On the plasma density variation in the F2 region during geomagnetic storms

2020 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Rose Chigoziri Anamezie ◽  
Kingsley Chukwudi Okpala ◽  
Obiageli Josephine Ugonabo
Keyword(s):  
Plasma Density ◽  
Geomagnetic Storms ◽  
Density Variation

On the plasma density variation in the F2 region during geomagnetic storms

2021 ◽  
Vol 6 (3) ◽  
pp. 275
Author(s):  
Rose Chigoziri Anamezie ◽  
Kingsley Chukwudi Okpala ◽  
Obiageli Josephine Ugonabo
Keyword(s):  
Plasma Density ◽  
Geomagnetic Storms ◽  
Density Variation

Fluid restitution and shift of blood volume in anesthetized rabbits subject to cyclic hemorrhage

1992 ◽  
Vol 262 (1) ◽  
pp. H190-H199
Author(s):  
A. J. LaForte ◽  
L. P. Lee ◽  
G. F. Rich ◽  
T. C. Skalak ◽  
J. S. Lee
Keyword(s):  
Blood Volume ◽  
Plasma Density ◽  
Volume Change ◽  
Density Variation ◽  
Density Change ◽  
Short Term ◽  
Arterial Blood ◽  
Bilateral Vagotomy ◽  
Blood Density ◽  
Volume Shift

We investigated the effect of a 10% cyclic blood volume change with a period of 2 or 4 min to study the short-term control of blood volume. In experiments with pentobarbital-anesthetized rabbits, the blood density variation over a 2-min cycle is 0.94 +/- 0.04 (SE) g/l, and the plasma density variation is 0.17 +/- 0.04 g/l. The plasma density variation could result from a fluid restitution from the extravascular space (with a density 1,005 g/l), with a volume equal to 14% of the withdrawn blood volume. This restitution cannot account, however, for the entire observed density change in arterial blood. Because of the Fahraeus effect in microvascular flow, a shift in blood volume from the microvasculature is another mechanism that could lead to a decrease in the density of arterial blood. An analysis of the blood and plasma density variations indicates that a blood volume (49% of the shed volume) is shifted from the micro- to macrocirculation. This volume compensation by fluid restitution and volume shift acts to minimize the effect of hemorrhage on the filling of the venous system. We found that the blood density waveform parallels the change in blood volume. When the blood volume change reverses its direction, the density change also reverses direction with a time delay less than 8 s. The blood density variations are not altered by bilateral vagotomy or its combination with hexamethonium (a sympathetic ganglionic blocker). These observations of anesthetized rabbits indicate that the short-term compensation is primarily due to the volume shift from the microcirculation and is not regulated by humoral or neural mechanisms but by local mechanisms such as autoregulation and the passive response due to changes in microvascular pressure.

High-latitude ionospheric response to co-rotating interaction region- and coronal mass ejection-driven geomagnetic storms revealed by GPS tomography and ionosondes

2010 ◽  
Vol 466 (2123) ◽  
pp. 3391-3408 ◽  
Author(s):  
D. Pokhotelov ◽  
P. T. Jayachandran ◽  
C. N. Mitchell ◽  
M. H. Denton
Keyword(s):  
Solar Wind ◽  
Coronal Mass Ejection ◽  
Plasma Density ◽  
Large Scale ◽  
Geomagnetic Storms ◽  
Interaction Region ◽  
Electron Content ◽  
Polar Cap ◽  
Total Electron ◽  
Mass Ejection

Positive ionospheric anomalies induced in the polar cap region by co-rotating interaction region (CIR)- and coronal mass ejection (CME)-driven geomagnetic storms are analysed using four-dimensional tomographic reconstructions of the ionospheric plasma density based on measurements of the total electron content along ray paths of GPS signals. The results of GPS tomography are compared with ground-based observations of F region plasma density by digital ionosondes located in the Canadian Arctic. It is demonstrated that CIR- and CME-driven storms can produce large-scale polar cap anomalies of similar morphology in the form of the tongue of ionization (TOI) that appears on the poleward edge of the mid-latitude dayside storm-enhanced densities in positive ionospheric storms. The CIR-driven event of 14–16 October 2002 was able to produce ionospheric anomalies (TOI) comparable to those produced by the CME-driven storms of greater Dst magnitude. From the comparison of tomographic reconstructions and ionosonde data with solar wind measurements, it appears that the formation of large-scale polar cap anomalies is controlled by the orientation of the interplanetary magnetic field (IMF) with the TOI forming during the periods of extended southward IMF under conditions of high solar wind velocity.

Machine learning model of the plasmasphere to forecast satellite charging caused by solar storms.

2021 ◽  
Author(s):  
Stefano Bianco ◽  
Irina Zhelavskaya ◽  
Yuri Shprits
Keyword(s):  
Machine Learning ◽  
Solar Wind ◽  
Plasma Density ◽  
Extreme Ultraviolet ◽  
Geomagnetic Storms ◽  
Learning Model ◽  
Horizon 2020 ◽  
Machine Learning Model ◽  
Energetic Radiation ◽  
Solar Storms

<p>Solar storms are hazardous events consisting of a high emission of particles and radiation from the sun that can have adverse effect both in space and on Earth. In particular, the satellites can be damaged by energetic particles through surface and deep dielectric charging. The Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) is an EU Horizon 2020 project, which aims to provide a forecast of satellite charging through a pipeline of algorithms connecting the solar activity with the satellite charging. The plasmasphere modeling is an essential component of this pipeline, as plasma density is a crucial parameter for evaluating surface charging. Moreover, plasma density in the plasmasphere has very significant scientific applications, as it controls the growth of waves and how waves interact with particles. Successful plasmasphere machine learning models have been already developed, using as input several geomagnetic indices. However, in the context of the PAGER project one is constrained to use solar wind features and Kp index, whose forecasts are provided by other components of the pipeline. Here, we develop a machine learning model of the plasma density using solar wind features and the Kp geomagnetic index. We validate and test the model by measuring its performance in particular during geomagnetic storms on independent datasets withheld from the training set and by comparing the model predictions with global images of He+ distribution in the Earth’s plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. Finally, we present the results of both local and global plasma density reconstruction. </p>

scholarly journals A combined neural network- and physics-based approach for modeling the plasmasphere dynamics

2020 ◽  
Author(s):  
Irina Zhelavskaya ◽  
Nikita Aseev ◽  
Yuri Shprits ◽  
Maria Spasojevic
Keyword(s):  
Neural Network ◽  
Plasma Density ◽  
Large Scale ◽  
Geomagnetic Storms ◽  
Feedforward Neural Networks ◽  
Particle Interactions ◽  
Training Set ◽  
The Earth ◽  
Night Side ◽  
Time Periods

<p>Plasmasphere is a torus of cold plasma surrounding the Earth and is a very dynamic region. Its dynamics is driven by space weather. Having an accurate model of the plasmasphere is very important for wave-particle interactions and radiation belt modeling. In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct the global plasmasphere dynamics in the equatorial plane [<em>Bortnik et al</em>., 2016, <em>Zhelavskaya et al</em>., 2017, <em>Chu et al</em>., 2017]. These neural network-based models have been able to capture the large-scale dynamics of the plasmasphere, such as plume formation and the erosion of the plasmasphere on the night side. However, NNs have one limitation. When data is abundant, NNs perform really well. In contrast, when the coverage is limited or non-existent, as during geomagnetic storms, NNs do not perform well. The reason is that since these data are underrepresented in the training set, NNs cannot learn from the limited number of examples. This limitation can be overcome by employing physics-based modeling during such intervals. Physics-based models perform stably during high geomagnetic activity time periods if initialized and configured correctly. In this work, we show the combined approach to model the global plasmasphere dynamics that utilizes advantages of both neural network- and physics-based modeling and produces accurate global plasma density reconstruction during extreme events. We present examples of the global plasma density reconstruction for a number of extreme geomagnetic storms that occured in the past including the Halloween storm in 2003. We validate the global density reconstructions by comparing them to the IMAGE EUV images of the He+ particles distribution in the Earth’s plasmasphere for the same time periods.</p>

scholarly journals Sub-Auroral and Mid-Latitude GNSS ROTI Performance during Solar Cycle 24 Geomagnetic Disturbed Periods: Towards Storm’s Early Sensing

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4325
Author(s):  
Kacper Kotulak ◽  
Andrzej Krankowski ◽  
Adam Froń ◽  
Paweł Flisek ◽  
Ningbo Wang ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Plasma Density ◽  
Ionospheric Plasma ◽  
Geomagnetic Storms ◽  
Electron Content ◽  
Total Electron ◽  
Content Index ◽  
Solar Cycle 24 ◽  
Ionospheric Plasma Density ◽  
Cycle 24

Geomagnetic storms—triggered by the interaction between Earth’s magnetosphere and interplanetary magnetic field, driven by solar activity—are important for many Earth-bound aspects of life. Serious events may impact the electroenergetic infrastructure, but even weaker storms generate noticeable irregularities in the density of ionospheric plasma. Ionosphere electron density gradients interact with electromagnetic radiation in the radiofrequency domain, affecting sub- and trans-ionospheric transmissions. The main objective of the manuscript is to find key features of the storm-induced plasma density behaviour irregularities in regard to the event’s magnitude and general geomagnetic conditions. We also aim to set the foundations for the mid-latitude ionospheric plasma density now-casting irregularities. In the manuscript, we calculate the GPS+GLONASS-derived rate of TEC (total electron content) index (ROTI) for the meridional sector of 10–20∘ E, covering the latitudes between 40 and 70∘ N. Such an approach reveals equatorward spread of the auroral TEC irregularities reaching down to mid-latitudes. We have assessed the ROTI performance for 57 moderate-to-severe storms that occurred during solar cycle 24 and analyzed their behaviors in regard to the geomagnetic conditions (described by Kp, Dst, AE, Sym-H and PC indices).

Intramitochondrial Viruses of Reptilian Cell Origin

1972 ◽  
Vol 30 ◽  
pp. 318-319
Author(s):  
Philip D. Lunger ◽  
H. Fred Clark
Keyword(s):  
Particle Production ◽  
Outer Zone ◽  
Density Variation ◽  
Core Region ◽  
Mitochondrial Membranes ◽  
Virus Particles ◽  
The Core ◽  
Vipera Russelli ◽  
Maturation Stages ◽  
Type Particle

In the course of fine structure studies of spontaneous “C-type” particle production in a viper (Vipera russelli) spleen cell line, designated VSW, virus particles were frequently observed within mitochondria. The latter were usually enlarged or swollen, compared to virus-free mitochondria, and displayed a considerable degree of cristae disorganization.Intramitochondrial viruses measure 90 to 100 mμ in diameter, and consist of a nucleoid or core region of varying density and measuring approximately 45 mμ in diameter. Nucleoid density variation is presumed to reflect varying degrees of condensation, and hence maturation stages. The core region is surrounded by a less-dense outer zone presumably representing viral capsid.Particles are usually situated in peripheral regions of the mitochondrion. In most instances they appear to be lodged between loosely apposed inner and outer mitochondrial membranes.

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