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The bulk abundances of exoplanetesimals can be measured when they are accreted by white dwarfs. Recently, lithium from the accretion of exoplanetesimals was detected in relatively high levels in multiple white dwarfs. There are presently three proposed hypotheses to explain the detection of excess lithium in white dwarf photospheres: Big Bang and Galactic nucleosynthesis, continental crust, and an exomoon formed from spalled ring material. We present new observations of three previously known lithium-polluted white dwarfs (WD J1824+1213, WD J2317+1830, and LHS 2534), and one with metal pollution without lithium (SDSS J1636+1619). We also present atmospheric model fits to these white dwarfs. We then evaluate the abundances of these white dwarfs and two additional lithium-polluted white dwarfs that were previously fit using the same atmospheric models (WD J1644$-$0449 and SDSS J1330+6435) in the context of the three extant hypotheses for explaining lithium excesses in polluted white dwarfs. We find Big Bang and Galactic nucleosynthesis to be the most plausible explanation of the abundances in WD J1644$-$0449, WD J1824+1213, and WD J2317+1830. SDSS J1330+6435 will require stricter abundances to determine its planetesimal's origins, and LHS 2534, as presently modeled, defies all three hypotheses. We find the accretion of an exomoon formed from spalled ring material to be highly unlikely to be the explanation of the lithium excess in any of these cases., Comment: Accepted to ApJ, 31 pages, 13 figures

In the repulsive regime of the sine-Gordon model, we work out a method, that enables one to formulate the UV limit of finite volume expectation values in terms of the integrable description of the UV limit of the corresponding spectral problem. Since these expectation values are related to 3-point couplings containing at least two identical operators, our computations provide with an integrable formulation to the 3-point couplings of the UV CFT. Our approach is based on the fermionic description of operators in the sine-Gordon theory, in which these expectation values are expressed in terms of a finite number of elements of an infinite matrix. Focusing on vacuum expectation values, in this paper, the first two nontrivial coefficients in the UV series representation of this matrix are expressed in terms of integrability data. This allows one to get an integrable description to some specific ratios of vacuum expectation values in the complex Liouville CFT.

The progenitor system(s) as well as the explosion mechanism(s) of thermonuclear (Type Ia) supernovae are long-standing issues in astrophysics. Here we present ejecta masses and other physical parameters for 28 recent Type Ia supernovae inferred from multiband photometric and optical spectroscopic data. Our results confirm that the majority of SNe Ia show {\it observable} ejecta masses below the Chandrasekhar-limit (having a mean $M_{\rm ej} \approx 1.1 \pm 0.3$ M$_\odot$), consistent with the predictions of recent sub-M$_{\rm Ch}$ explosion models. They are compatible with models assuming either single- or double-degenerate progenitor configurations. We also recover a sub-sample of supernovae within $1.2 $ M$_\odot$ $< M_{\rm {ej}} < 1.5$ M$_\odot$ that are consistent with near-Chandrasekhar explosions. Taking into account the uncertainties of the inferred ejecta masses, about half of our SNe are compatible with both explosion models. We compare our results with those in previous studies, and discuss the caveats and concerns regarding the applied methodology.

Bug prediction aims at finding source code elements in a software system that are likely to contain defects. Being aware of the most error-prone parts of the program, one can efficiently allocate the limited amount of testing and code review resources. Therefore, bug prediction can support software maintenance and evolution to a great extent. In this paper, we propose a function level JavaScript bug prediction model based on static source code metrics with the addition of a hybrid (static and dynamic) code analysis based metric of the number of incoming and outgoing function calls (HNII and HNOI). Our motivation for this is that JavaScript is a highly dynamic scripting language for which static code analysis might be very imprecise; therefore, using a purely static source code features for bug prediction might not be enough. Based on a study where we extracted 824 buggy and 1943 non-buggy functions from the publicly available BugsJS dataset for the ESLint JavaScript project, we can confirm the positive impact of hybrid code metrics on the prediction performance of the ML models. Depending on the ML algorithm, applied hyper-parameters, and target measures we consider, hybrid invocation metrics bring a 2-10% increase in model performances (i.e., precision, recall, F-measure). Interestingly, replacing static NOI and NII metrics with their hybrid counterparts HNOI and HNII in itself improves model performances; however, using them all together yields the best results.

The rapid rise of cyber-crime activities and the growing number of devices threatened by them place software security issues in the spotlight. As around 90% of all attacks exploit known types of security issues, finding vulnerable components and applying existing mitigation techniques is a viable practical approach for fighting against cyber-crime. In this paper, we investigate how the state-of-the-art machine learning techniques, including a popular deep learning algorithm, perform in predicting functions with possible security vulnerabilities in JavaScript programs. We applied 8 machine learning algorithms to build prediction models using a new dataset constructed for this research from the vulnerability information in public databases of the Node Security Project and the Snyk platform, and code fixing patches from GitHub. We used static source code metrics as predictors and an extensive grid-search algorithm to find the best performing models. We also examined the effect of various re-sampling strategies to handle the imbalanced nature of the dataset. The best performing algorithm was KNN, which created a model for the prediction of vulnerable functions with an F-measure of 0.76 (0.91 precision and 0.66 recall). Moreover, deep learning, tree and forest based classifiers, and SVM were competitive with F-measures over 0.70. Although the F-measures did not vary significantly with the re-sampling strategies, the distribution of precision and recall did change. No re-sampling seemed to produce models preferring high precision, while re-sampling strategies balanced the IR measures.

The popularity and wide adoption of JavaScript both at the client and server side makes its code analysis more important than ever before. Most of the algorithms for vulnerability analysis, coding issue detection, or type inference rely on the call graph representation of the underlying program. Despite some obvious advantages of dynamic analysis, static algorithms should also be considered for call graph construction as they do not require extensive test beds for programs and their costly execution and tracing. In this paper, we systematically compare five widely adopted static algorithms - implemented by the npm call graph, IBM WALA, Google Closure Compiler, Approximate Call Graph, and Type Analyzer for JavaScript tools - for building JavaScript call graphs on 26 WebKit SunSpider benchmark programs and 6 real-world Node.js modules. We provide a performance analysis as well as a quantitative and qualitative evaluation of the results. We found that there was a relatively large intersection of the found call edges among the algorithms, which proved to be 100 precise. However, most of the tools found edges that were missed by all others. ACG had the highest precision followed immediately by TAJS, but ACG found significantly more call edges. As for the combination of tools, ACG and TAJS together covered 99% of the found true edges by all algorithms, while maintaining a precision as high as 98%. Only two of the tools were able to analyze up-to-date multi-file Node.js modules due to incomplete language features support. They agreed on almost 60% of the call edges, but each of them found valid edges that the other missed.

Understanding the atmospheric parameters of stars on the top of the RGB is essential to reveal the chemical composition of the Milky Way, as they can be used to probe the farthest parts of our Galaxy. Our goal is to determine the chemical composition of 21 RGB stars with $T_{\mathrm{eff}}<4200$K selected from the APOGEE-2 DR17 database using new observations carried out with the spectrograph mounted on the 1-m telescope of the Hungarian Piszk\'estet\H{o} Observatory and the SONG spectrograph (R=77000) on the Hertzsprung SONG telescope in the 4500$-$5800\r{A} wavelength range. This is the first time the spectrograph (R=18000) on the 1-m telescope at Piszk\'estet\H{o} Observatory was used to measure the abundances of stars. We created a new LTE spectral library using MARCS model atmospheres and SYNSPEC by including the line list of 23 molecules to determine atmospheric parameters ($T_{\mathrm{eff}}$, $\log g$, [Fe/H], [$\alpha$/Fe]) and abundances of Si, Ca, Ti, V, Cr, Mn, and Ni with FERRE. The resulting parameters were compared to that of APOGEE. We found a good agreement in general, the average difference is $-$11.2K in $T_{\mathrm{eff}}$, 0.11dex in $\log g$, 0.10dex in [Fe/H], and $-$0.01dex in [$\alpha$/Fe]. Our analysis successfully demonstrates the ability of the spectrograph at Piszk\'estet\H{o} Observatory to reliably measure the abundance of bright stars., Comment: Accepted for publication in PASP, 18 pages, 6 figures

The correlations of several fundamental properties of human brain connections are investigated in a consensus connectome, constructed from 1064 braingraphs, each on 1015 vertices, corresponding to 1015 anatomical brain areas. The properties examined include the edge length, the fiber number, or edge width, meaning the number of discovered axon bundles forming the edge and the occurrence number of the edge, meaning the number of individual braingraphs where the edge exists. By using our previously published robust braingraphs at \url{https://braingraph.org}, we have prepared a single consensus graph from the data and compared the statistical similarity of the edge occurrence numbers, edge lengths, and fiber counts of the edges. We have found a strong positive Spearman correlation between the edge occurrence numbers and the fiber count numbers, showing that statistically, the most frequent cerebral connections have the largest widths, i.e., the fiber number. We have found a negative Spearman correlation between the fiber lengths and fiber counts, showing that, typically, the shortest edges are the widest or strongest by their fiber counts. We have also found a negative Spearman correlation between the occurrence numbers and the edge lengths: it shows that typically, the long edges are infrequent, and the frequent edges are short.

FarView is an early-stage concept for a large, low-frequency radio observatory, manufactured in-situ on the lunar far side using metals extracted from the lunar regolith. It consists of 100,000 dipole antennas in compact subarrays distributed over a large area but with empty space between subarrays in a core-halo structure. FarView covers a total area of ~200 km2, has a dense core within the inner ~36 km2, and a ~power-law falloff of antenna density out to ~14 km from the center. With this design, it is relatively easy to identify multiple viable build sites on the lunar far side. The science case for FarView emphasizes the unique capabilities to probe the unexplored Cosmic Dark Ages - identified by the 2020 Astrophysics Decadal Survey as the discovery area for cosmology. FarView will deliver power spectra and tomographic maps tracing the evolution of the Universe from before the birth of the first stars to the beginning of Cosmic Dawn, and potentially provide unique insights into dark matter, early dark energy, neutrino masses, and the physics of inflation. What makes FarView feasible and affordable in the timeframe of the 2030s is that it is manufactured in-situ, utilizing space industrial technologies. This in-situ manufacturing architecture utilizes Earth-built equipment that is transported to the lunar surface to extract metals from the regolith and will use those metals to manufacture most of the array components: dipole antennas, power lines, and silicon solar cell power systems. This approach also enables a long functional lifetime, by permitting servicing and repair of the observatory. The full 100,000 dipole FarView observatory will take 4 - 8 years to build, depending on the realized performance of the manufacturing elements and the lunar delivery scenario., Comment: 26 pages, 7 figures, 2 tables

Ultra-hot Jupiters (UHJs) orbiting pulsating A/F stars represent an important subset of the exoplanetary demographic, as they are excellent candidates for the study of exoplanetary atmospheres, as well as being astrophysical laboratories for the investigation of planet-to-star interactions. We analyse the \texttt{TESS} (Transiting Exoplanet Survey Satellite) light curve of the WASP-167 system, consisting of an F1V star and a substellar companion on a $\sim 2.02$ day orbit. We model the combination of the ellipsoidal variability and the Doppler beaming to measure the mass of WASP-167b, and the reflection effect to obtain constraints on the geometric albedo, while placing a special emphasis on noise separation. We implement a basic model to determine the dayside ($T_{\rm Day}$), nightside ($T_{\rm Night}$) and intrinsic ($T_{\rm Internal}$) temperatures of WASP-167b and put a constraint on its Bond albedo. We confirm the transit parameters of the planet seen in the literature. We find that a resonant $\sim 2P^{-1}$ stellar signal (which may originate from planet-to-star interactions) interferes with the phase curve analysis. After considerate treatment of this signal, we find $M_p = 0.34 \pm 0.22$~$M_J$. We measure a dayside temperature of $2790 \pm 100$ K, classifying WASP-167b as an UHJ. We find a $2\sigma$ upper limit of $0.51$ on its Bond albedo, and determine the geometric albedo at $0.34 \pm 0.11$ ($1 \sigma$ uncertainty). With an occultation depth of $106.8 \pm 27.3$ ppm in the \texttt{TESS} passband, the UHJ WASP-167b will be an excellent target for atmospheric studies, especially those at thermal wavelength ranges, where the stellar pulsations are expected to be be less influential., Comment: 19 pages, 15 figures, resubmitted to Astronomy and Astrophysics after minor revision

A control technique is developed via Reinforcement Learning that allows arbitrary controlling of the position of an acoustic cavitation bubble in a dual-frequency standing acoustic wave field. The agent must choose the optimal pressure amplitude values to manipulate the bubble position in the range of $x/\lambda_0\in[0.05, 0.25]$. To train the agent an actor-critic off-policy algorithm (Deep Deterministic Policy Gradient) was used that supports continuous action space, which allows setting the pressure amplitude values continuously within $0$ and $1\, \mathrm{bar}$. A shaped reward function is formulated that minimizes the distance between the bubble and the target position and implicitly encourages the agent to perform the position control within the shortest amount of time. In some cases, the optimal control can be 7 times faster than the solution expected from the linear theory.

We present the discovery of the eclipsing double white dwarf (WD) binary WDJ 022558.21-692025.38 that has an orbital period of 47.19 min. Following identification with the Transiting Exoplanet Survey Satellite, we obtained time-series ground based spectroscopy and high-speed multi-band ULTRACAM photometry which indicate a primary DA WD of mass 0.40 +- 0.04 Msol and a 0.28 +- 0.02 Msol mass secondary WD, which is likely of type DA as well. The system becomes the third-closest eclipsing double WD binary discovered with a distance of approximately 400 pc and will be a detectable source for upcoming gravitational wave detectors in the mHz frequency range. Its orbital decay will be measurable photometrically within 10 yrs to a precision of better than 1%. The fate of the binary is to merge in approximately 41 Myr, likely forming a single, more massive WD., Comment: Accepted for publication in MNRAS, 8 pages + 2 appendix pages, 6 figures

Integrability methods give us access to a number of observables in the planar N=4 SYM. Among them, the Quantum Spectral Curve (QSC) governs the spectrum of anomalous dimensions. Low lying states were successfully studied in the past using the QSC. However, with the increased demand for a systematic study of a large number of states for various applications, there is a clear need for a fast QSC solver which can easily access a large number of excited states. Here, we fill this gap by developing a new algorithm and applied it to study all 219 states with the bare dimension $\Delta_0 \leq 6$ in a wide range of couplings. The new algorithm has an improved performance at weak coupling and allows to glue numerics smoothly the available perturbative data, resolving the previous obstruction. Further ~ 8-fold efficiency gain comes from C++ implementation over the best available Mathematica implementation. We have made the code and the data to be available via a GitHub repository. The method is generalisable for non-local observables as well as for other theories such as deformations of N=4 SYM and ABJM. It may find applications in the separation of variables and bootstrability approaches to the correlation functions. Some applications to correlators at strong coupling are also presented., Comment: 73 pages, 3 figures, 35 tables; v2: data updated, GitHub repository updated, references included, typos fixed

The purpose of this study was to model the impact of mentoring on women's work-life balance. Indeed, this study considered mentoring as a solution to create a work-life balance of women. For this purpose, semi-structured interviews with both mentors and mentees of Tehran Municipality were conducted and the collected data were analyzed using constructivist grounded theory. Findings provided a model of how mentoring affects women's work-life balance. According to this model, role management is the key criterion for work-life balancing among women. In this model, antecedents of role management and the contextual factors affecting role management, the constraints of mentoring in the organization, as well as the consequences of effective mentoring in the organization are described. The findings of this research contribute to the mentoring literature as well as to the role management literature and provide recommendations for organizations and for future research.

Close-in, sub-stellar companions to $\delta$ Scuti type stars present a highly suitable testbed for examining how planetary-mass objects can influence stellar pulsations. We aim to constrain the mass of HD 31221 b, probe its atmosphere, and demonstrate how it affects the pulsational pattern of its host, HD 31221. We made use of the available data from the short-cadence Transiting Exoplanet Survey Satellite (TESS). We modeled the nine observed transits and the out-of-phase variations, including Doppler beaming, ellipsoidal variations, and the reflection effect. We also incorporated ground-based photometry from the MuSCAT2 imager installed at the 1.52 m Telescopio Carlos Sanchez in the Teide Observatory, Spain. We found HD 31221 b to have an orbital period of $4.66631 \pm 0.00011$ days, with a radius of $1.32 \pm 0.14$ R$_J$ and a mass of $11.5 \pm 10.3$ M$_J$ (from the ellipsoidal effect), making it consistent with either a brown dwarf or a giant planet. As HD 31221 is a rapid rotator ($v \sin I_\star = 175.31 \pm 1.74$ km s$^{-1}$), we deduced the spin-orbit misalignment to be $\lambda = -121.6 \pm 14.4^\circ$ and $I_\star = 55.9 \pm 11.3^\circ$. The phase curve is dominated by the reflection effect, with a geometric albedo of $1.58 \pm 0.50$. We also found evidence that HD 31221 is a $\delta$ Scuti/$\gamma$ Doradus hybrid pulsator. There are three cases for which the $3$rd, $85$th, and $221$st orbital harmonics almost exactly coincide with peaks in the Fourier spectrum of the star, hinting at tidally perturbed stellar oscillations. HD 31221 b is the third substellar object that is found to be disrupting the pulsations of its host, following HAT-P-2 and WASP-33. Additional photometric observations by CHEOPS and/or PLATO can be used to further constrain its mass and provide a more in-depth analysis of its atmosphere., Comment: Accepted for publication as a Letter in A&A, 12 pages, 10 figures

The presence of software vulnerabilities is an ever-growing issue in software development. In most cases, it is desirable to detect vulnerabilities as early as possible, preferably in a just-in-time manner, when the vulnerable piece is added to the code base. The industry has a hard time combating this problem as manual inspection is costly and traditional means, such as rule-based bug detection, are not robust enough to follow the pace of the emergence of new vulnerabilities. The actively researched field of machine learning could help in such situations as models can be trained to detect vulnerable patterns. However, machine learning models work well only if the data is appropriately represented. In our work, we propose a novel way of representing changes in source code (i.e. code commits), the Code Change Tree, a form that is designed to keep only the differences between two abstract syntax trees of Java source code. We compared its effectiveness in predicting if a code change introduces a vulnerability against multiple representation types and evaluated them by a number of machine learning models as a baseline. The evaluation is done on a novel dataset that we published as part of our contributions using a 2-phase dataset generator method. Based on our evaluation we concluded that using Code Change Tree is a valid and effective choice to represent source code changes as it improves performance.

We report the discovery of two apparently isolated stellar remnants that exhibit rotationally modulated magnetic Balmer emission, adding to the emerging DAHe class of white dwarf stars. While the previously discovered members of this class show Zeeman-split triplet emission features corresponding to single magnetic field strengths, these two new objects exhibit significant fluctuations in their apparent magnetic field strengths with variability phase. The Zeeman-split hydrogen emission lines in LP $705{-}64$ broaden from $9.4$ MG to $22.2$ MG over an apparent spin period of $72.629$ minutes. Similarly, WD J$143019.29{-}562358.33$ varies from $5.8$ MG to $8.9$ MG over its apparent $86.394$-minute rotation period. This brings the DAHe class of white dwarfs to at least five objects, all with effective temperatures within $500$ K of $8000$ K and masses ranging from $0.65{-}0.83\,M_{\odot}$., Comment: 7 pages, 3 figures. Accepted for publication in MNRAS

Context. The lack of sub-Jovian planets on orbits of $P_{\rm orb} < 3$ days is a puzzling aspect of galaxy formation with regard to the distribution of exoplanets whose origins are currently unresolved. Aims. The possible explanations behind the formation of the sub-Jovian or Neptunian desert include several scenarios that can lead to different shapes for the boundary, predicting various dependencies between the position of the boundary and the stellar parameters. Methods. We explored the exoplanet distribution in various 2D and 3D projections, revealing the stellar-dependent substructures in the $P_{\rm orb}-M_{P}$ and the $P_{\rm orb}-R_{P}$ parameter plane. Results. We demonstrate that the upper boundary includes a range of planets, namely, inflated hot Jupiters and normal hot Jupiters, in the two parameter planes, respectively. We confirm the dependence of the boundary on several stellar parameters and, based on a fuzzy clustering analysis, we provide quantitative formulae for the dependencies in groups of smaller and larger planets. The overall period-radius distribution shows chemical substructures as well, with the boundary being dependent on volatiles and alpha-elements, alongside marginal (to none) dependence found for refractory elements. Conclusions. These findings confirm multiple plausible causes for the formation of the desert, particularly preferring those scenarios related to the irradiation-driven loss of the atmospheres of moderately massive planets as the predominant process in shaping planetary distributions., Comment: Accepted for publication in A&A; 11 pages, 11 figuress

We consider the 1015-vertex human consensus connectome computed from the diffusion MRI data of 1064 subjects. We define seven different orders on these 1015 graph vertices, where the orders depend on parameters derived from the brain circuitry, that is, from the properties of the edges (or connections) incident to the vertices ordered. We order the vertices according to their degree, the sum, the maximum, and the average of the fiber counts on the incident edges, and the sum, the maximum and the average length of the fibers in the incident edges. We analyze the similarities of these seven orders by the Spearman correlation coefficient and by their inversion numbers and have found that all of these seven orders have great similarities. In other words, if we interpret the orders as scoring of the importance of the vertices in the consensus connectome, then the scores of the vertices will be similar in all seven orderings. That is, important vertices of the human connectome typically have many neighbors, connected with long and thick axonal fibers (where thickness is measured by fiber numbers), and their incident edges have high maximum and average values of length and fiber-number parameters, too. Therefore, these parameters may yield robust ways of deciding which vertices are more important in the anatomy of our brain circuitry than the others.

SDSS-IV APOGEE-2, GALAH and Gaia-ESO are high resolution, ground-based, multi-object spectroscopic surveys providing fundamental stellar atmospheric parameters and multiple elemental abundance ratios for hundreds of thousands of stars of the Milky Way. We undertake a comparison between the most recent data releases of these surveys to investigate the accuracy and precision of derived parameters by placing the abundances on an absolute scale. We discuss the correlations in parameter and abundance differences as a function of main parameters. Uncovering the variants provides a basis to on-going efforts of future sky surveys. Quality samples from the APOGEE-GALAH, APOGEE-GES and GALAH-GES overlapping catalogs are collected. We investigate the mean variants between the surveys, and linear trends are also investigated. We compare the slope of correlations and mean differences with the reported uncertainties. The average and scatter of vrad, Teff, log g, [M/H] and vmicro, along with numerous species of elemental abundances in the combined catalogs show that in general there is a good agreement between the surveys. We find large radial velocity scatters ranging from 1.3 km/s to 4.4 km/s when comparing the three surveys. We observe weak trends: e.g. in $\Delta$Teff vs. $\Delta$log g for the APOGEE-GES stars, and a clear correlation in the vmicro-$\Delta$vmicro planes in the APOGEE-GALAH common sample. For [$\alpha$/H], [Ti/H] (APOGEE-GALAH giants) and [Al/H] (APOGEE-GALAH dwarfs) potential strong correlations are discovered as a function of the differences in the main atmospheric parameters, and we find weak trends for other elements. In general we find good agreement between the three surveys within their respective uncertainties. However, there are certain regimes in which strong variants exist, which we discuss. There are still offsets larger than 0.1 dex in the absolute abundance scales., Comment: Accepted in A&A, 23 pages, 13 figures, 6 tables. A minor correction is applied to the Gaia-ESO Survey's solar reference: Grevesse et al. (2007) instead of Grevesse & Sauval (1998)

The Far-side Array for Radio Science Investigations of the Dark ages and Exoplanets (FARSIDE) is a proposed mission concept to the lunar far side that seeks to deploy and operate an array of 128 dual-polarization, dipole antennas over a region of 100 square kilometers. The resulting interferometric radio telescope would provide unprecedented radio images of distant star systems, allowing for the investigation of faint radio signatures of coronal mass ejections and energetic particle events and could also lead to the detection of magnetospheres around exoplanets within their parent star's habitable zone. Simultaneously, FARSIDE would also measure the "Dark Ages" of the early Universe at a global 21-cm signal across a range of red shifts (z approximately 50-100). Each discrete antenna node in the array is connected to a central hub (located at the lander) via a communication and power tether. Nodes are driven by cold=operable electronics that continuously monitor an extremely wide-band of frequencies (200 kHz to 40 MHz), which surpass the capabilities of Earth-based telescopes by two orders of magnitude. Achieving this ground-breaking capability requires a robust deployment strategy on the lunar surface, which is feasible with existing, high TRL technologies (demonstrated or under active development) and is capable of delivery to the surface on next-generation commercial landers, such as Blue Origin's Blue Moon Lander. This paper presents an antenna packaging, placement, and surface deployment trade study that leverages recent advances in tethered mobile robots under development at NASA's Jet Propulsion Laboratory, which are used to deploy a flat, antenna-embedded, tape tether with optical communication and power transmission capabilities., Comment: 8 pages, 17 figures, IEEE Aerospace Conference Proceedings, 2021