The development of a magnetospheric substorm may be classified into three phases: growth, expansion, and recovery. The growth phase is important as it includes processes that lead to the expansion. ...In a recent growth‐phase study, a type of fast discrete auroral transient phenomena—referred to as Lumikot—were observed. The Lumikot are several kilometers across and move in the high‐energy precipitation region, parallel to the main growth‐phase arc, with both east‐west and west‐east directions of travel during the same event. Their apparent transverse movement and quasi‐stable intensity make them distinct from cooccurring optical pulsating aurorae. Comparison to other studies show that they occur in the cosmic noise absorption region and it is likely that the Lumikot are colocated with high‐energy particle populations on the boundary between the outer radiation belt and the plasmasheet.
Key Points
Small, transient auroral features (Lumikot) have been observed in the growth phase of substorms.
They move bidirectionally along the boundary between the bright arc and the diffuse aurora.
They map magnetically to the boundary region between the plasmasheet and outer radiation belt.
UVO 0825+15 is a hot bright helium-rich subdwarf which lies in K2 Field 5 and in a sample of intermediate helium-rich subdwarfs observed the Subaru High Dispersion Spectrograph. The K2 light curve ...shows low-amplitude variations, whilst the Subaru spectrum shows Pb iv absorption lines, indicative of a very high lead overabundance. UVO 0825+15 also has a high proper motion with kinematics typical for a thick disc star. Analyses of ultraviolet and intermediate dispersion optical spectra rule out a short-period binary companion and provide fundamental atmospheric parameters of T sub( eff)=38900 plus or minus 270 K, logg/cm s super( -2)=5.97 plus or minus 0.11, log n sub( He)/n sub( H) = -0.57 plus or minus 0.01, E sub( B - V) ... 0.03, and angular radius ... = 1.062 plus or minus 0.006 x 10 super( -11) radians (formal errors). The high-resolution spectrum shows that carbon is >2 dex subsolar, iron is approximately solar, and all other elements heavier than argon are at least 2-4 dex overabundant, including germanium, yttrium and lead. Approximately 150 lines in the blue-optical spectrum remain unidentified. The chemical structure of the photosphere is presumed to be determined by radiatively dominated diffusion. The K2 light curve shows a dominant period around 10.8 h, with a variable amplitude, its first harmonic, and another period at 13.3 h. The preferred explanation is multiperiodic non-radial oscillation due to g modes with very high radial order, although this presents difficulties for pulsation theory. Alternative explanations fail for lack of radial-velocity evidence. UVO 0825+15 represents the fourth member of a group of hot subdwarfs having helium-enriched photospheres and 3-4 dex overabundances of trans-iron elements and is the first lead-rich subdwarf to show evidence of pulsations. (ProQuest: ... denotes formulae/symbols omitted.)
We present 3‐D excitation rate estimates of artificial aurora in the ionospheric F layer, induced by high‐frequency radio waves from the European Incoherent Scatter heating facility. Simultaneous ...imaging of the artificial aurora was done with four separate Auroral Large Imaging System stations, permitting tomography‐like 3‐D auroral reconstruction of the enhanced atomic oxygen emissions at 6,300, 5,577, and 8,446 Å. Inspection of the 3‐D reconstructions suggests that the distribution of energized electrons is less extended in altitude than predicted by transport calculations of electrons accelerated to 2–100 eV. A possible reason for this discrepancy is that high‐frequency pumping might induce an anisotropic distribution of energized electrons.
Plain Language Summary
Auroral lights can be artificially generated by transmitting high‐frequency radio waves with high power into the upper atmosphere. In this article, we use multiple viewpoint imaging of artificially produced aurora to estimate the 3‐D distribution of the auroral lights by employing tomography‐like techniques. The 3‐D distribution is estimated in the red, green, and infrared auroral emission lines with wavelengths of 630.0, 557.7, and 844.6 nm, respectively. These emissions are excited by energetic electrons, which have been accelerated through interaction processes between the transmitted radio waves and plasma in the upper atmosphere, at an altitude of about 220–250 km. We observe that the estimated 3‐D auroral distributions are less extended in altitude than indicated by previous theoretical work. A possible reason for this disagreement is that the radio wave‐plasma interaction processes might lead to a direction dependent electron acceleration.
Key Points
The first 3‐D estimates of induced emission at 8,446 Å are presented along with 3‐D estimates of the enhanced emission at 6,300 and at 5,577 Å
The altitude distribution of the resulting excitation rates is inconsistent with excitation rate predictions
We observe that the emission enhancements are strongly dependent on the pump frequency proximity to the double resonance
Abstract
We report the discovery of three pulsating subdwarf B stars in binary systems observed with the Kepler space telescope during Campaign 5 of K2. EPIC 211696659 (SDSS J083603.98+155216.4) is a ...g-mode pulsator with a white dwarf companion and a binary period of 3.16 d. EPICs 211823779 (SDSS J082003.35+173914.2) and 211938328 (LB 378) are both p-mode pulsators with main-sequence F companions. The orbit of EPIC 211938328 is long (635 ± 146 d) while we cannot constrain that of EPIC 211823779. The p modes are near the Nyquist frequency and so we investigate ways to discriminate super- from sub-Nyquist frequencies. We search for rotationally induced frequency multiplets and all three stars appear to be slow rotators with EPIC 211696659 subsynchronous to its orbit.
ABSTRACT
Objectives:
To study micronutrient status and nutritional intake from complementary feeding in children on a cows’ milk exclusion (CME) diet.
Methods:
Fifty‐seven children with cows’ milk ...allergy, younger than 2 years, were included in a cross‐sectional study. Blood was analyzed for micronutrient status. Complementary feeding was defined as all solids and liquids except of breast milk, and assessed by 3‐day food diary. The results were analyzed according to 3 feeding patterns: mainly breast‐fed (mBF), partially breast‐fed, and no breast milk group (nBM).
Results:
The children had a median age of 9 months and micronutrient status was within normal range for total homocysteine (p‐tHcy), s‐B12, s‐folate, b‐Hb, s‐ferritin, s‐zinc, and s‐25(OH)D. There were no significant differences between feedings groups, except for B12‐biomarkers. The mBF had higher p‐tHcy (P < 0.000) and lower s‐B12 (P = 0.002) compared nBM. Vitamin B12 deficiency (p‐tHcy >6.5 μmol/L combined with s‐B12 <250 pmol/L) was found in 12% of participants, most frequently among the mBF (36%) and none in nBM group (P = 0.009). Vitamin B12 intake from complementary feeding was negatively correlated with p‐tHcy (r = −0.479, P = 0.001) and positively with s‐B12 (r = 0.410, P = 0.003). Iron deficiency anemia was found in 5%. Iron intake correlated positively with b‐Hb (r = 0.324, P = 0.02). Zinc deficiency was found in 7% and low 25(OH)D in 9%. Vitamin D intake was positively correlated with the use of supplements (r = 0.456, P = 0.001).
Conclusion:
The risk of B12 deficiency was high in mBF infants on CME diet, and complementary feeding was associated with better B12 status. Iron, zinc, and vitamin D deficiencies were present in all feeding groups. Complementary feeding should be introduced at 4 to 6 months of age. Vitamin D supplement is recommended to ensure adequate intake.
Context.
Solar Orbiter provides dust detection capability in the inner heliosphere, but estimating physical properties of detected dust from the collected data is far from straightforward.
Aims.
...First, a physical model for dust collection considering a Poisson process is formulated. Second, it is shown that dust on hyperbolic orbits is responsible for the majority of dust detections with Solar Orbiter’s Radio and Plasma Waves (RPW). Third, the model for dust counts is fitted to Solar Orbiter RPW data and parameters of the dust are inferred, namely radial velocity, hyperbolic meteoroids predominance, and the solar radiation pressure to gravity ratio as well as the uncertainties of these.
Methods.
Nonparametric model fitting was used to get the difference between the inbound and outbound detection rate and dust radial velocity was thus estimated. A hierarchical Bayesian model was formulated and applied to available Solar Orbiter RPW data. The model uses the methodology of integrated nested Laplace approximation, estimating parameters of dust and their ncertainties.
Results.
Solar Orbiter RPW dust observations can be modeled as a Poisson process in a Bayesian framework and observations up to this date are consistent with the hyperbolic dust model with an additional background component. Analysis suggests a radial velocity of the hyperbolic component around (63 ± 7) km s
−1
with the predominance of hyperbolic dust being about (78 ± 4)%. The results are consistent with hyperbolic meteoroids originating between 0.02 AU and 0.1 AU and showing substantial deceleration, which implies effective solar radiation pressure to a gravity ratio ≳ 0.5. The flux of the hyperbolic component at 1 AU is found to be (1.1 ± 0.2) × 10
−4
m
−2
s
−1
and the flux of the background component at 1 AU is found to be (5.4 ± 1.5) × 10
−5
m
−2
s
−1
.
The machine-learning research community has focused greatly on bias in
algorithms and have identified different manifestations of it. Bias in
training samples is recognised as a potential source of ...prejudice
in machine learning. It can be introduced by the human experts who define
the training sets. As machine-learning techniques are being applied to
auroral classification, it is important to identify and address
potential sources of expert-injected bias. In an ongoing study,
13 947 auroral images were manually classified with significant
differences between classifications. This large dataset allowed for the
identification of some of these biases, especially those originating
as a result of the ergonomics of the classification process. These
findings are presented in this paper to serve as a checklist for
improving training data integrity, not just for expert
classifications, but also for crowd-sourced, citizen science
projects. As the application of machine-learning techniques to auroral
research is relatively new, it is important that biases are identified
and addressed before they become endemic in the corpus of training
data.
Results from regular monitoring of relativistic compact binaries like PSR 1913+16 are consistent with the dominant (quadrupole) order emission of gravitational waves (GWs). We show that observations ...associated with the binary black hole (BBH) central engine of blazar OJ 287 demand the inclusion of gravitational radiation reaction effects beyond the quadrupolar order. It turns out that even the effects of certain hereditary contributions to GW emission are required to predict impact flare timings of OJ 287. We develop an approach that incorporates this effect into the BBH model for OJ 287. This allows us to demonstrate an excellent agreement between the observed impact flare timings and those predicted from ten orbital cycles of the BBH central engine model. The deduced rate of orbital period decay is nine orders of magnitude higher than the observed rate in PSR 1913+16, demonstrating again the relativistic nature of OJ 287's central engine. Finally, we argue that precise timing of the predicted 2019 impact flare should allow a test of the celebrated black hole "no-hair theorem" at the 10% level.
Solar Orbiter is equipped with electrical antennas performing fast measurements of the surrounding electric field. The antennas register high-velocity dust impacts through the electrical signatures ...of impact ionization. Although the basic principle of the detection has been known for decades, the understanding of the underlying process is not complete, due to the unique mechanical and electrical design of each spacecraft and the variability of the process. We present a study of electrical signatures of dust impacts on Solar Orbiter's body, as measured with the Radio and Plasma Waves electrical suite. A large proportion of the signatures present double-peak electrical waveforms in addition to the fast pre-spike due to electron motion, which are systematically observed for the first time. We believe this is due to Solar Orbiter's unique antenna design and a high temporal resolution of the measurements. The double peaks are explained as being due to two distinct processes. Qualitative and quantitative features of both peaks are described. The process for producing the primary peak has been studied extensively before, and the process for producing the secondary peak has been proposed before (Pantellini et al., 2012a) for Solar Terrestrial Relations Observatory (STEREO), although the corresponding delay of 100–300 µs between the primary and the secondary peak has not been observed until now. Based on this study, we conclude that the primary peak's amplitude is the better measure of the impact-produced charge, for which we find a typical value of around 8 pC. Therefore, the primary peak should be used to derive the impact-generated charge rather than the maximum. The observed asymmetry between the primary peaks measured with individual antennas is quantitatively explained as electrostatic induction. A relationship between the amplitude of the primary and the secondary peak is found to be non-linear, and the relation is partially explained with a model for electrical interaction through the antennas' photoelectron sheath.
This article presents the results of automatic detection of dust impact signals observed by the Solar Orbiter – Radio and Plasma Waves instrument. A sharp and characteristic electric field signal is ...observed by the Radio and Plasma Waves instrument when a dust particle impacts the spacecraft at high velocity. In this way, ∼ 5–20 dust impacts are daily detected as the Solar Orbiter travels through the interplanetary medium. The dust distribution in the inner solar system is largely uncharted and statistical studies of the detected dust impacts will enhance our understanding of the role of dust in the solar system. It is however challenging to automatically detect and separate dust signals from the plural of other signal shapes for two main reasons. Firstly, since the spacecraft charging causes variable shapes of the impact signals, and secondly because electromagnetic waves (such as solitary waves) may induce resembling electric field signals. In this article, we propose a novel machine learning-based framework for detection of dust impacts. We consider two different supervised machine learning approaches: the support vector machine classifier and the convolutional neural network classifier. Furthermore, we compare the performance of the machine learning classifiers to the currently used on-board classification algorithm and analyze 2 years of Radio and Plasma Waves instrument data. Overall, we conclude that detection of dust impact signals is a suitable task for supervised machine learning techniques. The convolutional neural network achieves the highest performance with 96 % ± 1 % overall classification accuracy and 94 % ± 2 % dust detection precision, a significant improvement to the currently used on-board classifier with 85 % overall classification accuracy and 75 % dust detection precision. In addition, both the support vector machine and the convolutional neural network classifiers detect more dust particles (on average) than the on-board classification algorithm, with 16 % ± 1 % and 18 % ± 8 % detection enhancement, respectively. The proposed convolutional neural network classifier (or similar tools) should therefore be considered for post-processing of the electric field signals observed by the Solar Orbiter.
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