Radial evolution of the April 2020 stealth coronal mass ejection between 0.8 and 1 AU - Comparison of Forbush decreases at Solar Orbiter and near the Earth

Aims. We present observations of the first coronal mass ejection (CME) observed at the Solar Orbiter spacecraft on April 19, 2020, and the associated Forbush decrease (FD) measured by its High Energy Telescope (HET). This CME is a multispacecraft event also seen near Earth the next day. Methods. We highlight the capabilities of HET for observing small short-term variations of the galactic cosmic ray count rate using its single detector counters. The analytical ForbMod model is applied to the FD measurements to reproduce the Forbush decrease at both locations. Input parameters for the model are derived from both in situ and remote-sensing observations of the CME. Results. The very slow (~350 km/s) stealth CME caused a FD with an amplitude of 3 % in the low-energy cosmic ray measurements at HET and 2 % in a comparable channel of the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) on the Lunar Reconnaissance Orbiter, as well as a 1 % decrease in neutron monitor measurements. Significant differences are observed in the expansion behavior of the CME at different locations, which may be related to influence of the following high speed solar wind stream. Under certain assumptions, ForbMod is able to reproduce the observed FDs in low-energy cosmic ray measurements from HET as well as CRaTER, but with the same input parameters, the results do not agree with the FD amplitudes at higher energies measured by neutron monitors on Earth. We study these discrepancies and provide possible explanations. Conclusions. This study highlights that the novel measurements of the Solar Orbiter can be coordinated with other spacecraft to improve our understanding of space weather in the inner heliosphere. Multi-spacecraft observations combined with data-based modeling are also essential to understand the propagation and evolution of CMEs as well as their space weather impacts

Using gradient boosting regression to improve ambient solar wind model predictions

Studying the ambient solar wind, a continuous pressure‐driven plasma flow emanating from our Sun, is an important component of space weather research. The ambient solar wind flows in interplanetary space determine how solar storms evolve through the heliosphere before reaching Earth, and especially during solar minimum are themselves a driver of activity in the Earth’s magnetic field. Accurately forecasting the ambient solar wind flow is therefore imperative to space weather awareness. Here we present a machine learning approach in which solutions from magnetic models of the solar corona are used to output the solar wind conditions near the Earth. The results are compared to observations and existing models in a comprehensive validation analysis, and the new model outperforms existing models in almost all measures. In addition, this approach offers a new perspective to discuss the role of different input data to ambient solar wind modeling, and what this tells us about the underlying physical processes. The final model discussed here represents an extremely fast, well‐validated and open‐source approach to the forecasting of ambient solar wind at Earth

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Aberrant GABA-A receptor expression in the dentate gyrus of the epileptic mutant mouse stargazer

Stargazer (stg) mutant mice fail to express stargazin [transmembrane AMPA receptor regulatory protein 2 (TARP2)] and consequently experience absence seizure-like thalamocortical spike-wave discharges that pervade the hippocampal formation via the dentate gyrus (DG). As in other seizure models, the dentate granule cells of stg develop elaborate reentrant axon collaterals and transiently overexpress brain-derived neurotrophic factor. We investigated whether GABAergic parameters were affected by the stg mutation in this brain region. GABAA receptor (GABAR) 4 and 3 subunits were consistently upregulated, GABAR expression appeared to be variably reduced, whereas GABAR 1, 2, and 2 subunits and the GABAR synaptic anchoring protein gephyrin were essentially unaffected. We established that the 42 subunit-containing, flunitrazepam-insensitive subtype of GABARs, not normally a significant GABAR in DG neurons, was strongly upregulated in stg DG, apparently arising at the expense of extrasynaptic 4-containing receptors. This change was associated with a reduction in neurosteroid-sensitive GABAR-mediated tonic current. This switch in GABAR subtypes was not reciprocated in the tottering mouse model of absence epilepsy implicating a unique, intrinsic adaptation of GABAergic networks in stg

SmartAQnet – neuer smarter Weg zur räumlichen Erfassung von Feinstaub.

Mit dem Forschungsprojekt SmartAQnet wird ein smarter Weg zur räumlichen Bestimmung von Feinstaub untersucht und am Modellstandort Augsburg erprobt. Forschungsansatz ist die Erfassung und Zusammenführung unterschiedlicher Qualitäten von Feinstaubmesswerten mit Fernerkundungsdaten. Feinstaubmesswerte können hierbei von Jedermann (z. B. mit ultra-low-cost Sensoren) bis hin zu offiziellen Messnetzen (mit hochpräziser Messtechnik) in die Datenarchitektur eingespeist werden. Eine neuartige Internet of Things Analyseplattform soll Daten zur Anwendung sowohl für Planer als auch für den Bürger bieten, welche der nachhaltigen Gesundheitsvorsorge dienen können (z. B. App für eine luftqualitätsbezogene Navigation)