Top-N Recommendation on Graphs

Recommender systems play an increasingly important role in online applications to help users find what they need or prefer. Collaborative filtering algorithms that generate predictions by analyzing the user-item rating matrix perform poorly when the matrix is sparse. To alleviate this problem, this paper proposes a simple recommendation algorithm that fully exploits the similarity information among users and items and intrinsic structural information of the user-item matrix. The proposed method constructs a new representation which preserves affinity and structure information in the user-item rating matrix and then performs recommendation task. To capture proximity information about users and items, two graphs are constructed. Manifold learning idea is used to constrain the new representation to be smooth on these graphs, so as to enforce users and item proximities. Our model is formulated as a convex optimization problem, for which we need to solve the well-known Sylvester equation only. We carry out extensive empirical evaluations on six benchmark datasets to show the effectiveness of this approach.Comment: CIKM 201

Multiband effects on the conductivity for a multiband Hubbard model

The newly discovered iron-based superconductors have attracted lots of interests, and the corresponding theoretical studies suggest that the system should have six bands. In this paper, we study the multiband effects on the conductivity based on the exact solutions of one-dimensional two-band Hubbard model. We find that the orbital degree of freedom might enhance the critical value $U_c$ of on-site interaction of the transition from a metal to an insulator. This observation is helpful to understand why undoped High-$T_c$ superconductors are usually insulators, while recently discovered iron-based superconductors are metal. Our results imply that the orbital degree of freedom in the latter cases might play an essential role.Comment: 4 pages, 5 figure

Hidden Broad Line Seyfert 2 Galaxies in the CfA and 12micron Samples

We report the results of a spectropolarimetric survey of the CfA and 12micron samples of Seyfert 2 galaxies (S2s). Polarized (hidden) broad line regions (HBLRs) are confirmed in a number of galaxies, and several new cases (F02581-1136, MCG -3-58-7, NGC 5995, NGC 6552, NGC 7682) are reported. The 12micron S2 sample shows a significantly higher incidence of HBLR (50%) than its CfA counterpart (30%), suggesting that the latter may be incomplete in hidden AGNs. Compared to the non-HBLR S2s, the HBLR S2s display distinctly higher radio power relative to their far-infrared output and hotter dust temperature as indicated by the f25/f60 color. However, the level of obscuration is indistinguishable between the two types of S2. These results strongly support the existence of two intrinsically different populations of S2: one harboring an energetic, hidden S1 nucleus with BLR, and the other, a ``pure S2'', with weak or absent S1 nucleus and a strong, perhaps dominating starburst component. Thus, the simple purely orientation-based unification model is not applicable to all Seyfert galaxies.Comment: 5 pages with embedded figs, ApJ Letters, in pres

Ground-state fidelity of Luttinger liquids: A wave functional approach

We use a wave functional approach to calculate the fidelity of ground states in the Luttinger liquid universality class of one-dimensional gapless quantum many-body systems. The ground-state wave functionals are discussed using both the Schrodinger (functional differential equation) formulation and a path integral formulation. The fidelity between Luttinger liquids with Luttinger parameters K and K' is found to decay exponentially with system size, and to obey the symmetry F(K,K')=F(1/K,1/K') as a consequence of a duality in the bosonization description of Luttinger liquids.Comment: 13 pages, IOP single-column format. Sec. 3 expanded with discussion of short-distance cut-off. Some typos corrected. Ref. 44 in v2 is now footnote 2 (moved by copy editor). Published versio

Bioinformatics tools for analysing viral genomic data

The field of viral genomics and bioinformatics is experiencing a strong resurgence due to high-throughput sequencing (HTS) technology, which enables the rapid and cost-effective sequencing and subsequent assembly of large numbers of viral genomes. In addition, the unprecedented power of HTS technologies has enabled the analysis of intra-host viral diversity and quasispecies dynamics in relation to important biological questions on viral transmission, vaccine resistance and host jumping. HTS also enables the rapid identification of both known and potentially new viruses from field and clinical samples, thus adding new tools to the fields of viral discovery and metagenomics. Bioinformatics has been central to the rise of HTS applications because new algorithms and software tools are continually needed to process and analyse the large, complex datasets generated in this rapidly evolving area. In this paper, the authors give a brief overview of the main bioinformatics tools available for viral genomic research, with a particular emphasis on HTS technologies and their main applications. They summarise the major steps in various HTS analyses, starting with quality control of raw reads and encompassing activities ranging from consensus and de novo genome assembly to variant calling and metagenomics, as well as RNA sequencing