11,308 research outputs found

    Statistical Properties of Avalanches in Networks

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    We characterize the distributions of size and duration of avalanches propagating in complex networks. By an avalanche we mean the sequence of events initiated by the externally stimulated `excitation' of a network node, which may, with some probability, then stimulate subsequent firings of the nodes to which it is connected, resulting in a cascade of firings. This type of process is relevant to a wide variety of situations, including neuroscience, cascading failures on electrical power grids, and epidemology. We find that the statistics of avalanches can be characterized in terms of the largest eigenvalue and corresponding eigenvector of an appropriate adjacency matrix which encodes the structure of the network. By using mean-field analyses, previous studies of avalanches in networks have not considered the effect of network structure on the distribution of size and duration of avalanches. Our results apply to individual networks (rather than network ensembles) and provide expressions for the distributions of size and duration of avalanches starting at particular nodes in the network. These findings might find application in the analysis of branching processes in networks, such as cascading power grid failures and critical brain dynamics. In particular, our results show that some experimental signatures of critical brain dynamics (i.e., power-law distributions of size and duration of neuronal avalanches), are robust to complex underlying network topologies.Comment: 11 pages, 7 figure

    Tungsten resonance integrals and Doppler coefficients Third quarterly report, Jan. - Mar. 1966

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    Reactivities, Doppler coefficients, and resonance integrals for tungsten isotope

    Advanced Navigation Strategies For Asteroid Sample Return Missions

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    Flyby and rendezvous missions to asteroids have been accomplished using navigation techniques derived from experience gained in planetary exploration. This paper presents analysis of advanced navigation techniques required to meet unique challenges for precision navigation to acquire a sample from an asteroid and return it to Earth. These techniques rely on tracking data types such as spacecraft-based laser ranging and optical landmark tracking in addition to the traditional Earth-based Deep Space Network radio metric tracking. A systematic study of navigation strategy, including the navigation event timeline and reduction in spacecraft-asteroid relative errors, has been performed using simulation and covariance analysis on a representative mission

    New, efficient, and accurate high order derivative and dissipation operators satisfying summation by parts, and applications in three-dimensional multi-block evolutions

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    We construct new, efficient, and accurate high-order finite differencing operators which satisfy summation by parts. Since these operators are not uniquely defined, we consider several optimization criteria: minimizing the bandwidth, the truncation error on the boundary points, the spectral radius, or a combination of these. We examine in detail a set of operators that are up to tenth order accurate in the interior, and we surprisingly find that a combination of these optimizations can improve the operators' spectral radius and accuracy by orders of magnitude in certain cases. We also construct high-order dissipation operators that are compatible with these new finite difference operators and which are semi-definite with respect to the appropriate summation by parts scalar product. We test the stability and accuracy of these new difference and dissipation operators by evolving a three-dimensional scalar wave equation on a spherical domain consisting of seven blocks, each discretized with a structured grid, and connected through penalty boundary conditions.Comment: 16 pages, 9 figures. The files with the coefficients for the derivative and dissipation operators can be accessed by downloading the source code for the document. The files are located in the "coeffs" subdirector

    Extinction Risk and Bottlenecks in the Conservation of Charismatic Marine Species

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    The oceans face a biodiversity crisis, but the degree and scale of extinction risk remains poorly characterized. Charismatic species are most likely to gar- ner greatest support for conservation and thus provide a best-case scenario of the status of marine biodiversity. We summarize extinction risk and diagnose impediments to successful conservation for 1,568 species in 16 families of marine animals in the movie Finding Nemo. Sixteen percent (12–34%) of those that have been evaluated are threatened, ranging from 9% (7–28%) of bony fishes to 100% (83–100%) of marine turtles. A lack of scientific knowledge impedes analysis of threat status for invertebrates, which have 1,000 times fewer conservation papers than do turtles. Legal protection is severely deficient for sharks and rays; only 8% of threatened species in our analysis are protected. Extinction risk among wide-ranging taxa is higher thanmost terrestrial groups, suggesting a different conservation focus is required in the sea

    Estimating Community Stability and Ecological Interactions from Time-Series Data

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    Natural ecological communities are continuously buffeted by a varying environment, often making it difficult to measure the stability of communities using concepts requiring the existence of an equilibrium point. Instead of an equilibrium point, the equilibrial state of communities subject to environmental stochasticity is a stationary distribution, which is characterized by means, variances, and other statistical moments. Here, we derive three properties of stochastic multispecies communities that measure different characteristics associated with community stability. These properties can be estimated from multispecies time-series data using first-order multivariate autoregressive (MAR(1)) models. We demonstrate how to estimate the parameters of MAR(1) models and obtain confidence intervals for both parameters and the measures of stability. We also address the problem of estimation when there is observation (measurement) error. To illustrate these methods, we compare the stability of the planktonic communities in three lakes in which nutrient loading and planktivorous fish abundance were experimentally manipulated. MAR(1) models and the statistical methods we present can be used to identify dynamically important interactions between species and to test hypotheses about stability and other dynamical properties of naturally varying ecological communities. Thus, they can be used to integrate theoretical and empirical studies of community dynamics

    Tin telluride: a weakly co-elastic metal

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    We report resonant ultrasound spectroscopy (RUS), dilatometry/magnetostriction, magnetotransport, magnetization, specific heat, and 119^{119}Sn M\"ossbauer spectroscopy measurements on SnTe and Sn0.995_{0.995}Cr0.005_{0.005}Te. Hall measurements at T=77T=77 K indicate that our Bridgman-grown single crystals have a pp-type carrier concentration of 3.4×10193.4 \times 10^{19} cm3^{-3} and that our Cr-doped crystals have an nn-type concentration of 5.8×10225.8 \times 10^{22} cm3^{-3}. Although our SnTe crystals are diamagnetic over the temperature range 2KT1100K2\, \text{K} \leq T \leq 1100\, \text{K}, the Cr-doped crystals are room temperature ferromagnets with a Curie temperature of 294 K. For each sample type, three-terminal capacitive dilatometry measurements detect a subtle 0.5 micron distortion at Tc85T_c \approx 85 K. Whereas our RUS measurements on SnTe show elastic hardening near the structural transition, pointing to co-elastic behavior, similar measurements on Sn0.995_{0.995}Cr0.005_{0.005}Te show a pronounced softening, pointing to ferroelastic behavior. Effective Debye temperature, θD\theta_D, values of SnTe obtained from 119^{119}Sn M\"ossbauer studies show a hardening of phonons in the range 60--115K (θD\theta_D = 162K) as compared with the 100--300K range (θD\theta_D = 150K). In addition, a precursor softening extending over approximately 100 K anticipates this collapse at the critical temperature, and quantitative analysis over three decades of its reduced modulus finds ΔC44/C44=A(TT0)/T0κ\Delta C_{44}/C_{44}=A|(T-T_0)/T_0|^{-\kappa} with κ=0.50±0.02\kappa = 0.50 \pm 0.02 , a value indicating a three-dimensional softening of phonon branches at a temperature T075T_0 \sim 75 K, considerably below TcT_c. We suggest that the differences in these two types of elastic behaviors lie in the absence of elastic domain wall motion in the one case and their nucleation in the other

    A redshifted Fe Kα\alpha line from the unusual gamma-ray source PMN J1603-4904

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    Multiwavelength observations have revealed the highly unusual properties of the gamma-ray source PMN J1603-4904, which are difficult to reconcile with any other well established gamma-ray source class. The object is either a very atypical blazar or compact jet source seen at a larger angle to the line of sight. In order to determine the physical origin of the high-energy emission processes in PMN J1603-4904, we study the X-ray spectrum in detail. We performed quasi-simultaneous X-ray observations with XMM-Newton and Suzaku in 2013 September, resulting in the first high signal-to-noise X-ray spectrum of this source. The 2-10 keV X-ray spectrum can be well described by an absorbed power law with an emission line at 5.44±\pm0.05 keV (observed frame). Interpreting this feature as a K{\alpha} line from neutral iron, we determine the redshift of PMN J1603-4904 to be z=0.18±\pm0.01, corresponding to a luminosity distance of 872±\pm54 Mpc. The detection of a redshifted X-ray emission line further challenges the original BL Lac classification of PMN J1603-4904. This result suggests that the source is observed at a larger angle to the line of sight than expected for blazars, and thus the source would add to the elusive class of gamma-ray loud misaligned-jet objects, possibly a {\gamma}-ray bright young radio galaxy.Comment: 5 pages, 1 figure, A&A accepte

    The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development

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    With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a widespread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled
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