78,910 research outputs found

    The EM Algorithm and the Rise of Computational Biology

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    In the past decade computational biology has grown from a cottage industry with a handful of researchers to an attractive interdisciplinary field, catching the attention and imagination of many quantitatively-minded scientists. Of interest to us is the key role played by the EM algorithm during this transformation. We survey the use of the EM algorithm in a few important computational biology problems surrounding the "central dogma"; of molecular biology: from DNA to RNA and then to proteins. Topics of this article include sequence motif discovery, protein sequence alignment, population genetics, evolutionary models and mRNA expression microarray data analysis.Comment: Published in at http://dx.doi.org/10.1214/09-STS312 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Doping dependence of the electron-doped cuprate superconductors from the antiferromagnetic properties of the Hubbard model

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    Within the Kotliar-Ruckenstein slave-boson approach, we have studied the antiferromagnetic (AF) properties for the tt-tt'-tt''-UU model applied to electron-doped cuprate superconductors. Due to inclusion of spin fluctuations the AF order decreases with doping much faster than obtained in the Hartree-Fock theory. Under an intermediate {\it constant} UU the calculated doping evolution of the spectral intensity has satisfactorily reproduced the experimental results, without need of a strongly doping-dependent UU as argued earlier. This may reconcile a discrepancy suggested in recent studies on photoemission and optical conductivity.Comment: 5 pages, 4 eps figures, minor improvement, references added, to appear in Phys. Rev.

    Study of gossamer superconductivity and antiferromagnetism in the t-J-U model

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    The d-wave superconductivity (dSC) and antiferromagnetism are analytically studied in a renormalized mean field theory for a two dimensional t-J model plus an on-site repulsive Hubbard interaction UU. The purpose of introducing the UU term is to partially impose the no double occupancy constraint by employing the Gutzwiller approximation. The phase diagrams as functions of doping δ\delta and UU are studied. Using the standard value of t/J=3.0t/J=3.0 and in the large UU limit, we show that the antiferromagnetic (AF) order emerges and coexists with the dSC in the underdoped region below the doping δ0.1\delta\sim0.1. The dSC order parameter increases from zero as the doping increases and reaches a maximum near the optimal doping δ0.15\delta\sim0.15. In the small UU limit, only the dSC order survives while the AF order disappears. As UU increased to a critical value, the AF order shows up and coexists with the dSC in the underdoped regime. At half filing, the system is in the dSC state for small UU and becomes an AF insulator for large UU. Within the present mean field approach, We show that the ground state energy of the coexistent state is always lower than that of the pure dSC state.Comment: 7 pages, 8 figure

    Effects of QCD Resummation on W+hW^+h and tbˉt\bar b Production at the Tevatron

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    The resummation of multiple soft gluon emission affects the production rate and kinematic distributions of W+hW^+h (where h is a Higgs boson) and tbˉt \bar b pairs at the Tevatron with s=2\sqrt{s}=2 TeV. Using the Collins-Soper-Sterman resummation formalism, the production rate is enhanced over the next-to-leading-order (NLO) prediction by 2-3% for the W+hW^+h process, for Higgs boson masses between 80-120 GeV, and over 3% for the tbˉt\bar b process for mt=175m_t=175 GeV. After resummation, the tbˉt\bar b rate changes by 12-13% when mtm_t is varied by ±5\pm 5 GeV. Various kinematic distributions are presented for the individual final state particles and for the pair. The explicit radiation of hard gluons in NLO QCD is included also for the tbˉt\bar b final state.Comment: 9 pages, 12 Postscript figures, in RevTeX format, uses epsf.te

    Economic Sizing of Distributed Energy Resources for Reliable Community Microgrids

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    Community microgrids offer many advantages for power distribution systems. When there is an extreme event happening, distribution systems can be seamlessly partitioned into several community microgrids for uninterrupted supply to the end-users. In order to guarantee the system reliability, distributed energy resources (DERs) should be sized for ensuring generation adequacy to cover unexpected events. This paper presents a comprehensive methodology for DERs selection in community microgrids, and an economic approach to meet the system reliability requirements. Algorithms of discrete time Fourier transform (DTFT) and particle swarm optimization (PSO) are employed to find the optimal solution. Uncertainties of load demand and renewable generation are taken into consideration. As part of the case study, a sensitivity analysis is carried out to show the renewable generation impact on DERs' capacity planning.Comment: 5 pages, 6 figures, 1 table, 2017 IEEE Power & Energy Society General Meeting. arXiv admin note: substantial text overlap with arXiv:1708.0102

    Advection-dominated accretion, jets and the spectral energy distribution of LINERs

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    Low-luminosity active galactic nuclei (LLAGNs) represent the bulk of the AGN population in the present-day universe and they trace low-level accreting supermassive black holes. The observational properties of LLAGNs suggest that their central engines are intrinsically different from those of more luminous AGNs. It has been suggested that accretion in LLAGNs occurs via an advection-dominated accretion flow (ADAF) associated with strong jets. In order to probe the accretion physics in LLAGNs as a class, we model the multiwavelength spectral energy distributions (SEDs) of 24 LINERs (taken from a recent compilation by Eracleous et al.) with a coupled accretion-jet model. The accretion flow is modeled as an inner ADAF outside of which there is a truncated standard thin disk. These SEDs include radio, near-IR to near-UV HST data, and Chandra X-ray data. We find that the radio emission is severely underpredicted by ADAF models but can be explained by the relativistic jet. The origin of the X-ray radiation in most sources can be explained by three distinct scenarios: the X-rays can be dominated by emission from the ADAF, the jet, or from both components contributing at similar levels. From the model fits, we estimate important parameters of the central engine of LINERs, such as the mass accretion rate -- relevant for studies of the feeding of AGNs -- and the mass-loss rate in the jet and the jet power -- relevant for studies of the kinetic feedback from jets.Comment: 6 pages, 3 figures, to be published in the Proceedings of the IAU Symposium no. 267, "Co-Evolution of Central Black Holes and Galaxies: Feeding and Feedback", eds. B.M. Peterson, R.S. Somerville and T. Storchi-Bergmann, in pres

    Statistical Mechanical Treatments of Protein Amyloid Formation

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    Protein aggregation is an important field of investigation because it is closely related to the problem of neurodegenerative diseases, to the development of biomaterials, and to the growth of cellular structures such as cyto-skeleton. Self-aggregation of protein amyloids, for example, is a complicated process involving many species and levels of structures. This complexity, however, can be dealt with using statistical mechanical tools, such as free energies, partition functions, and transfer matrices. In this article, we review general strategies for studying protein aggregation using statistical mechanical approaches and show that canonical and grand canonical ensembles can be used in such approaches. The grand canonical approach is particularly convenient since competing pathways of assembly and dis-assembly can be considered simultaneously. Another advantage of using statistical mechanics is that numerically exact solutions can be obtained for all of the thermodynamic properties of fibrils, such as the amount of fibrils formed, as a function of initial protein concentration. Furthermore, statistical mechanics models can be used to fit experimental data when they are available for comparison.Comment: Accepted to IJM