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Fusion

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21.08.2019
07:31 Arxiv.org PhysicsEscape of \alpha-particle in inertial confinement fusion. (arXiv:1908.07130v1 [physics.plasm-ph])

Escape of $\alpha$-particles from a burning or an ignited burning deuterium-tritium (DT) fuel with temperature up to more than tens keV is very important in inertial confinement fusion, which can significantly influence not only the hot spot dynamics and the energy gain but also the shielding design in fusion devices. In this paper, we study the $\alpha $-particle escape from a burning or an ignited burning DT fuel by considering the modifications including the $\alpha $-particle stopping by both DT ions and electrons with their Maxwellian average stopping weights, the relativity effect on electron distribution, and the modified Coulomb logarithm of the DT-$\alpha $ particle collisions. As a result of our studies, the escape-effect from our modified model is obviously stronger than those from the traditional models. A fitted expression is presented to calculate the escape factor in a DT fuel,

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07:31 Arxiv.org CSTowards High-Resolution Salient Object Detection. (arXiv:1908.07274v1 [cs.CV])

Deep neural network based methods have made a significant breakthrough in salient object detection. However, they are typically limited to input images with low resolutions ($400\times400$ pixels or less). Little effort has been made to train deep neural networks to directly handle salient object detection in very high-resolution images. This paper pushes forward high-resolution saliency detection, and contributes a new dataset, named High-Resolution Salient Object Detection (HRSOD). To our best knowledge, HRSOD is the first high-resolution saliency detection dataset to date. As another contribution, we also propose a novel approach, which incorporates both global semantic information and local high-resolution details, to address this challenging task. More specifically, our approach consists of a Global Semantic Network (GSN), a Local Refinement Network (LRN) and a Global-Local Fusion

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20.08.2019
10:11 Arxiv.org Physics3D Gamma-ray and Neutron Mapping in Real-Time with the Localization and Mapping Platform from Unmanned Aerial Systems and Man-Portable Configurations. (arXiv:1908.06114v1 [physics.ins-det])

Nuclear Scene Data Fusion (SDF), implemented in the Localization and Mapping Platform (LAMP) fuses three-dimensional (3D), real-time volumetric reconstructions of radiation sources with contextual information (e.g. LIDAR, camera, etc.) derived from the environment around the detector system. This information, particularly when obtained in real time, may be transformative for applications, including directed search for lost or stolen sources, consequence management after the release of radioactive materials, or contamination avoidance in security-related or emergency response scenarios. 3D reconstructions enabled by SDF localize contamination or hotspots to specific areas or objects, providing higher resolution over larger areas than conventional 2D approaches, and enabling more efficient planning and response, particularly in complex 3D environments.
In this work, we present the expansion

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10:11 Arxiv.org CSEmploying Game Theory and TDMA Protocol to Enhance Security and Manage Power Consumption in WSNs-based Cognitive Radio. (arXiv:1908.06844v1 [eess.SP])

The rapid development of wireless sensor networks (WSNs) is the significant incentive to contribute in the vulnerable applications such as cognitive radio (CR). This paper proposes a Stackelberg game approach to enhance the WSN-based CR security against the spectrum sensing data falsification (SSDF) attack and conserve the consequent lost power consumption. The attack aims to corrupt the spectrum decision by imposing interference power to the delivered reports from the sensor nodes (SNs) to the fusion center (FC) to make a protection level below a specific threshold. The proposed model utilizes the intelligent Stackelberg game features along with the matched filter (MF) to maximize the number of protected reports sent by the SNs to the FC leading to accurate decision of the spectrum status. Furthermore, the TDMA protocol is utilized to resolve the complexity of employing MF for the spectrum

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16.08.2019
07:08 Arxiv.org PhysicsElectromagnetic full-$f$ gyrokinetics in the tokamak edge with discontinuous Galerkin methods. (arXiv:1908.05653v1 [physics.plasm-ph])

We present an energy-conserving discontinuous Galerkin scheme for the full-$f$ electromagnetic gyrokinetic system in the long-wavelength limit. We use the symplectic formulation and solve directly for $\partial A_\parallel/\partial t$, the inductive component of the parallel electric field, using a generalized Ohm's law derived directly from the gyrokinetic equation. Linear benchmarks are performed to verify the implementation and show that the scheme avoids the Amp\`ere cancellation problem. We perform a nonlinear electromagnetic simulation in a helical open-field-line system as a rough model of the tokamak scrape-off layer using parameters from the National Spherical Torus Experiment (NSTX). This is the first published nonlinear electromagnetic gyrokinetic simulation on open field lines. Comparisons are made to a corresponding electrostatic simulation.

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07:08 Arxiv.org PhysicsAn introduction to symmetries in stellarators. (arXiv:1908.05360v1 [physics.plasm-ph])

The field of plasma physics is broad, with applications in astrophysical and solar phenomena, laser experiments, electronics, and nuclear fusion. Rather than provide a comprehensive introduction to plasma physics, the goal of this document is to explain several important concepts for magnetic confinement in a stellarator. Specifically, we aim to provide the requisite background material in order to discuss challenges related to stellarator equilibrium models, as well as quasisymmetry. Both of these concepts are related to `hidden symmetries' in 3D systems. Tokamaks have a symmetry with respect to rotation about the toroidal angle, ensuring the existence of continuously nested magnetic surfaces and single particle confinement. While stellarators lack this symmetry, we will discuss how magnetic fields in a stellarators can be approximately integrable, providing some nested magnetic surfaces.

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15.08.2019
09:52 Arxiv.org CSD-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation. (arXiv:1908.05104v1 [eess.IV])

Assessing the location and extent of lesions caused by chronic stroke is critical for medical diagnosis, surgical planning, and prognosis. In recent years, with the rapid development of 2D and 3D convolutional neural networks (CNN), the encoder-decoder structure has shown great potential in the field of medical image segmentation. However, the 2D CNN ignores the 3D information of medical images, while the 3D CNN suffers from high computational resource demands. This paper proposes a new architecture called dimension-fusion-UNet (D-UNet), which combines 2D and 3D convolution innovatively in the encoding stage. The proposed architecture achieves a better segmentation performance than 2D networks, while requiring significantly less computation time in comparison to 3D networks. Furthermore, to alleviate the data imbalance issue between positive and negative samples for the network training, we

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13.08.2019
08:27 Arxiv.org StatisticsDynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction. (arXiv:1908.03918v1 [cs.LG])

Dynamical models estimate and predict the temporal evolution of physical systems. State Space Models (SSMs) in particular represent the system dynamics with many desirable properties, such as being able to model uncertainty in both the model and measurements, and optimal (in the Bayesian sense) recursive formulations e.g. the Kalman Filter. However, they require significant domain knowledge to derive the parametric form and considerable hand-tuning to correctly set all the parameters. Data driven techniques e.g. Recurrent Neural Networks have emerged as compelling alternatives to SSMs with wide success across a number of challenging tasks, in part due to their ability to extract relevant features from rich inputs. They however lack interpretability and robustness to unseen conditions. In this work, we present DynaNet, a hybrid deep learning and time-varying state-space model which can be

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08:27 Arxiv.org PhysicsDielectric kernels for Maxwellian tokamak plasmas. (arXiv:1908.03896v1 [physics.plasm-ph])

New integral kernels describing the full-wave dielectric response of Maxwellian tokamak plasmas are presented. They realistically account for the rotational transform and for wave dispersion in presence of equilibrium magnetic field parallel gradients. These kernels rely on special functions of three variables that generalize the standard plasma dispersion function; their main analytical properties are given, leading to efficient evaluation. This approach is free from the poloidal Fourier mode expansion of the HF fields which appears in earlier formulations and gives complete freedom for the numerical resolution of the wave equation: it will typically be applied to 2D finite element discretizations, allowing local mesh refinements as required near cyclotron resonance layers and in regions of rapid HF field variations. This first presentation is to lowest order in the Larmor radius for the

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08:27 Arxiv.org PhysicsWhole device gyrokinetic simulations using unstructured meshes in realistic tokamak geometry. (arXiv:1908.03824v1 [physics.plasm-ph])

In this work, we have formulated and implemented the mixed unstructured mesh-based finite element-Fourier spectrum scheme for gyrokinetic simulation in realistic tokamak geometry. An efficient particle deposition scheme using an intermediate grid as the search index for triangles has been implemented and a significant speed-up by a factor of ~30 is observed as compared with the brute force scheme for a medium-size simulation. The TRIMEG (TRIangular MEsh based Gyrokinetic) code has been developed. As an application, the ion temperature gradient (ITG) mode is simulated using the simplified gyrokinetic-Poisson model. Our simulation and that using ORB5 code for the DIII-D Cyclone case shows reasonable agreement. As an additional application, ITG simulations using an ASDEX Upgrade equilibrium have been performed with density and temperature gradient profiles similar to the Cyclone case.

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08:27 Arxiv.org CSDynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction. (arXiv:1908.03918v1 [cs.LG])

Dynamical models estimate and predict the temporal evolution of physical systems. State Space Models (SSMs) in particular represent the system dynamics with many desirable properties, such as being able to model uncertainty in both the model and measurements, and optimal (in the Bayesian sense) recursive formulations e.g. the Kalman Filter. However, they require significant domain knowledge to derive the parametric form and considerable hand-tuning to correctly set all the parameters. Data driven techniques e.g. Recurrent Neural Networks have emerged as compelling alternatives to SSMs with wide success across a number of challenging tasks, in part due to their ability to extract relevant features from rich inputs. They however lack interpretability and robustness to unseen conditions. In this work, we present DynaNet, a hybrid deep learning and time-varying state-space model which can be

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09.08.2019
12:19 Arxiv.org StatisticsHyperStream: a Workflow Engine for Streaming Data. (arXiv:1908.02858v1 [cs.LG])

This paper describes HyperStream, a large-scale, flexible and robust software package, written in the Python language, for processing streaming data with workflow creation capabilities. HyperStream overcomes the limitations of other computational engines and provides high-level interfaces to execute complex nesting, fusion, and prediction both in online and offline forms in streaming environments. HyperStream is a general purpose tool that is well-suited for the design, development, and deployment of Machine Learning algorithms and predictive models in a wide space of sequential predictive problems.
Source code, installation instructions, examples, and documentation can be found at: https://github.com/IRC-SPHERE/HyperStream.

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12:19 Arxiv.org CSHyperStream: a Workflow Engine for Streaming Data. (arXiv:1908.02858v1 [cs.LG])

This paper describes HyperStream, a large-scale, flexible and robust software package, written in the Python language, for processing streaming data with workflow creation capabilities. HyperStream overcomes the limitations of other computational engines and provides high-level interfaces to execute complex nesting, fusion, and prediction both in online and offline forms in streaming environments. HyperStream is a general purpose tool that is well-suited for the design, development, and deployment of Machine Learning algorithms and predictive models in a wide space of sequential predictive problems.
Source code, installation instructions, examples, and documentation can be found at: https://github.com/IRC-SPHERE/HyperStream.

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08.08.2019
06:32 Arxiv.org PhysicsEfficient and robust evaluation of fast particle losses in non-axisymmetric tokamak plasmas. (arXiv:1908.02494v1 [physics.plasm-ph])

We present various techniques that make orbit-following Monte Carlo simulations faster and more reliable when assessing collisionless fast particle losses due to magnetic field perturbations. These techniques are based on identifying various loss channels in constants of motion space using the so-called loss maps. We demonstrate that this allows one to attribute losses quantitatively to different transport mechanisms, increase signal-to-noise ratio when estimating FILD signal and peak power loads, and connect magnetic field structure directly to fast particle losses. Furthermore, we show that collisionless fast particle transport can be treated as an advection-diffusion process where the transport coefficients can be evaluated with the orbit-following method. Applying these techniques has the potential to make orbit-following simulations faster to perform, or to avoid them completely, while

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06:32 Arxiv.org PhysicsHigh-performance orbit-following code ASCOT5 for Monte Carlo simulations in fusion plasmas. (arXiv:1908.02482v1 [physics.plasm-ph])

We present a novel implementation of a Monte Carlo particle-following code for solving the distribution function of minority species in fusion plasmas, called ASCOT5, and verify it using theoretical results for neoclassical transport. The code has been developed from ground up with an OpenMP-MPI hybrid paradigm to take full advantage of current and next generation many-core CPUs with multithreading and SIMD operations. Up to 6-fold increase in performance is demonstrated compared to a previous version of the code which only utilizes MPI. The physics model of the code is comprehensively validated against existing theoretical work, and it is shown to faithfully reproduce neoclassical diffusion across three different collisionality regimes. In simulations for realistic tokamak plasmas, including complex non-axisymmetric geometry, ASCOT5 is verified to reproduce results from the previous version

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07.08.2019
09:20 Arxiv.org PhysicsRole of poloidal-pressure-asymmetry-driven flows in L-H transition and impurity transport during MGI shutdowns. (arXiv:1908.01936v1 [physics.plasm-ph])

Poloidal asymmetries in tokamaks are usually investigated in the context of various transport processes, usually invoking neoclassical physics. A simpler approach based on magnetohydrodynamics (MHD), focusing on the effects rather than the causes of asymmetries, yields useful insights into the generation of shear flows and radial electric field. The crucial point to recognize is that an MHD equilibrium in which the plasma pressure is not a flux function can be maintained only by contributions from mass flows. Coupling between the asymmetry-generated forces and toroidal geometry results in a strongly up-down asymmetric effect, where the flows exhibit a strong dependence on the location of the asymmetry with respect to the midplane. This location-dependence can be used as an effective control mechanism for the edge and thus the global confinement in tokamaks. It can also explain a number of

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06.08.2019
21:12 ScienceDaily.comSimulations demonstrate ion heating by plasma oscillations for fusion energy

Fusion scientists succeeded in proving that ions can be heated by plasma oscillations driven by high-energy particles. This has been confirmed by performing a large-scale simulation with a newly developed hybrid-simulation program that links calculations for plasma oscillations, high-energy particles and ions. This research will accelerate studies of plasma self-heating for realizing fusion energy.

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17:56 Phys.orgSimulations demonstrate ion heating by plasma oscillations for fusion energy

A research team of fusion scientists succeeded in proving that ions can be heated by plasma oscillations driven by high-energy particles. This has been confirmed by performing a large-scale simulation with a newly developed hybrid-simulation program that links calculations for plasma oscillations, high-energy particles and ions. This research will accelerate studies of plasma self-heating for realizing fusion energy.

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10:24 Phys.orgImproving the magnetic bottle that controls fusion power on Earth

Scientists who use magnetic fields to bottle up and control on Earth the fusion reactions that power the sun and stars must correct any errors in the shape of the fields that contain the reactions. Such errors produce deviations from the symmetrical form of the fields in doughnut-like tokamak fusion facilities that can have a damaging impact on the stability and confinement of the hot, charged plasma gas that fuels the reactions.

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01:43 ScienceDaily.comImproving the magnetic bottle that controls fusion power on Earth

The exhaustive detection method that discovered the error field in the initial run of the NSTX-U tokamak could serve as a model for error-field detection in future tokamaks.

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05.08.2019
07:53 Arxiv.org PhysicsMaximizing specific energy by breeding deuterium. (arXiv:1908.00834v1 [physics.pop-ph])

Specific energy (i.e. energy per unit mass) is one of the most fundamental and consequential properties of a fuel source. In this work, a systematic study of measured fusion cross-sections is performed to determine which reactions are potentially feasible and identify the fuel cycle that maximizes specific energy. This reveals that, by using normal hydrogen to breed deuterium via neutron capture, the conventional catalyzed D-D fusion fuel cycle can attain a specific energy greater than anything else. Simply surrounding a catalyzed D-D reactor with water enables deuterium fuel, the dominant stockpile of energy on Earth, to produce as much as 65% more energy. Lastly, the impact on space propulsion is considered, revealing that an effective exhaust velocity exceeding that of deuterium-helium-3 is theoretically possible.

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02.08.2019
09:02 Arxiv.org PhysicsGlobal scaling of the heat transport in fusion plasmas. (arXiv:1908.00397v1 [physics.plasm-ph])

A global heat flux model based on a fractional derivative of plasma pressure is proposed for the heat transport in fusion plasmas. The degree of the fractional derivative of the heat flux, $\alpha$, is defined through the power balance analysis of the steady state. The model was used to obtain the experimental values of $\alpha$ for a large database of the JET Carbon-wall as well as ITER Like-wall plasmas. The findings show that the average fractional degree of the heat flux over the database for electrons is $\alpha \sim 0.8$, suggesting a global scaling between the net heating and the pressure profile in the JET plasmas. The model is expected to provide an accurate and a simple description of heat transport that can be used in transport studies of fusion plasmas.

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01.08.2019
04:43 Arxiv.org PhysicsMeasuring the time a tunnelling atom spends in the barrier. (arXiv:1907.13523v1 [physics.atom-ph])

Tunnelling is one of the most paradigmatic and evocative phenomena of quantum physics, underlying processes such as photosynthesis and nuclear fusion, as well as devices ranging from SQUID magnetometers to superconducting qubits for quantum computers. The question of how long a particle takes to tunnel, however, has remained controversial since the first attempts to calculate it, which relied on the group delay. It is now well understood that this delay (the arrival time of the transmitted wave packet peak at the far side of the barrier) can be smaller than the barrier thickness divided by the speed of light, without violating causality. There have been a number of experiments confirming this, and even a recent one claiming that tunnelling may take no time at all. There have also been efforts to identify another timescale, which would better describe how long a given particle spends in the

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31.07.2019
07:11 Arxiv.org PhysicsDeuterium permeation in Er$_2$O$_3$ thin film fabricated on a type 316L stainless steel substrate. (arXiv:1907.12641v1 [physics.app-ph])

A metal-oxide film can be used as a hydrogen-isotope permeation barrier in the fuel circulation system for nuclear fusion. We fabricated Er$_2$O$_3$ thin film on a type 316L stainless-steel substrate by using a metal-organic chemical vapor deposition technique for the purpose of hydrogen-isotope permeation barrier. Electron microscopy based imaging and energy-dispersive X-ray spectroscopy measurements indicate a sound film quality together with X-ray diffraction experiments. We also measured deuterium permeation in the film at high temperatures ranging from 600 $^{\circ}$C to 800 $^{\circ}$C. The permeation reduction was most apparent at 650 $^{\circ}$C. Above 800 $^{\circ}$C, we confirmed that the film was damaged and did not work as a permeation barrier.

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07:11 Arxiv.org PhysicsHelical inward orbits of high-$Z$ impurities. (arXiv:1907.12631v1 [physics.plasm-ph])

In a tokamak the edge and the central region may become connected by helical orbits resulting from the combination of global poloidal rotation and localized radial shifts. The rotation sustained by the Stringer mechanism and the baroclinic effect are able to generate such helical orbit. This can be a contribution to the inward flow and central accumulation of high-$Z$ impurity ions.

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30.07.2019
09:47 Arxiv.org PhysicsDevelopment of CFETR scenarios with self-consistent core-pedestal coupled simulations. (arXiv:1907.11919v1 [physics.plasm-ph])

This paper develops two non-inductive steady state scenarios for larger size configuration of China Fusion Engineering Test Reactor (CFETR) with integrated modeling simulations. A self-consistent core-pedestal coupled workflow for CFETR is developed under integrated modeling framework OMFIT, which allows more accurate evaluation of CFETR performance. The workflow integrates equilibrium code EFIT, transport codes ONETWO and TGYRO, and pedestal code EPED. A fully non-inductive baseline phase I scenario is developed with the workflow, which satisfies the minimum goal of Fusion Nuclear Science Facility. Compared with previous work, which proves the larger size and higher toroidal field CFETR configuration than has the advantages of reducing heating and current drive requirements, lowering divertor and wall power loads, allowing higher bootstrap current fraction and better confinement. A fully

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09:47 Arxiv.org CSLeveraging Pre-trained Checkpoints for Sequence Generation Tasks. (arXiv:1907.12461v1 [cs.CL])

Unsupervised pre-training of large neural models has recently revolutionized Natural Language Processing. Warm-starting from the publicly released checkpoints, NLP practitioners have pushed the state-of-the-art on multiple benchmarks while saving significant amounts of compute time. So far the focus has been mainly on the Natural Language Understanding tasks. In this paper, we present an extensive empirical study on the utility of initializing large Transformer-based sequence-to-sequence models with the publicly available pre-trained BERT and GPT-2 checkpoints for sequence generation. We have run over 300 experiments spending thousands of TPU hours to find the recipe that works best and demonstrate that it results in new state-of-the-art results on Machine Translation, Summarization, Sentence Splitting and Sentence Fusion.

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29.07.2019
23:23 ScienceDaily.comDemonstration of alpha particle confinement capability in helical fusion plasmas

A team of fusion researchers demonstrated that ions with energy in mega electron volt range are superiorly confined in a plasma for the first time in helical systems. This promises alpha particle confinement required for realizing fusion energy in a helical reactor. The results were obtained by deuterium plasma experiments in the Large Helical Device and with a newly developed detector for measuring neutrons created by the reaction between background deuterons and fusion-born energetic ions.

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17:40 Phys.orgDemonstration of alpha particle confinement capability in helical fusion plasmas

A team of fusion researchers succeeded in proving that energetic ions with energy in mega electron volt (MeV) range are superiorly confined in a plasma for the first time in helical systems. This promises the alpha particle (helium ion) confinement required for realizing fusion energy in a helical reactor.

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05:20 Arxiv.org PhysicsExtended calculations of energy levels, radiative properties, and lifetimes for oxygen-like Mo XXXV. (arXiv:1907.11548v1 [physics.atom-ph])

Employing two state-of-the-art methods, second-order many-body perturbation theory and multiconfiguration Dirac-Fock, highly accurate calculations are performed for the lowest 318 fine-structure levels arising from the $2s^{2} 2p^{4}$, $2s 2p^{5}$, $2p^{6}$, $2s^{2} 2p^{3} 3l$, $2s 2p^{4} 3l$, $2p^{5} 3l$, and $2s^{2} 2p^{3} 4l$ configurations in O-like \mbox{Mo XXXV}. Complete and consistent atomic data, including excitation energies, lifetimes, wavelengths, and E1, E2, M1 line strengths, oscillator strengths, and transition rates among these 318 levels are provided. Comparisons are made between the present two data sets, as well as with other available experimental and theoretical values. The present data are accurate enough for identification and deblending of emission lines involving the $n=3,4$ levels and are also useful for modeling and diagnosing fusion plasmas\kw{. These data can} be

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25.07.2019
18:23 ScienceDaily.comSeeing clearly: Revised computer code accurately models an instability in fusion plasmas

Subatomic particles zip around fusion machines known as tokamaks and sometimes merge, releasing large amounts of energy. Now, physicists have confirmed that an updated computer code could help to predict and ultimately prevent the particles from leaking from the magnetic fields confining them.

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18:05 Phys.orgBalancing beams: Multiple laser beamlets show better electron and ion acceleration

A research team led by Osaka University showed how multiple overlapping laser beams are better at accelerating electrons to incredibly fast speeds, as compared with a single laser. This method can lead to more powerful and efficient X-ray and ion generation for laboratory astrophysics, cancer therapy research, as well as a path toward controlled nuclear fusion.

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09:02 Arxiv.org PhysicsMagnetic Levitation and Compression of Compact Tori. (arXiv:1907.10307v1 [physics.plasm-ph])

The magnetic compression experiment at General Fusion was a repetitive non-destructive test to study plasma physics applicable to Magnetic Target Fusion compression. A compact torus (CT) is formed with a co-axial gun into a containment region with an hour-glass shaped inner flux conserver, and an insulating outer wall. External coil currents keep the CT off the outer wall (radial levitation) and then rapidly compress it inwards. The optimal external coil configuration greatly improved both the levitated CT lifetime and the rate of shots with good flux conservation during compression. As confirmed by spectrometer data, the improved levitation field profile reduced plasma impurity levels by suppressing the interaction between plasma and the insulating outer wall during the formation process. Significant increases in magnetic field, density, and ion temperature were routinely observed at

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24.07.2019
22:54 Phys.orgSeeing clearly: Revised computer code accurately models an instability in fusion plasmas

Subatomic particles zip around ring-shaped fusion machines known as tokamaks and sometimes merge, releasing large amounts of energy. But these particles—a soup of charged electrons and atomic nuclei, or ions, collectively known as plasma—can sometimes leak out of the magnetic fields that confine them inside tokamaks. The leakage cools the plasma, reducing the efficiency of the fusion reactions and damaging the machine. Now, physicists have confirmed that an updated computer code could help to predict and ultimately prevent such leaks from happening.

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22:24 ScientificAmerican.ComWorld's Largest Nuclear Fusion Experiment Clears Milestone

The International Thermonuclear Experimental Reactor is set to launch operations in 2025 -- Read more on ScientificAmerican.com

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04:30 Arxiv.org PhysicsRetrospective of the ARPA-E ALPHA fusion program. (arXiv:1907.09921v1 [physics.plasm-ph])

In 2014 the Advanced Research Projects Agency-Energy (ARPA-E) of the U.S. Department of Energy (DOE) launched a new research program on low-cost approaches to fusion-energy development. The "Accelerating Low-Cost Plasma Heating and Assembly" (ALPHA) program set out to enable more rapid progress towards fusion energy by establishing a wider range of technological options that could be pursued with smaller, lower-cost experiments, short development and construction times, and high experimental throughput. Mainstream fusion research generally refers to magnetically or inertially confined fusion, both of which require expensive facilities for reasons briefly described below and explored in more detail in several books. ALPHA focused on magneto-inertial fusion (MIF), a class of pulsed fusion approaches with fuel densities in between those of magnetic and inertial fusion. This paper presents a

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22.07.2019
09:48 Arxiv.org PhysicsImpact of main ion pressure anisotropy on stellarator impurity transport. (arXiv:1907.08482v1 [physics.plasm-ph])

Main ions influence impurity dynamics through a variety of mechanisms; in particular, via impurity-ion collisions. To lowest order in an expansion in the main ion mass over the impurity mass, the impurity-ion collision operator only depends on the component of the main ion distribution that is odd in the parallel velocity. These lowest order terms give the parallel friction of the impurities with the main ions, which is typically assumed to be the main cause of collisional impurity transport. Next-order terms in the mass ratio expansion of the impurity-ion collision operator, proportional to the component of the main ion distribution that is even in the parallel velocity, are usually neglected. However, in stellarators, the even component of the main ion distribution can be very large. In this article, such next-order terms in the mass ratio expansion of the impurity-ion collision operator

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18.07.2019
06:17 Arxiv.org StatisticsConversational Help for Task Completion and Feature Discovery in Personal Assistants. (arXiv:1907.07564v1 [cs.HC])

Intelligent Personal Assistants (IPAs) have become widely popular in recent times. Most of the commercial IPAs today support a wide range of skills including Alarms, Reminders, Weather Updates, Music, News, Factual Questioning-Answering, etc. The list grows every day, making it difficult to remember the command structures needed to execute various tasks. An IPA must have the ability to communicate information about supported skills and direct users towards the right commands needed to execute them. Users interact with personal assistants in natural language. A query is defined to be a Help Query if it seeks information about a personal assistant's capabilities, or asks for instructions to execute a task. In this paper, we propose an interactive system which identifies help queries and retrieves appropriate responses. Our system comprises of a C-BiLSTM based classifier, which is a fusion of

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06:17 Arxiv.org StatisticsImproving Outbreak Detection with Stacking of Statistical Surveillance Methods. (arXiv:1907.07464v1 [cs.LG])

Epidemiologists use a variety of statistical algorithms for the early detection of outbreaks. The practical usefulness of such methods highly depends on the trade-off between the detection rate of outbreaks and the chances of raising a false alarm. Recent research has shown that the use of machine learning for the fusion of multiple statistical algorithms improves outbreak detection. Instead of relying only on the binary output (alarm or no alarm) of the statistical algorithms, we propose to make use of their p-values for training a fusion classifier. In addition, we also show that adding additional features and adapting the labeling of an epidemic period may further improve performance. For comparison and evaluation, a new measure is introduced which captures the performance of an outbreak detection method with respect to a low rate of false alarms more precisely than previous works. Our

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06:17 Arxiv.org Quantitative BiologyImproving Outbreak Detection with Stacking of Statistical Surveillance Methods. (arXiv:1907.07464v1 [cs.LG])

Epidemiologists use a variety of statistical algorithms for the early detection of outbreaks. The practical usefulness of such methods highly depends on the trade-off between the detection rate of outbreaks and the chances of raising a false alarm. Recent research has shown that the use of machine learning for the fusion of multiple statistical algorithms improves outbreak detection. Instead of relying only on the binary output (alarm or no alarm) of the statistical algorithms, we propose to make use of their p-values for training a fusion classifier. In addition, we also show that adding additional features and adapting the labeling of an epidemic period may further improve performance. For comparison and evaluation, a new measure is introduced which captures the performance of an outbreak detection method with respect to a low rate of false alarms more precisely than previous works. Our

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06:17 Arxiv.org PhysicsCharacterizations of thermal stability and electrical performance of Au-Ni coating on CuCrZr substrate for high vacuum radio-frequency contact application. (arXiv:1907.07236v1 [physics.app-ph])

Radio-frequency (RF) contacts-which are an example of electrical contacts-are commonly employed on accelerators and nuclear fusion experimental devices. RF contacts with a current load of 2 kA for steady-state operation were designed for application to the International Thermonuclear Experimental Reactor (ITER) device. In contrast to the typical working conditions of general commercial electrical contacts, those of RF contacts employed on fusion devices include high vacuum, high temperature, and neutron radiation. CuCrZr is currently of interest as a base material for the manufacture of louvers of RF contacts, which has excellent thermal and electrical properties and has low creep rate at 250 {\textdegree}C. In this study, a hard Au coating (Au-Ni) was electroplated on CuCrZr samples and the samples were then subjected to thermal aging treatment at 250 {\textdegree}C for 500 h in order to

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06:17 Arxiv.org CSConversational Help for Task Completion and Feature Discovery in Personal Assistants. (arXiv:1907.07564v1 [cs.HC])

Intelligent Personal Assistants (IPAs) have become widely popular in recent times. Most of the commercial IPAs today support a wide range of skills including Alarms, Reminders, Weather Updates, Music, News, Factual Questioning-Answering, etc. The list grows every day, making it difficult to remember the command structures needed to execute various tasks. An IPA must have the ability to communicate information about supported skills and direct users towards the right commands needed to execute them. Users interact with personal assistants in natural language. A query is defined to be a Help Query if it seeks information about a personal assistant's capabilities, or asks for instructions to execute a task. In this paper, we propose an interactive system which identifies help queries and retrieves appropriate responses. Our system comprises of a C-BiLSTM based classifier, which is a fusion of

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06:17 Arxiv.org CSImproving Outbreak Detection with Stacking of Statistical Surveillance Methods. (arXiv:1907.07464v1 [cs.LG])

Epidemiologists use a variety of statistical algorithms for the early detection of outbreaks. The practical usefulness of such methods highly depends on the trade-off between the detection rate of outbreaks and the chances of raising a false alarm. Recent research has shown that the use of machine learning for the fusion of multiple statistical algorithms improves outbreak detection. Instead of relying only on the binary output (alarm or no alarm) of the statistical algorithms, we propose to make use of their p-values for training a fusion classifier. In addition, we also show that adding additional features and adapting the labeling of an epidemic period may further improve performance. For comparison and evaluation, a new measure is introduced which captures the performance of an outbreak detection method with respect to a low rate of false alarms more precisely than previous works. Our

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16.07.2019
09:59 Nanowerk.comScientists create predictive model for hydrogen nanobubble interaction in metals

The researchers believe their study may enable quantitative understanding and evaluation of hydrogen-induced damage in hydrogen-rich environments such as fusion reactor cores.

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04:31 Arxiv.org MathOptimal Control of a Hot Plasma. (arXiv:1907.06403v1 [math-ph])

The time evolution of a collisionless plasma is modeled by the relativistic Vlasov-Maxwell system which couples the Vlasov equation (the transport equation) with the Maxwell equations of electrodynamics. We consider the case that the plasma is located in a bounded container $\Omega\subset\mathbb R^3$, for example a fusion reactor. Furthermore, there are external currents, typically in the exterior of the container, that may serve as a control of the plasma if adjusted suitably. We model objects, that are placed in space, via given matrix-valued functions $\varepsilon$ (the permittivity) and $\mu$ (the permeability). A typical aim in fusion plasma physics is to keep the amount of particles hitting $\partial\Omega$ as small as possible (since they damage the reactor wall), while the control costs should not be too exhaustive (to ensure efficiency). This leads to a minimizing problem with a PDE

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15.07.2019
07:14 Arxiv.org CSCoupled-Projection Residual Network for MRI Super-Resolution. (arXiv:1907.05598v1 [eess.IV])

Magnetic Resonance Imaging(MRI) has been widely used in clinical application and pathology research by helping doctors make more accurate diagnoses. On the other hand, accurate diagnosis by MRI remains a great challenge as images obtained via present MRI techniques usually have low resolutions. Improving MRI image quality and resolution thus becomes a critically important task. This paper presents an innovative Coupled-Projection Residual Network (CPRN) for MRI super-resolution. The CPRN consists of two complementary sub-networks: a shallow network and a deep network that keep the content consistency while learning high frequency differences between low-resolution and high-resolution images. The shallow sub-network employs coupled-projection for better retaining the MRI image details, where a novel feedback mechanism is introduced to guide the reconstruction of high-resolution images. The

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12.07.2019
08:26 Arxiv.org PhysicsOn low-energy nuclear reactions. (arXiv:1907.05211v1 [physics.gen-ph])

Based on our recent theoretical findings (Phys. Rev. C 99, 054620 (2019)) it is shown that proton and deuteron capture reactions of extremely low energy may have accountable rate in the case of all elements of the periodic table. Certain numerical results of rates of nuclear reactions of two final fragments of extremely low energy are also given. New way of thinking about low-energy nuclear reactions (LENR) phenomena is suggested. Possible explanations for the contradictory observations announced between 1905-1927 and possible reasons for negative results of 'cold fusion' experiments published recently by the Google-organized scientific group (https://www.nature.com/articles/s41586-019-1256-6) are given.

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11.07.2019
04:16 Arxiv.org PhysicsTheory of Edge Localized Mode Suppression by Static Resonant Magnetic Perturbations in the DIII-D Tokamak. (arXiv:1907.04366v1 [physics.plasm-ph])

Recent research (Hu, et al. 2019) has shed considerable light on the poorly understood physical mechanism that underlies the suppression of edge localized modes (ELMs) by externally applied resonant magnetic perturbations (RMPs) in H-mode tokamak plasmas. In particular, computer simulations (made using the cylindrical, multi-harmonic, five-field, nonlinear code, TM1) of RMP-induced ELM suppression experiments performed on the DIII-D tokamak find that the formation of RMP-driven magnetic island chains at the top and the bottom of the pedestal can account for both ELM suppression and the enhanced particle transport, known as density pump-out, that is invariably observed to accompany the application of edge-resonant magnetic perturbations to H-mode plasmas. This paper employs a combination of analytic theory and simulation to gain a more exact understanding of the physical mechanism that

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10.07.2019
19:36 Phys.orgDiscovered: A new way to measure the stability of next-generation magnetic fusion devices

Scientists seeking to bring to Earth the fusion that powers the sun and stars must control the hot, charged plasma—the state of matter composed of free-floating electrons and atomic nuclei, or ions—that fuels fusion reactions. For scientists who confine the plasma in magnetic fields, a key task calls for mapping the shape of the fields, a process known as measuring the equilibrium, or stability, of the plasma. At the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL), researchers have proposed a new measurement technique to avoid problems expected when mapping the fields on large and powerful future tokamaks, or magnetic fusion devices, that house the reactions.

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07:07 Arxiv.org PhysicsAn application of survival analysis to disruption prediction via Random Forests. (arXiv:1907.04291v1 [physics.plasm-ph])

One of the most pressing challenges facing the fusion community is adequately mitigating or, even better, avoiding disruptions of tokamak plasmas. However, before this can be done, disruptions must first be predicted with sufficient warning time to actuate a response. The established field of survival analysis provides a convenient statistical framework for time-to-event (i.e. time-to-disruption) studies. This paper demonstrates the integration of an existing disruption prediction machine learning algorithm with the Kaplan-Meier estimator of survival probability. Specifically discussed are the implied warning times from binary classification of disruption databases and the interpretation of output signals from Random Forest algorithms trained and tested on these databases. This survival analysis approach is applied to both smooth and noisy test data to highlight important features of the

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07:07 Arxiv.org PhysicsNuclear Recoil Scintillation Linearity of a High Pressure $^4$He Gas Detector. (arXiv:1907.03985v1 [physics.ins-det])

We investigate scintillation linearity of a commercial high pressure $^4$He gas detector using monoenergetic 2.8 MeV neutrons from a deuterium-deuterium fusion neutron generator. The scintillation response of the detector was measured for a range of recoil energies between 83 keV and 626 keV by tagging neutrons scattering into fixed angles with a far-side organic scintillator detector. Detailed Monte Carlo simulations were compared to experimental data to determine the linearity of the detector response by comparing the scaling of the energy deposits in the simulations to the detector output. In this analysis, a linear scintillation response corresponds to a consistent value for the scaling factor between simulated energy deposits and experimental data for several different scattering angles. We demonstrate that the detector can be used to detect fast neutron interactions down to 83 keV

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09.07.2019
09:57 Arxiv.org PhysicsA facility for direct measurements for nuclear astrophysics at IFIN-HH -- a 3 MV tandem accelerator and an ultra-low background laboratory. (arXiv:1907.03596v1 [physics.acc-ph])

We present a facility for direct measurements at low and very low energies typical for nuclear astrophysics (NA). The facility consists of a small and robust tandem accelerator where irradiations are made, and an ultra-low background laboratory located in a salt mine where very low radio-activities can be measured. Both belong to Horia Hulubei National Institute for Physics and Nuclear Engineering (IFIN-HH) but are situated 120 km apart. Their performances are shown using a few cases where they are used. We argue that this facility is competitive for the study of nuclear reactions induced by alpha particles and by light ions at energies close or down into the Gamow windows. A good case study was the 13C+12C fusion reaction, where the proton evaporation channel leads to an activity with T1/2 = 15 h, appropriate for samples' transfer to the salt mine. Measurements were done using the thick

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00:05 WhatReallyHappened.comFor 30 years, the Dept. of Energy and “scientific establishment” has blocked the truth about cold fusion (Low-Energy Nuclear Reactions), the ultimate “renewable” energy solution for humanity

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08.07.2019
05:40 Arxiv.org PhysicsInference of $\alpha$-particle density profiles from ITER collective Thomson scattering. (arXiv:1907.02756v1 [physics.plasm-ph])

The primary purpose of the collective Thomson scattering (CTS) diagnostic at ITER is to measure the properties of fast-ion populations, in particular those of fusion-born $\alpha$-particles. Based on the present design of the diagnostic, we compute and fit synthetic CTS spectra for the ITER baseline plasma scenario, including the effects of noise, refraction, multiple fast-ion populations, and uncertainties on nuisance parameters. As part of this, we developed a model for CTS that incorporates spatial effects of frequency-dependent refraction. While such effects will distort the measured ITER CTS spectra, we demonstrate that the true $\alpha$-particle densities can nevertheless be recovered to within ~10% from noisy synthetic spectra, using existing fitting methods that do not take these spatial effects into account. Under realistic operating conditions, we thus find the predicted performance

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05:40 Arxiv.org PhysicsModelling the electron cyclotron emission below the fundamental resonance in ITER. (arXiv:1907.02747v1 [physics.plasm-ph])

The electron cyclotron emission (ECE) in fusion devices is non-trivial to model in detail at frequencies well below the fundamental resonance where the plasma is optically thin. However, doing so is important for evaluating the background for microwave diagnostics operating in this frequency range. Here we present a general framework for estimating the ECE levels of fusion plasmas at such frequencies using ensemble-averaging of rays traced through many randomized wall reflections. This enables us to account for the overall vacuum vessel geometry, self-consistently include cross-polarization, and quantify the statistical uncertainty on the resulting ECE spectra. Applying this to ITER conditions, we find simulated ECE levels that increase strongly with frequency and plasma temperature in the considered range of 55-75 GHz. At frequencies smaller than 70 GHz, we predict an X-mode ECE level below

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03.07.2019
06:53 GizmagNuclear fusion plasma could be stabilized against large eruptions – by causing lots of small ones


As the Sun and stars themselves can attest, nuclear fusion could be an essentially unlimited energy source, if we can only harness it. The problem is that the plasma used is inherently unstable, and large eruptions can damage the reactors containing it. But now, physicists from the Princeton Plasma Physics Laboratory (PPPL) have found a way to prevent those large eruptions, by triggering lots of small ones through the injection of tiny pellets of beryllium.
.. Continue Reading Nuclear fusion plasma could be stabilized against large eruptions – by causing lots of small ones Category: Energy Tags: Energy Fusion Nuclear Physics Plasma Princeton Reactors Tokamak reactor

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04:50 Arxiv.org PhysicsStellarators with permanent magnets. (arXiv:1907.01363v1 [physics.plasm-ph])

It is shown that the magnetic-field coils of a stellarator can, at least in principle, be substantially simplified by the use of permanent magnets. Such magnets cannot create toroidal magnetic flux but they can be used to shape the plasma and thus to create poloidal flux and rotational transform, thereby easing the requirements on the magnetic-field coils. As an example, a quasiaxisymmetric stellarator configuration is constructed with only 8 circular coils (all identical) and permanent magnets.

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04:00 ScienceDaily.comTiny granules can help bring clean and abundant fusion power to Earth

Physicists have concluded that injecting tiny beryllium pellets into ITER could help stabilize the plasma that fuels fusion reactions.

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01:01 ScienceDaily.comMeasuring the laws of nature

One of the fundamental physical constants, the 'weak axial vector coupling constant' (gA), has now been measured with very high precision for the first time. It is needed to explain nuclear fusion in the sun, to understand the formation of elements shortly after the Big Bang, or to understand important experiments in particle physics. With the help of sophisticated neutron experiments, the value of gA has now been determined with an accuracy of 0.04%.

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02.07.2019
23:34 Phys.orgTiny granules can help bring clean and abundant fusion power to Earth

Beryllium, a hard, silvery metal long used in X-ray machines and spacecraft, is finding a new role in the quest to bring the power that drives the sun and stars to Earth. Beryllium is one of the two main materials used for the wall in ITER, a multinational fusion facility under construction in France to demonstrate the practicality of fusion power. Now, physicists from the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) and General Atomics have concluded that injecting tiny beryllium pellets into ITER could help stabilize the plasma that fuels fusion reactions.

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07:39 Arxiv.org PhysicsFirst Results from an Event Synchronized -- High Repetition Thomson Scattering System at Wendelstein 7-X. (arXiv:1907.00492v1 [physics.plasm-ph])

The Wendelstein 7-X (W7-X) Thomson scattering (TS) diagnostic was upgraded to transiently achieve kilohertz sampling rates combined with adjustable measuring times. The existing Nd:YAG lasers are employed to repetitively emit "bursts", i.e. multiple laser pulses in a short time interval. Appropriately timing burst in the three available lasers, up to twelve evenly spaced consecutive measurements per burst are possible. The pulse-to-pulse increment within a burst can be tuned from 2 ms to 33.3 ms (500 kHz - 30 Hz). Additionally, an event trigger system was developed to synchronize the burst Thomson scattering measurements to plasma events. Exemplary, a case of fast electron density and temperature evolution after cryogenic H2 pellet injection is presented in order to demonstrate the capabilities of the method.

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01.07.2019
10:15 Arxiv.org PhysicsSimulating the nonlinear interaction of relativistic electrons and tokamak plasma instabilities: Implementation and validation of a fluid model. (arXiv:1906.12137v1 [physics.plasm-ph])

For the simulation of disruptions in tokamak fusion plasmas, a fluid model describing the evolution of relativistic runaway electrons and their interaction with the background plasma is presented. The overall aim of the model is to self-consistently describe the nonlinear coupled evolution of runaway electrons (REs) and plasma instabilities during disruptions. In this model, the runaway electrons are considered as a separate fluid species in which the initial seed is generated through the Dreicer source, which eventually grows by the avalanche mechanism (further relevant source mechanisms can easily be added). Advection of the runaway electrons is considered primarily along field lines, but also taking into account the ExB drift. The model is implemented in the nonlinear magnetohydrodynamic (MHD) code JOREK based on Bezier finite elements, with current coupling to the thermal plasma.

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28.06.2019
04:16 Arxiv.org PhysicsExperimental and synthetic measurements of polarized synchrotron emission from runaway electrons in Alcator C-Mod. (arXiv:1906.11304v1 [physics.plasm-ph])

This paper presents the first experimental analysis of polarized synchrotron emission from relativistic runaway electrons (REs) in a tokamak plasma. Importantly, we show that the polarization information of synchrotron radiation can be used to diagnose spatially-localized RE pitch angle distributions. Synchrotron-producing REs were generated during low density, Ohmic, diverted plasma discharges in the Alcator C-Mod tokamak. The ten-channel Motional Stark Effect diagnostic was used to measure spatial profiles of the polarization angle $\theta_{\mathrm{pol}}$ and the fraction $\mathrm{f}_{\mathrm{pol}}$ of detected light that was linearly-polarized. Spatial transitions in $\theta_{\mathrm{pol}}$ of 90$\deg$---from horizontal to vertical polarization and vice versa---are observed in experimental data and are well-explained by the gyro-motion of REs and high directionality of synchrotron

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25.06.2019
05:24 Arxiv.org StatisticsFault Matters: Sensor Data Fusion for Detection of Faults using Dempster-Shafer Theory of Evidence in IoT-Based Applications. (arXiv:1906.09769v1 [cs.LG])

Fault detection in sensor nodes is a pertinent issue that has been an important area of research for a very long time. But it is not explored much as yet in the context of Internet of Things. Internet of Things work with a massive amount of data so the responsibility for guaranteeing the accuracy of the data also lies with it. Moreover, a lot of important and critical decisions are made based on these data, so ensuring its correctness and accuracy is also very important. Also, the detection needs to be as precise as possible to avoid negative alerts. For this purpose, this work has adopted Dempster-Shafer Theory of Evidence which is a popular learning method to collate the information from sensors to come up with a decision regarding the faulty status of a sensor node. To verify the validity of the proposed method, simulations have been performed on a benchmark data set and data collected

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05:24 Arxiv.org CSFault Matters: Sensor Data Fusion for Detection of Faults using Dempster-Shafer Theory of Evidence in IoT-Based Applications. (arXiv:1906.09769v1 [cs.LG])

Fault detection in sensor nodes is a pertinent issue that has been an important area of research for a very long time. But it is not explored much as yet in the context of Internet of Things. Internet of Things work with a massive amount of data so the responsibility for guaranteeing the accuracy of the data also lies with it. Moreover, a lot of important and critical decisions are made based on these data, so ensuring its correctness and accuracy is also very important. Also, the detection needs to be as precise as possible to avoid negative alerts. For this purpose, this work has adopted Dempster-Shafer Theory of Evidence which is a popular learning method to collate the information from sensors to come up with a decision regarding the faulty status of a sensor node. To verify the validity of the proposed method, simulations have been performed on a benchmark data set and data collected

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20.06.2019
04:22 Arxiv.org PhysicsSingle-particle velocity distributions of collisionless, steady-state plasmas must follow Superstatistics. (arXiv:1906.08072v1 [cond-mat.stat-mech])

The correct modelling of velocity distribution functions for particles in steady-state plasmas is a central element in the study of nuclear fusion and also in the description of space plasmas. In this work, a statistical mechanical formalism for the description of collisionless plasmas in a steady state is presented, based solely on the application of the rules of probability and not relying on the concept of entropy. Beck and Cohen's superstatistical framework is recovered as a limiting case, and a "microscopic" definition of inverse temperature $\beta$ is given. Non-extensivity is not invoked a priori but enters the picture only through the analysis of correlations between parts of the system.

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19.06.2019
07:07 Arxiv.org PhysicsValidating the ASCOT modelling of NBI fast ions in Wendelstein 7-X stellarator. (arXiv:1906.07457v1 [physics.plasm-ph])

The first fast ion experiments in Wendelstein 7-X were performed in 2018. They are one of the first steps in demonstrating the optimised fast ion confinement of the stellarator. The fast ions were produced with a neutral beam injection (NBI) system and detected with infrared cameras (IR), a fast ion loss detector (FILD), fast ion charge exchange spectroscopy (FIDA), and post-mortem analysis of plasma facing components. The fast ion distribution function in the plasma and at the wall is being modelled with the ASCOT suite of codes. They calculate the ionisation of the injected neutrals and the consecutive slowing down process of the fast ions. The primary output of the code is the multidimensional fast ion distribution function within the plasma and the distribution of particle hit locations and velocities on the wall. Synthetic measurements based on ASCOT output are compared to experimental

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18.06.2019
09:48 Arxiv.org PhysicsCurl-free magnetic fields for stellarator optimization. (arXiv:1906.06807v1 [physics.plasm-ph])

This paper describes a new and efficient method of defining an annular region of a curl-free magnetic field with specific physics and coil properties that can be used in stellarator design. Three statements define the importance: (1) Codes can follow an optimized curl-free initial state to a final full-pressure equilibrium. The large size of the optimization space of stellarators, approximately fifty externally-produced distributions of magnetic field, makes success in finding a global optimum largely determined by the starting point. (2) The design of a stellarator is actually improved when the central region of the plasma has rapid transport with the confinement provided by a surrounding annulus of magnetic surfaces with low transport. (3) The stellarator is unique among all fusion concepts, inertial as well as magnetic, in not using the plasma itself to provide an essential part of its

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09:48 Arxiv.org PhysicsFusion hindrance effects in laser-induced non-neutral plasmas. (arXiv:1906.06724v1 [nucl-th])

Inertial confinement fusion hotspots and cluster Coulomb explosion plasmas may develop a positive net electric charge. The Coulomb barrier penetrability and the rate of nuclear fusion reactions at ultra-low energies ($\lesssim 10$ keV) are altered by such an environment. These effects are here studied via the screening potential approach. Approximate analytical results are developed by evaluating the average screening potential for some scenarios of interest. It is found that fusion is hindered for reactions between thermal fuel nuclei, while an enhancement is expected for secondary and "beam-target" reactions. Depending on the plasma conditions, the variations can be relevant even for relatively small net charges (several % difference or more in the fusion rate for an average net charge per nucleus of $10^{-5}$ proton charges).

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08:50 Arxiv.org StatisticsData-Driven Machine Learning Techniques for Self-healing in Cellular Wireless Networks: Challenges and Solutions. (arXiv:1906.06357v1 [cs.NI])

For enabling automatic deployment and management of cellular networks, the concept of self-organizing network (SON) was introduced. SON capabilities can enhance network performance, improve service quality, and reduce operational and capital expenditure (OPEX/CAPEX). As an important component in SON, self-healing is defined as a network paradigm where the faults of target networks are mitigated or recovered by automatically triggering a series of actions such as detection, diagnosis and compensation. Data-driven machine learning has been recognized as a powerful tool to bring intelligence into network and to realize self-healing. However, there are major challenges for practical applications of machine learning techniques for self-healing. In this article, we first classify these challenges into five categories: 1) data imbalance, 2) data insufficiency, 3) cost insensitivity, 4) non-real-time

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08:50 Arxiv.org CSEnlightenGAN: Deep Light Enhancement without Paired Supervision. (arXiv:1906.06972v1 [cs.CV])

Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As one such example, this paper explores the low-light image enhancement problem, where in practice it is extremely challenging to simultaneously take a low-light and a normal-light photo of the same visual scene. We propose a highly effective unsupervised generative adversarial network, dubbed EnlightenGAN, that can be trained without low/normal-light image pairs, yet proves to generalize very well on various real-world test images. Instead of supervising the learning using ground truth data, we propose to regularize the unpaired training using the information extracted from the input itself, and benchmark a series of innovations for the low-light image enhancement problem, including a global-local discriminator

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08:50 Arxiv.org CSData-Driven Machine Learning Techniques for Self-healing in Cellular Wireless Networks: Challenges and Solutions. (arXiv:1906.06357v1 [cs.NI])

For enabling automatic deployment and management of cellular networks, the concept of self-organizing network (SON) was introduced. SON capabilities can enhance network performance, improve service quality, and reduce operational and capital expenditure (OPEX/CAPEX). As an important component in SON, self-healing is defined as a network paradigm where the faults of target networks are mitigated or recovered by automatically triggering a series of actions such as detection, diagnosis and compensation. Data-driven machine learning has been recognized as a powerful tool to bring intelligence into network and to realize self-healing. However, there are major challenges for practical applications of machine learning techniques for self-healing. In this article, we first classify these challenges into five categories: 1) data imbalance, 2) data insufficiency, 3) cost insensitivity, 4) non-real-time

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17.06.2019
04:29 Arxiv.org CSFusion vectors: Embedding Graph Fusions for Efficient Unsupervised Rank Aggregation. (arXiv:1906.06011v1 [cs.CV])

The vast increase in amount and complexity of digital content led to a wide interest in ad-hoc retrieval systems in recent years. Complementary, the existence of heterogeneous data sources and retrieval models stimulated the proliferation of increasingly ingenious and effective rank aggregation functions. Although recently proposed rank aggregation functions are promising with respect to effectiveness, existing proposals in the area usually overlook efficiency aspects. We propose an innovative rank aggregation function that is unsupervised, intrinsically multimodal, and targeted for fast retrieval and top effectiveness performance. We introduce the concepts of embedding and indexing of graph-based rank-aggregation representation models, and their application for search tasks. Embedding formulations are also proposed for graph-based rank representations. We introduce the concept of fusion

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14.06.2019
20:45 CNBC top newsBrad Pitt and Laurene Powell Jobs are reportedly invested in a mysterious 'cold fusion' energy company

Brad Pitt, Laurene Powell Jobs and UK-investor Neil Woodford are all investors in North Carolina-based energy company Industrial Heat.

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20:23 FT.com TechnologyFacebook’s crucial crypto coin play

E3 clouds and consoles, meat moves, Brad Pitt and cold fusion, brain-machine gadgets

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09:58 Financial TimesThe long-shot that attracted Brad Pitt and Neil Woodford

Promise of abundant nuclear power propelled ‘cold fusion’ company to $918m valuation

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07:04 FT.com ScienceThe long-shot that attracted Brad Pitt and Neil Woodford

Promise of abundant nuclear power propelled ‘cold fusion’ company to $918m valuation

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06:28 Arxiv.org PhysicsAnalysis of Alfven Eigenmode destabilization in ITER using a Landau closure model. (arXiv:1906.05700v1 [physics.plasm-ph])

Alfven Eigenmodes (AE) can be destabilized during ITER discharges driven by neutral beam injection (NBI) energetic particles (EP) and alpha particles. The aim of the present study is to analyze the AE stability of different ITER operation scenarios considering multiple energetic particle species. We use the reduced magneto-hydrodynamic (MHD) equations to describe the linear evolution of the poloidal flux and the toroidal component of the vorticity in a full 3D system, coupled with equations of density and parallel velocity moments for the energetic particles species including the effect of the acoustic modes. The AEs driven by the NBI EP and alpha particles are stable in the configurations analyzed, only MHD-like modes with large toroidal couplings are unstable, although both can be destabilized if the EP beta increases above a threshold. The threshold is two times the model beta value for

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06:28 Arxiv.org PhysicsSolving the Grad-Shafranov equation using spectral elements for tokamak equilibrium with toroidal rotation. (arXiv:1906.05534v1 [physics.plasm-ph])

The Grad-Shafranov equation is solved using spectral elements for tokamak equilibrium with toroidal rotation. The Grad-Shafranov solver builds upon and extends the NIMEQ code [Howell and Sovinec, Comput. Phys. Commun. 185 (2014) 1415] previously developed for static tokamak equilibria. Both geometric and algebraic convergence are achieved as the polynomial degree of the spectral-element basis increases. A new analytical solution to the Grad-Shafranov equation is obtained for Solov'ev equilibrium in presence of rigid toroidal rotation, in addition to a previously obtained analytical solution for a defferent set of equilibrium and rotation profiles. The numerical solutions from the extended NIMEQ are benchmarked with the analytical solutions, with good agreements. Besides, the extended NIMEQ code is benchmarked with the FLOW code [L. Guazzotto, R. Betti, et al., Phys. Plasma

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05:53 Arxiv.org CSMIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data. (arXiv:1906.05512v1 [cs.CV])

Multi-modal data fusion has recently been shown promise in classification tasks in remote sensing. Optical data and radar data, two important yet intrinsically different data sources, are attracting more and more attention for potential data fusion. It is already widely known that, a machine learning based methodology often yields excellent performance. However, the methodology relies on a large training set, which is very expensive to achieve in remote sensing. The semi-supervised manifold alignment (SSMA), a multi-modal data fusion algorithm, has been designed to amplify the impact of an existing training set by linking labeled data to unlabeled data via unsupervised techniques. In this paper, we explore the potential of SSMA in fusing optical data and polarimetric SAR data, which are multi-sensory data sources. Furthermore, we propose a MAPPER-induced manifold alignment (MIMA) for

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12.06.2019
04:38 Arxiv.org PhysicsShear Alfv\'en and acoustic continuum in general axisymmetric toroidal geometry. (arXiv:1906.04451v1 [physics.plasm-ph])

The equations describing the continuous spectrum of shear Alfv\'en and ion sound waves propagating along magnetic field lines are introduced and solved in the ballooning space for general geometry in the ideal MHD limit. This approach is equivalent to earlier analyses by Chu et al. 1992 but the present formulation in the ballooning space allows to readily extend it to include gyrokinetic and three-dimensional equilibrium effects. In particular, following Chen and Zonca 2017, the MHD limit is adopted to illustrate the general methodology in a simple case, and the equations are solved within the framework of Floquet and Hill's equation theory. The connection of shear Alfv\'en and ion sound wave continuum structures to the generalized plasma inertia in the general fishbone like dispersion relation is also illustrated and discussed. As an application, the continuous frequency spectrum is

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04:03 Arxiv.org StatisticsFast and Accurate Least-Mean-Squares Solvers. (arXiv:1906.04705v1 [cs.LG])

Least-mean squares (LMS) solvers such as Linear / Ridge / Lasso-Regression, SVD and Elastic-Net not only solve fundamental machine learning problems, but are also the building blocks in a variety of other methods, such as decision trees and matrix factorizations.
We suggest an algorithm that gets a finite set of $n$ $d$-dimensional real vectors and returns a weighted subset of $d+1$ vectors whose sum is \emph{exactly} the same. The proof in Caratheodory's Theorem (1907) computes such a subset in $O(n^2d^2)$ time and thus not used in practice. Our algorithm computes this subset in $O(nd)$ time, using $O(\log n)$ calls to Caratheodory's construction on small but "smart" subsets. This is based on a novel paradigm of fusion between different data summarization techniques, known as sketches and coresets.
As an example application, we show how it can be used to boost the performance of

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04:03 Arxiv.org CSFast and Accurate Least-Mean-Squares Solvers. (arXiv:1906.04705v1 [cs.LG])

Least-mean squares (LMS) solvers such as Linear / Ridge / Lasso-Regression, SVD and Elastic-Net not only solve fundamental machine learning problems, but are also the building blocks in a variety of other methods, such as decision trees and matrix factorizations.
We suggest an algorithm that gets a finite set of $n$ $d$-dimensional real vectors and returns a weighted subset of $d+1$ vectors whose sum is \emph{exactly} the same. The proof in Caratheodory's Theorem (1907) computes such a subset in $O(n^2d^2)$ time and thus not used in practice. Our algorithm computes this subset in $O(nd)$ time, using $O(\log n)$ calls to Caratheodory's construction on small but "smart" subsets. This is based on a novel paradigm of fusion between different data summarization techniques, known as sketches and coresets.
As an example application, we show how it can be used to boost the performance of

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11.06.2019
21:37 ScienceDaily.comTracking major sources of energy loss in compact fusion facilities

Analysis of energy loss in low-aspect ratio tokamaks opens a new chapter in the development of predictions of transport in such facilities.

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19:53 Phys.orgTracking major sources of energy loss in compact fusion facilities

A key obstacle to controlling on Earth the fusion that powers the sun and stars is leakage of energy and particles from plasma, the hot, charged state of matter composed of free electrons and atomic nuclei that fuels fusion reactions. At the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL), physicists have been focusing on validating computer simulations that forecast energy losses caused by turbulent transport during fusion experiments.

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06:43 Arxiv.org CSFederated AI lets a team imagine together: Federated Learning of GANs. (arXiv:1906.03595v1 [cs.AI])

Envisioning a new imaginative idea together is a popular human need. Imagining together as a team can often lead to breakthrough ideas, but the collaboration effort can also be challenging, especially when the team members are separated by time and space. What if there is a AI that can assist the team to collaboratively envision new ideas?. Is it possible to develop a working model of such an AI? This paper aims to design such an intelligence. This paper proposes a approach to design a creative and collaborative intelligence by employing a form of distributed machine learning approach called Federated Learning along with fusion on Generative Adversarial Networks, GAN. This collaborative creative AI presents a new paradigm in AI, one that lets a team of two or more to come together to imagine and envision ideas that synergies well with interests of all members of the team. In short, this paper

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10.06.2019
09:28 Arxiv.org StatisticsFASTER: Fusion AnalyticS for public Transport Event Response. (arXiv:1906.03040v1 [cs.CY])

Increasing urban concentration raises operational challenges that can benefit from integrated monitoring and decision support. Such complex systems need to leverage the full stack of analytical methods, from state estimation using multi-sensor fusion for situational awareness, to prediction and computation of optimal responses. The FASTER platform that we describe in this work, deployed at nation scale and handling 1.5 billion public transport trips a year, offers such a full stack of techniques for this large-scale, real-time problem. FASTER provides fine-grained situational awareness and real-time decision support with the objective of improving the public transport commuter experience. The methods employed range from statistical machine learning to agent-based simulation and mixed-integer optimization. In this work we present an overview of the challenges and methods involved, with details

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09:28 Arxiv.org CSFASTER: Fusion AnalyticS for public Transport Event Response. (arXiv:1906.03040v1 [cs.CY])

Increasing urban concentration raises operational challenges that can benefit from integrated monitoring and decision support. Such complex systems need to leverage the full stack of analytical methods, from state estimation using multi-sensor fusion for situational awareness, to prediction and computation of optimal responses. The FASTER platform that we describe in this work, deployed at nation scale and handling 1.5 billion public transport trips a year, offers such a full stack of techniques for this large-scale, real-time problem. FASTER provides fine-grained situational awareness and real-time decision support with the objective of improving the public transport commuter experience. The methods employed range from statistical machine learning to agent-based simulation and mixed-integer optimization. In this work we present an overview of the challenges and methods involved, with details

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07.06.2019
03:50 Arxiv.org PhysicsValidating fast-ion wall-load IR analysis-methods against W7-X NBI empty-torus experiment. (arXiv:1906.02434v1 [physics.plasm-ph])

The first neutral beam injection (NBI) experiments in Wendelstein 7-X (W7-X) stellarator were conducted in the summer of 2018. The NBI system is used to heat the magnetically confined plasma by neutralising an accelerated hydrogen ion beam and directing it into the plasma, where the resulting energetic ions release their energy to heat the plasma. The modelling of the NBI fast ion experiments has commenced, including estimation of the shine-through and the orbit-losses. The stellarator has a wide-angle infra red (IR) imaging system to monitor the machine plasma facing component surface temperatures. This work validates the NBI model "Beamlet Based NBI (BBNBI)" and the newly written synthetic IR camera model. The validation is accomplished by comparing the measured and the synthetic IR camera measurements of an experiment where the NBI was injected into the vacuum vessel without a plasma. A

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06.06.2019
23:23 Phys.orgResearchers uncover a new obstacle to effective accelerator beams

High-energy ion beams—laser-like beams of atomic particles fired through accelerators—have applications that range from inertial confinement fusion to the production of superhot extreme states of matter that are thought to exist in the core of giant planets like Jupiter and that researchers are eager to study. These positively charged ion beams must be neutralized by negatively charged electrons to keep them sharply focused. However, researchers have found many obstacles to the neutralization process.

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05:45 Arxiv.org CSAutomated Activity Recognition of Construction Equipment Using a Data Fusion Approach. (arXiv:1906.02070v1 [eess.SP])

Automated monitoring of construction operations, especially operations of equipment and machines, is an essential step toward cost-estimating, and planning of construction projects. In recent years, a number of methods were suggested for recognizing activities of construction equipment. These methods are based on processing single types of data (audio, visual, or kinematic data). Considering the complexity of construction jobsites, using one source of data is not reliable enough to cover all conditions and scenarios. To address the issue, we utilized a data fusion approach: This approach is based on collecting audio and kinematic data, and includes the following steps: 1) recording audio and kinematic data generated by machines, 2) preprocessing data, 3) extracting time- and frequency-domain-features, 4) feature-fusion, and 5) categorizing activities using a machine-learning algorithm. The

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05:45 Arxiv.org CSCreativeBioMan: Brain and Body Wearable Computing based Creative Gaming System. (arXiv:1906.01801v1 [cs.HC])

Current artificial intelligence (AI) technology is mainly used in rational work such as computation and logical analysis. How to make the machine as aesthetic and creative as humans has gradually gained attention. This paper presents a creative game system (i.e., CreativeBioMan) for the first time. It combines brain wave data and multimodal emotion data, and then uses an AI algorithm for intelligent decision fusion, which can be used in artistic creation, aiming at separating the artist from repeated labor creation. To imitate the process of humans' artistic creation, the creation process of the algorithm is related to artists' previous artworks and their emotion. EEG data is used to analyze the style of artists and then match them with a style from a data set of historical works. Then, universal AI algorithms are combined with the unique creativity of each artist that evolve into a

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05.06.2019
08:40 Arxiv.org MathFusion of spin fields in $W_3$ conformal field theories. (arXiv:1906.01323v1 [math-ph])

In generic conformal field theories with $W_3$ symmetry, we identify a primary field $\sigma$ with rational Kac indices, which produces the full $\mathbb{Z}_3$ charged and neutral sectors by the fusion processes $\sigma \times \sigma$ and $\sigma \times \sigma^*$, respectively. In this sense, this field generalises the $\mathbb{Z}_3$ fundamental spin field of the three-state Potts model. Among the degenerate fields produced by these fusions, we single out a `parafermion' field $\psi$ and an `energy' field $\varepsilon$. In analogy with the Virasoro case, the exact curves for conformal dimensions $(h_\sigma,h_\psi)$ and $(h_\sigma,h_\varepsilon)$ are expected to give close estimates for the unitarity bounds in the conformal bootstrap analysis.

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04.06.2019
14:41 FT.com ScienceThirty years on, the cold fusion dream is alive

Despite low chances of success, the rewards of limitless energy are too great to give up on

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04:39 Arxiv.org PhysicsPopulation stability risks and biophysical benefits of cell-cell fusion in macrophage, osteoclast, and giant multinucleated cells. (arXiv:1906.00441v1 [physics.bio-ph])

Plant and animal cells are commonly understood as acquiring specialized functions through differentiation and asymmetric division. However, unique capabilities are also acquired when two or more cells fuse together, mixing cytoplasmic and genetic material. Here, we combine imaging experiments with biophysical modeling to perform the first risk-benefit analysis of cell-cell fusion. On one hand, we find fusion introduces an intrinsic instability to the population dynamics. On the other hand, we measure an unusual physiological scaling suggesting these cells grow substantially larger at lower energetic costs. Further analysis of the cytoskeleton finds a size-associated phase separation of F-actin that self-organizes multinucleated cell phenotypes.

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03.06.2019
07:25 Arxiv.org PhysicsSinglet-Triplet Energy Gaps of Organic Biradicals and Polyacenes with Auxiliary-Field Quantum Monte Carlo. (arXiv:1905.13316v1 [physics.chem-ph])

The energy gap between the lowest-lying singlet and triplet states is an important quantity in chemical photocatalysis, with relevant applications ranging from triplet fusion in optical upconversion to the design of organic light-emitting devices. The ab initio prediction of singlet-triplet (ST) gaps is challenging due to the potentially biradical nature of the involved states, combined with the potentially large size of relevant molecules. In this work, we show that phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can accurately predict ST gaps for chemical systems with singlet states of highly biradical nature, including a set of 13 small molecules and the ortho-, meta-, and para-isomers of benzyne. With respect to gas-phase experiments, ph-AFQMC using CASSCF trial wavefunctions achieves a mean averaged error of ~1 kcal/mol. Furthermore, we find that in the context of a

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29.05.2019
04:36 TechInvestorNews.comGoogle Revives Controversial Cold-Fusion Experiments (Slashdot)

SlashdotGoogle Revives Controversial Cold-Fusion Experiments - According to a peer-reviewed paper revealed this week, Google is continuing its experiments into the controversial science of cold fusion -- the theory that nuclear fusion, the process that powers the Sun, can produce energy in a table-top experiment at room temperature. While Googles recent project found no evidence that ...

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28.05.2019
17:32 ExtremeTech.comNew Data From the Sun May Lead to Advances in Nuclear Fusion

Scientists have made new observations of the Sun's atmosphere that reveal new information about the instability of its plasma. This information may turn out to be the key to generating power through nuclear fusion.
The post New Data From the Sun May Lead to Advances in Nuclear Fusion appeared first on ExtremeTech.

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16:36 Phys.orgRadiation damage lowers melting point of potential fusion reactor material

Radiation damage lowers the melting point of the metal tungsten, an effect that could contribute to material failure in nuclear fusion reactors and other applications where materials are exposed to particle radiation from extremely hot fusion plasma. That's the result of a study, published today in Science Advances, that was led by researchers at the Department of Energy's SLAC National Accelerator Laboratory.

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14:59 Phys.orgResearcher discusses reopening the case of cold fusion

Researchers at MIT have collaborated with a team of scientists from the University of British Columbia, the University of Maryland, Lawrence Berkeley National Laboratory, and Google to conduct a multiyear investigation into cold fusion, a type of benign nuclear reaction hypothesized to occur in benchtop apparatus at room temperature.

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