Characterization of an energy source for modeling hypothetical core disruptive accidents in nuclear reactors

The experimental methods for and results of determining the expansion characteristics of the detonation products of an energy source that simulates the pressure-volume change relationships for sodium vapor expansions during hypothetical core disruptive accidents in a fast test reactor are presented. Rigid cylinder-piston experiments performed at two scales (ratio 1:3) to determine a pressure-volume relationship as a function of source mass and expansion environment are described. Some of these measurements are compared with code calculations for the source. The results show: (1) that the pressure-volume relationship depends significantly on the presence of water in the cylinder and comparatively little on the timescale of the expansion, the presence of steel balls in the water, or a Mylar sheet on the water surface; and (2) the experiment's scale. A relationship between the measured work energy from the source and the charge mass is presented, and pressure-volume change measurements are compared with previous experimental measurements and with theoretical calculations for a 150 MWsec hypothetical core disruptive accident. The measurements and code calculations of the pressure-volume relationship for the source agree reasonably well.     

Hardware Implementation of Enhancement Embedded Reduced Runtime Recovery Algorithm for Compressively Sensed Images

Compressed sensing is based on the principle that, through optimization, the sparsity of a signal can be exploited to recover it from fewer samples than required by the criterion. In compressed sensing, data is compressed and converted into fewer measurements and transmitted through wireless channel which is reconstructed at the receiver. Since very few samples are used for reconstruction, there are possibilities of degradation in quality of reconstruction. Unlike traditional methods, enhancement can now be done using the recent technique of compressed sensing by embedding image enhancement techniques like edge detection, histogram, filtering and their combinations with CS recovery procedure. This work proposes such a method by binding the image enhancement techniques along with the compressed sensing process. Filter of Gaussian filter (FGF), a combinational filter proposed in this study enables an increase in PSNR of 1 dB when compared to other filtering techniques besides using least number of measurements and maintaining minimum time consumption. The runtime difference with and without the FGF is ~?3 s, which is affordable even in hardware with minimum specifications. Real time experimentation of embedded enhancement CS was carried out in WINGZ board to prove the feasibility of enhanced recovery process with lower end hardware.     

Method for three-dimensional data registration from disparate imaging modalities in the NOGA Myocardial Viability Trial

Region-by-region comparison of data concerning left ventricular (LV) status is difficult to perform quantitatively if the data was acquired from disparate imaging modalities. We validated a method for comparing measurements obtained by electromechanical mapping (EMM) catheter with dobutamine stress echocardiography (DSE) via biplane contrast ventriculography, with the assistance of three-dimensional (3-D) echocardiographic data. The ventriculograms were traced and the borders were used to reconstruct the LV in 3-D with the aid of a database of 3-D echocardiographic studies. The 3-D LV was oriented to the EMM data based on the body coordinates and then manually scaled and translated to fit. The EMM data were mapped to the 3-D surface. The 3-D surface was divided into the 16 regions defined for echocardiographic assessment. The mean EMM value for local linear shortening, a parameter of function, was computed in each segment. The EMM and semiquantitative echocardiographic assessments of regional myocardial function were compared by segment, and the volume of the 3-D LV was compared with the volume computed from the ventriculogram. The volume of the 3-D surface correlated closely with that of the ventriculogram (r = 0.97, SEE = 27.4 ml) but with a significant overestimation of 63 +/- 35 ml. There was a highly significant (p < 0.0001) agreement in regional function between EMM and echo. Local linear shortening correlated significantly (p < 0.0001) with echocardiographic severity of wall motion, averaging 9.5 +/- 6.5, 8.1 +/- 5.4, 5.9 +/- 4.8, and 6.2 +/- 3.3 in segments read as normal, hypokinetic, akinetic, and dyskinetic, respectively. The method presented is valid for comparing cardiac parameters derived from disparate image data on a region-by-region basis by employing anatomic landmarks on 3-D reconstructions of the LV endocardial surface.     

Conductometric biosensor based on glucose oxidase and beta-galactosidase for specific lactose determination in milk

This paper investigates the development of a biosensor associating two distinct enzymatic activities, that of the beta-galactosidase and that of the glucose oxidase, in order to apply it for the quantitative detection of lactose in milk. To eliminate interferences with glucose, a differential mode of measurement was used. Results show a linear calibration curve for lactose concentration between 60 and 800 μM (0.03 to 0.3 g/L). Tests with real commercial milk samples were carried out to validate the conductometric biosensor.     

Three characterization techniques coupled with adsorption for studying the nanoporosity of supported films and membranes

Three characterization techniques are described for studying the open nanoporosity, i.e. the open free volume, the microporosity, the mesoporosity and the thickness variation of thin deposited films during gas adsorption and condensation. They are all based on the coupling of the sorption of a probe gaseous molecule at room temperature and a physical characterization tool of thin deposited films: the quartz crystal microbalance, ellipsometry and X-ray reflectometry, giving the mass uptake, the refractive index variation and the electronic density variation, respectively, of the film due to the adsorbate intrusion inside the open free volume and pores. The film thickness evolution during the sorption can also be followed by the two last techniques. These techniques are complementary because each one can bring specific properties and can validate the results of another one. Both static and dynamic measurements can be carried out to characterize the porosity, the contraction or the swelling of the film and the penetration rate of the gas.     

Laser sintering of coated polyamide 12: a new way to improve flammability

Journal of Materials Science - In this study coatings of kaolin and talc particles were successfully applied on the surface of polyamide 12 powder intended for laser sintering (LS). Microscopic...     

Nano-structured zinc oxide–cotton fibers: synthesis, characterization and applications

Zinc oxide nanoparticles were prepared and subsequently deposited onto the surface of the cotton fiber by ultrasonic irradiation. The optical, structure and morphology of the coated and un-coated cotton were examined by UV, fourier transform infrared spectroscopy, X-ray diffraction analysis (XRD) and scanning electron microscope (SEM)/Energy Dispersive X-ray analysis. XRD analysis revealed the presence of the crystalline metal oxide of hexagonal phase with an average crystallite size of 12 nm. These nanoparticles are probably physically adsorbed onto the cotton fiber surface. SEM analysis showed a distribution of ZnO nanorod assemblies of various diameters and lengths physically adsorbed onto the cotton fiber surface may take place. The ZnO-cotton fiber nano-composite were tested against Escherichia coli (gram negative) and Staphylococcus aureus (gram positive) cultures, and showed a significant antimicrobial activity.     

Association of indigo with zeolites for improved color stabilization

The durability of an organic color and its resistance against external chemical agents and exposure to light can be significantly enhanced by hybridizing the natural dye with a mineral. In search for stable natural pigments, the present work focuses on the association of indigo blue with several zeolitic matrices (LTA zeolite, mordenite, MFI zeolite). The manufacturing of the hybrid pigment is tested under varying oxidizing conditions, using Raman and ultraviolet-visible (UV-Vis) spectrometric techniques. Blending indigo with MFI is shown to yield the most stable composite in all of our artificial indigo pigments. In the absence of defects and substituted cations such as aluminum in the framework of the MFI zeolite matrix, we show that matching the pore size with the dimensions of the guest indigo molecule is the key factor. The evidence for the high color stability of indigo@MFI opens a new path for modeling the stability of indigo in various alumino-silicate substrates such as in the historical Maya Blue pigment.     

Asymptotic performances of a constructive algorithm

We present a numerical study of a neural tree learning algorithm, the “triolearning≓ strategy. We study the behaviour of the algorithm as a function of the size of the training set. The results show that a limited number of examples can be used to estimate both the network performance and the network complexity that would result from running the algorithm on a large data set.     

Dynamic and scalable multi-level trust management model for Social Internet of Things

The Internet of Things (IoT) is a paradigm that has made everyday objects intelligent by offering them the ability to connect to the Internet and communicate. Integrating the social component into IoT gave rise to the Social Internet of Things (SIoT), which has helped overcome various issues such as heterogeneity and navigability. In this kind of environment, participants compete to offer a variety of attractive services. Nevertheless, some of them resort to malicious behaviour to spread poor-quality services. They perform so-called Trust-Attacks and break the basic functionality of the system. Trust management mechanisms aim to counter these attacks and provide the user with an estimate of the trust degree they can place in other users, thus ensuring reliable and qualified exchanges and interactions. Several works in literature have interfered with this problem and have proposed different Trust-Models. The majority tried to adapt and reapply Trust-Models designed for common social networks or peer-to-peer ones. That is, despite the similarities between these types of networks, SIoT ones present specific peculiarities. In SIoT, users, devices and services are collaborating. Devices entities can present constrained computing and storage capabilities, and their number can reach some millions. The resulting network is complex, constrained and highly dynamic, and the attacks-implications can be more significant. In this paper, we propose DSL-STM a new dynamic and scalable multi-level Trust-Model, specifically designed for SIoT environments. We propose multidimensional metrics to describe and SIoT entities behaviours. The latter are aggregated via a Machine Learning-based method, allowing classifying users, detecting attack types and countering them. Finally, a hybrid propagation method is suggested to spread trust values in the network, while minimizing resource consumption and preserving scalability and dynamism. Experimentation made on various simulated scenarios allows us to prove the resilience and performance of DSL-STM.