Parameter constraints in a near-equipartition model with multi-frequency \emph{NuSTAR}, \emph{Swift} and \emph{Fermi-LAT} data from 3C 279

Precise spectra of 3C 279 in the 0.5-70 keV range, obtained during two epochs of \emph{Swift} and \emph{NuSTAR} observations, are analyzed using a near-equipartition model. We apply a one-zone leptonic model with a three-parameter log-parabola electron energy distribution (EED) to fit the \emph{Swift} and \emph{NuSTAR} X-ray data, as well as simultaneous optical and \emph{Fermi}-LAT $\gamma$-ray data. The Markov Chain Monte Carlo (MCMC) technique is used to search the high-dimensional parameter space and evaluate the uncertainties on model parameters. We show that the two spectra can be successfully fit in near-equipartition conditions, defined by the ratio of the energy density of relativistic electrons to magnetic field $\zeta_{\rm e}$ being close to unity. In both spectra, the observed X-rays are dominated by synchrotron-self Compton photons, and the observed $\gamma$ rays are dominated by Compton scattering of external infrared photons from a surrounding dusty torus. Model parameters are well constrained. From the low state to the high state, both the curvature of the log-parabola width parameter and the synchrotron peak frequency significantly increase. The derived magnetic fields in the two states are nearly identical ($\sim1$\ G), but the Doppler factor in the high state is larger than that in the low state ($\sim$28 versus $\sim$18). We derive that the gamma-ray emission site takes place outside the broad-line region, at $\gtrsim$ 0.1 pc from the black hole, but within the dusty torus. Implications for 3C 279 as a source of high-energy cosmic-rays are discussed.Comment: accepted by MNRA

Graphical condensation of plane graphs: a combinatorial approach

The method of graphical vertex-condensation for enumerating perfect matchings of plane bipartite graph was found by Propp (Theoret. Comput. Sci. 303(2003), 267-301), and was generalized by Kuo (Theoret. Comput. Sci. 319 (2004), 29-57) and Yan and Zhang (J. Combin. Theory Ser. A, 110(2005), 113-125). In this paper, by a purely combinatorial method some explicit identities on graphical vertex-condensation for enumerating perfect matchings of plane graphs (which do not need to be bipartite) are obtained. As applications of our results, some results on graphical edge-condensation for enumerating perfect matchings are proved, and we count the sum of weights of perfect matchings of weighted Aztec diamond.Comment: 13 pages, 5 figures. accepted by Theoretial Computer Scienc

Band structure reconstruction across nematic order in high quality FeSe single crystal as revealed by optical spectroscopy study

We perform an in-plane optical spectroscopy measurement on high quality FeSe single crystals grown by a vapor transport technique. Below the structural transition at $T_{\rm s}\sim$90 K, the reflectivity spectrum clearly shows a gradual suppression around 400 cm$^{-1}$ and the conductivity spectrum shows a peak at higher frequency. The energy scale of this gap-like feature is comparable to the width of the band splitting observed by ARPES. The low-frequency conductivity consists of two Drude components and the overall plasma frequency is smaller than that of the FeAs based compounds, suggesting a lower carrier density or stronger correlation effect. The plasma frequency becomes even smaller below $T_{\rm s}$ which agrees with the very small Fermi energy estimated by other experiments. Similar to iron pnictides, a clear temperature-induced spectral weight transfer is observed for FeSe, being indicative of strong correlation effect.Comment: 6 page

The consistency test on the cosmic evolution

We propose a new and robust method to test the consistency of the cosmic evolution given by a cosmological model. It is realized by comparing the combined quantity r_d^CMB/D_V^SN, which is derived from the comoving sound horizon r_d from cosmic microwave background (CMB) measurements and the effective distance D_V derived from low-redshift Type-Ia supernovae (SNe Ia) data, with direct and independent r_d/D_V obtained by baryon acoustic oscillation (BAO) measurements at median redshifts. We apply this test method for the Lambda-CDM and wCDM models, and investigate the consistency of the derived value of r_d/D_V from Planck 2015 and the SN Ia data sets of Union2.1 and JLA (z<1.5), and the r_d/D_V directly given by BAO data from six-degree-field galaxy survey (6dFGS), Sloan Digital Sky Survey Data Release 7 Main Galaxy Survey (SDSS-DR7 MGS), DR11 of SDSS-III, WiggleZ and Ly-alpha forecast surveys from Baryon Oscillation Spectroscopic Data (BOSS) DR-11 over 0.1<z<2.36. We find that r_d^CMB/D_V^SN for both non-flat Lambda-CDM and flat wCDM models with Union2.1 and JLA data are well consistent with the BAO and CMB measurements within 1-sigma CL. Future surveys will further tight up the constraints significantly, and provide stronger test on the consistency.Comment: 11 pages, 5 figures, 4 tables. Version accepted by PR

An iteration normalization and test method for differential expression analysis of RNA-seq data

BACKGROUND: Next generation sequencing technologies are powerful new tools for investigating a wide range of biological and medical questions. Statistical and computational methods are key to analyzing massive and complex sequencing data. In order to derive gene expression measures and compare these measures across samples or libraries, we first need to normalize read counts to adjust for varying sample sequencing depths and other potentially technical effects. RESULTS: In this paper, we develop a normalization method based on iterating median of M-values (IMM) for detecting the differentially expressed (DE) genes. Compared to a previous approach TMM, the IMM method improves the accuracy of DE detection. Simulation studies show that the IMM method outperforms other methods for the sample normalization. We also look into the real data and find that the genes detected by IMM but not by TMM are much more accurate than the genes detected by TMM but not by IMM. What’s more, we discovered that gene UNC5C is highly associated with kidney cancer and so on