Electronic and magnetic properties of V-doped anatase TiO2_{2} from first principles

We report a first-principles study on the geometric, electronic and magnetic properties of V-doped anatase TiO$_{2}$. The DFT+U (Hubbard coefficient) approach predicts semiconductor band structures for Ti$_{1-x}$V$_{x}$O$_{2}$ (x=6.25 and 12.5%), in good agreement with the poor conductivity of samples, while the standard calculation within generalized gradient approximation fails. Theoretical results show that V atoms tend to stay close and result in strong ferromagnetism through superexchange interactions. Oxygen vacancy induced magnetic polaron could produce long-range ferromagnetic interaction between largely separated magnetic impurities. The experimentally observed ferromagnetism in V-doped anatase TiO$_{2}$ at room temperature may originate from a combination of short-range superexchange coupling and long-range bound magnetic polaron percolation.Comment: 12 pages and 4 figures (to be appeared in PRB as a brief report

Microbial community pattern detection in human body habitats via ensemble clustering framework

The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural patterns. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome.Comment: BMC Systems Biology 201