Gravitational waves with dark matter minispikes: the combined effect

It was shown that the dark matter(DM) minihalo around an intermediate mass black hole(IMBH) can be redistributed into a cusp, called the DM minispike. We consider an intermediate-mass-ratio inspiral consisting of an IMBH harbored in a DM minispike with nonannihilating DM particles and a small black hole(BH) orbiting around it. We investigate gravitational waves(GWs) produced by this system and analyze the waveforms with the comprehensive consideration of gravitational pull, dynamical friction and accretion of the minispike and calculate the time difference and phase difference caused by it. We find that for a certain range of frequency, the inspiralling time of the system is dramatically reduced for smaller central IMBH and large density of DM. For the central IMBH with $10^5M_\odot$, the time of merger is ahead, which can be distinguished by LISA, Taiji and Tianqin. We focus on the effect of accretion and compare it with that of gravitational pull and friction. We find that the accretion mass is a small quantity compared to the initial mass of the small BH and the accretion effect is inconspicuous compared with friction. However, the accumulated phase shift caused by accretion is large enough to be detected by LISA, Taiji and Tianqin, which indicate that the accretion effect can not be ignored in the detection of GWs.Comment: 10 pages, 14 figure

Product-based Neural Networks for User Response Prediction

Predicting user responses, such as clicks and conversions, is of great importance and has found its usage in many Web applications including recommender systems, web search and online advertising. The data in those applications is mostly categorical and contains multiple fields; a typical representation is to transform it into a high-dimensional sparse binary feature representation via one-hot encoding. Facing with the extreme sparsity, traditional models may limit their capacity of mining shallow patterns from the data, i.e. low-order feature combinations. Deep models like deep neural networks, on the other hand, cannot be directly applied for the high-dimensional input because of the huge feature space. In this paper, we propose a Product-based Neural Networks (PNN) with an embedding layer to learn a distributed representation of the categorical data, a product layer to capture interactive patterns between inter-field categories, and further fully connected layers to explore high-order feature interactions. Our experimental results on two large-scale real-world ad click datasets demonstrate that PNNs consistently outperform the state-of-the-art models on various metrics.Comment: 6 pages, 5 figures, ICDM201

The effects of large extra dimensions on associated ttˉh0t\bar{t} h^0 production at linear colliders

In the framework of the large extra dimensions (LED) model, the effects of LED on the processes \rrtth and \eetth at future linear colliders are investigated in both polarized and unpolarized collision modes. The results show that the virtual Kaluza-Klein (KK) graviton exchange can significantly modify the standard model expectations for these processes with certain polarizations of initial states. The process \rrtth with $\sqrt{s}=3.5 TeV$ allows the effective scale $\Lambda_T$ to be probed up to 7.8 and 8.6 TeV in the unpolarized and $P_{\gamma} = 0.9$, J=2 polarized $\gamma \gamma$ collision modes, respectively. For the \eetth process with $\sqrt{s}=3.5 TeV$, the upper limits of $\Lambda_T$ to be observed can be 6.7 and 7.0 TeV in the unpolarized and $P_{e^+} = 0.6$, $P_{e^-} = 0.8$, $-+$ polarized $e^+e^-$ collision modes, respectively. We find the \rrtth channel in J=2 polarized photon collision mode provides a possibility to improve the sensitivity to the graviton tower exchange.Comment: To be appeard in Physical Review

Gene cloning and characterization of a novel esterase from activated sludge metagenome

A metagenomic library was prepared using pCC2FOS vector containing about 3.0 Gbp of community DNA from the microbial assemblage of activated sludge. Screening of a part of the un-amplified library resulted in the finding of 1 unique lipolytic clone capable of hydrolyzing tributyrin, in which an esterase gene was identified. This esterase/lipase gene consists of 834 bp and encodes a polypeptide (designated EstAS) of 277 amino acid residuals with a molecular mass of 31 kDa. Sequence analysis indicated that it showed 33% and 31% amino acid identity to esterase/lipase from Gemmata obscuriglobus UQM 2246 (ZP_02733109) and Yarrowia lipolytica CLIB122 (XP_504639), respectively; and several conserved regions were identified, including the putative active site, HSMGG, a catalytic triad (Ser92, His125 and Asp216) and a LHYFRG conserved motif. The EstAS was overexpressed, purified and shown to hydrolyse p-nitrophenyl (NP) esters of fatty acids with short chain lengths (≤ C8). This EstAS had optimal temperature and pH at 35°C and 9.0, respectively, by hydrolysis of p-NP hexanoate. It also exhibited the same level of stability over wide temperature and pH ranges and in the presence of metal ions or detergents. The high level of stability of esterase EstAS with its unique substrate specificities make itself highly useful for biotechnological applications