1,305 research outputs found

    Bath Road Master Plan, Wiscasset, Maine

    Get PDF
    The Wiscasset Bath Road Master Plan seeks to maximize development opportunities along Bath Road through the strategic coordination of traffic infrastructure improvements, land use policies and design standards while maintaining or improving the mobility and safety of U.S. Route 1. By planning for growth, Bath Road will increase safety, reduce congestion and enhance the visual character. Ultimately, this Master Plan is intended to help Wiscasset (the Town) shape a future for Bath Road and surrounding areas that reflects the needs and values of the community and preserves the Midcoast Region’s most important arterial highway. The Plan covers the areas adjacent to U.S. Route 1 from the Woolwich-Wiscasset town line to the northerly intersection of Flood Avenue and Bath Road. Bath Road Master Plan prepared for the town of Wiscasset, Maine. Report funded by Maine Department of Transportation and the town of Wiscasset. Contents include: Part I: 1. Introduction - 4. Public Outreach Part II: 5. Recommendations Part III: Appendix A - B Part IV: Appendix C -

    J/Psi Propagation in Hadronic Matter

    Full text link
    We study J/ψ\psi propagation in hot hadronic matter using a four-flavor chiral Lagrangian to model the dynamics and using QCD sum rules to model the finite size effects manifested in vertex interactions through form factors. Charmonium breakup due to scattering with light mesons is the primary impediment to continued propagation. Breakup rates introduce nontrivial temperature and momentum dependence into the J/ψ\psi spectral function.Comment: 6 Pages LaTeX, 3 postscript figures. Proceedings for Strangeness in Quark Matter 2003, Atlantic Beach, NC, March 12-17, 2003; minor corrections in version 2, to appear in J. Phys.

    Convergence of invariant densities in the small-noise limit

    Full text link
    This paper presents a systematic numerical study of the effects of noise on the invariant probability densities of dynamical systems with varying degrees of hyperbolicity. It is found that the rate of convergence of invariant densities in the small-noise limit is frequently governed by power laws. In addition, a simple heuristic is proposed and found to correctly predict the power law exponent in exponentially mixing systems. In systems which are not exponentially mixing, the heuristic provides only an upper bound on the power law exponent. As this numerical study requires the computation of invariant densities across more than 2 decades of noise amplitudes, it also provides an opportunity to discuss and compare standard numerical methods for computing invariant probability densities.Comment: 27 pages, 19 figures, revised with minor correction

    Adaptive Evolutionary Clustering

    Full text link
    In many practical applications of clustering, the objects to be clustered evolve over time, and a clustering result is desired at each time step. In such applications, evolutionary clustering typically outperforms traditional static clustering by producing clustering results that reflect long-term trends while being robust to short-term variations. Several evolutionary clustering algorithms have recently been proposed, often by adding a temporal smoothness penalty to the cost function of a static clustering method. In this paper, we introduce a different approach to evolutionary clustering by accurately tracking the time-varying proximities between objects followed by static clustering. We present an evolutionary clustering framework that adaptively estimates the optimal smoothing parameter using shrinkage estimation, a statistical approach that improves a naive estimate using additional information. The proposed framework can be used to extend a variety of static clustering algorithms, including hierarchical, k-means, and spectral clustering, into evolutionary clustering algorithms. Experiments on synthetic and real data sets indicate that the proposed framework outperforms static clustering and existing evolutionary clustering algorithms in many scenarios.Comment: To appear in Data Mining and Knowledge Discovery, MATLAB toolbox available at http://tbayes.eecs.umich.edu/xukevin/affec

    Pharmacological and Toxicological Properties of the Potent Oral γ-Secretase Modulator BPN-15606.

    Get PDF
    Alzheimer's disease (AD) is characterized neuropathologically by an abundance of 1) neuritic plaques, which are primarily composed of a fibrillar 42-amino-acid amyloid-β peptide (Aβ), as well as 2) neurofibrillary tangles composed of aggregates of hyperphosporylated tau. Elevations in the concentrations of the Aβ42 peptide in the brain, as a result of either increased production or decreased clearance, are postulated to initiate and drive the AD pathologic process. We initially introduced a novel class of bridged aromatics referred tγ-secretase modulatoro as γ-secretase modulators that inhibited the production of the Aβ42 peptide and to a lesser degree the Aβ40 peptide while concomitantly increasing the production of the carboxyl-truncated Aβ38 and Aβ37 peptides. These modulators potently lower Aβ42 levels without inhibiting the γ-secretase-mediated proteolysis of Notch or causing accumulation of carboxyl-terminal fragments of APP. In this study, we report a large number of pharmacological studies and early assessment of toxicology characterizing a highly potent γ-secretase modulator (GSM), (S)-N-(1-(4-fluorophenyl)ethyl)-6-(6-methoxy-5-(4-methyl-1H-imidazol-1-yl)pyridin-2-yl)-4-methylpyridazin-3-amine (BPN-15606). BPN-15606 displayed the ability to significantly lower Aβ42 levels in the central nervous system of rats and mice at doses as low as 5-10 mg/kg, significantly reduce Aβ neuritic plaque load in an AD transgenic mouse model, and significantly reduce levels of insoluble Aβ42 and pThr181 tau in a three-dimensional human neural cell culture model. Results from repeat-dose toxicity studies in rats and dose escalation/repeat-dose toxicity studies in nonhuman primates have designated this GSM for 28-day Investigational New Drug-enabling good laboratory practice studies and positioned it as a candidate for human clinical trials

    Genome maps across 26 human populations reveal population-specific patterns of structural variation.

    Get PDF
    Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome
    • …
    corecore