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(Auf) Humboldts Spuren
(2021)
Vor seiner Besteigung des Antisana in Ecuador verbrachte Alexander von Humboldt mit seinem Expeditionsteam die Nacht vom 15. auf den 16. März 1802 in einer Hacienda am Fuße des Vulkangipfels, deren letztes bauliches Zeugnis eine steinerne Hütte darstellt. Bauforscherische Untersuchungen eines internationalen Forscherteams konnten die mehrschichtige Bau- und Reparaturgeschichte dieses Baudenkmals ermitteln und über eine Auswertung von Reiseberichten mehrerer Andenforscher die Nutzungsgeschichte des einzelnen Gebäudes und des gesamten Anwesens klären. Schließlich ergaben sich daraus neue Erkenntnisse zu Humboldts Aufenthalt am Antisana.
30 Jahre Universität Potsdam
(2021)
Das Referat für Presse- und Öffentlichkeitsarbeit hat anlässlich des 30-jährigen Universitätsjubiläums einen Bildband zusammengestellt. Auf 168 Seiten finden sich rund 400 Fotos aus der Geschichte der Potsdamer Alma Mater – von der Pressekonferenz, auf der Brandenburgs Wissenschaftsminister Dr. Hinrich Enderlein die Gründung der Universität bekannt gibt, bis zu den traurig-schönen menschenleeren Campusimpressionen Anfang 2021. Die Auswahl aus Zehntausenden Bildern, die im Laufe der Jahre entstanden sind, dokumentiert die rasante Entwicklung der drei Uni-Standorte Golm, Am Neuen Palais und Griebnitzsee, begleitet Studierende und Forschende verschiedener Generationen und zeigt Eindrücke von wichtigen großen und kleinen Veranstaltungen und Ereignissen sowie – vor allem – vom Alltag einer Universität.
Ground-penetrating radar (GPR) is a standard geophysical technique used to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practices today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We have developed and applied a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume, which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of our workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments.
Die Technologie des 3D-Drucks hat sich in den letzten Jahrzehnten rasant entwickelt. Im Industriebereich entstehen immer modernere und spezialisiertere Druckverfahren, im Hobby- und Privatanwenderbereich hingegen werden stetig kostengünstigere und einfacher zu bedienende Geräte zugänglich. Einzig im Bildungsbereich scheint das Themenfeld hingegen erst langsam eine Rolle zu spielen, obwohl sich zahlreiche Bezugspunkte für einen Einsatz in verschiedensten Fächern finden lassen. Insbesondere im Fach Wirtschaft-Arbeit-Technik sind die Schnittstellen zum Rahmenlehrplan Berlin/Brandenburg augenscheinlich, doch es liegen erst vereinzelt konkrete und systematische didaktische Konzepte und Vorschläge zur unterrichtspraktischen Einbettung vor. Die Verfasserin versucht daher in dieser Arbeit die Relevanz des Themas für die technische Bildung deutlich zu machen, eine kurze technische Einführung in das für einen schulischen Einsatz besonders geeignete FDM-Druckverfahren zu geben und daran anknüpfend konkrete Umsetzungsvorschläge aufzuzeigen: einerseits in Form eines allgemeinen Phasenmodells zur Planung von Technikunterricht sowie andererseits in Form eines exemplarischen Unterrichtskonzepts. Am Beispiel eines Schachsets wird verdeutlicht, wie Schülerinnen und Schüler zum Anfertigen der Konstruktionsunterlagen digitale CAD-Programme nutzen und anschließend mit Hilfe eines 3D-Druckers additiv fertigen können.
The prehistory of electrets is not known yet, but it is quite likely that the electrostatic charging behavior of amber (Greek: τò ηλεκτρoν, i.e., “electron”) already was familiar to people in ancient cultures (China, Egypt, Greece, etc.), before the Greek philosopher and scientist Thales of Miletus (6th century BCE)-or rather his disciples and followers-reported it in writing (cf. Figure 1). More than two millennia later, William Gilbert (1544–1603), the physician of Queen Elizabeth I, coined the term “electric” in his book De Magnete, Magneticisque Corporibus, et de Magno Magnete Tellure (1600) for dielectric materials that attract like amber and that included sulfur and glass [1]. The second half of the 18th century saw the invention of the electrophorus or electrophore [2], a capacitive electret device, in 1762 by Johan Carl Wilcke (1732–1796).
An easy-to-do synthesis for the hexanuclear niobium cluster compound [Nb6Cl12(CH3OH)(4)(OCH3)(2)] . DABCO . 1.66 CH2Cl2 has been developed. An one-pot reaction between the cluster precursor [Nb6Cl14(H2O)(4)] . 4H(2)O and methanol with the addition of DABCO leads to the crystallization of the title compound in high yield within a few minutes. The single-crystal X-ray structure of this cluster compound has been determined. Very strong, nearly symmetric intercluster hydrogen bonds Nb-6-MeO...H...OMe-Nb-6 are present between the cluster units. A bridging co-crystalline DABCO molecule is also involved in a three-dimensional hydrogen-bonding network.
In eye-movement control during reading, advanced process-oriented models have been developed to reproduce behavioral data. So far, model complexity and large numbers of model parameters prevented rigorous statistical inference and modeling of interindividual differences. Here we propose a Bayesian approach to both problems for one representative computational model of sentence reading (SWIFT; Engbert et al., Psychological Review, 112, 2005, pp. 777-813). We used experimental data from 36 subjects who read the text in a normal and one of four manipulated text layouts (e.g., mirrored and scrambled letters). The SWIFT model was fitted to subjects and experimental conditions individually to investigate between- subject variability. Based on posterior distributions of model parameters, fixation probabilities and durations are reliably recovered from simulated data and reproduced for withheld empirical data, at both the experimental condition and subject levels. A subsequent statistical analysis of model parameters across reading conditions generates model-driven explanations for observable effects between conditions.
Abstract
In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network‐based models capture the large‐scale dynamics of the plasmasphere, such as plume formation and erosion of the plasmasphere on the nightside. However, their performance depends strongly on the availability of training data. When the data coverage is limited or non‐existent, as occurs during geomagnetic storms, the performance of NNs significantly decreases, as networks inherently cannot learn from the limited number of examples. This limitation can be overcome by employing physics‐based modeling during strong geomagnetic storms. Physics‐based models show a stable performance during periods of disturbed geomagnetic activity if they are correctly initialized and configured. In this study, we illustrate how to combine the neural network‐ and physics‐based models of the plasmasphere in an optimal way by using data assimilation. The proposed approach utilizes advantages of both neural network‐ and physics‐based modeling and produces global plasma density reconstructions for both quiet and disturbed geomagnetic activity, including extreme geomagnetic storms. We validate the models quantitatively by comparing their output to the in‐situ density measurements from RBSP‐A for an 18‐month out‐of‐sample period from June 30, 2016 to January 01, 2018 and computing performance metrics. To validate the global density reconstructions qualitatively, we compare them to the IMAGE EUV images of the He+ particle distribution in the Earth's plasmasphere for a number of events in the past, including the Halloween storm in 2003.