Testing the Distance-Duality Relation with a Combination of Cosmological Distance Observations

In this paper, we propose an accurate test of the distance-duality (DD) relation, $\eta=D_{L}(z)(1+z)^{-2}/D_{A}(z)=1$ (where $D_{L}$ and $D_{A}$ are the luminosity distances and angular diameter distances, respectively), with a combination of cosmological observational data of Type Ia Supernave (SNe Ia) from Union2 set and the galaxy cluster sample under an assumption of spherical model. In order to avoid bias brought by redshift incoincidence between observational data and to consider redshift error bars of both clusters and SNe Ia in analysis, we carefully choose the SNe Ia points which have the minimum acceptable redshift difference of the galaxy cluster sample ($|\Delta z|_{\rm min} =\sigma_{z, \rm SN}+\sigma_{z, \rm cluster}$). By assuming $\eta$ a constant and functions of the redshift parameterized by six different expressions, we find that there exists no conceivable evidence for variations in the DD relation concerning with observational data, since it is well satisfied within $1\sigma$ confidence level for most cases. Further considering different values of $\Delta z$ in constraining, we also find that the choosing of $\Delta z$ may play an important role in this model-independent test of the distance-duality relation for the spherical sample of galaxy clusters.Comment: 9 pages, 4 figures, 1 table. accepted for publication in Res. Astron. Astrophy

Testing the phenomenological interacting dark energy with observational H(z)H(z) data

In order to test the possible interaction between dark energy and dark matter, we investigate observational constraints on a phenomenological scenario, in which the ratio between the dark energy and matter densities is proportional to the power law case of the scale factor, $r\equiv (\rho_X/\rho_m)\propto a^{\xi}$. By using the Markov chain Monte Carlo method, we constrain the phenomenological interacting dark energy model with the newly revised $H(z)$ data, as well as the cosmic microwave background (CMB) observation from the 7-year Wilkinson Microwave Anisotropy Probe (WMAP7) results, the baryonic acoustic oscillation (BAO) observation from the spectroscopic Sloan Digital Sky Survey (SDSS) data release 7 (DR7) galaxy sample and the type Ia supernovae (SNe Ia) from Union2 set. The best-fit values of the model parameters are $\Omega_{m0}=0.27_{-0.02}^{+0.02}(1\sigma)_{-0.03}^{+0.04}(2\sigma)$, $\xi=3.15_{-0.50}^{+0.48}(1\sigma)_{-0.71}^{+0.72}(2\sigma)$, and $w_X=-1.05_{-0.14}^{+0.15}(1\sigma)_{-0.21}^{+0.21}(2\sigma)$, which are more stringent than previous results. These results show that the standard $\Lambda$CDM model without any interaction remains a good fit to the recent observational data; however, the interaction that the energy transferring from dark matter to dark energy is slightly favored over the interaction from dark energy to dark matter. It is also shown that the $H(z)$ data can give more stringent constraints on the phenomenological interacting scenario when combined to CMB and BAO observations, and the confidence regions of $H(z)$+BAO+CMB, SNe+BAO+CMB, and $H(z)$+SNe+BAO+CMB combinations are consistent with each other.Comment: 6 pages, 4 figures, 1 table. MNRAS in pres

Structure and Mechanism of Mycobacterial Topoisomerase I

The enzyme DNA topoisomerase I is an essential enzyme that plays an important role in eukaryotic and prokaryotic cellular processes such as DNA replication, transcription, recombination and repair. Mycobacterium tuberculosistopoisomerase I (MtTOP1) is a validated drug target for antituberculosis treatment. Mycobacterial topoisomerase I regulates the topological constraints in chromosomes and helps in maintaining the growth of mycobacteria. The N- terminal domain (NTD) of mycobacterial topoisomerase I contains conserved catalytic domains that along with the active site Tyrosine are involved in cleaving and rejoining a single strand of DNA. Magnesium is required in DNA cleavage activity of type IA topoisomerases. The C-terminal domain (CTD) of mycobacterial topoisomerase I is divided into four subdomains (D5-D8) and a positively charged tail. Each subdomain has a GxxGPY sequence motif. The DNA binding, relaxation, cleavage, religation, catenation and decatenation ability of each subdomains of CTD were studied. The present study shows that each subdomain has its own characteristics. Subdomain D8 and D7 are responsible for maintaining the relaxation activity of mycobacterial topoisomerase I. Subdomain D5 is essential to maintain the DNA cleavage, religation, catenation and decatenation activity. A new crystal structure of MtTOP1-704t (amino acids A2-T704 containing NTD+D5 domains) was obtained. Structures with ssDNA substrate bound to the active site (Y342) in the presence and absence of Mg2+ were also investigated. Significant enzyme conformational changes upon DNA binding place the catalytic tyrosine in a pre-transition position for cleavage of a specific phosphodiester linkage to form a covalent intermediate. Meanwhile, the enzyme/DNA complex with Mg2+ bound at active site may present the post- transition state for religation in the enzyme’s multiple-state DNA relaxation activity. The critical function of a strictly conserved glutamic acid in acid-base catalysis of the DNA cleavage step was also demonstrated by site-directed mutagenesis. The present work provides new functional insights into the more stringent requirement for DNA rejoining versus cleavage by type IA topoisomerase, and further establishes the potential for select interference of DNA rejoining via specific inhibitors

ヒトの高周波振動知覚の類似特性に基づく触覚変調

Tohoku University昆陽雅司課

Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

In this paper, we study the problem of Team Member Replacement: given a team of people embedded in a social network working on the same task, find a good candidate who can fit in the team after one team member becomes unavailable. We conjecture that a good team member replacement should have good skill matching as well as good structure matching. We formulate this problem using the concept of graph kernel. To tackle the computational challenges, we propose a family of fast algorithms by (a) designing effective pruning strategies, and (b) exploring the smoothness between the existing and the new team structures. We conduct extensive experimental evaluations on real world datasets to demonstrate the effectiveness and efficiency. Our algorithms (a) perform significantly better than the alternative choices in terms of both precision and recall; and (b) scale sub-linearly.Comment: Initially submitted to KDD 201