Weak Delocalization in Graphene on a Ferromagnetic Insulating Film

Graphene has been predicted to develop a magnetic moment by proximity effect when placed on a ferromagnetic film, a promise that could open exciting possibilities in the fields of spintronics and magnetic data recording. In this work, the interplay between the magnetoresistance of graphene and the magnetization of an underlying ferromagnetic insulating film is studied in detail. A clear correlation between both magnitudes is observed but through a careful modeling of the magnetization and the weak localization measurements, that such correspondence can be explained by the effects of the magnetic stray fields arising from the ferromagnetic insulator is found. The results emphasize the complexity arising at the interface between magnetic and 2D materials.     

A self‐scalable load injection service

Load testing of applications is an important and costly activity for software provider companies. Classical solutions are very difficult to set up statically, and their cost is prohibitive in terms of both human and hardware resources. Virtualized cloud computing platforms provide new opportunities for stressing an application's scalability, by providing a large range of flexible and less expensive (pay‐per‐use model) computation units. On the basis of these advantages, load testing solutions could be provided on demand in the cloud. This paper describes a Benchmark‐as‐a‐Service solution that automatically scales the load injection platform and facilitates its setup according to load profiles. Our approach is based on: (i) virtualization of the benchmarking platform to create self‐scaling injectors; (ii) online calibration to characterize the injector's capacity and impact on the benched application; and (iii) a provisioning solution to appropriately scale the load injection platform ahead of time. We also report experiments on a benchmark illustrating the benefits of this system in terms of cost and resource reductions. Copyright © 2013 John Wiley & Sons, Ltd.     

Impact on the photothermal emission from single wall nanotubes by some alkali halide salts

We demonstrate that alkali-halide salts, particularly potassium bromide, can reduce the photothermal emission (PTE) from single walled carbon nanotubes (SWNT). PTE is a prominent spectral feature in Raman spectroscopy when a near infrared laser is used to analyze a dark colored sample. We subsequently show that trapping salts inside SWNT and coating SWNT with the salt has a more pronounced impact on not only reducing PTE, but also enhancing the intensity of the Raman spectral features. The effect, which we have called nanotube enhanced Raman spectroscopy (NERS), has differences and similarities to the widely studied surface enhanced Raman spectroscopy (SERS).     

On the issue of trend and noise in the estimation of extreme rainfall properties.

Up until today extreme rainfall properties are frequently applied in sewer design guidelines. Uncertainty in the estimation of such properties will hence directly influence the dimensions of sewers, structures and pumps. In this paper the issue of potential trend and noise in the estimation is investigated for 6 rain series ranging from 19 to 55 years in duration. Different to recent research that predicts a climate induced-increase in heavy precipitation no clear indication for such trend was found in the investigated historical rain series. Another important aspect is the length of the rain series that is required for the estimation of extreme rainfall properties and the associated uncertainty. The analysis indicates that at least a period of 10 years should be used for the estimation. But even so the possible deviation expressed in terms of the 90 percentile is in the order of 5 to 10% of the 'true value', defined as the value derived when the whole given series is used for the estimation.     

On the effect of spatial variances in historical rainfall time series to CSO performance evaluation.

Historical, high-resolution rain series are the backbone of modern combined sewer overflow (CSO) structure design. These rain series are the input to the computational estimation of the performance of the measures with respect to CSO pollution abatement. However, those historical precipitation measurements are available at only a few locations. Frequently rain series have to be used from gauging stations at a significant distance. In order to judge and to compensate for this influence an estimate between rain characteristics and combined sewer outflow (CSO) performance indicators would be useful. In this paper such correlations have been sought for a collection of 37 rain series covering large areas of Europe. It was found that the mean annual rain volume can explain most of the variances for the performance indicators Number of overflows and CSO volume. For explaining the spatial differences in the efficiency of the CSO structure another rain characteristic, i.e. the maximum event with a return period of one year, is to be used.