855 research outputs found

    Bifurcation Analysis of Reaction Diffusion Systems on Arbitrary Surfaces

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    In this paper we present computational techniques to investigate the solutions of two-component, nonlinear reaction-diffusion (RD) systems on arbitrary surfaces. We build on standard techniques for linear and nonlinear analysis of RD systems, and extend them to operate on large-scale meshes for arbitrary surfaces. In particular, we use spectral techniques for a linear stability analysis to characterize and directly compose patterns emerging from homogeneities. We develop an implementation using surface finite element methods and a numerical eigenanalysis of the Laplace-Beltrami operator on surface meshes. In addition, we describe a technique to explore solutions of the nonlinear RD equations using numerical continuation. Here, we present a multiresolution approach that allows us to trace solution branches of the nonlinear equations efficiently even for large-scale meshes. Finally, we demonstrate the working of our framework for two RD systems with applications in biological pattern formation: a Brusselator model that has been used to model pattern development on growing plant tips, and a chemotactic model for the formation of skin pigmentation patterns. While these models have been used previously on simple geometries, our framework allows us to study the impact of arbitrary geometries on emerging patterns.Comment: This paper was submitted at the Journal of Mathematical Biology, Springer on 07th July 2015, in its current form (barring image references on the last page and cosmetic changes owning to rebuild for arXiv). The complete body of work presented here was included and defended as a part of my PhD thesis in Nov 2015 at the University of Ber

    Retrofitting of a non-invasive Bunch Shape Monitor for GSI LINACs

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    Performance demonstration of the non-intercepting Bunch Shape Monitor at UNILAC

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    {EgoRenderer}: {R}endering Human Avatars from Egocentric Camera Images

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    Goodbye to Chi-by-Eye: A Bayesian Analysis of Photometric Binaries in Six Open Clusters

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    Using Gaia DR3, Pan-STARRS and 2MASS data, we self-consistently define the cluster parameters and binary demographics for the open clusters (OCs) NGC 2168 (M35), NGC 7789, NGC 6819, NGC 2682 (M67), NGC 188, and NGC 6791. These clusters span in age from ~200 Myr (NGC 2168) to more than ~8 Gyr (NGC 6791) and have all been extensively studied in the literature. We use the Bayesian Analysis of Stellar Evolution software suite (BASE-9) to derive the age, distance, reddening, metallicity, binary fraction, and binary mass-ratio posterior distributions for each cluster. We perform a careful analysis of our completeness and also compare our results to previous spectroscopic surveys. For our sample of main-sequence stars with masses between 0.6 - 1 M_Sun, we find that these OCs have similar binary fractions that are also broadly consistent with the field multiplicity fraction. Within the clusters, the binary fraction increases dramatically toward the cluster centers, likely a result of mass segregation. Furthermore nearly all clusters show evidence of mass segregation within the single and binary populations, respectively. The OC binary fraction increases significantly with cluster age in our sample, possibly due to a combination of mass-segregation and cluster dissolution processes. We also find a hint of an anti-correlation between binary fraction and cluster central density as well as total cluster mass, possibly due to an increasing frequency of higher energy close stellar encounters that inhibit long-period binary survival and/or formation.Comment: 20 pages, 11 figures, and 5 tables. Submitted to Ap

    Fin whale (Balaenoptera physalus) acoustic presence off Elephant Island (South Shetland Islands), Antarctica

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    Summertime visual observations suggest that the region around Elephant Island may serve as an important feeding area for fin whales. To explore its year-round relevance, passive acoustic recordings collected northwest of Elephant Island (61°0.88’S, 55°58.53’W) from January 2013 to February 2016 were analysed for seasonal and diel patterns of fin whale 20 Hz calls. Calls were detected year-round, although in some years calls were not present during all months. For all years, fin whale calls were consistently present from March to July for more than 90% of days per month. From August to January, percentage of days with calls varied between years, with presence exceeding 75% of days per month throughout 2014, whereas in 2015 calls were absent in October and November. In 2013, fin whale calling dropped in August and increased again towards October and November. Quantitative analyses of power spectral density for the 20-Hz and 89-Hz fin whale bands, showed that fin whale acoustic power in both frequency bands followed a Gaussian-like temporal pattern, increasing in late January, peaking during April-May and decreasing in late August for all years. A second shoulder peak in PSD seemed to occur during the second part of July showing strongest for the upper fin whale band, followed by a rapid decrease, after which SNR for both bands dropped to zero. Diel patterns in call activity were analysed for a 10-month subset of the data from 2013. Fluctuations in call rates did not follow a diel pattern nor correspond to local insolation. The observed peaks in fin whale call activity correspond to the periods during which fin whale super groups have been observed visually in this region. Our year-round acoustic analysis indicates that the Elephant Island region likely carries an important role for fin whales throughout the entire year

    SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

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    Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short-and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.Fil: Snider, G.. Dalhousie University Halifax; CanadáFil: Weagle, C. L.. Dalhousie University Halifax; CanadáFil: Martin, R. V.. Dalhousie University Halifax; Canadá. University of Cambridge; Reino UnidoFil: van Donkelaar, A.. Dalhousie University Halifax; CanadáFil: Conrad, K.. Dalhousie University Halifax; CanadáFil: Cunningham, D.. Dalhousie University Halifax; CanadáFil: Gordon, C.. Dalhousie University Halifax; CanadáFil: Zwicker, M.. Dalhousie University Halifax; CanadáFil: Akoshile, C.. University of Ilorin; NigeriaFil: Artaxo, P.. Governo Do Estado de Sao Paulo; BrasilFil: Anh, N. X.. Vietnam Academy of Science and Technology. Institute of Geophysics; VietnamFil: Brook, J.. University of Toronto; CanadáFil: Dong, J.. Tsinghua University; ChinaFil: Garland, R. M.. North-West University; SudáfricaFil: Greenwald, R.. Rollins School of Public Health; Estados UnidosFil: Griffith, D.. Council for Scientific and Industrial Research; SudáfricaFil: He, K.. Tsinghua University; ChinaFil: Holben, B. N.. NASA Goddard Space Flight Center; Estados UnidosFil: Kahn, R.. NASA Goddard Space Flight Center; Estados UnidosFil: Koren, I.. Weizmann Institute Of Science Israel; IsraelFil: Lagrosas, N.. Manila Observatory, Ateneo de Manila University campus; FilipinasFil: Lestari, P.. Institut Teknologi Bandung; IndonesiaFil: Ma, Z.. Rollins School of Public Health; Estados UnidosFil: Vanderlei Martins, J.. University of Maryland; Estados UnidosFil: Quel, Eduardo Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rudich, Y.. Weizmann Institute Of Science Israel; IsraelFil: Salam, A.. University Of Dhaka; BangladeshFil: Tripathi, S. N.. Indian Institute Of Technology, Kanpur; IndiaFil: Yu, C.. Rollins School of Public Health; Estados UnidosFil: Zhang, Q.. Tsinghua University; ChinaFil: Zhang, Y.. Tsinghua University; ChinaFil: Brauer, M.. University of British Columbia; CanadáFil: Cohen, A.. Health Effects Institute; Estados UnidosFil: Gibson, M. D.. Dalhousie University Halifax; CanadáFil: Liu, Y.. Rollins School of Public Health; Estados Unido
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