Mass Function of Binary Massive Black Holes in Active Galactic Nuclei

If the activity of active galactic nuclei (AGNs) is predominantly induced by major galaxy mergers, then a significant fraction of AGNs should harbor binary massive black holes in their centers. We study the mass function of binary massive black holes in nearby AGNs based on the observed AGN black-hole mass function and theory of evolution of binary massive black holes interacting with a massive circumbinary disk in the framework of coevolution of massive black holes and their host galaxies. The circumbinary disk is assumed to be steady, axisymmetric, geometrically thin, self-regulated, self-gravitating but non-fragmenting with a fraction of Eddington accretion rate, which is typically one tenth of Eddington value. The timescale of orbital decay is {then} estimated as ~10^8yr for equal mass black-hole, being independent of the black hole mass, semi-major axis, and viscosity parameter but dependent on the black-hole mass ratio, Eddington ratio, and mass-to-energy conversion efficiency. This makes it possible for any binary massive black holes to merge within a Hubble time by the binary-disk interaction. We find that (1.8+-0.6%) for the equal mass ratio and (1.6+-0.4%) for the one-tenth mass ratio of the total number of nearby AGNs have close binary massive black holes with orbital period less than ten years in their centers, detectable with on-going highly sensitive X-ray monitors such as Monitor of All-sky X-ray Image and/or Swift/Burst Alert Telescope. Assuming that all binary massive black holes have the equal mass ratio, about 20% of AGNs with black hole masses of 10^{6.5-7}M_sun has the close binaries and thus provides the best chance to detect them.Comment: 22 pages, 11 figures, accepted for publication in PASJ. The draft was significantly revised. The major differences from the previous version are as follows: (1)The circumbinary disk is assumed to be a steady, axisymmetric, geometrically thin, self-gravitating, self-regulated but non-fragmenting. (2)The stellar scattering process is taken account of in the merging process of binary black hole

Single-epoch supernova classification with deep convolutional neural networks

Supernovae Type-Ia (SNeIa) play a significant role in exploring the history of the expansion of the Universe, since they are the best-known standard candles with which we can accurately measure the distance to the objects. Finding large samples of SNeIa and investigating their detailed characteristics have become an important issue in cosmology and astronomy. Existing methods relied on a photometric approach that first measures the luminance of supernova candidates precisely and then fits the results to a parametric function of temporal changes in luminance. However, it inevitably requires multi-epoch observations and complex luminance measurements. In this work, we present a novel method for classifying SNeIa simply from single-epoch observation images without any complex measurements, by effectively integrating the state-of-the-art computer vision methodology into the standard photometric approach. Our method first builds a convolutional neural network for estimating the luminance of supernovae from telescope images, and then constructs another neural network for the classification, where the estimated luminance and observation dates are used as features for classification. Both of the neural networks are integrated into a single deep neural network to classify SNeIa directly from observation images. Experimental results show the effectiveness of the proposed method and reveal classification performance comparable to existing photometric methods with multi-epoch observations.Comment: 7 pages, published as a workshop paper in ICDCS2017, in June 201

Coalition structure generation in cooperative games with compact representations

This paper presents a new way of formalizing the coalition structure generation problem (CSG) so that we can apply constraint optimization techniques to it. Forming effective coalitions is a major research challenge in AI and multi-agent systems. CSG involves partitioning a set of agents into coalitions to maximize social surplus. Traditionally, the input of the CSG problem is a black-box function called a characteristic function, which takes a coalition as input and returns the value of the coalition. As a result, applying constraint optimization techniques to this problem has been infeasible. However, characteristic functions that appear in practice often can be represented concisely by a set of rules, rather than treating the function as a black box. Then we can solve the CSG problem more efficiently by directly applying constraint optimization techniques to this compact representation. We present new formalizations of the CSG problem by utilizing recently developed compact representation schemes for characteristic functions. We first characterize the complexity of CSG under these representation schemes. In this context, the complexity is driven more by the number of rules than by the number of agents. As an initial step toward developing efficient constraint optimization algorithms for solving the CSG problem, we also develop mixed integer programming formulations and show that an off-the-shelf optimization package can perform reasonably well

Metro traffic optimisation accounting for the disbenefit of halting between stations

Computerised regulation for disturbed traffic in metro-type railways is proposed. Previous work has used optimisation techniques to minimise disbenefits to passengers, such as waiting time and journey time, in the objective function. The particular disbenefit of trains being halted between stations is introduced in this thesis, in combination with those already mentioned. An effective method in real operations for preventing trains being halted between stations is to hold trains already at stations and to allow running trains to reach the next station when a particular train departure is delayed. The proposed algorithm uses this ‘stop-all-trains-at-once’ philosophy combined with optimisation ideas, in a sequentially structured approach. A further consideration from real operations is the fact that it is not possible to predict precisely when the delayed train will re-start. Estimates of the re-starting time will improve as the delay increases, and the proposed scheme takes this into account. Numerous simulations were undertaken to investigate the performance of the regulation algorithm. It is shown that the proposed regulation algorithm is effective in reducing the disbenefit to passengers from disturbed traffic for various characteristic metros with different passenger flows.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of a yeast cell surface display method using the SpyTag/SpyCatcher system

生体内タンパク質ライゲーションを用いた新規細胞表層ディスプレイ法の開発 --新しい手法によるタンパク質工学の進展--. 京都大学プレスリリース. 2021-05-28.Yeast cell surface display (YSD) has been used to engineer various proteins, including antibodies. Directed evolution, which subjects a gene to iterative rounds of mutagenesis, selection and amplification, is useful for protein engineering. In vivo continuous mutagenesis, which continuously diversifies target genes in the host cell, is a promising tool for accelerating directed evolution. However, combining in vivo continuous evolution and YSD is difficult because mutations in the gene encoding the anchor proteins may inhibit the display of target proteins on the cell surface. In this study, we have developed a modified YSD method that utilises SpyTag/SpyCatcher-based in vivo protein ligation. A nanobody fused with a SpyTag of 16 amino acids and an anchor protein fused with a SpyCatcher of 113 amino acids are encoded by separate gene cassettes and then assembled via isopeptide bond formation. This system achieved a high display efficiency of more than 90%, no intercellular protein ligation events, and the enrichment of target cells by cell sorting. These results suggested that our system demonstrates comparable performance with conventional YSD methods; therefore, it can be an appropriate platform to be integrated with in vivo continuous evolution

Differential Regulation by IL-1β and EGF of Expression of Three Different Hyaluronan Synthases in Oral Mucosal Epithelial Cells and Fibroblasts and Dermal Fibroblasts: Quantitative Analysis Using Real-Time RT-PCR

Using “real-time RT-PCR”, we assessed the expression of three different hyaluronan synthase genes, HAS1, HAS2, and HAS3, by measuring their mRNA amounts in cultured human oral mucosal epithelial (COME) cells, oral mucosal fibroblasts, and dermal fibroblasts, and investigated the effects of interleukin-1β (IL-1β) and epidermal growth factor (EGF). When COME cells were treated with IL-1β or EGF, early and marked increases and subsequent rapid decreases were observed for all HAS genes and, moreover, actual changes in hyaluronan synthesis subsequently occurred. The effects of IL-1β stimulation were concentration-dependent and the maximal response to the EGF stimulation was observed at a low concentration (0.1 ng per mL). When two different types of fibroblasts were treated with IL-1β or EGF, increased expression with different degrees and rates of three different HAS genes and subsequent increased synthesis of hyaluronan were also observed. In addition, HAS1 gene expression was not detectable in the mucosal fibroblasts, while weak HAS3 gene expression was detected in the dermal fibroblasts. Taken together, it is likely that the regulation of the expression of the three different HAS genes is different between oral mucosa and skin, which may be of significance for elucidating some of the differences between these tissues in wound healing

Infrared and hard X-ray diagnostics of AGN identification from the Swift/BAT and AKARI all-sky surveys

We combine data from two all-sky surveys in order to study the connection between the infrared and hard X-ray (>10keV) properties for local active galactic nuclei (AGN). The Swift/Burst Alert Telescope all-sky survey provides an unbiased, flux-limited selection of hard X-ray detected AGN. Cross-correlating the 22-month hard X-ray survey with the AKARI all-sky survey, we studied 158 AGN detected by the AKARI instruments. We find a strong correlation for most AGN between the infrared (9, 18, and 90 micron) and hard X-ray (14-195 keV) luminosities, and quantify the correlation for various subsamples of AGN. Partial correlation analysis confirms the intrinsic correlation after removing the redshift contribution. The correlation for radio galaxies has a slope and normalization identical to that for Seyfert 1s, implying similar hard X-ray/infrared emission processes in both. In contrast, Compton-thick sources show a large deficit in the hard X-ray band, because high gas column densities diminish even their hard X-ray luminosities. We propose two photometric diagnostics for source classification: one is an X-ray luminosity vs. infrared color diagram, in which type 1 radio-loud AGN are well isolated from the others in the sample. The other uses the X-ray vs. infrared color as a useful redshift-independent indicator for identifying Compton-thick AGN. Importantly, Compton-thick AGN and starburst galaxies in composite systems can also be differentiated in this plane based upon their hard X-ray fluxes and dust temperatures. This diagram may be useful as a new indicator to classify objects in new and upcoming surveys such as WISE and NuSTAR.Comment: 17 pages, 5 figures, 5 tables. Accepted for publication in the Astrophysical Journa