2,912 research outputs found
Collisions, magnetization, and transport coefficients in the lower solar atmosphere
The lower solar atmosphere is an intrinsically multi-component and
collisional environment with electron and proton collision frequencies in the
range Hz, which may be considerably higher than the
gyro-frequencies for both species. We aim to provide a reliable quantitative
set of data for collision frequencies, magnetization, viscosity, and thermal
conductivity for the most important species in the lower solar atmosphere.
Having such data at hand is essential for any modeling that is aimed at
describing realistic properties of the considered environment.
We describe the altitude dependence of the parameters and the different
physics of collisions between charged species, and between charged and neutrals
species. Regions of dominance of each type of collisions are clearly
identified. We determine the layers within which either electrons or ions or
both are unmagnetized. Protons are shown to be un-magnetized in the lower
atmosphere in a layer that is at least 1000 km thick even for a kilo-Gauss
magnetic field that decreases exponentially with altitude. In these layers the
dynamics of charged species cannot be affected by the magnetic field, and this
fact is used in our modeling. Viscosity and thermal conductivity coefficients
are calculated for layers where ions are unmagnetized. We compare viscosity and
friction and determine the regions of dominance of each of the phenomena.
We provide the most reliable quantitative values for most important
parameters in the lower solar atmosphere to be used in analytical modeling and
numerical simulations of various phenomena such as waves, transport and
magnetization of particles, and the triggering mechanism of coronal mass
ejections.Comment: To appear in Astron. Astrophy
On quantum plasma: a plea for a common sense
The quantum plasma theory has flourished in the past few years without much
regard to the physical validity of the formulation or its connection to any
real physical system. It is argued here that there is a very limited physical
ground for the application of such a theory.Comment: EPL, to be published 201
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Prediction of solar particle events with SRAM-based soft error rate monitor and supervised machine learning
This work introduces an embedded approach for the prediction of Solar Particle Events (SPEs) in space applications by combining the real-time Soft Error Rate (SER) measurement with SRAM-based detector and the offline trained machine learning model. The proposed approach is intended for the self-adaptive fault-tolerant multiprocessing systems employed in space applications. With respect to the state-of-the-art, our solution allows for predicting the SER 1 h in advance and fine-grained hourly tracking of SER variations during SPEs as well as under normal conditions. Therefore, the target system can activate the appropriate mechanisms for radiation hardening before the onset of high radiation levels. Based on the comparison of five different machine learning algorithms trained with the public space flux database, the preliminary results indicate that the best prediction accuracy is achieved with the recurrent neural network (RNN) with long short-term memory (LSTM). © 2020 The Author
The Magellanic Stream and the density of coronal gas in the Galactic halo
The properties of the Magellanic Stream constrain the density of coronal gas
in the distant Galactic halo. We show that motion through ambient gas can
strongly heat Stream clouds, driving mass loss and causing evaporation. If the
ambient gas density is too high, then evaporation occurs on unreasonably short
timescales. Since heating dominates drag, tidal stripping appears to be
responsible for producing the Stream. Requiring the survival of the cloud MS IV
for 500 Myr sets an upper limit on the halo gas density n_H< 10^{-5} cm^{-3} at
50 kpc, roughly a factor of 10 lower than that estimated from the drag model of
Moore & Davis (1994). Implications for models of the evolution of gas in galaxy
halos are discussed.Comment: 4 pages, 1 figure, in press, ApJ
Adaptive Tuning of Feedback Gain in Time-Delayed Feedback Control
We demonstrate that time-delayed feedback control can be improved by
adaptively tuning the feedback gain. This adaptive controller is applied to the
stabilization of an unstable fixed point and an unstable periodic orbit
embedded in a chaotic attractor. The adaptation algorithm is constructed using
the speed-gradient method of control theory. Our computer simulations show that
the adaptation algorithm can find an appropriate value of the feedback gain for
single and multiple delays. Furthermore, we show that our method is robust to
noise and different initial conditions.Comment: 7 pages, 6 figure
The role of farmed fish in the diets of the resource-poor in Egypt.
The Egyptian aquaculture industry provides more than 100,000 full-time or part-time jobs and produces the country’s least-expensive farmed animal protein. Thus, aquaculture plays an important role in both sustaining livelihoods and improving the diet quality and nutritional health of Egyptians, including a significant proportion of the 25.5% who are resource-poor. Recognizing this dual role, WorldFish has promoted sustainable growth in Egyptian aquaculture for more than 20 years. Through its work, WorldFish has identified a lack of quality data about fish consumption preferences and practices. Eager to fill this knowledge gap, WorldFish partnered with the Environment and Development Group (EDG) to study consumption of fish, red meat and poultry among the resource-poor in Egypt. This study aimed to characterize current consumer preferences for and consumption patterns of animal-source foods, comparing red meat, poultry and fish. The resulting data is meant to contribute to a better understanding of what drives demand for fish among the resource-poor in Egypt, allowing value chain actors to more successfully market their products to this segment of the population
Localization, Coulomb interactions and electrical heating in single-wall carbon nanotubes/polymer composites
Low field and high field transport properties of carbon nanotubes/polymer
composites are investigated for different tube fractions. Above the percolation
threshold f_c=0.33%, transport is due to hopping of localized charge carriers
with a localization length xi=10-30 nm. Coulomb interactions associated with a
soft gap Delta_CG=2.5 meV are present at low temperature close to f_c. We argue
that it originates from the Coulomb charging energy effect which is partly
screened by adjacent bundles. The high field conductivity is described within
an electrical heating scheme. All the results suggest that using composites
close to the percolation threshold may be a way to access intrinsic properties
of the nanotubes by experiments at a macroscopic scale.Comment: 4 pages, 5 figures, Submitted to Phys. Rev.
Magnetic Brightening of Carbon Nanotube Photoluminescence through Symmetry Breaking
Often a modification of microscopic symmetry in a system can result in a
dramatic change in its macroscopic properties. Here we report that symmetry
breaking by a tube-threading magnetic field can drastically increase the
photoluminescence quantum yield of semiconducting single-walled carbon
nanotubes, by as much as a factor of six, at low temperatures. To explain this
striking connection between seemingly unrelated properties, we have developed a
comprehensive theoretical model based on magnetic-field-dependent
one-dimensional exciton band structure and the interplay of strong Coulomb
interactions and the Aharonov-Bohm effect. This conclusively explains our data
as the first experimental observation of dark excitons 5-10 meV below the
bright excitons in single-walled carbon nanotubes. We predict that this quantum
yield increase can be made much larger in disorder-free samples
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PID Tuning Using Extremum Seeking
Although proportional-integral-derivative (PID) controllers are widely used in the process industry, their effectiveness is often limited due to poor tuning. Manual tuning of PID controllers, which requires optimization of three parameters, is a time-consuming task. To remedy this difficulty, much effort has been invested in developing systematic tuning methods. Many of these methods rely on knowledge of the plant model or require special experiments to identify a suitable plant model. Reviews of these methods are given in [1] and the survey paper [2]. However, in many situations a plant model is not known, and it is not desirable to open the process loop for system identification. Thus a method for tuning PID parameters within a closed-loop setting is advantageous. In relay feedback tuning [3]-[5], the feedback controller is temporarily replaced by a relay. Relay feedback causes most systems to oscillate, thus determining one point on the Nyquist diagram. Based on the location of this point, PID parameters can be chosen to give the closed-loop system a desired phase and gain margin. An alternative tuning method, which does not require either a modification of the system or a system model, is unfalsified control [6], [7]. This method uses input-output data to determine whether a set of PID parameters meets performance specifications. An adaptive algorithm is used to update the PID controller based on whether or not the controller falsifies a given criterion. The method requires a finite set of candidate PID controllers that must be initially specified [6]. Unfalsified control for an infinite set of PID controllers has been developed in [7]; this approach requires a carefully chosen input signal [8]. Yet another model-free PID tuning method that does not require opening of the loop is iterative feedback tuning (IFT). IFT iteratively optimizes the controller parameters with respect to a cost function derived from the output signal of the closed-loop system, see [9]. This method is based on the performance of the closed-loop system during a step response experiment [10], [11]. In this article we present a method for optimizing the step response of a closed-loop system consisting of a PID controller and an unknown plant with a discrete version of extremum seeking (ES). Specifically, ES is used to minimize a cost function similar to that used in [10], [11], which quantifies the performance of the PID controller. ES, a non-model-based method, iteratively modifies the arguments (in this application the PID parameters) of a cost function so that the output of the cost function reaches a local minimum or local maximum. In the next section we apply ES to PID controller tuning. We illustrate this technique through simulations comparing the effectiveness of ES to other PID tuning methods. Next, we address the importance of the choice of cost function and consider the effect of controller saturation. Furthermore, we discuss the choice of ES tuning parameters. Finally, we offer some conclusions
Improved ocular delivery of quercetin and resveratrol : A comparative study between binary and ternary cyclodextrin complexes
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