A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the $d$-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate \lambda. At rate \alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability

Disorder-induced double resonant Raman process in graphene

An analytical study is presented of the double resonant Raman scattering process in graphene, responsible for the D and D$^{\prime}$ features in the Raman spectra. This work yields analytical expressions for the D and D$^{\prime}$ integrated Raman intensities that explicitly show the dependencies on laser energy, defect concentration, and electronic lifetime. Good agreement is obtained between the analytical results and experimental measurements on samples with increasing defect concentrations and at various laser excitation energies. The use of Raman spectroscopy to identify the nature of defects is discussed. Comparison between the models for the edge-induced and the disorder-induced D band intensity suggests that edges or grain boundaries can be distinguished from disorder by the different dependence of their Raman intensity on laser excitation energy. Similarly, the type of disorder can potentially be identified not only by the intensity ratio $I_{\mathrm{D}}/I_{\mathrm{D}^{\prime}}$, but also by its laser energy dependence. Also discussed is a quantitative analysis of quantum interference effects of the graphene wavefunctions, which determine the most important phonon wavevectors and scattering processes responsible for the D and D$^{\prime}$ bands.Comment: 10 pages, 4 figure

Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited