9,790 research outputs found

    On the Estimation of Euler Equations in the Presence of a Potential Regime Shift

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    The concept of a peso problem is formalized in terms of a linear Euler equation and a nonlinear marginal model describing the dynamics of the exogenous driving process. It is shown that, using a threshold autoregressive model as a marginal model, it is possible to produce time-varying peso premia. A Monte Carlo method and a method based on the numerical solution of integral equations are considered as tools for computing conditional future expectations in the marginal model. A Monte Carlo study illustrates the poor performance of the generalized method of moment (GMM) estimator in small and even relatively large samples. The poor performance is particularly acute in the presence of a peso problem but is also serious in the simple linear case.peso problem; Euler equations; GMM; threshold autoregressive models

    Simulation of UHE muons propagation for GEANT3

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    A simulation package for the transport of high energy muons has been developed. It has been conceived to replace the muon propagation software modules implemented in the detector simulation program GEANT3. Here we discuss the results achieved with our package and we check the agreement with numerical calculations up to 10**8 GeV.Comment: 21 pages, 6 figures, 1 Table. AMSTeX document, acknowledgments adde

    Guest editorial

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    The 21st International EurOMA (EurOMA, 2014) Conference was hosted by Università degli Studi di Palermo. The conference theme was Operations Management in an Innovation Economy. According to innovation economists what primarily drives economic growth in today’s knowledge-based economy is not capital accumulation but innovative capacity spurred by appropriable knowledge and technological externalities. Economics growth in innovation economics is the end- product of knowledge, R&D expenditures, licenses, technological spillovers, and externalities between collaborative firms, i.e. supply chains and networks of innovation. When firms do not explicitly acknowledge and manage their operations as a concurrent activity to the management of innovation, they often encounter problems late in product development, or with manufacturing launch, logistical support, quality control, and production costs. As such, innovation process and operations management should be coordinated, rather than being viewed as separate sets of decisions and activities. We received 592 abstracts and used a doubled-blind review process, involving 127 members of the Scientific Committee, to review 586 abstracts (six abstracts were desk rejected) and provide feedback to the authors. Of these, 513 were accepted and 73 rejected. The accepted abstracts resulted in 405 full papers in the Scientific Programme. With three papers subsequently withdrawn, there were 402 paper presentations in prospect. The most recurrent OM themes were: sustainability in operations and logistics (42 papers); supply chain management (35 papers); innovation, product and service development (32 papers); managing inter-firm relationships in supply chains (30 papers); healthcare OM (21 papers); lean and agile operations (21 papers). The Scientific Programme incorporated 134 parallel sessions and was enriched by two keynote speakers: Professor Robert Handfield (Bank of America University Distinguished Professor of Supply Chain Management, North Carolina State University) and the Chief Operations Officer of Luxottica, Massimo Vian, who provided insightful reflections on the conference theme from their academic and industry perspectives, respectively. In addition there were six special sessions providing unique opportunities for engagement and insights on teaching in OM, crowdsourcing and open innovation in OM, OM as practice, OM research in the fashion industry, new supply chains, and the role of social media in OM and EurOMA. Also, besides this interesting topic-specific special sessions, the conference hosted a “Meet the Editors” session with editors and co-editors from eight OM journals

    Linear Theory of Electron-Plasma Waves at Arbitrary Collisionality

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    The dynamics of electron-plasma waves are described at arbitrary collisionality by considering the full Coulomb collision operator. The description is based on a Hermite-Laguerre decomposition of the velocity dependence of the electron distribution function. The damping rate, frequency, and eigenmode spectrum of electron-plasma waves are found as functions of the collision frequency and wavelength. A comparison is made between the collisionless Landau damping limit, the Lenard-Bernstein and Dougherty collision operators, and the electron-ion collision operator, finding large deviations in the damping rates and eigenmode spectra. A purely damped entropy mode, characteristic of a plasma where pitch-angle scattering effects are dominant with respect to collisionless effects, is shown to emerge numerically, and its dispersion relation is analytically derived. It is shown that such a mode is absent when simplified collision operators are used, and that like-particle collisions strongly influence the damping rate of the entropy mode.Comment: 23 pages, 10 figures, accepted for publication on Journal of Plasma Physic

    Response to Comment on `Undamped electrostatic plasma waves' [Phys. Plasmas 19, 092103 (2012)]

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    Numerical and experimental evidence is given for the occurrence of the plateau states and concomitant corner modes proposed in \cite{valentini12}. It is argued that these states provide a better description of reality for small amplitude off-dispersion disturbances than the conventional Bernstein-Greene-Kruskal or cnoidal states such as those proposed in \cite{comment

    Instantaneous cell migration velocity may be ill-defined

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    Cell crawling is critical to biological development, homeostasis and disease. In many cases, cell trajectories are quasi-random-walk. In vitro assays on flat surfaces often described such quasi-random-walk cell trajectories as approximations to a solution of a Langevin process. However, experiments show quasi-diffusive behavior at small timescales, indicating that instantaneous velocity and velocity autocorrelations are not well-defined. We propose to characterize mean-squared cell displacement using a modified F\"urth equation with three temporal and spatial regimes: short- and long-time/range diffusion and intermediate time/range ballistic motion. This analysis collapses mean-squared displacements of previously published experimental data onto a single-parameter family of curves, allowing direct comparison between movement in different cell types, and between experiments and numerical simulations. Our method also show that robust cell-motility quantification requires an experiment with a maximum interval between images of a few percent of the cell-motion persistence time or less, and a duration of a few orders-of-magnitude longer than the cell-motion persistence time or more.Comment: 5 pages, plus Supplemental materia

    Vertically resolved aerosol properties by multi-wavelength lidar measurements

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    An approach based on the graphical method of Gobbi and co-authors (2007) is introduced to estimate the dependence on altitude of the aerosol fine mode radius (<i>R</i><sub>f</sub>) and of the fine mode contribution (η) to the aerosol optical thickness (AOT) from three-wavelength lidar measurements. The graphical method of Gobbi and co-authors (2007) was applied to AERONET (AErosol RObotic NETwork) spectral extinction observations and relies on the combined analysis of the Ångstrom exponent (<i>å</i>) and its spectral curvature Δ<i>å</i>. Lidar measurements at 355, 532 and 1064 nm were used in this study to retrieve the vertical profiles of <i>å</i> and Δ<i>å</i> and to estimate the dependence on altitude of <i>R</i><sub>f</sub> and η(532 nm) from the <i>å</i>–Δ<i>å</i> combined analysis. Lidar measurements were performed at the Department of Mathematics and Physics of the Universita' del Salento, in south-eastern Italy. Aerosol from continental Europe, the Atlantic, northern Africa, and the Mediterranean Sea are often advected over south-eastern Italy and as a consequence, mixed advection patterns leading to aerosol properties varying with altitude are dominant. The proposed approach was applied to ten measurement days to demonstrate its feasibility in different aerosol load conditions. The selected days were characterized by AOTs spanning the 0.26–0.67, 0.15–0.39, and 0.04–0.27 range at 355, 532, and 1064 nm, respectively. Mean lidar ratios varied within the 31–83, 32–84, and 11–47 sr range at 355, 532, and 1064 nm, respectively, for the high variability of the aerosol optical and microphysical properties. <i>å</i> values calculated from lidar extinction profiles at 355 and 1064 nm ranged between 0.1 and 2.5 with a mean value &pm; 1 standard deviation equal to 1.3 ± 0.7. Δ<i>å</i> varied within the −0.1–1 range with mean value equal to 0.25 ± 0.43. <i>R</i><sub>f</sub> and η(532 nm) values spanning the 0.05–0.3 μm and the 0.3–0.99 range, respectively, were associated with the <i>å</i>–&Delta;<i>å</i> data points. <i>R</i><sub>f</sub> and η values showed no dependence on the altitude. 60% of the data points were in the &Delta;<i>å</i>–<i>å</i> space delimited by the &eta; and <i>R</i><sub>f</sub> curves varying within 0.80–0.99 and 0.05–0.15 μm, respectively, for the dominance of fine-mode particles in driving the AOT over south-eastern Italy. Vertical profiles of the linear particle depolarization ratio retrieved from lidar measurements, aerosol products from AERONET sun photometer measurements collocated in space and time, analytical back trajectories, satellite true colour images, and dust concentrations from the BSC–DREAM (Barcelona Super Computing Center-Dust REgional Atmospheric Model) model were used to demonstrate the robustness of the proposed method

    Self-Organized Criticality model for Brain Plasticity

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    Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Here we present a model based on self-organized criticality and taking into account brain plasticity, which is able to reproduce the spectrum of electroencephalograms (EEG). The model consists in an electrical network with threshold firing and activity-dependent synapse strenghts. The system exhibits an avalanche activity power law distributed. The analysis of the power spectra of the electrical signal reproduces very robustly the power law behaviour with the exponent 0.8, experimentally measured in EEG spectra. The same value of the exponent is found on small-world lattices and for leaky neurons, indicating that universality holds for a wide class of brain models.Comment: 4 pages, 3 figure
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