Particle acceleration and radiation friction effects in the filamentation instability of pair plasmas

The evolution of the filamentation instability produced by two counter-streaming pair plasmas is studied with particle-in-cell (PIC) simulations in both one (1D) and two (2D) spatial dimensions. Radiation friction effects on particles are taken into account. After an exponential growth of both the magnetic field and the current density, a nonlinear quasi-stationary phase sets up characterized by filaments of opposite currents. During the nonlinear stage, a strong broadening of the particle energy spectrum occurs accompanied by the formation of a peak at twice their initial energy. A simple theory of the peak formation is presented. The presence of radiative losses does not change the dynamics of the instability but affects the structure of the particle spectra.Comment: 8 pages, 8 figures, submitted to MNRA

A hybrid asymptotic-FVTD method for the estimation of the radar cross section of 3D structures

The Finite Volume Time-Domain (FVTD) method is an effective full-wave technique which allows an accurate computation of the electromagnetic field. In order to analyze the scattering effects due to electrically large structures, it can be combined with methods based on high-frequency approximations. This paper proposes a hybrid technique, which combines the FVTD method with an asymptotic solver based on the physical optics (PO) and the equivalent current method (ECM), allowing the solution of electromagnetic problems in the presence of electrically large structures with small details. Preliminary numerical simulations, aimed at computing the radar cross section of perfect electric conducting (PEC) composite objects, are reported in order to evaluate the effectiveness of the proposed method

New statistical RI index allow to better track the dynamics of COVID-19 outbreak in Italy

COVID-19 pandemic in Italy displayed a spatial distribution that made the tracking of its time course quite difficult. The most relevant anomaly was the marked spatial heterogeneity of COVID-19 diffusion. Lombardia region accounted for around 60% of fatal cases (while hosting 15% of Italian population). Moreover, 86% of fatalities concentrated in four Northern Italy regions. The ‘explosive’ outbreak of COVID-19 in Lombardia at the very beginning of pandemic fatally biased the R-like statistics routinely used to control the disease dynamics. To (at least partially) overcome this bias, we propose a new index RI = dH/dI (daily derivative ratio of H and I, given H = Healed and I = Infected), corresponding to the ratio between healed and infected patients relative daily changes. The proposed index is less flawed than R by the uncertainty related to the estimated number of infected persons and allows to follow (and possibly forecast) epidemic dynamics in a largely model-independent way. To analyze the dynamics of the epidemic, starting from the beginning of the virus spreading—when data are insufficient to make an estimate by adopting SIR model—a "sigmoidal family with delay" logistic model was introduced. That approach allowed in estimating the epidemic peak using the few data gathered even before mid-March. Based on this analysis, the peak was correctly predicted to occur by end of April. Analytical methodology of the dynamics of the epidemic we are proposing herein aims to forecast the time and intensity of the epidemic peak (forward prediction), while allowing identifying the (more likely) beginning of the epidemic (backward prediction). In addition, we established a relationship between hospitalization in intensive care units (ICU) versus deaths daily rates by avoiding the necessity to rely on precise estimates of the infected fraction of the population The joint evolution of the above parameters over time allows for a trustworthy and unbiased estimation of the dynamics of the epidemic, allowing us to clearly detect the qualitatively different character of the ‘so-called’ second wave with respect to the previous epidemic peak

Ultra-intense laser interaction with nanostructured near-critical plasmas

Near-critical plasmas irradiated at ultra-high laser intensities (I > 1018W/cm2) allow to improve the performances of laser-driven particle and radiation sources and to explore scenarios of great astrophysical interest. Near-critical plasmas with controlled properties can be obtained with nanostructured low-density materials. By means of 3D Particle-In-Cell simulations, we investigate how realistic nanostructures influence the interaction of an ultra-intense laser with a plasma having a near-critical average electron density. We find that the presence of a nanostructure strongly reduces the effect of pulse polarization and enhances the energy absorbed by the ion population, while generally leading to a significant decrease of the electron temperature with respect to a homogeneous near-critical plasma. We also observe an effect of the nanostructure morphology. These results are relevant both for a fundamental understanding and for the foreseen applications of laser-plasma interaction in the near-critical regime

Mapping the dielectric properties of unknown targets by using a network of microwave sensors: A proof-of-concept

The subject of this paper is the possible use of a network of microwave sensors to achieve a map of the electromagnetic properties of unknown targets. The basic idea is to use a set of microwave sensors to illuminate a region of interest and to measure the resulting axial component of the electric field. Measurements are then processed by means of a technique based on inverse-scattering, which provides an estimate map of the dielectric values of the area under examination, allowing to discriminate among possible targets. In order to initially evaluate the feasibility of the proposed approach, numerical results in a simulated environment are preliminarily considered and discussed. Furthermore, an initial test on experimental data in a simplified configuration is also presented

Initial Experimental Tests of an ANN-Based Microwave Imaging Technique for Neck Diagnostics

In this letter, a microwave imaging strategy based on an artificial neural network (ANN) is applied, for the first time, to experimental data gathered from simplified neck phantoms. The ANN is used for solving the underlying inverse scattering problem, with the aim of retrieving the dielectric properties of the neck for monitoring and diagnostic purposes. The ANN is trained using simulated phantoms, to overcome the limited availability of experimental data. First, a simple configuration with a liquid-filled glass beaker is tested. Then, simplified 3-D-printed models of the human neck are considered. The preliminary findings indicate the possibility of training the network with numerical simulations and testing it against experimental measurements

Silicon slow-light-based photonic mixer for microwave-frequencyconversion applications

This paper was published in OPTICS LETTERS and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OL.37.001721. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law[EN] We describe and demonstrate experimentally a method for photonic mixing of microwave signals by using a silicon electro-optical Mach¿Zehnder modulator enhanced via slow-light propagation. Slow light with a group index of ~11, achieved in a one-dimensional periodic structure, is exploited to improve the upconversion performance of an input frequency signal from 1 to 10.25 GHz. A minimum transmission point is used to successfully demonstrate the upconversion with very low conversion losses of ~7¿¿dB and excellent quality of the received I/Q modulated QPSK signal with an optimum EVM of ~8%.Financial support from FP7-224312 HELIOS project and Generalitat Valenciana under PROMETEO-2010-087 R&D Excellency Program (NANOMET) are acknowledged. F. Y.Gardes, D. J. Thomson, and G. T. Reed are supported by funding received from the UK EPSRC funding body under the grant “UK Silicon Photonics.” The author A. M. Gutiérrez thanks D. Marpaung for his useful help.Gutiérrez Campo, AM.; Brimont, ACJ.; Herrera Llorente, J.; Aamer, M.; Martí Sendra, J.; Thomson, DJ.; Gardes, FY.... (2012). Silicon slow-light-based photonic mixer for microwave-frequencyconversion applications. Optics Letters. 37(10):1721-1723. https://doi.org/10.1364/OL.37.001721S17211723371

Comparison of an X-ray selected sample of massive lensing clusters with the MareNostrum Universe LCDM simulation

A long-standing problem of strong lensing by galaxy clusters regards the observed high rate of giant gravitational arcs as compared to the predictions in the framework of the "standard" cosmological model. Recently, few other inconsistencies between theoretical expectations and observations have been claimed which regard the large size of the Einstein rings and the high concentrations of few clusters with strong lensing features. All of these problems consistently indicate that observed galaxy clusters may be gravitational lenses stronger than expected. We use clusters extracted from the MareNostrum Universe to build up mock catalogs of galaxy clusters selected through their X-ray flux. We use these objects to estimate the probability distributions of lensing cross sections, Einstein rings, and concentrations for the sample of 12 MACS clusters at $z>0.5$ presented in Ebeling et al. (2007) and discussed in Zitrin et al. (2010). We find that simulated clusters produce $\sim 50$ less arcs than observed clusters do. The medians of the distributions of the Einstein ring sizes differ by $\sim 25$ between simulations and observations. We estimate that, due to cluster triaxiality and orientation biases affecting the lenses with the largest cross sections, the concentrations of the individual MACS clusters inferred from the lensing analysis should be up to a factor of $\sim 2$ larger than expected from the $\Lambda$CDM model. The arc statistics, the Einstein ring, and the concentration problems in strong lensing clusters are mitigated but not solved on the basis of our analysis. Nevertheless, due to the lack of redshifts for most of the multiple image systems used for modeling the MACS clusters, the results of this work will need to be verified with additional data. The upcoming CLASH program will provide an ideal sample for extending our comparison (abridged).Comment: 11 pages, 9 figures, accepted for publication on A&

Demonstration of a heterogeneously integrated III-V/SOI single wavelength tunable laser

A heterogeneously integrated III-V-on-silicon laser is reported, integrating a III-V gain section, a silicon ring resonator for wavelength selection and two silicon Bragg grating reflectors as back and front mirrors. Single wavelength operation with a side mode suppression ratio higher than 45 dB is obtained. An output power up to 10 mW at 20 °C and a thermo-optic wavelength tuning range of 8 nm are achieved. The laser linewidth is found to be 1.7 MHz

Diallyl trisulfide-induced prostate cancer cell death is associated with Akt/PKB dephosphorylation mediated by P-p66shc

PURPOSE: P66Shc, an isoform of adaptor proteins, is known to mediate various signals including those leading to apoptosis or cell proliferation. Previously, we have shown that diallyl trisulfide (DATS)-induced prostate cancer cell death was mediated by increased ROS formation. In this study, we investigated the role of p66Shc protein and its serine 36 phosphorylation in DATS induced decrease in prostate cancer cell viability (PC-3). METHODS: PC-3 prostate cancer cells were used in this study. Stable cell lines expressing p66ShcS36A or an empty vector have been obtained. Cell viability, concentration of ROS, changes in P-p66Shc and P-Akt and DNA damage were determined. RESULTS: We observed that DATS treatment increased p66Shc phosphorylation at serine 36. Importantly, the phosphorylation was abolished by JNK inhibitor SP600125. Cells expressing plasmid-encoded variant of p66ShcS36A showed much higher resistance to DATS-induced cells death. In addition to that, we observed that DATS-induced ROS formation was completely abolished in cells expressing the p66ShcS36A variant. Interestingly, SP600125 proved to prevent DATS-induced Akt inactivation. In order to confirm that the observed effect is related to phosphorylation of p66Shc, we performed experiments on a stable cell line expressing p66ShcS36A. In such cells, DATS-induced Akt dephosphorylation was significantly reduced. On the other hand, hydrogen peroxide induced Akt activation in PC-3 cells, which was abrogated in cells expressing p66ShcS36A. CONCLUSIONS: Our results uncover a novel signaling pathway with p66Shc being indispensable for DATS-induced inactivation of Akt due to hypophosphorylation