5,811 research outputs found

    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

    A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks

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    An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose inference techniques exist for more realistic, complex models. To achieve this, two inferential challenges need to be addressed: (1) population data are exchangeable, calling for methods that efficiently exploit the symmetries of the data, and (2) computing likelihoods is intractable as it requires integrating over a set of correlated, extremely high-dimensional latent variables. These challenges are traditionally tackled by likelihood-free methods that use scientific simulators to generate datasets and reduce them to hand-designed, permutation-invariant summary statistics, often leading to inaccurate inference. In this work, we develop an exchangeable neural network that performs summary statistic-free, likelihood-free inference. Our framework can be applied in a black-box fashion across a variety of simulation-based tasks, both within and outside biology. We demonstrate the power of our approach on the recombination hotspot testing problem, outperforming the state-of-the-art.Comment: 9 pages, 8 figure

    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

    Multi-objective optimization of steel nitriding

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    Steel nitriding is a thermo-chemical process largely employed in the machine components production to solve mainly wear and fatigue damage in materials. The process is strongly influenced by many different variables such as steel composition, nitrogen potential (range 0.8–35), temperature (range 350–1200 °C), time (range 2–180 hours). In the present study, the influence of such parameters affecting the nitriding layers' thickness, hardness, composition and residual stress was evaluated. The aim was to streamline the process by numerical–experimental analysis allowing to define the optimal conditions for the success of the process. The optimization software that was used is modeFRONTIER (Esteco), through which was defined a set of input parameters (steel composition, nitrogen potential, nitriding time, etc.) evaluated on the basis of an optimization algorithm carefully chosen for the multi-objective analysis. The mechanical and microstructural results belonging to the nitriding process, performed with different processing conditions for various steels, are presented. The data were employed to obtain the analytical equations describing nitriding behavior as a function of nitriding parameters and steel composition. The obtained model was validated through control designs and optimized by taking into account physical and processing conditions

    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

    Integration of Open Slag Bath Furnace with Direct Reduction Reactors for New-Generation Steelmaking

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    The present paper illustrates an innovative steel processing route developed by employing hydrogen direct reduced pellets and an open slag bath furnace. The paper illustrates the direct reduction reactor employing hydrogen as reductant on an industrial scale. The solution allows for the production of steel from blast furnace pellets transformed in the direct reduction reactor. The reduced pellets are then melted in open slag bath furnaces, allowing carburization for further refining. The proposed solution is clean for the decarbonization of the steel industry. The kinetic, chemical and thermodynamic issues are detailed with particular attention paid to the slag conditions. The proposed solution is also supported by the economic evaluation compared to traditional routes

    Four-dimensional drift-kinetic model for scrape-off layer plasmas

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    A four-dimensional plasma model able to describe the scrape-off layer region of tokamak devices at arbitrary collisionality is derived in the drift-reduced limit. The basis of the model is provided by a drift-kinetic equation that retains the full non-linear Coulomb collision operator and describes arbitrarily far from equilibrium distribution functions. By expanding the dependence of distribution function over the perpendicular velocity in a Laguerre polynomial basis and integrating over the perpendicular velocity, a set of four-dimensional moment equations for the expansion coefficients of the distribution function is obtained. The Coulomb collision operator, as well as Poisson's equation, are evaluated explicitly in terms of perpendicular velocity moments of the distribution function.Comment: 12 page

    Ionospheric precursors for crustal earthquakes in Italy

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    Crustal earthquakes with magnitude 6.0&gt;M&ge;5.5 observed in Italy for the period 1979–2009 including the last one at L'Aquila on 6 April 2009 were considered to check if the earlier obtained relationships for ionospheric precursors for strong Japanese earthquakes are valid for the Italian moderate earthquakes. The ionospheric precursors are based on the observed variations of the sporadic E-layer parameters (<I>h</I>'Es, <I>fb</I>Es) and <I>fo</I>F2 at the ionospheric station Rome. Empirical dependencies for the seismo-ionospheric disturbances relating the earthquake magnitude and the epicenter distance are obtained and they have been shown to be similar to those obtained earlier for Japanese earthquakes. The dependences indicate the process of spreading the disturbance from the epicenter towards periphery during the earthquake preparation process. Large lead times for the precursor occurrence (up to 34 days for M=5.8–5.9) tells about a prolong preparation period. A possibility of using the obtained relationships for the earthquakes prediction is discussed

    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>Ă„</i>) and its spectral curvature Δ<i>Ă„</i>. Lidar measurements at 355, 532 and 1064 nm were used in this study to retrieve the vertical profiles of <i>Ă„</i> and Δ<i>Ă„</i> and to estimate the dependence on altitude of <i>R</i><sub>f</sub> and η(532 nm) from the <i>Ă„</i>–Δ<i>Ă„</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>Ă„</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>Ă„</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 ÎŒm and the 0.3–0.99 range, respectively, were associated with the <i>Ă„</i>–&Delta;<i>Ă„</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>Ă„</i>–<i>Ă„</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 ÎŒm, 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

    Ionospheric precursors for crustal earthquakes in Italy

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    Crustal earthquakes with magnitude 6.0>M 5.5 observed in Italy for the period 1979–2009 including the last one at L’Aquila on 6 April 2009 were considered to check if the earlier obtained relationships for ionospheric precursors for strong Japanese earthquakes are valid for the Italian moderate earthquakes. The ionospheric precursors are based on the observed variations of the sporadic E-layer parameters (h0Es, fbEs) and foF2 at the ionospheric station Rome. Empirical dependencies for the seismo-ionospheric disturbances relating the earthquake magnitude and the epicenter distance are obtained and they have been shown to be similar to those obtained earlier for Japanese earthquakes. The dependences indicate the process of spreading the disturbance from the epicenter towards periphery during the earthquake preparation process. Large lead times for the precursor occurrence (up to 34 days for M=5.8–5.9) tells about a prolong preparation period. A possibility of using the obtained relationships for the earthquakes prediction is discussed
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