Conditional Graphical Lasso for Multi-label Image Classification

© 2016 IEEE. Multi-label image classification aims to predict multiple labels for a single image which contains diverse content. By utilizing label correlations, various techniques have been developed to improve classification performance. However, current existing methods either neglect image features when exploiting label correlations or lack the ability to learn image-dependent conditional label structures. In this paper, we develop conditional graphical Lasso (CGL) to handle these challenges. CGL provides a unified Bayesian framework for structure and parameter learning conditioned on image features. We formulate the multi-label prediction as CGL inference problem, which is solved by a mean field variational approach. Meanwhile, CGL learning is efficient due to a tailored proximal gradient procedure by applying the maximum a posterior (MAP) methodology. CGL performs competitively for multi-label image classification on benchmark datasets MULAN scene, PASCAL VOC 2007 and PASCAL VOC 2012, compared with the state-of-the-art multi-label classification algorithms

The σHβ\sigma_{\rm H\beta}-based dimensionless accretion rate and its connection with the corona for AGN

With respect to the $\rm H\beta$ full width at half-maximum ($\rm FWHM_{H\beta}$), the broad $\rm H\beta$ line dispersion ($\sigma_{\rm H\beta}$) was preferred as a velocity tracer to calculate the single-epoch supermassive black hole mass ($M_{\rm BH}$) suggested by \cite{Yu2020b}. For a compiled sample of 311 broad-line active galactic nuclei (AGN) with measured hard X-ray photon index ($z<0.7$), $\sigma_{\rm H\beta}$ and the optical Fe II relative strength ($R_{\rm Fe}$) are measured from their optical spectra, which are used to calculate $\sigma_{\rm H\beta}$-based virial $M_{\rm BH}$ and dimensionless accretion rate ($\dot{\mathscr{M}}$). With respect to $\rm FWHM_{\rm H\beta}$, it is found that the mean value of $\sigma_{\rm H\beta}$-based $M_{\rm BH}$ is on average larger by 0.26 dex, and the mean value of $\sigma_{\rm H\beta}$-based $\dot{\mathscr{M}}$ is on average smaller by 0.51 dex. It is found that there exists a non-linear relationship between the Eddington ratio ($L_{\rm Bol}/L_{\rm Edd}$) and $\dot{\mathscr{M}}$, i.e., $L_{\rm Bol}/L_{\rm Edd} \propto \dot{\mathscr{M}}^{0.56\pm 0.01}$. This non-linear relationship comes from the accretion efficiency $\eta$, which is smaller for AGN with higher $\dot{\mathscr{M}}$. We find a strong bivariate correlation of the fraction of energy released in the corona $F_{\rm X}$ with $\dot{\mathscr{M}}$ and \mbh, $F_{\rm X} \propto \dot{\mathscr{M}}^{-0.57\pm 0.05} M_{\rm BH}^{-0.54\pm 0.06}$. The flat slope of $-0.57\pm 0.05$ favours the shear stress tensor of the accretion disk being proportional to the geometric mean of gas pressure and total pressure. We find a strong bivariate relation of $\Gamma$ with $\dot{\mathscr{M}}$ and $F_{\rm X}$, $\Gamma \propto \dot{\mathscr{M}}^{-0.21\pm 0.02}F_{\rm X}^{0.02\pm 0.04}$. The hard X-ray spectrum becomes softer with increasing of $F_{\rm X}$, although the scatter is large.Comment: 18 pages, 9 figures, ApJ, in pres

The cumulative effects of known susceptibility variants to predict primary biliary cirrhosis risk.

Multiple genetic variants influence the risk for development of primary biliary cirrhosis (PBC). To explore the cumulative effects of known susceptibility loci on risk, we utilized a weighted genetic risk score (wGRS) to evaluate whether genetic information can predict susceptibility. The wGRS was created using 26 known susceptibility loci and investigated in 1840 UK PBC and 5164 controls. Our data indicate that the wGRS was significantly different between PBC and controls (P=1.61E-142). Moreover, we assessed predictive performance of wGRS on disease status by calculating the area under the receiver operator characteristic curve. The area under curve for the purely genetic model was 0.72 and for gender plus genetic model was 0.82, with confidence limits substantially above random predictions. The risk of PBC using logistic regression was estimated after dividing individuals into quartiles. Individuals in the highest disclosed risk group demonstrated a substantially increased risk for PBC compared with the lowest risk group (odds ratio: 9.3, P=1.91E-084). Finally, we validated our findings in an analysis of an Italian PBC cohort. Our data suggested that the wGRS, utilizing genetic variants, was significantly associated with increased risk for PBC with consistent discriminant ability. Our study is a first step toward risk prediction for PBC

Low frequency split cycle cryocooler

A split cycle Stirling cryocooler with two different drive motors and operating at a low drive frequency can have high thermodynamic efficiency. The temperature of the cold end of the cryocooler varies with drive frequency, voltage of the input electrical power and initial charge pressure values. The cryocooler operating at 8 Hz can provide 7 watts of refrigeration at 77 K for 230 watts of electrical input power

The accretion ratios in Seyfert 2 galaxies with and without hidden broad-line regions

Using a large sample of 90 Seyfert 2 galaxies (Sy2s) with spectropolarimetric observations, we tested the suggestion that the presence of hidden broad-line regions (HBLRs) in Sy2s is dependent upon the Eddington ratio. The stellar velocity dispersion and the extinction-corrected \OIII luminosity are used to derive the mass of central super-massive black holes and the Eddington ratio. We found that: (1) below the Eddington ratio threshold of $10^{-1.37}$, all but one object belong to non-HBLRs Sy2s; while at higher Eddington ratio, there is no obvious discrimination in the Eddington ratio and black hole mass distributions for Sy2s with and without HBLRs; (2) nearly all low-luminosity Sy2s (e.g., \LOIII < 10^{41} \ergs) do not show HBLRs regardless of the column density of neutral hydrogen ($N_{\rm H}$); (3) for high-luminosity Sy2s, the possibility to detect HBLRs Sy2s is almost the same as that of non-HBLRs Sy2s; (4) when considering only Compton-thin Sy2s with higher \OIII luminosity (>10^{41} \ergs), we find a very high detectability of HBLRs ,$\sim$ 85%. These results suggested that AGN luminosity plays a major role in not detecting HBLRs in low-luminosity Sy2s, while for high-luminosity Sy2s, the detectability of HBLRs depends not only upon the AGN activity, but also upon the torus obscuration.Comment: Accepted by ApJ, 3 Tables, 6 Figure

An Improved Method for Monitoring Multiscale Plant Species Diversity of Alpine Grassland Using UAV: A Case Study in the Source Region of the Yellow River, China.

Plant species diversity (PSD) is essential in evaluating the function and developing the management and conservation strategies of grassland. However, over a large region, an efficient and high precision method to monitor multiscale PSD (α-, β-, and γ-diversity) is lacking. In this study, we proposed and improved an unmanned aerial vehicle (UAV)-based PSD monitoring method (UAVB) and tested the feasibility, and meanwhile, explored the potential relationship between multiscale PSD and precipitation on the alpine grassland of the source region of the Yellow River (SRYR), China. Our findings showed that: (1) UAVB was more representative (larger monitoring areas and more species identified with higher α- and γ-diversity) than the traditional ground-based monitoring method, though a few specific species (small in size) were difficult to identify; (2) UAVB is suitable for monitoring the multiscale PSD over a large region (the SRYR in this study), and the improvement by weighing the dominance of species improved the precision of α-diversity (higher R 2 and lower P values of the linear regressions); and (3) the species diversity indices (α- and β-diversity) increased first and then they tended to be stable with the increase of precipitation in SRYR. These findings conclude that UAVB is suitable for monitoring multiscale PSD of an alpine grassland community over a large region, which will be useful for revealing the relationship of diversity-function, and helpful for conservation and sustainable management of the alpine grassland.Published onlin

Topological phase diagram and saddle point singularity in a tunable topological crystalline insulator

We report the evolution of the surface electronic structure and surface material properties of a topological crystalline insulator (TCI) Pb1-xSnxSe as a function of various material parameters including composition x, temperature T and crystal structure. Our spectroscopic data demonstrate the electronic groundstate condition for the saddle point singularity, the tunability of surface chemical potential, and the surface states' response to circularly polarized light. Our results show that each material parameter can tune the system between trivial and topological phase in a distinct way unlike as seen in Bi2Se3 and related compounds, leading to a rich and unique topological phase diagram. Our systematic studies of the TCI Pb1-xSnxSe are valuable materials guide to realize new topological phenomena.Comment: 10 pages, 7 figures. Expanded version of arXiv:1403.156