Universality and correlations in individuals wandering through an online extremist space

The 'out of the blue' nature of recent terror attacks and the diversity of apparent motives, highlight the importance of understanding the online trajectories that individuals follow prior to developing high levels of extremist support. Here we show that the physics of stochastic walks, with and without temporal correlation, provides a unifying description of these online trajectories. Our unique dataset comprising all users of a global social media site, reveals universal characteristics in individuals' online lifetimes. Our accompanying theory generates analytical and numerical solutions that describe the characteristics shown by individuals that go on to develop high levels of extremist support, and those that do not. The existence of these temporal and also many-body correlations suggests that existing physics machinery can be used to quantify and perhaps mitigate the risk of future events

Optical study of phase transitions in single-crystalline RuP

RuP single crystals of MnP-type orthorhombic structure were synthesized by the Sn flux method. Temperature-dependent x-ray diffraction measurements reveal that the compound experiences two structural phase transitions, which are further confirmed by enormous anomalies shown in temperature-dependent resistivity and magnetic susceptibility. Particularly, the resistivity drops monotonically upon temperature cooling below the second transition, indicating that the material shows metallic behavior, in sharp contrast with the insulating ground state of polycrystalline samples. Optical conductivity measurements were also performed in order to unravel the mechanism of these two transitions. The measurement revealed a sudden reconstruction of band structure over a broad energy scale and a significant removal of conducting carriers below the first phase transition, while a charge-density-wave-like energy gap opens below the second phase transition.Comment: 5 pages, 6 figure

Analysis of Superconductivity in d-p Model on Basis of Perturbation Theory

We investigate the mass enhancement factor and the superconducting transition temperature in the d-p model for the high-\Tc cuprates. We solve the \'Eliashberg equation using the third-order perturbation theory with respect to the on-site Coulomb repulsion $U$. We find that when the energy difference between d-level and p-level is large, the mass enhancement factor becomes large and \Tc tends to be suppressed owing to the difference of the density of state for d-electron at the Fermi level. From another view point, when the energy difference is large, the d-hole number approaches to unity and the electron correlation becomes strong and enhances the effective mass. This behavior for the electron number is the same as that of the f-electron number in the heavy fermion systems. The mass enhancement factor plays an essential role in understanding the difference of \Tc between the LSCO and YBCO systems.Comment: 4pages, 9figures, to be published in J. Phys. Soc. Jp

Advances in representing interactive methane in ModelE2-YIBs (version 1.1)

This is the final version. Available on open access from EGU via the DOI in this recordCode and data availability: The source code for the site-level YIBs model version 1.0 (Yue and Unger, 2015) is available at https://github.com/YIBS01/YIBS site (last access: 5 August 2015). The source code for the frozen CMIP5/AR5 version of the GISS ModelE2 (Schmidt et al., 2014) can be obtained from NASA GISS (https://www.giss.nasa.gov/tools/modelE/, last access: 31 July 2014). Included as supplemental information are the gridded natural methane fluxes and the numerical model output used to make the figures. Gridded files of natural methane fluxes associated with the Fung et al. (1991) dataset were obtained from NASA GISS (https://data.giss.nasa.gov/ch4_fung/, last access: 4 June 2014). Column-averaged methane concentrations from SCIAMACHY (Schneising et al., 2009) were obtained from the University of Bremen (http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/index.html, last access: 27 April 2015). Other data used as model input or for analysis of model output are listed in the references.Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry-climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry-climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry-climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 yr-1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 yr-1 and a global annual methane soil sink of 60 Tg CH4 yr-1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to-1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry-climate model is able to capture the principal processes that control atmospheric methane