From technological acceptability to appropriation by users: Methodological steps for device assessment in road safety

This article presents the methodology developed within the framework of the research project SARI (Automated Road Surveillance for Driver and Administrator Information). This methodology is based on the logic of action research. The article presents the different stages in the development of technological innovation addressing vehicle control loss when driving on a curve. The results observed in speed reduction illustrate that no matter how optimal an innovation may be technologically speaking, it is only as effective as it is acceptable from a user standpoint. This acceptability can only be obtained if the technology is developed by engineers in liaison with social science specialists.     

Wide-field optical imaging of surface nanostructures

We present a new technique that increases the sensitivity of incoherent light optical microscopy to a point where it becomes possible to directly visualize ultrathin films (approximately nanometers) and isolated nano-objects. The technique is based on the use of nonreflecting substrate surfaces for cross-polarized reflected light microscopy. These surfaces generate a contrast enhancement of about 2 orders of magnitude, extending the application field of wide-field optical microscopy toward the nanoworld. The efficiency of the method is proven experimentally on well-characterized samples. Wide-field imaging of a nonlabeled lambda-DNA molecule is also presented.     

A comparison tool between two ASN.1 specifications

ASN.1 (Abstract Syntax Notation number One) is a standardized formal notation used to describe data exchanged between heterogeneous systems. An ASN.1 specification consists of modules which break down into formal definitions. When a protocol is updated, a new version of its ASN. 1 specification is produced. To keep interoperability between applications which support different versions of the same protocol, the specifier has to ensure that the new modules are compatible with the old ones. Our comparator, based on a complete formalization of comparison rules, can indicate the potential incompatibilities between ASN. 1:1997 specifications.     

Coelenterazine (Marine Bioluminescent Substrate): A Source of Inspiration for the Discovery of Novel Antioxidants

Coelenterazine and derivatives were initially considered in the scientific community for their (bio)luminescent properties. Now, another interest of such hetero-bicycles has been pointed out by the discovery of remarkable antioxidative properties, and an unique mode of action as a “cascade”: the mother-compound (imidazolopyrazinone) is transformed by ROS into a daughter-compound (2-amino-pyrazine) also endowed with antioxidative properties. This review illustrates the therapeutic potential of synthetic imidazolopyrazinones (coelenterazine analogues): chemical reactivity assays with singulet oxygen, radical anion superoxide, peroxynitrite, and radicals formed during lipid and LDL peroxidation, cellular tests of protection against oxidative stress using keratinocyte, hepatocyte, neuronal and erythrocyte cells, and finally in vivo evaluation in a hamster model of ischemia-reperfusion, are fully described.     

A simplified method for evaluating time dependent fault-trees,using Weibull distribution

A new formula for calculating the failure rate of the mode failure for a time dependent fault tree is derived. The time-to-failure distribution for each component (primary failure) is assumed to be Weibull model with different values of parameters for each component. By using this formula, the TOP failure rate for the fault tree can be easily calculated. By appropriate choice of the two parameters of the Weibull model, a wide range of hazard curves can be approximated. The equations are derived by applying the “Kinetic Tree Theory” mentioned by Vesely [1]. The assumptions of the methodology are the independence of the primary failures and that the mode failures are previously known.     

An automated study of EEG: a method of detection of non-stationary points

The purpose of this paper is to present an automatic method of signal analysis. To help physicians in their diagnostics, this method is implemented on a minicomputer in order to detect non-stationary points in electroencephalograms. The signal is modelled with an autoregressive filter. The parameters of this filter are adapted at each step. Identification gives the best model in the sense of a cost function representing the mean square error of noise, which is estimated during the optimisation time-window. The cost function is expressed by a quadratic formula. This allows the use of a fast algorithm, the 'conjugate gradient method'. An original statistical test is developed to detect non-stationary points in the signal. The performance of this method is tested with artificial data to determine the sensitivity of method parameters. Detection using real data is presented.     

Artificial Neural Networks vs. Fuzzy Logic: Simple Tools to Predict and Control Complex Processes—Application to Plasma Spray Processes

The plasma-sprayed coating architecture and in-service properties are derived from an amalgamation of intrinsic and extrinsic spray parameters. These parameters are interrelated; following mostly non-linear relationships. For example, adjusting power parameters (to modify particle temperature and velocity upon impact) also implies an adjustment of the feedstock injection parameters in order to optimize geometric and kinematic parameters. Optimization of the operating parameters is a first step. Controlling these is a second step and consists of defining unique combinations of parameter sets and maintaining them as constant during the entire spray process. These unique combinations must be defined with regard to the in-service coating properties. Several groups of operating parameters control the plasma spray process; namely (i) extrinsic parameters that can be adjusted directly (e.g., the arc current intensity) and (ii) intrinsic parameters, such as the particle velocity or its temperature upon impact, that are indirectly adjusted. Artificial intelligence (AI) is a suitable approach to predict operating parameters to attain required coating characteristics. Artificial Neural Networks (ANN) and Fuzzy Logic (FL) were implemented to predict in-flight particles characteristics as a function of power process parameters. The so-predicted operating parameters resulting from both methods were compared. The spray parameters are also predicted as a function of achieving a specified hardness or a required porosity level. The predicted operating parameters were compared with the predicted in-flight particle characteristics. The specific case of the deposition of alumina-titania (Al₂O₃-TiO₂, 13% by weight) by APS is considered.     

Irradiation creep of SA 304L and CW 316 stainless steels: Mechanical behaviour and microstructural aspects. Part I: Experimental results

Solution annealed 304L (SA 304L) and cold work 316 (CW 316) austenitic stainless steel irradiation creep behaviour have been studied thoroughly. Irradiations were carried out in fast breeder reactors BOR-60 (at 330 °C, up to 120 dpa) and EBR-II (at 375 °C, up to 10.5 dpa), and in the OSIRIS mixed spectrum reactor (at 330 °C, up to 9.8 dpa). After an incubation threshold, the irradiation creep of the austenitic stainless steels is linear in stress and in dose. Creep appears to be athermal in this temperature range. A significant difference in the behaviour is measured between the creep of SA 304L and CW 316.In order to study the anisotropy of loop population, which would be the signature of a possible stress induced preferential absorption (SIPA) mechanism for irradiation creep, special attention was given to the measurement of anisotropy of loop distribution between the four families. The anisotropy induced by an applied stress has been shown to be in the range of the statistical scatter in the situation where no stress is applied. TEM microstructural analyses performed on this sample show slight difference between the microstructure of specimens deformed under irradiation and the microstructure of specimens irradiated without stress under the same irradiation conditions.     

Partitioning of metal species during an enriched fuel combustion experiment. speciation in the gaseous and particulate phases

Combustion processes are the most important source of metal in the atmosphere and need to be better understood to improve flue gas treatment and health impact studies. This combustion experiment was designed to study metal partitioning and metal speciation in the gaseous and particulate phases. A light fuel oil was enriched with 15 organometallic compounds of the following elements: Pb, Hg, As, Cu, Zn, Cd, Se, Sn, Mn, V, Tl, Ni, Co, Cr, and Sb. The resulting mixture was burnt in a pilot-scale fuel combustion boiler under controlled conditions. After filtration of the particles, the gaseous species were sampled in the stack through a heated sampling tube simultaneously by standardized washing bottles-based sampling techniques and cryogenically. The cryogenic samples were collected at -80 degrees C for further speciation analysis by LT/GC-ICPMS. Three species of selenium and two of mercury were evidenced as volatile species in the flue gas. Thermodynamic predictions and experiments suggest the following volatile metal species to be present in the flue gas: H2Se, CSSe, CSe2, SeCl2, Hg(0), and HgCl2. Quantification of volatile metal species in comparison between cryogenic techniques and the washing bottles-based sampling method is also discussed. Concerning metal partitioning, the results indicated that under these conditions, at least 60% (by weight) of the elements Pb, Sn, Cu, Co, Tl, Mn, V, Cr, Ni, Zn, Cd, and Sb mixed to the fuel were found in the particulate matter. For As and Se, 37 and 17%, respectively, were detected in the particles, and no particulate mercury was found. Direct metal speciation in particles was performed by XPS allowing the determination of the oxidation state of the following elements: Sb(V), Tl(III), Mn(IV), Cd(II), Zn(II), Cr(III), Ni(II), Co(II), V(V), and Cu(II). Water soluble species of inorganic Cr, As, and Se in particulate matter were determined by HPLC/ICP-MS and identified in the oxidation state Cr(III), As(V), and Se(IV).