1,123 research outputs found

    Spatial and Seasonal Distribution of American Whaling and Whales in the Age of Sail

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    American whalemen sailed out of ports on the east coast of the United States and in California from the 18th to early 20th centuries, searching for whales throughout the world’s oceans. From an initial focus on sperm whales (Physeter macrocephalus) and right whales (Eubalaena spp.), the array of targeted whales expanded to include bowhead whales (Balaena mysticetus), humpback whales (Megaptera novaeangliae), and gray whales (Eschrichtius robustus). Extensive records of American whaling in the form of daily entries in whaling voyage logbooks contain a great deal of information about where and when the whalemen found whales. We plotted daily locations where the several species of whales were observed, both those caught and those sighted but not caught, on world maps to illustrate the spatial and temporal distribution of both American whaling activity and the whales. The patterns shown on the maps provide the basis for various inferences concerning the historical distribution of the target whales prior to and during this episode of global whaling

    Preliminary Limits on the WIMP-Nucleon Cross Section from the Cryogenic Dark Matter Search (CDMS)

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    We are conducting an experiment to search for WIMPs, or weakly-interacting massive particles, in the galactic halo using terrestrial detectors. This generic class of hypothetical particles, whose properties are similar to those predicted by extensions of the standard model of particle physics, could comprise the cold component of non-baryonic dark matter. We describe our experiment, which is based on cooled germanium and silicon detectors in a shielded low-background cryostat. The detectors achieve a high degree of background rejection through the simultaneous measurement of the energy in phonons and ionization. Using exposures on the order of one kilogram-day from initial runs of our experiment, we have achieved (preliminary) upper limits on the WIMP-nucleon cross section that are comparable to much longer runs of other experiments.Comment: 5 LaTex pages, 5 eps figs, epsf.sty, espcrc2dsa2.sty. Proceedings of TAUP97, Gran Sasso, Italy, 7-11 Sep 1997, Nucl. Phys. Suppl., A. Bottino, A. di Credico and P. Monacelli (eds.). See also http://cfpa.berkeley.ed

    A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

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    The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

    An Anti-Human ICAM-1 Antibody Inhibits Rhinovirus-Induced Exacerbations of Lung Inflammation

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    Human rhinoviruses (HRV) cause the majority of common colds and acute exacerbations of asthma and chronic obstructive pulmonary disease (COPD). Effective therapies are urgently needed, but no licensed treatments or vaccines currently exist. Of the 100 identified serotypes, ∼90% bind domain 1 of human intercellular adhesion molecule-1 (ICAM-1) as their cellular receptor, making this an attractive target for development of therapies; however, ICAM-1 domain 1 is also required for host defence and regulation of cell trafficking, principally via its major ligand LFA-1. Using a mouse anti-human ICAM-1 antibody (14C11) that specifically binds domain 1 of human ICAM-1, we show that 14C11 administered topically or systemically prevented entry of two major groups of rhinoviruses, HRV16 and HRV14, and reduced cellular inflammation, pro-inflammatory cytokine induction and virus load in vivo. 14C11 also reduced cellular inflammation and Th2 cytokine/chemokine production in a model of major group HRV-induced asthma exacerbation. Interestingly, 14C11 did not prevent cell adhesion via human ICAM-1/LFA-1 interactions in vitro, suggesting the epitope targeted by 14C11 was specific for viral entry. Thus a human ICAM-1 domain-1-specific antibody can prevent major group HRV entry and induction of airway inflammation in vivo

    Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation

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    Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas

    Characterization of complex networks: A survey of measurements

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    Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

    Frequent, Geographically Structured Heteroplasmy in the Mitochondria of a Flowering Plant, Ribwort Plantain (Plantago lanceolata)

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    Recent research has convincingly documented cases of mitochondrial heteroplasmy in a small set of wild and cultivated plant species. Heteroplasmy is suspected to be common in flowering plants and investigations of additional taxa may help understand the mechanisms generating heteroplasmy as well as its effects on plant phenotypes. The role of mitochondrial heteroplasmy is of particular interest in plants as cytoplasmic male sterility is controlled by mitochondrial genotypes, sometimes leading to co-occurring female and hermaphroditic individuals (gynodioecy). Paternal leakage may be important in the evolution of mating systems in such populations. We conducted a genetic survey of the gynodioecious plant Plantago lanceolata, in which heteroplasmy has not previously been reported, and estimated the frequencies of mitochondrial genotypes and heteroplasmy. Sanger sequence genotyping of 179 individuals from 15 European populations for two polymorphic mitochondrial loci, atp6 and rps12, identified 15 heteroplasmic individuals. These were distributed among 6 of the 10 populations that had polymorphisms in the target loci and represented 8% of all sampled individuals and 15% of the individuals in those 6 populations. The incidence was highest in Northern England and Scotland. Our results are consistent with geographic differences in the incidence of paternal leakage and/or the rates of nuclear restoration of male fertility

    Alien Invasive Slider Turtle in Unpredicted Habitat: A Matter of Niche Shift or of Predictors Studied?

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    BACKGROUND: Species Distribution Models (SDMs) aim on the characterization of a species' ecological niche and project it into geographic space. The result is a map of the species' potential distribution, which is, for instance, helpful to predict the capability of alien invasive species. With regard to alien invasive species, recently several authors observed a mismatch between potential distributions of native and invasive ranges derived from SDMs and, as an explanation, ecological niche shift during biological invasion has been suggested. We studied the physiologically well known Slider turtle from North America which today is widely distributed over the globe and address the issue of ecological niche shift versus choice of ecological predictors used for model building, i.e., by deriving SDMs using multiple sets of climatic predictor. PRINCIPAL FINDINGS: In one SDM, predictors were used aiming to mirror the physiological limits of the Slider turtle. It was compared to numerous other models based on various sets of ecological predictors or predictors aiming at comprehensiveness. The SDM focusing on the study species' physiological limits depicts the target species' worldwide potential distribution better than any of the other approaches. CONCLUSION: These results suggest that a natural history-driven understanding is crucial in developing statistical models of ecological niches (as SDMs) while "comprehensive" or "standard" sets of ecological predictors may be of limited use
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