Fe isotopic composition of Martian meteorites and some terrestrial analogues

We report Fe isotopic composition of seven martian meteorites and other terrestrial materials that may be considered Martian analogues

Electrical and Magnetic behaviour of PrFeAsO0.8F0.2 superconductor

The superconducting and ground state samples of PrFeAsO0.8F0.2 and PrFeAsO have been synthesised via easy and versatile single step solid state reaction route. X-ray & Reitveld refine parameters of the synthesised samples are in good agreement to the earlier reported value of the structure. The ground state of the pristine compound (PrFeAsO) exhibited a metallic like step in resistivity below 150K followed by another step at 12K. The former is associated with the spin density wave (SDW) like ordering of Fe spins and later to the anomalous magnetic ordering for Pr moments. Both the resistivity anomalies are absent in case of superconducting PrFeAsO0.8F0.2 sample. Detailed high field (up to 12Tesla) electrical and magnetization measurements are carried out for superconducting PrFeAsO0.8F0.2 sample. The PrFeAsO0.8F0.2 exhibited superconducting onset (Tconset) at around 47K with Tc({\rho} =0) at 38K. Though the Tconset remains nearly invariant, the Tc({\rho} =0) is decreased with applied field, and the same is around 23K under applied field of 12Tesla. The upper critical field (Hc2) is estimated from the Ginzburg Landau equation (GL) fitting, which is found to be ~ 182Tesla. Critical current density (Jc) being calculated from high field isothermal magnetization (MH) loops with the help of Beans critical state model, is found to be of the order of 103 A/cm2. Summarily, the superconductivity characterization of single step synthesised PrFeAsO0.8F0.2 superconductor is presented.Comment: 15 Pages Text + Fig

Late movement of basin-edge lobate scarps on Mercury

Basin-edge lobate scarps are a sub-type of tectonic shortening structure on the surface of Mercury that have formed at the edge of volcanic units that fill or partly fill impact basins. We have performed a global survey of these features and find that they are widespread in basins across the planet. We obtained model ages from crater size–frequency distribution analysis for a subset of our surveyed basins, for both the smooth plains infill and for the last resolvable tectonic activity on the associated basin-edge scarps. Our results indicate that some of these lobate scarps were still accumulating strain in the late Mansurian (approximately 1 Ga). From a photogeological assessment, we find that the orientations of these basin-edge lobate scarps are similar to those reported for the global population of lobate scarps in earlier studies, appearing to align ∼north–south at low latitudes and ∼east–west at higher latitudes. However, reassessing these landforms’ orientation with artificially illuminated topographic data does not allow us to rule out the effect of illumination bias. We propose that these landforms, the result of crustal shortening in response to global contraction, formed along the interface between the basin floor and the smooth plains unit, which acted as a mechanical discontinuity along which shortening strains were concentrated

Feature Extraction and Classification of Flaws in Radio Graphical Weld Images Using ANN

In this paper, a novel approach for the detection and classification of flaws in weld images is presented. Computer based weld image analysis is most significant method. The method has been applied for detecting and discriminating flaws in the weld that may corresponds false alarms or all possible nine types of weld defects (Slag Inclusion, Wormhole, Porosity, Incomplete penetration, Under cuts, Cracks, Lack of fusion, Weaving fault Slag line), after being successfully tested on80 radiographic images obtained from EURECTEST, International scientific Association Brussels, Belgium, and 24 radiographs of ship weld provided by Technic Control Co. (Poland) were used, obtained from Ioannis Valavanis Greece.. The procedure to detect all the types of flaws and feature extraction is implemented by segmentation algorithm which can overcome computer complexity problem. Our problem focuses on the high performance classification by optimization of feature set by various selection algorithms like sequential forward search (SFS), sequential backward search algorithm (SBS) and sequential forward floating search algorithm (SFFS). Features are important for measuring parameters which leads in directional to understand image. We introduced 23 geometric features, and 14 texture features. The Experimental results show that our proposed method gives good performance of radiographic images