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    <title language="eng">Criteria for dynamical clustering in permanently excited granular gases: comparison and estimation with machine learning approaches</title>
    <abstract language="eng">When granular gases in microgravity are continuously excited mechanically, spatial inhomogeneities of the particle distribution can emerge. At a sufficiently large overall packing fraction, a significant share of particles tend to concentrate in strongly overpopulated regions, so-called clusters, far from the excitation sources. This dynamical clustering is caused by a complex balance between energy influx and dissipation. The mean number density of particles, the geometry of the container, and the excitation strength influence cluster formation. A quantification of clustering thresholds is not trivial. We generate ‘synthetic’ data sets by Discrete Element Method simulations of frictional spheres in a cuboid container and apply established criteria to classify the local packing fraction profiles. Machine learning approaches that predict dynamic clustering from known system parameters on the basis of classical test criteria areoposed and tested. It avoids the necessity of complex numerical simulations.</abstract>
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    <title language="eng">Granular gases of rough spheres: Velocity, rotation and collision statistics from in-situ measurements, optical data and simulations</title>
    <abstract language="eng">Granular gases are not only of interest in fundamental physics, but they can also serve as a test ensembles for the validity of collision models employed in (loose) granular matter. The theoretical literature mainly addresses spheres under ideal conditions and simulations allow full access to all particle parameters, but experiments cannot fulfill these idealizations. We investigate granular gases of soft, rough spheres by combining microgravity experiments and adjusted simulations. We introduce Smart Particles with embedded autarkic micro-sensors for in-situ measurements of rotation rates and accelerations. Additionally, we extract 3D positions, translations and orientations of the particles from stereoscopic video data using Machine-Learning based algorithms. We address the partition of kinetic energy between the degrees of freedom, the angular and translational velocity as well as collision statistics. A simulation is adjusted to experiment parameters, showing good agreement of translational motion, but qualitative differences in the decay of rotational kinetic energy.</abstract>
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    <title language="eng">Forces on a sphere suspended in flowing granulate</title>
    <abstract language="eng">We investigate the forces of flowing granular material on an obstacle. A sphere suspended in a discharging silo experiences both weight of the overlaying layers and drag of the surrounding moving grains. In experiments with frictional hard glass beads, the force on the obstacle was found to be practically flow-rate independent. In contrast, flow of nearly frictionless soft hydrogel spheres added drag forces which increased with the flow rate until reaching saturation at high flow speeds. The total force grew quadratically with the obstacle diameter in the soft, low friction material, while it grew much weaker, nearly linearly with the obstacle diameter, in the bed of hard, frictional glass spheres. In addition to the drag, obstacles embedded in the flowing hydrogel spheres experience a weight force from the top as if immersed in a hydrostatic pressure profile, but negligible counter-forces from below. In contrast, the frictional hard particles create a strong pressure gradient near the upper surface of the obstacle. Numerical simulations provide additional information that is difficult to access experimentally. They reproduce the experimental results and give hints for the origin of the different force contributions. The results have considerable practical importance for the discharge of storage containers with large objects suspended in flowing granular material.</abstract>
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    <title language="eng">Machine learning for prediction of dynamical clustering in granular gases</title>
    <abstract language="eng">Continuously excited dense granular gases in microgravity can develop spatial inhomogeneities of the particle distribution. Dynamical clustering is a phenomenon where a significant share of particles concentrate in strongly overpopulated regions. It is caused by a complex interplay between the energy influx and dissipation in collisions. The overall packing fraction, container geometry, and excitation parameters influence the gas-cluster transition. We perform Discrete Element Method (DEM) simulations for frictional spheres in a cuboid container and apply statistical criteria to the packing fraction profiles. Machine learning (ML) methods are used to study the dependence of the gas-cluster transition on system parameters. It is a promising alternative to predict the state of the system without the need for the time-consuming DEM simulations. We identify the best models for predicting the dynamical clustering of frictional spheres in a specific experimental geometry.</abstract>
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    <author>Sai Preetham Sata</author>
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    <title language="eng">Naked eye celestial objects and phenomena: how far can we see at night?</title>
    <abstract language="eng">How far can we see with the naked eye at night? Many celestial objects like stars and galaxies as well as transient phenomena such as comets and supernovae can be observed in the night sky. We discuss the furthest distances of such objects and phenomena observable with the naked eye during the night-time for Earth-bound observers. The physics of night-time visual ranges differs from that of daytime observations because human vision shifts from cones to rods. In addition, mostly point sources are observed due to the large distances involved. Whether celestial objects and phenomena can be detected depends on the contrast of their radiation and the background sky luminance. We present a concise overview of how far we can see at night by first discussing the effects of the Earth's atmosphere. This includes attenuation of transmitted radiation as well as its role as a source of background radiation. Disregarding the attenuation of light due to interstellar and intergalactic dust, simple maximum night-time visual range estimates are based on the inverse square law, which can be easily verified by laboratory and demonstration experiments. From the respective calculations, we find that individual stars within the Milky Way galaxy of up to 15 000 light years are observable. Even further away are observable galaxies with several billion stars. The Andromeda galaxy can be observed with the naked eye at a distance of around 2.5 million light years. Similarly, the observability of supernovae also allows a visual range beyond the Milky Way galaxy. Finally, gamma ray bursts as the most energetic events in the universe are discussed concerning naked eye observations.</abstract>
    <parentTitle language="eng">European Journal of Physics</parentTitle>
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    <title language="eng">How far can we see at day?</title>
    <abstract language="eng">We discuss the farthest objects on Earth observable for the unaided, healthy naked eye during the daytime, i.e., the maximum visual range for observers on Earth. Visual range depends first on the properties of the material between observer and object and its interaction processes with radiation, but second also on our visual perception system. After a rough comparison of ranges in water, glass, and the atmosphere, we focus on the physical basis of visual range for the latter. As a contrast phenomenon, visual range refers to allowed light paths within the atmosphere. It results from the interplay of geometry, refraction, and light scattering. We present a concise overview of this field by qualitative descriptions and quantitative estimates as well as classroom demonstration experiments. The starting point is the common geometrical visual ranges, followed by extensions due to refraction and limitations due to contrast, which depend on scattering and absorption processes within the atmosphere. The quantitative discussion of scattering is very helpful to easily understand the huge ranges in nature from meters in dense fog to hundreds of kilometers in clear atmospheres. Extreme visual ranges from about 300 km to above 500 km require optimal atmospheric conditions, cleverly chosen locations and times, and a sophisticated topography analysis. Even longer visual ranges are possible when looking through the vertical atmosphere. From the ISS, daytime ranges well above 1000 km are possible.</abstract>
    <parentTitle language="eng">European Journal of Physics</parentTitle>
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    <title language="eng">Data Reduction for Energy-Constrained Sensors via Event-Aware Sampling</title>
    <abstract language="eng">Environmental monitoring plays a crucial role in analyzing environmental parameters and detecting anomalies. However, sensor systems work continuously, which results in constant energy consumption and data redundancy, especially for sensors with limited computing power and memory. In addition, installing and maintaining sensors in remote places creates additional challenges. An adaptive environmental sensing approach is developed to reduce data redundancy and energy consumption. A custom-designed sensor based on PIC16LF19156 microcontroller measures CO2, humidity and temperature simultaneously. The sensor is connected to a Raspberry Pi, where a signal processing algorithm is executed, aimed at reducing data redundancy, thereby increasing the energy efficiency of the system. The algorithm includes the discrete wavelet transform (DWT) to extract spectral features from the signals. A machine learning model trained on previous data estimates the daily variability of the signal and saves data labeled as SAVE (deviations) or SKIP (consistency). As a result, only the relevant intervals showing significant fluctuations are retained. The effectiveness of the proposed approach was evaluated by reconstructing the compressed signals and comparing them with the original data based on RMSE and MAE metrics, which confirms the insignificant loss of information.</abstract>
    <parentTitle language="eng">Konferenz: 2025 IEEE SENSORS, Vancouver, BC, Canada, 2025</parentTitle>
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    <author>Nursultan Daupayev</author>
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    <author>Ricky Bendyk</author>
    <author>Christian Engel</author>
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    <title language="deu">Elektromagnetische Wellen – Grundlagen und ausgewählte Anwendungen</title>
    <abstract language="deu">Schwingungen und Wellen zeigen sich in vielen Alltagsphänomenen der Physik, d. h. in der Lebenswelt von Schülerinnen und Schülern. Dazu zählen in der Mechanik Beispiele wie Schaukeln, Seilwellen oder Wasserwellen am Strand, in der Akustik Schallwellen durch beliebige Geräusche oder stehende Wellen in Musikinstrumenten und im Elektromagnetismus die allgegenwärtigen elektromagnetischen Wellen. Letztere haben vielfältigste Anwendungen, z. B. Erhitzen mit Mikrowellengeräten, Kommunizieren mit Smartphones, Datenübertragung mit Lichtleitern oder Fotografieren mit Kameras, ganz zu schweigen von medizinischen Anwendungen der Endoskopie, des Röntgens oder laserbasierten chirurgischen Eingriffen. Viele dieser Anwendungen haben ein enormes Motivationspotenzial in der Lehre, weshalb das Thema fest in Lehrplänen der Sekundarstufen verankert ist. Im Folgenden werden zunächst allgemeine Grundlagen und Gemeinsamkeiten der Beschreibung beliebiger Wellen diskutiert, bevor das Hauptaugenmerk auf elektromagnetische Wellen und ausgewählte Anwendungen gelegt wird.</abstract>
    <parentTitle language="deu">Schwingungen und Wellen in Alltagskontexten</parentTitle>
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    <author>Michael Vollmer</author>
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    <title language="deu">Optik und ihre Phänomene</title>
    <abstract language="deu">Dieses Lehr-, Lern-, Fach- und Sachbuch präsentiert die Grundlagen der Optik in Theorie und ausführlich beschriebenem Experiment sowie vielfältige faszinierende optische Phänomene. Ob in Vorlesungen, Seminaren, für Projektarbeiten, Schulunterricht oder Selbststudium - dieses Buch ist eine wertvolle Ressource für alle, die sich für Optik interessieren. Durch die große Zahl zitierter Originalarbeiten schlägt es nicht nur die Brücke zur Lehre sondern auch zur Forschung.</abstract>
    <subTitle language="deu">Lichtspiele in der Natur: von Luftspiegelungen und Himmelsfarben bis in die Weiten des Alls</subTitle>
    <identifier type="isbn">978-3-662-69308-7</identifier>
    <identifier type="doi">10.1007/978-3-662-69309-4</identifier>
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    <author>Michael Vollmer</author>
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