Electron Density Model Research Articles

Synthesis, Crystal Structure, Hirshfeld Surface Analysis and Computational Study of Hydrazone Derivative of 5,5-dimethylcyclohexane-1,3-dione

The diazotization reaction of p-fluoroaniline from aromatic amines with 5,5-dimethylcyclohexane-1,3-dione was studied, as a result 2-(2-(p-fluorophenyl)hydrazone)-5,5-dimethylcyclohexane-1,3-dione (FHDCD) was synthesized and its structure was confirmed by single crystal X-ray diffraction (XRD) technique. The crystal packing was governed by various intermolecular interactions which was inspected by Hirshfeld surface analysis. 2D fingerprint plots were formed to find the contact that has most significant contribution in crystal packing. Enrichment ratio was calculated in order to find the contact that has highest propensity to form crystal packing interaction. Void analysis was carried out to predict the mechanical response of the crystal. Moreover, interaction energy calculations were performed at HF/3-21G electron density model to further inspect the supramolecular assembly of the crystal.

QSAR Studies, Molecular Docking, Molecular Dynamics, Synthesis, and Biological Evaluation of Novel Quinolinone-Based Thiosemicarbazones against Mycobacterium tuberculosis.

In this study, a series of novel quinolinone-based thiosemicarbazones were designed in silico and their activities tested in vitro against Mycobacterium tuberculosis (M. tuberculosis). Quantitative structure-activity relationship (QSAR) studies were performed using quinolinone and thiosemicarbazide as pharmacophoric nuclei; the best model showed statistical parameters of R2 = 0.83; F = 47.96; s = 0.31, and was validated by several different methods. The van der Waals volume, electron density, and electronegativity model results suggested a pivotal role in antituberculosis (anti-TB) activity. Subsequently, from this model a new series of quinolinone-thiosemicarbazone 11a-e was designed and docked against two tuberculosis protein targets: enoyl-acyl carrier protein reductase (InhA) and decaprenylphosphoryl-β-D-ribose-2'-oxidase (DprE1). Molecular dynamics simulation over 200 ns showed a binding energy of -71.3 to -12.7 Kcal/mol, suggesting likely inhibition. In vitro antimycobacterial activity of quinolinone-thiosemicarbazone for 11a-e was evaluated against M. bovis, M. tuberculosis H37Rv, and six different strains of drug-resistant M. tuberculosis. All compounds exhibited good to excellent activity against all the families of M. tuberculosis. Several of the here synthesized compounds were more effective than the standard drugs (isoniazid, oxafloxacin), 11d and 11e being the most active products. The results suggest that these compounds may contribute as lead compounds in the research of new potential antimycobacterial agents.

Electron Density Analysis of Metal–Metal Bonding in a Ni4 Cluster Featuring Ferromagnetic Exchange

We present a combined experimental and theoretical study of the nature of the proposed metal-metal bonding in the tetranuclear cluster Ni4(NPtBu3)4, which features four nickel(I) centers engaged in strong ferromagnetic coupling. High-resolution single-crystal synchrotron X-ray diffraction data collected at 25 K provide an accurate geometrical structure and a multipole model electron density description. Topological analysis of the electron density in the Ni4N4 core using the quantum theory of atoms in molecules clearly identifies the bonding as an eight-membered ring of type [Ni-N-]4 without direct Ni-Ni bonding, and this result is generally corroborated by an analysis of the energy density distribution. In contrast, the calculated bond delocalization index of ∼0.6 between neighboring Ni atoms is larger than what has been found for other bridged metal-metal bonds and implies direct Ni-Ni bonding. Similar support for the presence of direct Ni-Ni bonding is found in the interacting quantum atom approach, an energy decomposition scheme, which suggests the presence of stabilizing Ni-Ni bonding interactions with an exchange-correlation energy contribution approximately 50% of that of the Ni-N interactions. Altogether, while the direct interactions between neighboring Ni centers are too weak and sterically constrained to bear the signature of a topological bond critical point, other continuous measures clearly indicate significant Ni-Ni bonding. These metal-metal bonding interactions likely mediate direct ferromagnetic exchange, giving rise to the high-spin ground state of the molecule.

New refinement strategies for a pseudoatom databank – toward rapid electrostatic interaction energy estimations

Pseudoatom databanks, collections of parameters from the multipole model of electron densities for various atom types, are used to replace the Independent Atom Model with the more accurate Transferable Aspherical Atom Model (TAAM) in crystal structure refinements. The databanks are also employed to reconstruct the electron density of a molecule, crystal or biomacromolecular complex in a fast yet accurate way and compute various properties such as the energy of electrostatic interactions, for example. A even faster but similarly accurate model for estimations of electrostatic energy exists called aug-PROmol [Bojarowski, Kumar & Dominiak (2016). ChemPhysChem, 17, 2455–2460]. A model analogous to aug-PROmol cannot be built from the current pseudoatom databanks, as they perform badly when truncated to the monopole level. Here, new strategies for multipole model refinements were sought, leading to better parametrization at the monopole level. This would allow the creation of a pseudoatom databank in a single route of model parametrization, which would be suitable for both crystal structure refinement and rapid electrostatic energy calculations. Here it is shown that the cumulative approach to multipole model refinements, as opposed to simultaneous or iterative refinements of all multipole model parameters (Pv , κ, Plm , κ′), leads to substantially different models of electron density. Cumulative refinement of two blocks of parameters, the first with Pv and κ and then the second with Plm and κ′, leads to the P v κ|P lm κ′ model having promising properties. The P v κ|P lm κ′ model is as good as the University at Buffalo DataBank (UBDB) in X-ray structure TAAM refinements and electrostatic energy estimations, especially for less polar molecules. When truncated to the monopole level, the P v κ model has a chance to replace aug-PROmol in fast yet accurate electrostatics energy calculations, although some improvements in κ parametrization for polar functional groups are still needed. The P v κ model is also a source of point charges which behave similarly to restrained electrostatic potential (RESP) charges in electrostatic interaction energy estimations.

Size Distribution of Inactivated Tick-Borne Encephalitis Virus Particles Revealed by a Comprehensive Physicochemical Approach.

Tick-borne encephalitis virus (TBEV) is an enveloped RNA virus, a member of the genus Flavivirus (family Flaviviridae). Here, we provide a detailed analysis of the size and structure of the inactivated TBEV vaccine strain Sofjin-Chumakov. Four analytical methods were used to analyze individual TBEV particles—negative staining TEM, cryo-EM, atomic force microscopy (AFM), and nanoparticle tracking analysis (NTA). All methods confirmed that the particles were monodisperse and that their mean size was ~50 nm. Cryo-EM data allowed us to obtain a 3D electron density model of the virus with clearly distinguishable E protein molecules. STEM-EELS analysis detected phosphorus in the particles, which was interpreted as an indicator of RNA presence. Altogether, the described analytical procedures can be valuable for the characterization of inactivated vaccine virus samples.

A Statistical Model of Inner Magnetospheric Electron Density: Van Allen Probes Observations

AbstractBased on electron density observations between September 2012 and July 2019 from the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) on board the Van Allen Probes (VAPs) spacecraft, this paper makes a statistical investigation on the distribution of inner magnetospheric electron density in the magnetic equatorial plane (MEP) under different Kp levels, and further develops a new model of inner magnetospheric electron density in the MEP with multi‐parameters (Kp, SYM‐H, Pdyn, F10.7). The statistical results show that the plasmaspheric electron density in the inner magnetosphere in the MEP has an obvious Magnetic Local Time (MLT) distribution characteristic. With the increase of Kp index, the asymmetrical distribution of plasmaspheric electron density in the MEP increases, reaching the maximum value of erosion at MLT = 02:00, and the erosion at MLT = 14:00 is much less than that at MLT = 02:00. The distribution of plasmaspheric electron density in the low L‐value (L is shell parameter) region (L ≤ 2.8) is less affected by the geomagnetic activity than that in the high L‐value region (L ≥ 3.6). Comparison between the model outputs and the VAP's observations indicates that this statistical model could accurately describe the dynamic distribution characteristics of plasmaspheric electron density in the MEP during geomagnetic storms, such as erosion and refilling, and can be applied to space weather forecast.

Ionospheric electron density modelling using B-splines and constraint optimization

Many modern applications, such as precise point positioning, autonomous driving or precision agriculture would benefit significantly if a high-precision and high-resolution model of electron density in the ionosphere and the plasmasphere would be globally available. Since the development of such a model still relies on data with insufficient and uneven global coverage, the consideration of background information and the introduction of equality and inequality constraints on Chapman key parameters are essential. In this work, we develop a multi-layer Chapman model based on B-spline expansions of selected key parameters of the electron density. The unknown series coefficients of the key parameters are subject to equality and inequality constraints. Finally, the developed model is applied to a combination of real and semi-simulated input data; the results are validated through ionosonde measurements.Graphical

Predicting accurate ab initio DNA electron densities with equivariant neural networks

One of the fundamental limitations of accurately modeling biomolecules like DNA is the inability to perform quantum chemistry calculations on large molecular structures. We present a machine learning model based on an equivariant Euclidean neural network framework to obtain accurate ab initio electron densities for arbitrary DNA structures that are much too large for conventional quantum methods. The model is trained on representative B-DNA basepair steps that capture both base pairing and base stacking interactions. The model produces accurate electron densities for arbitrary B-DNA structures with typical errors of less than 1%. Crucially, the error does not increase with system size, which suggests that the model can extrapolate to large DNA structures with negligible loss of accuracy. The model also generalizes reasonably to other DNA structural motifs such as the A- and Z-DNA forms, despite being trained on only B-DNA configurations. The model is used to calculate electron densities of several large-scale DNA structures, and we show that the computational scaling for this model is essentially linear. We also show that this machine learning electron density model can be used to calculate accurate electrostatic potentials for DNA. These electrostatic potentials produce more accurate results compared with classical force fields and do not show the usual deficiencies at short range.

A method for reconstructing the Galactic magnetic field using dispersion of fast radio bursts and Faraday rotation of radio galaxies

ABSTRACT With the rapid increase of fast radio burst (FRB) detections within the past few years, there is now a catalogue being developed for all-sky extragalactic dispersion measure (DM) observations in addition to the existing collection of all-sky extragalactic Faraday rotation measurements (RMs) of radio galaxies. We present a method of reconstructing all-sky information of the Galactic magnetic field component parallel to the line of sight, B∥, using simulated observations of the RM and DM along lines of sight to radio galaxies and FRB populations, respectively. This technique is capable of distinguishing between different input Galactic magnetic fields and thermal electron density models. Significant extragalactic contributions to the DM are the predominant impediment in accurately reconstructing the Galactic DM and 〈B∥〉 skies. We look at ways to improve the reconstruction by applying a filtering algorithm on the simulated DM lines of sight and we derive generalized corrections for DM observations at |b| > 10° that help to disentangle Galactic and extragalactic DM contributions. Overall, we are able to reconstruct both large-scale Galactic structure and local features in the Milky Way’s magnetic field from the assumed models. We discuss the application of this technique to future FRB observations and address possible differences between our simulated model and observed data, namely: adjusting the priors of the inference model, an unevenly distributed population of FRBs on the sky, and localized extragalactic DM structures.

Multipolar Atom Types from Theory and Statistical Clustering (MATTS) Data Bank: Restructurization and Extension of UBDB.

A fast and accurate operational model of electron density is crucial in many scientific disciplines including crystallography, molecular biology, pharmaceutical, and structural chemistry. In quantum crystallography, the aspherical refinement of crystal structures is becoming increasingly popular because of its accurate description in terms of physically meaningful properties. The transferable aspherical atom model (TAAM) is quick and precise, though it requires a robust algorithm for atom typing and coverage of the most popular atom types present in small organic molecules. Thus, the University at Buffalo Databank (UBDB) has been renamed to the Multipolar Atom Types from Theory and Statistical clustering (MATTS) data bank, broadened, restructured, and implemented into the software DiSCaMB with 651 atom types obtained from 2316 small-molecule crystal structures containing C, H, N, O, P, S, F, Cl, and Br atoms. MATTS2021 data bank now covers most of the small molecules, peptides, RNA, DNA, and some frequently occurring cations and anions in biological, pharmaceutical, and organic materials, including the majority of known crystal structures composed of the above elements. The multipole model parameters (Pval, κ, κ′, Plm) obtained for different atom types were greatly influenced by neighboring atom types, hybridization, geometrical strain in the ring system, and charges on the molecule. Contrary to previous findings, the atoms showing variable oxidation states and ions deviate from the linear dependence of monopole-derived charges on the expansion–contraction κ parameter.

Improving estimates of the ionosphere during geomagnetic storm conditions through assimilation of thermospheric mass density

Dynamical changes in the ionosphere and thermosphere during geomagnetic storm times can have a significant impact on our communication and navigation applications, as well as satellite orbit determination and prediction activities. Because of the complex electrodynamics coupling processes during storms, which cannot be fully described with the sparse set of thermosphere–ionosphere (TI) observations, it is crucial to accurately model the state of the TI system. The approximation closest to the true state can be obtained by assimilating relevant measurements into physics-based models. Thermospheric mass density (TMD) derived from satellite measurements is ideal to improve the thermosphere through data assimilation. Given the coupled nature of the TI system, the changes in the thermosphere will also influence the ionosphere state. This study presents a quantification of the changes and improvement of the model state produced by assimilating TMD not only for the thermosphere density but also for the ionosphere electron density under storm conditions. TMD estimates derived from a single Swarm satellite and the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physics-based model are used for the data assimilation. The results are presented for a case study during the St. Patricks Day storm 2015. It is shown that the TMD data assimilation generates an improvement of the model’s thermosphere density of up to 40% (measured along the orbit of the non-assimilated Swarm satellites). The model’s electron density during the course of the storm has been improved by approximately 8 and 22% relative to Swarm-A and GRACE, respectively. The comparison of the model’s global electron density against a high-quality 3D electron density model, generated through assimilation of total electron content, shows that TMD assimilation modifies the model’s ionosphere state positively and negatively during storm time. The major improvement areas are the mid-low latitudes during the storm’s recovery phase.Graphical

Spatial Selectivity of Plasma Sheath Channel at Millimeter Wave Band for Hypersonic Vehicle

Millimeter wave is a potential way to overcome the blackout problem. However, the plasma sheath is axially nonuniform, and it has different effects on millimeter wave at different axial positions. In this article, the influences of the spatially inhomogeneous time-varying plasma sheath on millimeter waves are investigated. The electron density model is established, the time-domain sequence of the random channel is calculated, and the channel statistical parameters at different axial positions are extracted. The results show that the millimeter wave channel is spatially selective. Millimeter waves can transmit through the plasma sheath with less attenuation, multiplicative interference, and nonlinear effects at any position of the vehicle except the nose. When the antenna position is properly selected, the attenuation and multiplicative interference intensity can be further reduced. This indicates that millimeter wave communication technology is the most promising way to overcome the blackout problem and accomplish diverse communication tasks of a hypersonic vehicle.

Analysis of Electron Precipitation and Ionospheric Density Enhancements Due To Hiss Using Incoherent Scatter Radar and Arase Observations

AbstractPlasmaspheric hiss can cause energetic electron precipitation from the magnetosphere to the Earth's upper atmosphere and affect the ionospheric electron density profiles. In this study, we use Arase satellite measurements in the dayside plasmasphere to model the electron precipitation and the resultant ionospheric response, and compare the results to the electron density measured by the Poker Flat Incoherent Scatter Radar (PFISR). We analyzed two close conjunction events between Arase and PFISR at L ∼ 6 in the afternoon sector, when Arase was in the outer plasmasphere and traveled into the plasmaspheric plumes. Modest or strong hiss waves were observed with amplitudes higher than 50 pT during both events. Quasilinear modeling suggests that the hiss waves could cause intense electron precipitation ranging from several keV to several hundred keV energies. The electron density profiles at 60–90 km modeled by the Boulder Electron Radiation to Ionization (BERI) model suggest significant electron density enhancements due to the precipitating electrons. PFISR simultaneously observed electron density enhancements during both events, and provided evidence for the electron precipitation at altitudes down to <70 km. The temporal modulation of hiss caused the modulated density profiles in BERI modeling, but was not evident in PFISR observations. The modeled altitude profiles of the perturbed electron density overall agree with PFISR observation. At altitudes below 75 km, the modeled electron densities are lower than the observation, suggesting additional high energy electron precipitation possibly due to low frequency (<50 Hz) waves or hiss wave powers ducted to high latitudes.

Reconstruction of precipitating electrons and three-dimensional structure of a pulsating auroral patch from monochromatic auroral images obtained from multiple observation points

Abstract. In recent years, aurora observation networks using high-sensitivity cameras have been developed in the polar regions. These networks allow dimmer auroras, such as pulsating auroras (PsAs), to be observed with a high signal-to-noise ratio. We reconstructed the horizontal distribution of precipitating electrons using computed tomography with monochromatic PsA images obtained from three observation points. The three-dimensional distribution of the volume emission rate (VER) of the PsA was also reconstructed. The characteristic energy of the reconstructed precipitating electron flux ranged from 6 to 23 keV, and the peak altitude of the reconstructed VER ranged from 90 to 104 km. We evaluated the results using a model aurora and compared the model's electron density with the observed one. The electron density was reconstructed correctly to some extent, even after a decrease in PsA intensity. These results suggest that the horizontal distribution of precipitating electrons associated with PsAs can be effectively reconstructed from ground-based optical observations.

Radio Scattering Horizons for Galactic and Extragalactic Transients

Radio wave scattering can cause severe reductions in detection sensitivity for surveys of Galactic and extragalactic fast (∼ms duration) transients. While Galactic sources like pulsars undergo scattering in the Milky Way interstellar medium (ISM), extragalactic fast radio bursts (FRBs) can also experience scattering in their host galaxies and other galaxies intervening in their lines of sight. We assess Galactic and extragalactic scattering horizons for fast radio transients using a combination of NE2001 to model the dispersion measure and scattering time (τ) contributed by the Galactic disk, and independently constructed electron density models for the Galactic halo and other galaxies’ ISMs and halos that account for different galaxy morphologies, masses, densities, and strengths of turbulence. For source redshifts 0.5 ≤ z s ≤ 1, an all-sky, isotropic FRB population has simulated values of τ (1 GHz) ranging from ∼1 μs to ∼2 ms (90% confidence, observer frame) that are dominated by host galaxies, although τ can be ≫2 ms at low Galactic latitudes. A population at z s = 5 has 0.01 ≲ τ ≲ 300 ms at 1 GHz (90% confidence), dominated by intervening galaxies. About 20% of these high-redshift FRBs are predicted to have τ > 5 ms at 1 GHz (observer frame), and ≳40% of FRBs between z s ∼ 0.5–5 have τ ≳ 1 ms for ν ≤ 800 MHz. Our scattering predictions may be conservative if scattering from circumsource environments is significant, which is possible under specific conditions. The percentage of FRBs selected against from scattering could also be substantially larger than we predict if circumgalactic turbulence causes more small-scale (≪1 au) density fluctuations than observed from nearby halos.

Neural Decision Tree: A New Tool for Building Forecast Models for Plasmasphere Dynamics

AbstractThe Neural Decision Tree (NDT) is a hybrid supervised machine‐learning algorithm that combines the self‐limiting property of a decision tree (Classification and Regression Tree [CART]) algorithm with the artificial neural network. We demonstrate the use of NDT for a regression problem of building a prediction model for the plasmasphere electron density with solar and geomagnetic measurements as inputs. Our work replicates the work by Zhelavskaya et al. reported in their 2017 article (I. S. Zhelavskaya et al., 2017, https://doi.org/10.1002/2017JA024406) to show that NDT makes available sophisticated network layout for building a predictive model, thus taking advantage of deep‐learning potential of the neural network. We also demonstrate that with the ability to automatically select an appropriate network layout, as well as, effective initialization, the NDT algorithm allows research scientists in space weather to focus more of their attention on physically and statistically relevant aspects of using machine‐learning techniques. In fact, our example highlights the fact that the basic assumptions of standard supervise machine‐learning problems are often unsatisfied in real‐world space weather applications. Greater attention to these fundamental issues may create significantly different solutions to space weather forecast problems.

Pulsar Survey With the QiTai 110 m Radio Telescope

With a collecting area of 9400 m2, the Xinjiang QiTai 110 m radio Telescope (QTT) will allow for a significant advance in the search and observation of pulsars. We have updated the galactic electron density model, scattering model, spectral distribution, and radial distribution of PsrPopPy to generate the population of isolate radio pulsars in the Galaxy. The spiral arm, including the local spiral arm, is considered when generating pulsar locations. By simulation, we estimate the number of previously undetected radio pulsars that QTT will discover with its possible receivers for different strategies. Using the PAF receiver, 2200 previously unknown pulsars could be discovered in 43 days. The 96-beam PAF receiver can produce ∼10.56 GB of data per second.

Active Precipitation of Radiation Belt Electrons Using Rocket Exhaust Driven Amplification (REDA) of Man-Made Whistlers.

Ground‐based very low frequency (VLF) transmitters located around the world generate signals that leak through the bottom side of the ionosphere in the form of whistler mode waves. Wave and particle measurements on satellites have observed that these man‐made VLF waves can be strong enough to scatter trapped energetic electrons into low pitch angle orbits, causing loss by absorption in the lower atmosphere. This precipitation loss process is greatly enhanced by intentional amplification of the whistler waves using a newly discovered process called rocket exhaust driven amplification (REDA). Satellite measurements of REDA have shown between 30 and 50 dB intensification of VLF waves in space using a 60 s burn of the 150 g/s thruster on the Cygnus satellite that services the International Space Station. This controlled amplification process is adequate to deplete the energetic particle population on the affected field lines in a few minutes rather than the multi‐day period it would take naturally. Numerical simulations of the pitch angle diffusion for radiation belt particles use the UCLA quasi‐linear Fokker Planck model to assess the impact of REDA on radiation belt remediation of newly injected energetic electrons. The simulated precipitation fluxes of energetic electrons are applied to models of D‐region electron density and bremsstrahlung X‐rays for predictions of the modified environment that can be observed with satellite and ground‐based sensors.

A New Global Ionospheric Electron Density Model Based on Grid Modeling Method

AbstractBased on nearly 4.6 million radio occultation (RO) ionospheric profile data from Constellation Observing System for Meteorology, Ionosphere, and Climate satellites in 2006–2020, a global three‐dimensional ionospheric electron density model was constructed with a new concept. The global 3D ionosphere structure was divided into total 338,661 grids with longitude intervals of 10°, latitude intervals of 2°, and height intervals of 5 km. On each grid, the electron density is modeled as a function of solar activity, geomagnetic activity, local time, and season variation using 21 coefficients. Then all grid models are combined to form a global ionospheric model. This method makes full use of all ionospheric electron density data. The spatial resolution of the model is high with 10° in longitude, 2° in latitude, and 5 km in height, which can effectively model the fine ionospheric spatial structure like the longitudinal wavenumber‐4 structure in low latitudes. The model also takes into account the influence of both solar and geomagnetic activities on the ionosphere. At the altitude below the F2 peak, the RO electron density observation suffers from an artificial meridional maximum between the double peaks of the equatorial ionization anomaly, referred hereafter as the three‐peak error. By combining our model with the International Reference Ionospheric electron density results of the E layer below 140 km, the problem of three‐peak error is effectively solved. Compared the with other data sources such as the ZH01 and the ROCSAT‐1, the modeling ability of model in fine spatial structure is verified.

A 3D Empirical Model of Electron Density Based on CSES Radio Occultation Measurements

AbstractChina Seismo‐Electromagnetic Satellite (CSES) was successfully launched in February 2018. About 280 thousand ionospheric radio occultation (RO) electron density profiles (EDP) have been accumulated till the end of 2020. The CSES is a Sun‐synchronous orbit satellite with descending and ascending nodes around 14:00 and 02:00 LT, respectively, at the height of 507 km. Thus, most of the RO EDP concentrate on these two local time bins. First, we constructed empirical NmF2, hmF2, and Hm models at two local time windows 14:00 and 02:00 LT, respectively. The three models describe that NmF2, hmF2, and Hm vary with solar activity, season, longitude, and latitude. Through the comparison with CSES observations, the NmF2, hmF2, and Hm models could reproduce the physical characteristics rather well. Then, according to Chapman profile function, a EDP model was reconstructed based on the NmF2, hmF2, and Hm models, named CSES_Ne‐Profile Model. To evaluate the model performance, we simulated the COSMIC‐2 observations by CSES_Ne‐Profile Model and international reference ionosphere (IRI) model respectively. The results show that CSES_Ne‐Profile Model precedes the IRI model. Additionally, our model captures the merging phenomenon of the two peaks of equatorial ionospheric anomaly, which is missed by IRI. Further, CSES_NePrf model is a useful tool to provide the quiet background for case studies and joint studies with other payloads onboard CSES.