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In aerospace engineering, data-driven surrogate models are increasingly employed to mitigate the computational and temporal costs of simulations, numerical analyses, and experiments. Two major challenges accompany this trend. First, the training of surrogate models often requires a sufficient amount of data, the determination of which is inherently difficult. Second, these models often exhibit high complexity, limiting both the traceability of their outputs and the extraction of useful insights. Explainable Artificial Intelligence (XAI) methods have therefore emerged as promising tools to enhance the interpretability, explainability, and transparency of such models. In this work, a combination of the established Shapley Additive Explanations (SHAP) approach with a bootstrap-based method is investigated. The proposed framework provides insights into the contribution of individual features and enables an assessment of data sufficiency with respect to surrogate model performance. Building upon these findings, the Bootstrap-Informed Feature Importance (BIFI) method is proposed. BIFI offers a model-agnostic, robust identification of relevant features.The method is analyzed in the context of Design of Experiments (DOE) processes used for surrogate model construction. Evaluation on four synthetic datasets of increasing complexity, as well as a dataset from aero-engine development, demonstrates that BIFI-based DOEs can improve surrogate model quality measured in terms of R and MSE by up to 90%. Consequently, the proposed method enables more efficient utilization of simulations, computations, and experiments while reducing the required number of samples.
Light is the primary cue driving zooplankton diel vertical migration (DVM), a strategy that balances predation risk with resource access. However, DVM is often oversimplified, with limited consideration of how light-driven risks and resource needs vary across taxa and life stages. This simplification is partly due to constraints on collecting high-resolution, size-resolved data —especially at night, when subtle shifts in illumination reshape nocturnal risk landscapes. To overcome these limitations, we deployed a high-resolution in situ modular Deep-focus Plankton Imager and an image-recognition approach to quantify fine scale DVM and body sizes of Cladocerans and Copepods in Lake Stechlin, Germany. Data was collected from day into night and across moonrise and was compared with environmental data from vertical profiling sondes. Typical DVM patterns emerged, with deeper daytime distributions, however, moonlight introduced additional behavioural complexity: larger individuals avoided illuminated layers, likely managing predation risk, while smaller individuals moved into these layers, possibly exploiting foraging opportunities and reduced risk. These light-mediated shifts were further shaped by ecological conditions; copepods tracked food-rich layers regardless of light levels at night, while cladocerans showed light-dependent responses to both temperature and food, such that light caused them to avoid otherwise favourable (warm, food-rich) layers. Our approach provides new insight into how zooplankton navigate nocturnal lightscapes, revealing size- and taxon-specific strategies. By establishing size-dependent responses to natural moonlight, this work provides a crucial baseline for predicting how artificial light at night may restructure zooplankton communities and destabilize freshwater food webs.
Dieses Lehrbuch führt am Beispiel der Technischen Mechanik in die Nutzung der Mathematiksoftware SMath Studio für die Durchführung und Dokumentation technischer Berechnungen ein. Das für Privatanwender kostenlose SMath ist, ähnlich wie Mathcad, eine leistungsfähige Alternative zu Papier, Bleistift und Taschenrechner oder auch zu den bekannten Tabellenkalkulationsprogrammen. Das Buch nimmt Einsteiger an die Hand, behandelt aber auch Erweiterungen wie numerische Methoden und Computeralgebra. Mit Beispielen aus Statik, Festigkeitslehre und Dynamik wird das typische Themenspektrum der Technischen Mechanik in technischen Studiengängen, insbesondere im Maschinenbau, abgedeckt.
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.
Following a brief description of the atmosphere and spectra of the Sun as dominant daytime light source, the most common optical phenomena within the troposphere are discussed, which are due to scattering of radiation with the constituents of the atmosphere. At first mirages, rainbows, coronas, iridescence, glories and halos are explained. Then light scattering phenomena which give rise to sunset colors, blue and colorful skies are presented as well as related phenomena like blue mountains, white clouds, green flashes and visual ranges. The review ends with a short survey of other less easily observable optical phenomena of the atmosphere and a very detailed bibliography.
Optik und ihre Phänomene
(2024)
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.
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.
How far can we see at day?
(2025)
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.
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.
Naked eye studies of the clear night sky reveal that a certain percentage of all observable stars can be perceived as having color. Subjective estimates differ widely, ranging from just a few to a maximum of above two hundred. Explanations are based on the emission spectra of the stars, which are modified by interstellar dust clouds, the Earth atmosphere, and mostly the inverse square law. Color changes occur not only for variation of the star’s angular elevation above the horizon, but as well for decreasing nighttime sky brightness due to the transition from photopic via mesopic to scotopic vision. The maximum number of stars showing color to the naked eye depends on star illuminances on Earth and the background sky luminance. The limit of observing color is found to correspond to apparent visual magnitudes around , defining the number of colored stars. This also means that naked eye perception of stars with color is only possible for a certain star distance range, which is well below the maximum naked eye visual range of stars.
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.
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.
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.
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.
Microgravity experiments with three-dimensional (3D) granular gases, i.e., ensembles of freemoving macroscopic particles which collide inelastically, produce large amounts of stereo video footage which require processing and analysis. The main steps of data treatment are particle detection, 3D matching and tracking in stereoscopic views, and quantification of ensemble statistical properties such as, e.g. mean kinetic energy or collision processes. Frequent overlapping or clustering of particles and their complicated movement patterns require smart software solutions. In recent years, Artificial Intelligence/Machine Learning (AI/ML) methods were successfully used for analysis of granular systems. We have applied such techniques to the granular gases of rod-like particles and developed a software tool which enables a full cycle of semi-automatic experimental data analysis. The approach is now tested on more complex, non-convex particles, shaped as 3D crosses (hexapods). Another challenge is optical analysis of dense granular gases, where individual particles cannot be tracked. We present a preliminary result of application of an ML method for number density profiles extraction in VIP-Gran experiment with dense ensemble of rod-like particles.
Microgravity (µg)-generated three-dimensional (3D) multicellular aggregates can serve as models of tissue and disease development. They are relevant in the fields of cancer and in vitro metastasis or regenerative medicine (tissue engineering). Driven by the 3R concept—replacement, reduction, and refinement of animal testing—µg-exposure of human cells represents a new alternative method that avoids animal experiments entirely. New Approach Methodologies (NAMs) are used in biomedical research, pharmacology, toxicology, cancer research, radiotherapy, and translational regenerative medicine. Various types of human cells grow as 3D spheroids or organoids when exposed to µg-conditions provided by µg simulating instruments on Earth. Examples for such µg-simulators are the Rotating Wall Vessel, the Random Positioning Machine, and the 2D or 3D clinostat. This review summarizes the most recent literature focusing on µg-engineered tissues. We are discussing all reports examining different tumor cell types from breast, lung, thyroid, prostate, and gastrointestinal cancers. Moreover, we are focusing on µg-generated spheroids and organoids derived from healthy cells like chondrocytes, stem cells, bone cells, endothelial cells, and cardiovascular cells. The obtained data from NAMs and µg-experiments clearly imply that they can support translational medicine on Earth.
Genetic risk factor identification for common epilepsies guided by integrative omics data analysis
(2025)
Objective
Genetic generalized epilepsies (GGEs) comprise the most common genetically determined epilepsy syndromes, following a complex mode of inheritance. Although many important common and rare genetic factors causing or contributing to these epilepsies have been identified in the past decades, many features of the genetic architecture are still insufficiently understood. This study integrates genome-wide association study (GWAS) data from the International League Against Epilepsy Consortium on Complex Epilepsies with transcriptome-wide association studies to identify genes whose genetically regulated expression levels are associated with epilepsy.
Methods
To achieve this, we used multiple computational approaches, including MAGMA, a tool for gene analysis of GWAS data, and its derivatives E-MAGMA and H-MAGMA, to improve gene mapping accuracy by utilizing tissue-specific expression and chromatin interaction data. Furthermore, we developed ME-MAGMA to incorporate methylation quantitative trait loci data, providing insights into epigenetic factors.
Results
We identified a total of 897 false discovery rate-corrected (<.05) candidates. These include voltage-gated calcium channels, voltage-gated potassium channels, and other genes such as NPRL2, CACNB2, and KCNT1 associated with epilepsy pathogenesis that act as key players in neuronal communication and signaling in the brain.
Significance
In this study, we propose new candidate genes to expand the dataset of potential epilepsy-causing genes. Further research on these genes may enhance our understanding of the complex regulatory mechanisms underlying GGE and other types of epilepsy, potentially revealing targets for therapeutic intervention.
Anecdotal reports in angling media suggest that using fluorescent lures may increase catch rates in dim light or at high turbidity. We conducted a controlled angling experiment, comprising 501 30-min experimental fishing trials in three meso- to eutrophic waterbodies and assessed catch rates and sizes of European perch (Perca fluviatilis) caught when offered two soft plastic lures (fluorescent vs. non-fluorescent) with similar reflective spectra. We also examined fluorescent properties of a range of market-available lures and modelled the experimental lure’s fluorescing effects under natural lake light. Considering the specific light environment of the study waters, the experimental fluorescent lure could get excited by downwelling visible daylight and fluoresce at depths of up to 3 meters. Based on a sample catch of 331 perch, and after controlling for interactions with illuminance, cloud cover, water depth and daytime, the fluorescence of the experimental lure did, however, neither affect the catch rate nor the size of perch caught. Lure fluorescence maybe less important than many anglers believe, but further studies in different lake conditions are needed.
Artificial light at night (ALAN) disrupts ecosystems by altering natural light cycles and affecting the physiology and behaviour of species, and represents a widespread and increasingly recognised global ecological threat. This meta‐analysis investigates the effects of varying wavelengths and illuminance levels of ALAN on organisms. Broad‐spectrum ‘cool’ light, enriched with blue and ultraviolet radiation, strongly disrupts circadian rhythms, melatonin production and nocturnal activity. However, contrary to common assumptions, broad‐spectrum ‘warm’ light can be nearly as impactful as broad‐spectrum ‘cool’ light lacking ultraviolet radiation, despite the predominant influence of short wavelengths on physiological processes. The impact of ALAN is not consistently dose‐dependent, as even low light levels (< 5 lx) can cause substantial biological disruptions. Thus, effective mitigation strategies require tailored solutions to specific ecological contexts and should generally avoid nocturnal illumination unless clearly needed, as there is no single ‘safe dose’ and ‘safe spectrum’ of ALAN.
The design of fan-blisks is a multi-criterion optimisation challenge primarily involving the aerodynamic shape optimisation of blade profiles and subsequent blade balancing, i.e., shifting profiles in axial and circumferential directions to avoid stress hotspots. Although it is already known that blade balancing affects aerodynamic properties, this correlation is often not taken into account, which is why it is usually performed as an independent step after solving the aerodynamic design problem. However, this assumption is questionable because such shifts should be used to control both secondary flow effects and resulting stress. Therefore, the paper proposes problem formulations combining both aspects.
Since optimisation requires costly numerical evaluations, machine learning methods are investigated to predict aerodynamic performance and stress constraints more efficiently. This enables a global optimisation process by reducing computational costs. Various different surrogate types are investigated, where stress constraints are formulated either as regression task predicting stress maxima, or as classification problem directly assessing design feasibility.
In turbomachinery blade design, rapid and accurate performance prediction is essential to accelerate optimization and reduce reliance on costly high-fidelity simulations. Traditional data-driven approaches often use dense surface point-cloud representations as input features, requiring extensive training datasets and computational resources. This work presents a more efficient methodology leveraging a compact B-Spline-based surface representation, where control points serve as input features, significantly reducing geometric dimensionality and computational overhead.
A systematic Design of Experiments (DoE) is performed to generate a diverse set of blade geometries for NASA Rotor 67. Each design is evaluated via computational fluid dynamics (CFD) simulations in ANSYS CFX, providing key aerodynamic performance metrics such as isentropic efficiency. We train and compare Graph Convolutional Neural Networks (GCNN) and Random Forest Regression (RFR) models to predict blade performance directly from the reduced control-point parameterization. Incorporating first- and second-order geometric derivatives (gradients and Laplacians) into the feature set significantly enhances predictive accuracy and stability, capturing essential curvature-related flow physics.
Results demonstrate that this B-Spline-based, CAD-centric methodology can achieve competitive accuracy in predictions with as few as 150–200 training simulations—comparable to other GCNN-based approaches. Consequently, the proposed framework reduces training overhead from days to minutes, enabling faster, more cost-effective turbomachinery design workflows and guiding optimization toward high-performing blade geometries.
Numerical Study of Ice Accretion on Fan Blades: Implications for the Design of Blade Geometries
(2025)
Ice formation on aircraft components due to the impact of supercooled droplets poses a severe safety risk. In particular, the formation of ice on the fan blades can lead to vibrations that affect the entire engine. While numerous studies have examined the effects of environmental conditions on ice accumulation, the influence of blade geometry has received little attention. This study investigates how variations in blade geometry affect ice accretion in a low-pressure compressor using a numerical approach. A Design of Experiments (DoE) is conducted on the NASA Rotor67, focusing on the sensitivity of ice formation to geometric modifications. The workflow includes geometry generation (ParaBlade), flow simulation (ANSYS CFX), and ice accretion modeling (ANSYS FENSAP-ICE) under rime ice conditions. The results reveal a strong correlation between the inlet metal angle and both accreted ice mass and maximum ice thickness. Furthermore, designs with good aerodynamic performance tend to exhibit higher ice accumulation. These findings enhance the understanding of icing behavior in low-pressure compressors and offer valuable insights for optimizing blade design in adverse environmental conditions.
Environmental monitoring systems often operate continuously, measuring various parameters, including carbon dioxide levels (CO2), relative humidity (RH), temperature (T), and other factors that affect environmental conditions. Such systems are often referred to as smart systems because they can autonomously monitor and respond to environmental conditions and can be integrated both indoors and outdoors to detect, for example, structural anomalies. However, these systems typically have high energy consumption, data overload, and large equipment sizes, which makes them difficult to install in constrained spaces. Therefore, three challenges remain unresolved: efficient energy use, accurate data measurement, and compact installation. To address these limitations, this study proposes a two-to-one threshold sampling approach, where the CO2 measurement is activated when the specified T and RH change thresholds are exceeded. This event-driven method avoids redundant data collection, minimizes power consumption, and is suitable for resource-constrained embedded systems. The proposed approach was implemented on a low-power, small-form and self-made multivariate sensor based on the PIC16LF19156 microcontroller. In contrast, a commercial monitoring system and sensor modules based on the Arduino Uno were used for comparison. As a result, by activating only key points in the T and RH signals, the number of CO2 measurements was significantly reduced without loss of essential signal characteristics. Signal reconstruction from the reduced points demonstrated high accuracy, with a mean absolute error (MAE) of 0.0089 and root mean squared error (RMSE) of 0.0117. Despite reducing the number of CO2 measurements by approximately 41.9%, the essential characteristics of the signal were saved, highlighting the efficiency of the proposed approach. Despite its effectiveness in controlled conditions (in buildings, indoors), environmental factors such as the presence of people, ventilation systems, and room layout can significantly alter the dynamics of CO2 concentrations, which may limit the implementation of this approach. Future studies will focus on the study of adaptive threshold mechanisms and context-dependent models that can adjust to changing conditions. This approach will expand the scope of application of the proposed two-to-one sampling technique in various practical situations.
Light pollution is an emerging ecological threat. To mitigate its negative consequences, creative inter- and transdisciplinary solutions and societal interactions are needed. To this end, we introduce nocturnal umbrella species representative of light-sensitive biodiversity whose protection will safeguard vital ecosystem services and a wide range of co-occurring species.
Light pollution poses significant ecological challenges for nocturnal animals reliant on natural light for migration, orientation, and circadian rhythms. The physiological effects of abrupt exposure to artificial light at night (ALAN) on migratory fish, such as the light experienced passing near illuminated infrastructures, remain poorly understood. This study investigates the physiological responses of brown trout (Salmo trutta) smolts to low-intensity (0.02 lx) and short-term (30 s) ALAN, simulating nocturnal migration light conditions near illuminated bridges. To evaluate the influence of social dynamics, trout were tested individually (solitary) or in groups of six. Using continuous cardiac monitoring with data storage tags, alongside analyses of oxidative stress markers and adenylate kinase (AK) activity in the heart, we identified distinct patterns of physiological responses. Solitary fish exhibited significant heart rate variability (HRV) increases following repeated ALAN exposure, suggesting impaired physiological regulation under repeated ALAN exposure. In contrast, trout in groups displayed consistently lower HRV over the entire 90-min experiment, implying that social dynamics likely influenced a sustained oxidative stress response, corroborated by increased AK activity. Oxidative stress markers further reflected social effects, with significant upregulation of key antioxidant enzymes (sod1, sod2, gpx1, gpx4) and elevated lipid peroxidation, identifying lipids as primary oxidative targets. The observed divergence between superoxide dismutase (SOD) activity and sod gene expression suggests adaptive post-transcriptional regulation to maintain redox balance under combined environmental and social stress. These findings reveal that social dynamics under ALAN can amplify physiological stress, potentially affecting migratory outcomes.
Ensuring the reliability, safety, and efficiency of railway systems is increasingly critical in global transportation networks. This paper addresses the necessity for advanced monitoring systems by introducing a multivariate energy-efficient wireless sensor node designed for proactive maintenance in rail applications.
Cortical actomyosin flows, among other mechanisms, scale up spontaneous symmetry breaking and thus play pivotal roles in cell differentiation, division, and motility. According to many model systems, myosin motor-induced local contractions of initially isotropic actomyosin cortices are nucleation points for generating cortical flows. However, the positive feedback mechanisms by which spontaneous contractions can be amplified towards large-scale directed flows remain mostly speculative. To investigate such a process on spherical surfaces, we reconstituted and confined initially isotropic minimal actomyosin cortices to the interfaces of emulsion droplets. The presence of ATP leads to myosin-induced local contractions that self-organize and amplify into directed large-scale actomyosin flows. By combining our experiments with theory, we found that the feedback mechanism leading to a coordinated directional motion of actomyosin clusters can be described as asymmetric cluster vibrations, caused by intrinsic non-isotropic ATP consumption with spatial confinement. We identified fingerprints of vibrational states as the basis of directed motions by tracking individual actomyosin clusters. These vibrations may represent a generic key driver of directed actomyosin flows under spatial confinement in vitro and in living systems.
Climate change, but also geopolitical circumstances, are moving topics such as energy efficiency and renewable energies more and more into the focus of the population, economy , and politics. As a result, the will to optimize new and existing energy systems extends from private individuals to companies and even entire communities. This work describes the development and usage of a new software called FINEconcepts which creates a digital twin of an energy system. This virtual model can then be used to optimize the energy system based on annual costs, CO2 emissions or other relevant criteria such as self-sufficiency. Because all system components, which include renewable technologies as well, can be added as a building block with chosen but changeable parameters, the software allows the user to explore and awaken interest and understanding of technologies that were previously considered too costly, irrelevant, or unrealistic. Implemented projects in small and large companies as well as in residential areas did prove, that the usage of FINEconcepts leads not only to more efficient energy systems by increasing the use of renewable energy, but also increased knowledge and understanding in terms of energy. Besides economics, ecology and security, understanding is an equally important factor in achieving a sustainable energy supply.
Employee Engagement and Soft Skills in the Digitalization of the Economy. Preliminary Study Results
(2023)
The fast-paced digitalization and automation make hard skills acquired by employees in their academic study programs outdated and irrelevant very fast. Hence, researchers and practitioners have recently demonstrated a growing interest in studying soft skills in various settings, including leadership, education, and training. Additionally, in times of digital transformation, businesses are promoting employee engagement evermore, particularly in the present context of crises and instability. The research intends to investigate this issue from the viewpoint of employee soft skills. We specifically look into the link between employees’ soft skills and workplace engagement. While doing our research in two different countries, we distinguish between commercial and non-commercial organizations as well as add an international perspective. Based on an acknowledged European skills framework, we focus our study on such soft skills as teamwork, communication, and conflict management and use recognized surveys to quantify them. We use a well-known Gallup methodology to evaluate employee engagement. Using correlation analysis, we investigate the impact of the three selected skills on employee engagement while considering the organization type and country, factors that may play an important role in the digital transformation of businesses and companies.
We present a very simple model for estimating time dependent atmospheric CO2 concentrations c(t) from global carbon emission scenarios, serving as single input data. We derive a single linear differential equation of 1st order, based on parameters which are estimated from quantitative data of the global carbon project and Mauna Loa data for CO2 concentrations. The model is tested first by comparing it to the 1960–2021 period with reasonably good quantitative agreement and, second to two of the typical current IPCC scenarios with good qualitative agreement. Finally, some new emission scenarios are modelled. Despite several drawbacks concerning absolute quantitative predictions, there are two important advantages of the model. First, it can be easily executed by students already with simple programmable spreadsheet programs such as Excel. Second input emission scenarios can be changed easily and expected changes are immediately seen for discussion during undergraduate and graduate courses on the carbon cycle and climate change.
Es wird das vielleicht einfachst mögliche Modell vorgestellt, mit dem zeitabhängige CO2 Konzent-rationen c(t) in der Atmosphäre ausgehend von verschiedenen globalen Emissionsszenarien für CO2berechnet werden. Dazu wird eine einzelne inhomogene lineare Differenzialgleichung 1. Ordnung hergeleitet, deren Parameter sich aus den quantitativen Daten des global carbon project sowie Mauna Loa Daten für CO2 Konzentrationen errechnen. Das Modell wird erstens getestet am Zeitraum 1960 bis 2020 mit vergleichsweise guter quantitativer Übereinstimmung zu Messdaten. Zweitens wird für zwei typische IPCC Emissions-Szenarien ein Vergleich der Modellvorhersagen mit denen der kom-plexen IPCC Earth-System-Klimamodelle diskutiert mit qualitativer Übereinstimmung des zeitli-chen Verlaufs. Drittens werden Ergebnisse einiger ausgewählter neuer Emissionsszenarien präsen-tiert. Ungeachtet einiger Abweichungen zu komplexeren Klimamodellen zeichnet sich unser Mo-dell durch zwei wichtige Vorteile für die Lehre aus. Zum einen ist es sehr einfach für Studierende und begabte Schüler nutzbar, da die erforderliche Lösung der Differentialgleichung bereits mit han-delsüblicher Tabellenkalkulationssoftware wie z.B. Excel programmiert werden kann. Dadurch ge-stattet es zum anderen auch sehr einfach, den zeitlichen Verlauf von Emissionsszenarien zu verän-dern und innerhalb weniger Sekunden Veränderungen aufgrund geänderter Eingaben zu berechnen. Insofern eignet sich das Modell sehr gut als Einstieg in das Thema Klimamodellierung in einführen-den Hochschulvorlesungen zum Themenbereich Kohlenstoffkreislauf und Klimawandel. In der Schule kann es gegen Ende der Sekundarstufe 2 beispielsweise im Projektunterricht zum Themen-komplex Nachhaltigkeit in Physik und/oder Mathematik eingesetzt werden
Electromagnetic (EM) waves, spanning about 15 orders of magnitude of wavelength (or frequency or energy) from radio waves via microwaves, infrared radiation, visible light, ultraviolet radiation, and X-rays to the highly energetic γ-rays, are utilized in food processing. In order to explain all uses of these waves in the food industry, the chapter begins with a general discussion of properties of waves and their description with wavelength frequency, speed of propagation, and also energy transport. Using visible light as starting point, electromagnetic waves in other wavelength regimes are discussed. The interaction of EM radiation with matter reveals that the wave description alone is insufficient to explain all observed phenomena. Understanding the attenuation of EM radiation in matter requires knowledge of the particle properties of electromagnetic waves, most easily summarized by the concept of photons which carry energy as well as momentum. This wave–particle duality does apply not only to EM waves, i.e. photons, but also to the particles which build up matter, in particular electrons, which also need to be described as waves. This leads to respective quantum mechanical explanations of the microscopic structure of matter in the form of atoms, molecules, and nuclei. Knowledge of their structure is a prerequisite to understand, first, the generation of EM radiation and, second, also its interaction with matter. As a result, it will become obvious that there are mostly three different usages of EM radiation in the food industry: preserving, characterizing, and heating.
The quantitative explanation of thermal radiation in 1900 by Max Planck started a development, which today has resulted in modern infrared technologies with thermal imaging cameras. The present work briefly describes the fundamentals of infrared imaging, based on the fact, that every object at a temperature T > 0 K emits thermal radiation. Its amount is only governed by temperature and the material quantity emissivity. Factors that define types and properties of commercial IR cameras, such as temperature range in nature and industry, the atmospheric windows for IR radiation as well as available optics and detectors are discussed. A short summary of typical specifications of IR cameras and interpretation of recorded images is given.
The vast majority of all human sensory inputs occur through our eyes. Light from direct sources or scattered light from objects enters our eyes and is focused onto the retina. The resulting signals are interpreted by the brain, which leads to the perception of the image of the observed objects.
Although quite efficient for our daily life, many technological applications require sensor properties beyond the characteristics of our eyes. A major limitation regarding microscopic objects is spatial resolution, which is overcome by microscopes. Time resolution can be dealt with using either time-lapse or high-speed cameras. Finally, eyes only detect visible radiation within the wavelength range from about 380 nm to 780 nm.
Changing the detected spectral range of electromagnetic radiation can dramatically enhance our vision. Shorter wavelengths such as x-rays are valuable tools for medical imaging, while ultraviolet (UV) imaging is used for forensics. Longer-wavelength thermal radiation used for imaging is often defined within spectral ranges, characterized by the photoelectric detector materials used and the respective atmospheric windows.
Coarsening of quasi two-dimensional emulsions formed by islands in free-standing smectic films
(2024)
We study the coarsening behavior of assemblies of islands on smectic A freely suspended films in ISS microgravity experiments. The islands can be regarded as liquid inclusions in a two-dimensional fluid in analogy to liquid droplets of the discontinuous phase of an emulsion. The coarsening is effectuated by two processes, predominantly by island coalescence, but to some extend also by Ostwald ripening, whereby large islands grow at the expense of surrounding smaller ones. A peculiarity of this system is that the continuous and the discontinuous phases consist of the same material. We determine the dynamics, analyze the self-similar aging of the island size distribution and discuss characteristic exponents of the mean island growth.
Granular gases are fascinating non-equilibrium systems with interesting features such as spontaneous clustering and non-Gaussian velocity distributions. Mixtures of different components represent a much more natural composition than monodisperse ensembles but attracted comparably little attention so far. We present the observation and characterization of a mixture of rod-like particles with different sizes and masses in a drop tower experiment. Kinetic energy decay rates during granular cooling and collision rates were determined and Haff’s law for homogeneous granular cooling was confirmed. Thereby, energy equipartition between the mixture components and between individual degrees of freedom is violated. Heavier particles keep a slightly higher average kinetic energy than lighter ones. Experimental results are supported by numerical simulations.
Saudi Aramco’s influence upon the Kingdom of Saudi Arabia cannot be overstated. After the discovery of oil in 1938, a nationwide metamorphosis began to infiltrate desert communities, sleepy fishing villages, and traditional urban centres ultimately influencing the people and their environments in unimaginable ways. Becoming one of the world’s largest oil producers has meant the loss and/or transformation of traditional ways of life. Shepherds, pearl divers, fishermen, and farmers are today’s business owners, executives, and international leaders. How could the development of a single company influence a country and its populace so dramatically? Besides the financial gains, how were individuals, families, and ecosystems affected? What were some of the personal challenges experienced by Saudi citizens? In this paper, the authors address these questions and others using local Saudi knowledge. In total, 20 female university students who participated in an oral history project interviewed their family members to learn how Saudi Aramco affected them personally, their traditions, landscapes, and society more generally. Excerpts from the interviews are highlighted to expose the nuances experienced by the various research participants.
This is the Mission Description Document (MDD) for a future Earth observation satellite mission addressing visible band observations of nighttime lights. The mission driving science applications are for the remote sensing of electricity, energy, and ecological impacts via the observation of artificial light. The MDD covers the mission requirements justification from the high-level scientific objectives and societal benefits to measurement requirements at product level 1b, i.e. radiances at the top of the atmosphere. In providing justification for the individual requirements and their traceability to scientific objectives and societal challenges, we address Scientific Readiness Levels 1 to 3. The MDD is the outcome of the European Space Agency New Earth Observation Mission Ideas project "Night Watch". The Task Reports (TR) from the project are appended to the MDD, and are authored by the same group as the MDD itself.
The proportion of female ophthalmologists in Germany has risen to approximately 50% in recent years, and approximately 66% of medical students are women. This represents a reversal of the past situation with a male predominance. Despite this change, many international studies show that women are still underrepresented at scientific conferences, particularly among invited speakers, chairpersons, and program committees. This study aims to investigate whether these differences in gender representation are also reflected at German ophthalmological congresses and whether the situation has changed in recent years. MethodsData collection covered the years 2013, 2022, and 2023 and included the congresses of the five large German ophthalmological associations: the German Ophthalmological Society (DOG), German Ophthalmic Surgical Society (DOC), German Ophthalmological Academy (AAD), German Society of Cataract and Refractive Surgery (DGII) and the German Retinological Society (RG). Data were collected based on online programs and information provided by the offices and the managing committees. The numbers of female and male speakers and chairpersons were identified, as were the gender distributions of the specific program committees. Overall, the percentage of female speakers across all years and conferences surveyed averaged 25%, while female chairs averaged 17%. The percentage of females in the program committees ranged from 0% to 17%. There was an increase in the percentage of female speakers over 10 years (2013-2023). For the DOG (ptrend < 0.01) and the DOC (ptrend = 0.01) there was a significant rise, while it was highest at the DOG (37%) and lowest at the DGII (11%). The percentage of female chairs was in general lower than the percentage of female speakers for all conferences (between 11% and 26% in 2023). Only for the DOG was there a statistically significant increase over the 10 years (ptrend < 0.01). The representation of women as speakers and chairpersons at German ophthalmology conferences is low; these continue to be predominantly male dominated. Although there has been an increase in female representation over time, it remains lower than the overall proportion of women in the profession in 2023. Significant differences are observed between the various ophthalmological conferences. Further investigation into the underrepresentation of women at these conferences is necessary, and measures to encourage greater female participation at congresses should be implemented.
One of the most dramatic changes occurring on our planet is the ever- increasing extensive use of artificial light at night, which drastically altered the environment to which nocturnal animals are adapted. Such light pollution has been identified as a driver in the dramatic insect decline of the past years. One nocturnal species group experiencing marked declines are moths, which play a key role in food webs and ecosystem services such as plant pollination. Moths can be easily monitored within the illuminated area of a streetlight, where they typically exhibit disoriented behavior. Yet, little is known about their behavior beyond the illuminated area. Harmonic radar tracking enabled us to close this knowledge gap. We found a significant change in flight behavior beyond the illuminated area of a streetlight. A detailed analysis of the recorded trajectories revealed a barrier effect of streetlights on lappet moths whenever the moon was not available as a natural celestial cue. Furthermore, streetlights increased the tortuosity of flights for both hawk moths and lappet moths. Surprisingly, we had to reject our fundamental hypothesis that most individuals would fly toward a streetlight. Instead, this was true for only 4% of the tested individuals, indicating that the impact of light pollution might be more severe than assumed to date. Our results provide experimental evidence for the fragmentation of landscapes by streetlights and demonstrate that light pollution affects movement patterns of moths beyond what was previously assumed, potentially affecting their reproductive success and hampering a vital ecosystem service.
This work presents an advanced sensor system design developed to improve diagnostic methods for sustainable building renovation, with focus on the optimization of energy efficiency and the achievement of significant CO2 reduction in the construction sector. Introduction Considering the challenges posed by climate change, it is imperative to adopt innovative strategies in all sectors, with particular focus on construction and real estate, which are well-known contributors to energy consumption and CO2 emissions. Sustainable renovation represents a pivotal approach for enhancing energy efficiency , reducing energy demand and improving environmental footprints through precise resource management and energy-efficient construction practices [1].
In-flight icing, the formation of ice during flight, poses risks to the safety and reliability of aircraft. Due to environmental conditions, ice accumulation occurs on the low-pressure compressor blades of an engine, diminishing aerodynamic performance and potentially causing damage to the engine. Numerical simulations of ice accretion are conducted on the blades of the NASA Rotor 67 utilizing the Computational Fluid Dynamics (CFD) software ANSYS CFX and the in-flight icing software FENSAP-ICE. One-dimensional and two-dimensional sensitivity studies aim to analyze the influences of temperature, droplet diameter and liquid water content (LWC) on the resulting ice build-up on the blade. The analyses reveal that ice accumulates predominantly at the leading edge of the blade, where collection efficiency is maximal. Additionally, an ice layer forms at the blade root on the pressure side. While LWC and temperature exerts a significant influence on the ice mass, only a marginal impact on droplet diameter is observed.
In recent decades, inland water remote sensing has seen growing interest and very strong development. This includes improved spatial resolution, increased revisiting times, advanced multispectral sensors and recently even hyperspectral sensors. However, inland waters are more challenging than oceanic waters due to their higher complexity of optically active constituents and stronger adjacency effects due to their small size and nearby vegetation and built structures. Thus, bio-optical modeling of inland waters requires higher ground-truthing efforts. Large-scale ground-based sensor networks that are robust, self-sufficient, non-maintenance-intensive and low-cost could assist this otherwise labor-intensive task. Furthermore, most existing sensor systems are rather expensive, precluding their employability. Recently, low-cost mini-spectrometers have become widely available, which could potentially solve this issue. In this study, we analyze the characteristics of such a mini-spectrometer, the Hamamatsu C12880MA, and test it regarding its application in measuring water-leaving radiance near the surface. Overall, the measurements performed in the laboratory and in the field show that the system is very suitable for the targeted application.
Unleashing the power of remote sensing data in aquatic research: Guidelines for optimal utilization
(2024)
The growing utilization of remote sensing data in lake studies provides crucial spatial insights into biogeochemistry and biology. However, clarity regarding the development and intended use of remote sensing products is often lacking. This letter aims to elucidate the tradeoffs for the utilization of remote sensing data in limnological studies with an example of based on the estimation of chlorophyll a due to its importance as a water quality indicator. The analysis initiates with a meticulous product selection, requiring an evaluation of its capacity to address the optical complexity of freshwater systems. Assessing atmospheric correction and product limitations ensures alignment with the study's objectives. Subsequently, rigorous validation of remote sensing products is essential, accompanied by a cautious interpretation of the data. This letter advocates for the use of remote sensing data, offering key strategies for their optimal utilization in lake studies.
SMath Studio is mathematical notebook software similar to Mathcad. Its outstanding and intuitive support for scientific units makes it an invaluable asset in higher engineering education. SMath Studio has been used for more than ten years in various courses at Brandenburg University of Applied Sciences, Germany (Technische Hochschule Brandenburg, THB). To enhance the usability of the software, substantial contributions have been made. One of them is the Maxima plugin for access to the free and open-source computer algebra system Maxima. This plugin combines the flexible notebook format of SMath Studio with powerful symbolic functions like integrals and solvers for algebraic and differential equations. Additionally, the plugin adds interactive 3D graphics to SMath. The paper discusses the basic design, features, and limitations, and showcases some applications.
The attraction of insects to artificial light is a global environmental problem with far-reaching implications for ecosystems. Since light pollution is rarely integrated into conservation approaches, effective mitigation strategies towards environmentally friendly lighting that drastically reduce insect attraction are urgently needed. Here, we tested novel luminaires in two experiments (i) at a controlled experimental field site and (ii) on streets within three municipalities. The luminaires are individually tailored to only emit light onto the target area and to reduce spill light. In addition, a customized shielding renders the light source nearly invisible beyond the lit area. We show that these novel luminaires significantly reduce the attraction effect on flying insects compared to different conventional luminaires with the same illuminance on the ground. This underlines the huge potential of spatially optimized lighting to help to bend the curve of global insect decline without compromising human safety aspects. A customized light distribution should therefore be part of sustainable future lighting concepts, most relevant in the vicinity of protected areas.
Live music is often linked to elaborate light shows, particularly at large outdoor music festivals. However, artificial light at night is one form of environmental pollution, light pollution, and because outdoor festivals emit a substantial amount of artificial light into the environment, they are a potential source of light pollution. So far, no studies that quantified the impact of such festivals on urban light pollution and skyglow exist. Here, the light pollution produced by a major rock festival (Lollapalooza Berlin 2016 with 70,000 visitors per day in an urban park) was investigated with ground-based radiometry and night-time light data. A small night-sky radiometer installed near the main stages and a calibrated digital camera from a nearby observation spot inside of the park were used to quantify changes in night sky brightness and direct light emissions within the park. The impact of the music festival on the urban skyglow was indeed measurable. Zenith luminance increased locally by up to a factor of 8 and illuminance increased by about 50% at the observation spot within the park. The radiance detected by night-time satellite was also increased during the festival. This is the first time, that light pollution from such a major rock music event was quantified.
Light pollution has increased globally, with 80% of the total population now living under light-polluted skies. In this Review, we elucidate the scope and importance of light pollution and discuss techniques to monitor it. In urban areas, light emissions from sources such as street lights lead to a zenith radiance 40 times larger than that of an unpolluted night sky. Non-urban areas account for over 50% of the total night-time light observed by satellites, with contributions from sources such as transportation networks and resource extraction. Artificial light can disturb the migratory and reproductive behaviours of animals even at the low illuminances from diffuse skyglow. Additionally, lighting (indoor and outdoor) accounts for 20% of global electricity consumption and 6% of CO2 emissions, leading to indirect environmental impacts and a financial cost. However, existing monitoring techniques can only perform a limited number of measurements throughout the night and lack spectral and spatial resolution. Therefore, satellites with improved spectral and spatial resolution are needed to enable time series analysis of light pollution trends throughout the night.
Artificial light at night originating from bridge illumination can cause polarised light pollution when it is reflected at water body surfaces. This alters the optical conditions of a river at night and potentially interferes with natural polarisation signals from, for example, moonlight. Therefore, this type of light pollution could detrimentally change the behaviour of organisms sensitive to polarised light, a navigational cue and signal known to be used e.g. by flying water-seeking insects to detect suitable aquatic habitats to reproduce and lay eggs. So far, polarised light pollution from artificial light at night is understudied. Here, we quantify polarised light pollution at the water’s surface near seven illuminated bridges crossing the river Spree in Berlin. Our measurements show for the first time, that nocturnal bridge illumination induces polarised light pollution towards potential flying paths of polarotactic aquatic insects. On average, around 9% of the water surfaces at the investigated bridges were highly polluted by polarised light, with values ranging between 3 and 12 % for each bridge. Thus, polarised light pollution from artificial light at night is an emergent pollutant for aquatic systems. Future work on this topic should include more comprehensive measurements, further ecological studies on its impacts and the development of sustainable lighting solutions that can contribute to the protection of riverine nightscapes.
Coarsening of Quasi Two-Dimensional Emulsions Formed by Islands in Free-Standing Smectic Films
(2024)
We study the coarsening behavior of assemblies of islands on smectic A freely suspended films in ISS microgravity experiments. The islands can be regarded as liquid inclusions in a two-dimensional fluid in analogy to liquid droplets of the discontinuous phase of an emulsion. The coarsening is effectuated by two processes, predominantly by island coalescence, but to some extend also by Ostwald ripening, whereby large islands grow at the expense of surrounding smaller ones. A peculiarity of this system is that the continuous and the discontinuous phases consist of the same material. We determine the dynamics, analyze the self-similar aging of the island size distribution and discuss characteristic exponents of the mean island growth.
Smectic islands on a thin freely suspended smectic film form a quasi two-dimensional emulsion, without a liquid subphase. We describe the coarsening dynamics that involves island coalescence and Ostwald ripening.
The German government's initiative to cover 80% of the gross electricity supply with renewable energies by 2050 brings considerable ecological benefits, but also poses several challenges. One of these challenges is the growing number of photovoltaic systems (PV systems), which, due to their high feed-in power, already pose a risk to the security of the electricity distribution grid during long periods of sunny weather. To counteract this, active research is being carried out in the field of PV power forecasting. This research is primarily aimed at providing the grid operator with a predicted power output, which enables a longer planning horizon and thus increases the operational grid security. However, the considerable annual electricity consumption of private households and the increasing spread of PV systems for self-consumption show that the energy behavior of households, especially self-consumption, also influences grid security. Additionally, households have an incentive to boost their self-consumption because the cost of drawing each kilowatt-hour from the grid is substantially higher than the compensation received for injecting an equivalent amount of energy back into the grid. However, as of now, there is no software available that easily enables households to tailor the usage patterns of their electrical appliances according to a photovoltaic (PV) forecast. The project described here aims to close this gap by creating such software. Various PV forecasting models are used and tested for their suitability for this purpose. A self-generated optimization process is implemented in this project to optimize the consumer configuration based on the PV forecasts. The here-developed tool enables the user to enter parameters for his PV system and the specific load profiles of his electrical appliances. Based on this data, the optimization algorithm determines a consumption plan with a forecast horizon until the end of the next day that maximizes the user's self-consumption. To validate the tool, the optimization process is carried out over a period of 60 days using a predefined scenario and the results are compared with a scenario in which the electrical appliances are intuitively operated at midday. The analysis of these results ultimately shows the potential impact of such a tool on the economic efficiency of private households and the supply stability.
The problem of increasing the efficiency of existing photodetectors and creating their new types attracts much research attention. Among new photodetector types are photosensitive structures based on cascade concentrators, whose operational principle involves the absorption of optical radiation followed by its reemission at a longer wavelength and radiation concentration onto a highly efficient small-area photodetector. The absorption and re-emission spectra of each cascade layer depend on the characteristics of the material used. Сolloidal quantum dots are among the most promising materials for cascade layers due to their manufacturing technology, which provides for accurate control over the photoluminescence maximum position. It seems highly relevant to develop and to study photosensitive structures with cascade concentrators of various shapes based on CdS, CdSe/ZnS, and PbS colloidal quantum dots. Aim . To develop photosensitive structures with a wide-range sensitivity spectrum based on concentrators containing arrays of metal chalcogenide CQDs and to study their characteristics. Materials and methods . Cascade photosensitive structures were manufactured based on layers made of polymethyl methacrylate and layers of colloidal quantum dots embedded in a polystyrene matrix. Results . Three-layer concentrators were manufactured with different colloidal quantum dots in each concentrator layers. A 22 % increase in the output power was observed for a three-layer cascade structure based on different cascade layer materials compared to a similar structure using a single layer concentrator. Conclusion . The conducted studies showed an increase in the efficiency of photosensitive structures with a cascade concentrator based on colloidal quantum dots of various types (CdS, CdSe/ZnS, and PbS) in the cascade layers.
Illuminated bridges have become important assets to navigable aquatic systems. However, if artificial light at night (ALAN) from illuminated bridges reaches aquatic habitats, such as rivers, it can threaten the river's natural heterogeneity and alter the behavioural responses of migratory fish. Here, via a pilot study, we quantified levels of ALAN at illuminated bridges that cross a river and, propose a conceptual model to estimate its potential implications on two migrating fish species with contrasting life histories. Night-time light measurements on the river Spree in Berlin were performed continuously along a transect and in detail at seven illuminated bridges. Photometric data of the pilot study showed rapidly increased and decreased light levels at several illuminated bridges from which we derived several model illumination scenarios. These illumination scenarios and their potential effect on migrating Atlantic salmon smolts (Salmo salar) and European silver eel (Anguilla anguilla) are presented as a conceptual model, considering illuminated bridges as behavioural barriers to fish migration. ALAN's adverse effects on freshwater habitats must be better researched, understood, managed, and properly communicated to develop future sustainable lighting practices and policies that preserve riverscapes and their biodiversity.
So weit das Auge trägt
(2023)
Sichtweiten in der Atmosphäre reichen von wenigen Metern im Nebel bis zu einigen hundert Kilometern bei extrem guten Fernsichtbedingungen. Die zugrundeliegende Physik geht vom Wahrnehmungskontrast aus. Dieser ändert sich mit der Entfernung entlang der Sichtlinie zwischen Objekt und Auge aufgrund von Lichtstreuung und Absorption an den Bestandteilen der Atmosphäre. Dazu kommt bei der Fernsicht die Refraktion, die es erlaubt, auch über den durch die Kugelform der Erde geometrisch bedingten Horizont hinaus zu sehen.
This study examines the impact of Artificial Light at Night (ALAN) on two coral species, Acropora eurystoma and Pocillopora damicornis, in the Gulf of Aqaba/Eilat Red Sea, assessing their natural isotopic responses to highlight changes in energy and nutrient sourcing due to sensory light pollution. Our findings indicate significant disturbances in photosynthetic processes in Acropora eurystoma, as evidenced by shifts in δ13C values under ALAN, pointing to alterations in carbon distribution or utilization. In Pocillopora damicornis, similar trends were observed, with changes in δ13C and δ15N values suggesting a disruption in its nitrogen cycle and feeding strategies.
The study also uncovers species-specific variations in heterotrophic feeding, a crucial factor in coral resilience under environmental stress, contributing to the corals' fixed carbon budget. Light measurements across the Gulf demonstrated a gradient of light pollution which possess the potential of affecting marine biology in the region. ALAN was found to disrupt natural diurnal tentacle behaviors in both coral species, crucial for prey capture and nutrient acquisition, thereby impacting their isotopic composition and health.
Echoing previous research, our study underscores the need to consider each species' ecological and physiological contexts when assessing the impacts of anthropogenic changes. The findings offer important insights into the complexities of marine ecosystems under environmental stress and highlight the urgency of developing effective mitigation strategies.
In this study, we have investigated the form of velocity and pressure functions of a fluid oscillating between two parallel glass sheets that form a circular Hele-Shaw cell. The flow has been considered to be radial, incompressible and laminar. The time-dependent Navier-Stokes equation has been solved in cylindrical coordinates using Fourier transform, and the oscillating flow velocity across the thickness of the cell has been obtained at different times. The flow velocity function in the unsteady state is related to the vertical component of the coordinates in the form of parabolic functions and also to the inverse of the radial component. The time dependence appears as a simple harmonic with a frequency equal to the oscillation frequency. The velocity of the flow is maximum at the middle of the cell along its height and gradually decreases from the middle towards the top or bottom plane and reaches zero. Pressure does not depend on the height and changes logarithmically with the radius. The dependence of pressure on time is also a simple harmonic with the external frequency, but it has a phase shift with respect to the velocity.
Ubiquitous Music is an interdisciplinary research area that combines methodologies from music, computer science, education, creativity studies, human sciences and engineering.
The Ubiumus 2023 symposium, held at Ulster University and North West Regional College in Derry~Londonderry, Northern Ireland, included contributions on the following topics:
Rapid Prototyping and Live Environments
Ecological Approaches to Ubiquitous Music
Ubiquitous Music Creative Practices, Tools and Influences
The symposium also included a number of artistic contributions and workshops, which are also discussed in the proceedings volume. A number of events (including all paper presentations, an invited lecture, a panel discussion, and a keynote and associated performance) were also documented via video, with a link available in this Proceedings volume.
We investigate micrometer-sized flat droplets consisting of an isotropic core surrounded by a nematic rim in freely suspended smectic A liquid-crystal films. In contrast to purely isotropic droplets which are characterized by a sharp edge and no long-range interactions, the nematic fringe introduces a continuous film thickness change resulting in long-range mutual attraction of droplets. The coalescence scenario is divided in two phases. The first one consists in the fusion of the nematic regions. The second phase involves the dissolution of a thin nematic film between the two isotropic cores. The latter has many similarities with the rupture of thin liquid films between droplets coalescing in an immiscible viscous liquid.
Coalescence of biphasic droplets in free-standing smectic films is controlled in part by the rupture of a thin nematic membrane separating the isotropic droplet cores.
Sensing is nowadays an accepted application of phononic crystals with chemical and biosensors for liquid analytes being the perhaps most promising ones. A liquid-filled defect is introduced that turns into a resonant cavity. Similar to the well-known resonant sensors sensitivity can be increased with higher operating frequencies. We introduce a Sandwiched Phononic Crystal (SPC), which applies a resonant cavity located between two stacked layers on top of a SAW device. Key challenges are coupling of surface acoustic wave into the liquid cavities and avoiding scattering of the guided waves into the bulk of the sensor chip.
Phononic crystals (PnC) with a specifically designed liquid-filled defect have been recently introduced as a novel sensor platform (Lucklum et al. in Sens Actuators B Chem 171–172:271–277, 2012). Sensors based on this principle feature a band gap covering the typical input span of the measurand as well as a narrow transmission peak within the band gap where the frequency of maximum transmission is governed by the measurand. This approach has been applied for determination of volumetric properties of liquids (Lucklum et al. in Sens Actuators B Chem 171–172:271–277, 2012; Oseev et al. in Sens Actuators B Chem 189:208–212, 2013; Lucklum and Li in Meas Sci Technol 20(12):124014, 2009) and has demonstrated attractive sensitivity. One way to improve sensitivity requires higher probing frequencies in the range of 100 MHz and above. In this range surface acoustic wave (SAW) devices are an established basis for sensors. We have performed first tests towards a PnC microsensors (Lucklum et al. in Towards a SAW based phononic crystal sensor platform. In: 2013 Joint European frequency and time forum and international frequency control symposium (EFTF/IFC), pp 69–72, 2013). The respective feature size of the PnC SAW sensor has dimensions in the range of 10 µm and below. Whereas those dimensions are state of the art for common MEMS materials, etching of holes and cavities in piezoelectric materials that have an aspect ratio diameter/depth is still challenging. In this contribution we describe an improved technological process able to realize considerably deep and uniform holes in a SAW substrate.
The study focuses on high-performance combined electro-spark alloying of titanium and titanium alloy (VT1-0, VT16) surface and porous matrix structure oxidation. The metal-oxide coatings morphology is the result of melt drop transfer, heat treatment, and oxidation. The study establishes the influence of technological regimes of alloying and oxidation on morphological heterogeneity of biocompatible layered metal-oxide system Ti-Ta-(Ti,Ta)xOy. It was found that during electro-spark alloying the concentration of tantalum on the titanium surface ranges from 0.1 to 3.2 at.%. Morphology of the deposited splats is represented by uniformly grown crystals of titanium and tantalum oxides, which increase from nano- to submicron size.
Water can exhibit many different colors due to a variety of physical properties. Here, we focus on some observable colors within very pure freshwater. We only treat the absorption of light due to electronic and ro-vibrational excitations and scattering due to refractive index fluctuations of the water and the respective consequences for the appearance of colors.
Freezing of lakes is described using a simplified one-dimensional model, which gives ice thickness, ice growth rates, and ice surface temperature as a function of time. Model data for a specific lake with known meteorological conditions are compared to estimated ice thickness using a simple optical method. Finally, more advanced potential students projects are briefly discussed and results of a numerical solution are compared to the simplified model.
The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the co-creation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus still limited. Our research framework promotes the concept and stimulates the strengthening of the role of Text Analytics techniques to support public sector organisations and their use of co-creation process. From policy-makers' and public administration managers' standpoints, our findings and the proposed research framework can be used as a guideline in developing a strategy for the designing co-created and user-centred public services.
Disclinations or disclination clusters in smectic C freely suspended films with topological charges larger than one are unstable. They disintegrate, preferably in a spatially symmetric fashion, into single defects with individual charges of +1, which is the smallest positive topological charge allowed in polar vector fields. While the opposite process of defect annihilation is well-defined by the initial defect positions, disintegration starts from a singular state and the following scenario including the emerging regular defect patterns must be selected by specific mechanisms. We analyze experimental data and compare them with a simple model where the defect clusters adiabatically pass quasi-equilibrium solutions in one-constant approximation. It is found that the defects arrange in geometrical patterns that correspond very closely to superimposed singular defect solutions, without additional director distortions. The patterns expand by affine transformations where all distances between individual defects scale with the same time-dependent scaling factor proportional to the square-root of time.
The Patellostabilometer: A New Device for Quantification of Mediolateral Patella Displacement
(2023)
Mediolateral patella displacement is of interest for diagnostics and clinically relevant
research questions. Apart from manual testing, no standardized method is currently available. Proper
quantification of patella mobility is necessary to better understand pathologies at the patellofemoral
joint. Patella mobility was assessed in 25 healthy individuals using a Patellostabilometer, a new
prototype instrument for quantification of the mediolateral patella displacement. The participants
underwent measurements of the mediolateral displacement three times using the Patellostabilome-
ter. A maximal force of 10 N was applied for patella movement. Additionally, leg length and
circumference of the knee, upper- and lower-leg were measured. Lateral patella displacement of
18.27 ± 3.76 mm (range 15.85–20.64 mm, interquartile range (IQR) of 4.79) was measured. The medial
patella displacement showed 24.47 ± 6.59 mm (range 19.29–29.76 mm, IQR of 10.47). The test–retest
measurement error was 2.32 ± 1.76 mm (IQR of 2.38 mm), with five outliers. There was greater
test–retest variability between the measurements of the medial displacement compared to the lateral
one. The test–retest variability reached 7% of the patella displacement. Other parameters provided no
significant correlations. Based on the natural patellofemoral mobility, a precise and clinically relevant
quantification of patella mobility is allowed.
Context awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it becomes essential to employ relevant text analytics techniques to increase the awareness of process workers, which is important for process execution. The present paper addresses this demand by developing a framework for context awareness based on process executions-related textual data using a well-established layered BPM context model. This framework combines and maps various text analytics techniques to the layers of the context model, aiming to increase the context awareness of process workers and facilitate informed decision-making. The framework is applied in an IT ticket processing case study. The findings show that contextual information obtained using our framework enriches the awareness of process workers regarding the process instance urgency, complexity, and upcoming tasks and assists in making decisions in terms of these aspects.
An approach for analyzing business process execution complexity based on textual data and event log
(2023)
With the advent of digital transformation, organizations increasingly rely on various information systems to support their business processes (BPs). Recorded data, including textual data and event log, expand exponentially, complicating decision-making and posing new challenges for BP complexity analysis in Business Process Management (BPM). Herein, Process Mining (PM) serves to derive insights based on historic BP execution data, called event log. However, in PM, textual data is often neglected or limited to BP descriptions. Therefore, in this study, we propose a novel approach for analyzing BP execution complexity by combining textual data serving as an input at the BP start and event log. The approach is aimed at studying the connection between complexities obtained from these two data types. For textual data-based complexity, the approach employs a set of linguistic features. In our previous work, we have explored the design of linguistic features favorable for BP execution complexity prediction. Accordingly, we adapt and incorporate them into the proposed approach. Using these features, various machine learning techniques are applied to predict textual data-based complexity. Moreover, in this prediction, we show the adequacy of our linguistic features, which outperformed the linguistic features of a widely-used text analysis technique. To calculate event log-based complexity, the event log and relevant complexity metrics are used. Afterward, a correlation analysis of two complexities and an analysis of the significant differences in correlations are performed. The results serve to derive recommendations and insights for BP improvement. We apply the approach in the IT ticket handling process of the IT department of an academic institution. Our findings show that the suggested approach enables a comprehensive identification of BP redesign and improvement opportunities.
Large three-dimensional metallic parts can be printed layer-by-layer using gas metal arc directed energy deposition (GMA-DED) process at a high deposition rate and with little or no material wastage. Fast responsive real-time monitoring of GMA-DED process signatures and their transient variations is required for printing of dimensionally accurate and structurally sound parts. A systematic experimental investigation is presented here on multi-layer GMA-DED with two different scanning strategies using a high strength low alloy (HSLA) filler wire. The dynamic metal transfer, melt pool temperature field and its longitudinal cross-section, and arc voltage and current are monitored synchronously. The transient arc heat input and the melt pool solidification cooling rate are estimated from the monitored signals. The layer-wise variations of the melt pool dimension, surface temperature profile, thermal cycles, and solidification cooling rate are examined for different scanning strategies. It is comprehended that the part defects can be minimized, and the mass production of zero-defect parts can be achieved in GMA-DED process with synchronized monitoring and assessment of the real-time process signatures.
When a droplet is brought in contact with an undercooled surface, it wets the substrate and solidifies at the same time. The interplay between the phase transition effects and the contact-line motion, leading to its arrest, remains poorly understood. Here we reveal the early solidification patterns and dynamics of spreading hexadecane droplets. Total internal reflection imaging is employed to temporally and spatially resolve the early solidification behavior. With this, we determine the conditions leading to the contact-line arrest. We quantify the overall nucleation behavior, i.e., the nucleation rate and the crystal growth speed and show its sensitivity to the applied undercooling of the substrate. We also show that for strong enough undercooling it is the rapid growth of the crystals which determines the eventual arrest of the spreading contact line. By combining the Johnson-Mehl-Avrami-Kolmogorov nucleation theory and scaling relations for the spreading, we calculate the temporal evolution of the solid area fraction, which is in good agreement with our observations.
A central idea of ubiquitous music is that music does not arise from the ideas of an isolated genius, but rather from the interaction of several participants [Keller et al. 2014]. But this requires a certain amount of restraint on the part of the designers of the respective setting and at the same time seems to require a full disclosure of the underlying theoretical and aesthetic concepts to the participants, if the participants are really to be taken seriously and given the means to actually be able to become creative themselves in an understandable way within the given context. In this paper, the consequences of such a demand are first discussed theoretically. Finally, for the concept developed by the author, ”Every human being can compose on the basis of natural numbers”, an attempt is made in this specific case to determine in what form such a concept could be passed on in order to meet the above criteria.
Der Erwartungswert einer Zufallsgröße kann generell am Graphen ihrer Verteilungsfunktion durch eine naheliegende Gleichheit zweier Flächeninhalte festgelegt werden. Äquivalent dazu lässt er sich mit zwei uneigentlichen Riemann-Integralen darstellen. Davon ausgehend werden die Tschebyschow-Ungleichung und ihre Modifikation mit strikten Ungleichheitszeichen hergeleitet.
Fast protein and metabolite liquid chromatography (FPLMC) was introduced years ago to enable the easy separation of high-molecular compounds such as proteins from small molecules and the identification of the low-molecular substances. In this paper, the method is applied for the rapid evaluation of freshness and monitoring the aging of animal meat and fish. A novel chromatographic sensor was developed with a deep UV LED-based photometric detection unit (255–265 nm), an original flow cuvette and registration scheme; the processing of a chromatogram with the sensor takes approximately 15 min. Strict isochronism between the elution of ATP metabolites, mainly hypoxanthine (Hx) and inosine monophosphate (IMP), and the time of maturation of meat or fish, was discovered. A new freshness index H* = [Hx]/[IMP] was introduced, which is proportional to the instrumental delay time in the FPMLC chromatograms: the H* index < 0.5 indicates the presence of inosine monophosphate (IMP) and the high quality of the meat or fish. Reasonably strong correlations were revealed between data obtained by FPMLC and total volatile basic nitrogen TVB-N (for fish) or volatile fatty acids VFA (for meat) content. Moreover, putative nucleotide salvage and an increase in the concentration of IMP were observed in fish after heat treatment using the FPMLC sensor and NMR technique.
A sample set of calculations is presented in this supplemental document to analytically estimate joint distortion for gas metal arc lap joining of aluminum and steel thin sheets following the published article "Analytical Estimation of Thermomechanical Distortion and Interface Layer Thickness for Gas Metal Arc Lap Joining of Dissimilar Sheets"
Untersuchung der Rotorfestigkeit von permanenterregten Synchronmaschinen mit vergrabenen Magneten
(2023)
Diese Projektarbeit behandelt die mechanische Simulation der Rotoren von permanenterregten Synchronmaschinen für den Festigkeitsnachweis. Hierzu wird die Finite-Elemente-Methode mit dem Programm CalculiX verwendet. Als Beispiel wird der Elektromotor des Toyota Prius II im Detail betrachtet. Hierbei werden die unterschiedlichen Lasten modelliert, dazu zählen neben der Zentrifugalkraft auch der Innendruck durch eine Presspassung sowie die elektromagnetischen Kräfte. Für die Modellierung von Kräften auf der Rotoroberfläche wird eine Methodik zur Umsetzung in CalculiX entwickelt und anhand eines Beispielmodells demonstriert. Der angestrebte Festigkeitsnachweis kann im Rahmen dieser Arbeit erbracht werden. Weiterhin wird gezeigt, dass der Einfluss der elektromagnetischen Kräfte im Arbeitspunkt mit der höchsten Drehzahl sehr gering ausfällt. Insgesamt bietet diese Arbeit die Grundlagen für mechanische Modellierungen von Rotoren unter Berücksichtigung aller Kräfte. Dies kann direkt auf andere Elektromotoren angewendet werden.