geological disposal, drilled in the Callovo-Oxfordian claystone (Cox) formation. To do so, a carbon steel casing will be inserted inside disposal cells, which are horizontal tunnels drilled in the Cox. A specific cement grout will be injected between the carbon steel casing and the claystone. A study was conducted to evaluate the possibility of MIC on carbon steel in the foreseeable high radioactive waste disposal. The corrosiveness of various environments was investigated at 50°C and 80°C with or without microorganisms enriched from samples of Andra's underground research laboratory. The monitoring of corrosion during the experiments was ensured using gravimetric method and real-time corrosion monitoring using sensors based on the measurements of the electrical resistance. The corrosion data were completed with microbiological analyses including cultural and molecular characterizations.     

The polymerisation of 2-furyl vinyl ketone

Summary 2-Furyl vinyl ketone was polymerised using anionic, cationic and free-radical initiators. Yields and molecular weights varied with the type of activation. Whereas radical polymerisation gave a product possessing a regular vinylic structure, other kinds of units were detected in the polymers prepared with anionic and cationic catalysts.     

The use of direct tension tests for the assessment of low temperature properties of bituminous binders

In France, tensile tests on bituminous binders are usually performed on vertical electromechanical loading frames, the test samples being placed in an insulated temperature control chamber and the deformations determined from the displacement of the cross-head. The paper presents the results of an inter-laboratory study of which the objective was to evaluate the suitability of this kind of equipment for the performance of direct tension tests at low temperatures. Most of the test parameters, used for this study complied with the procedure proposed by SHRP as from 1995 (AASHTO TP3). The various operating factors, and more particularly those affecting the determination of true sample elongation (mechanical plays, deformation of the gripping systems, ....), are discussed and a number of correcting procedures are proposed. Nevertheless, the results remained scattered. Considering the “flat” evolution of strain at failure with temperature in the domain of brittle behaviour, this makes it rather difficult to accurately define the temperature for failure at 1% elongation (T_ε=1%). This is also the case when this temperature is located in the zone of transition between brittle and ductile behaviour. The authors suggest that, together with the corresponding tensile strain, this “transition temperature” could be used as an alternative criterion which has the advantage of being linked to a physical behaviour of the material.     

Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection

Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature and here the study centres on the use of the Generalized Radial Basis Function Neural Networks (GRBFNNs). An interesting property of the GRBF is that it can continuously and smoothly reproduce different RBFs by changing a real parameter τ. In addition, the mixed use of different RBF shapes in only one RBFNN is allowed. Generalized Radial Basis Function (GRBF) is based on Generalized Gaussian Distribution (GGD), which adds a shape parameter, τ, to standard Gaussian Distribution. Moreover, this paper describes a hybrid approach, Hybrid Algorithm (HA), which combines evolutionary and gradient-based learning methods to estimate the architecture, weights and node topology of GRBFNN classifiers. The feasibility and benefits of the approach are demonstrated by means of six gene microarray classification problems taken from bioinformatic and biomedical domains. Three filters were applied: Fast Correlation-Based Filter (FCBF), Best Incremental Ranked Subset (BIRS), and Best Agglomerative Ranked Subset (BARS); this was done in order to identify salient expression genes from among the thousands of genes in microarray data that can directly contribute to determining the class membership of each pattern. After different gene subsets were obtained, the proposed methodology was performed using the selected gene subsets as new input variables. The results confirm that the GRBFNN classifier leads to a promising improvement in accuracy.     

微通道内气-液传质研究

以CO₂-H₂O为模型体系，实验考察了当量直径为667 μm的单通道和16个并行通道内的气-液传质行为.实验发现，液体表观速度增加，单通道内液侧体积传质系数明显提高;同一液体表观速度下，液侧体积传质系数随气体表观速度增加而增加;在实验数据基础上关联了液侧体积传质系数与气-液两相流参数间的关系.微通道内的液侧体积传质系数较常规尺度气-液接触设备至少高1～2个数量级.并讨论了并行微通道内气-液两相流分配特性对整体传质性能的影响，表明合理设计气、液流动分布结构，可保证微通道内优异的传质特性.     

Rheological,thermal, and morphological properties of blends based on poly(propylene), ethylene propylene rubber,and ethylene-1-octene copolymer that could result from end of life vehicles: Effect of maleic anhydride grafted poly(propylene)

The objective of this work is to study the properties of blends that could result from the recycling of end-of-life vehicles (ELV). While ethylene propylene rubber (EPR) and ethylene propylene diene monomer (EPDM) have been used extensively as elastomeric additives in poly(propylene) (PP), they can be substituted by ethylene-1-octene copolymer (EOC). As a consequence, the matter resulting from the sorting of ELV might be more complex and made of PP, EPR, and EOC. The effect of incorporating EOC [that is a polyethylene elastomer (PEE)] and maleic anhydride grafted polypropylene (PP-g-MAH) on the rheological, thermal, and morphological properties of PP/EPR blends has been investigated. Blends of various compositions (with and without compatibilizer) were prepared using a corotating twin-screw extruder. The results were compared to the ones presented by a commercial (PP/EPR) blend. The EPR phase is dispersed in the form of spherical particles in (PP/EPR). The EOC phase is dispersed in the form of aggregated particles. Dynamic viscoelastic and differential scanning calorimetry properties of (PP/EPR)/EOC blends shows the incompatibility of the components even in presence of PP-g-MAH copolymer. POLYM. ENG. SCI., 47:1009–1015, 2007. © 2007 Society of Plastics Engineers     

QoS aggregation for service orchestrations based on workflow pattern rules and MCDM method: evaluation at design time and runtime

Service consumers satisfaction is considered today as one of the main concern to be ensured by service providers, especially with the spread of concurrency and the increase of functionally equivalent services. This satisfaction is closely related to quality of service (QoS) perceived by service consumers. In this context, we propose an approach to determine the satisfaction degree corresponding to the QoS of service-based applications, with regard to service consumers’ QoS expectations. Our approach is based on a preference model, which is built only on the basis of service consumer’s provided information. This preference model is also based on the 2-additive Choquet operator that takes into account preferential dependencies. In this paper, we target both design time and runtime aggregation of QoS of service-based applications.     

Quantification of different effects occurring during fatigue tests on bituminous mixtures

Quantification of different effects (nonlinearity, heating, thixotropy, and fatigue) occurring during fatigue tests on bituminous mixtures is presented in this paper. A focus is given on the nonlinearity phenomenon. Continuous fatigue tests and a test with specific protocol (called fatigue tests to estimate biasing effects) were performed in tension/compression mode on cylindrical samples of the same material. The analysis of results reveals that reversible effects (nonlinearity, heating, and thixotropy) are important (more than 90% decrease at 100,000 cycles for a strain amplitude of 100 μm/m at 10 Hz) and cannot be ignored when interpreting classical fatigue tests. The nonlinearity effects respect the time‐temperature superposition principle, and they are more pronounced at “high” temperature (at the same frequency). Direction of nonlinearity curve in the Cole‐Cole axes is shown to be independent of temperature and frequency for the considered range.     

Weighting Efficient Accuracy and Minimum Sensitivity for Evolving Multi-Class Classifiers

Recently, a multi-objective Sensitivity–Accuracy based methodology has been proposed for building classifiers for multi-class problems. This technique is especially suitable for imbalanced and multi-class datasets. Moreover, the high computational cost of multi-objective approaches is well known so more efficient alternatives must be explored. This paper presents an efficient alternative to the Pareto based solution when considering both Minimum Sensitivity and Accuracy in multi-class classifiers. Alternatives are implemented by extending the Evolutionary Extreme Learning Machine algorithm for training artificial neural networks. Experiments were performed to select the best option after considering alternative proposals and related methods. Based on the experiments, this methodology is competitive in Accuracy, Minimum Sensitivity and efficiency.