Gesamtliste aus der Hochschulbibliographie

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Rochyadi-Reetz, Mira; Wolling, Jens
Environmental communication publications in Indonesia’s leading communication journals : a systematic review. - In: Jurnal Aspikom, ISSN 2548-8309, Bd. 8 (2023), 1, S. 15-28

As an emerging country, Indonesia is facing many environmental problems, with some of the most critical being plastic waste, severe deforestation, and climate change. Under such conditions, communication science plays an important role in pointing to the best way to inform the public so as to stimulate engagement and action to solve these problems. In this article, a systematic literature review of papers on environmental communication published in three leading communication journals in Indonesia was conducted. The findings show that despite the severe environmental problems in Indonesia, a limited number of studies on environmental communication have been published, and only a few methods and designs have been used. Therefore, more attention from communication scholars and intellectuals in Indonesia is needed to address environmental problems in their research. Creating an environmental communication division in existing communication associations is proposed as a practical solution, among others, and is discussed in the outlook section of this study



https://doi.org/10.24329/aspikom.v8i1.1210
Walther, Dominik; Viehweg, Johannes; Haueisen, Jens; Mäder, Patrick
A systematic comparison of deep learning methods for EEG time series analysis. - In: Frontiers in neuroinformatics, ISSN 1662-5196, Bd. 17 (2023), 1067095, S. 01-17

Analyzing time series data like EEG or MEG is challenging due to noisy, high-dimensional, and patient-specific signals. Deep learning methods have been demonstrated to be superior in analyzing time series data compared to shallow learning methods which utilize handcrafted and often subjective features. Especially, recurrent deep neural networks (RNN) are considered suitable to analyze such continuous data. However, previous studies show that they are computationally expensive and difficult to train. In contrast, feed-forward networks (FFN) have previously mostly been considered in combination with hand-crafted and problem-specific feature extractions, such as short time Fourier and discrete wavelet transform. A sought-after are easily applicable methods that efficiently analyze raw data to remove the need for problem-specific adaptations. In this work, we systematically compare RNN and FFN topologies as well as advanced architectural concepts on multiple datasets with the same data preprocessing pipeline. We examine the behavior of those approaches to provide an update and guideline for researchers who deal with automated analysis of EEG time series data. To ensure that the results are meaningful, it is important to compare the presented approaches while keeping the same experimental setup, which to our knowledge was never done before. This paper is a first step toward a fairer comparison of different methodologies with EEG time series data. Our results indicate that a recurrent LSTM architecture with attention performs best on less complex tasks, while the temporal convolutional network (TCN) outperforms all the recurrent architectures on the most complex dataset yielding a 8.61% accuracy improvement. In general, we found the attention mechanism to substantially improve classification results of RNNs. Toward a light-weight and online learning-ready approach, we found extreme learning machines (ELM) to yield comparable results for the less complex tasks.



https://doi.org/10.3389/fninf.2023.1067095
Pöthig, Pascal; Grätzel, Michael; Bergmann, Jean Pierre
Influence of different surface conditions on mechanical properties during ultrasonic welding of aluminum wire strands and copper terminals. - In: Welding in the world, ISSN 1878-6669, Bd. 67 (2023), 6, S. 1427-1436

Ultrasonic metal welding (USMW) has become considerable attention in terms of its suitable applications compared to conventional fusion welding techniques. The main advantage of USMW results from the comparatively low process times and joining temperatures below the melting point. Thus, USMW is particularly used for the joining of dissimilar material combinations, e.g., aluminum and copper (Al/Cu), in battery cell production or wiring harness applications. However, process fluctuations in USMW of Al/Cu joints can occur due to varying surface conditions of the joining materials. Therefore, this study investigated different surface conditions of copper terminals and their effects on mechanical properties. At first, three different surface conditions were generated, respectively: surface cleaning (sulfuric acid and ethanol), structuring process by laser, and structuring process by milling. These modifications are compared with the terminals in the initial state (contaminated). The characterization of the terminal surfaces was carried out with 3-D laser scanning microscopy as well as light microscopy. The mechanical conditions were examined with shear tensile tests. The tensile tests showed a significant influence of the surface condition on the resulting failure loads compared to the initial state. The highest failure loads could be achieved with the structured terminals (+ 48%), whereas contaminated terminals and terminals with notches exhibited comparatively poor failure loads (- 28%). This can be explained by varying interface formations between the terminal and the wire, which was detected by metallography and SEM analysis. Furthermore, it was figured out that the interface between aluminum and copper exhibits a firm and formed closure bond and hence increased failure loads for laser-structured terminals. Additional investigations by SEM revealed no detectable occurrence of intermetallic phases.



https://doi.org/10.1007/s40194-023-01490-x
Hamatschek, Christopher; Augsburg, Klaus; Schobel, David; Gramstat, Sebastian; Stich, Anton; Gulden, Florian; Hesse, David
Comparative study on the friction behaviour and the particle formation process between a laser cladded brake disc and a conventional grey cast iron disc. - In: Metals, ISSN 2075-4701, Bd. 13 (2023), 2, 300, S. 1-19

Brake-wear particle emissions are the result of the components of a friction brake being in tribological contact, and they are classified as non-exhaust emissions. Since most of the emitted particles belong to the size classes of particulate matter (≤10 μm) and differ significantly in terms of their physico-chemical properties from automotive exhaust emissions, this source is of particular relevance to human health and, therefore, the focus of scientific studies. Previous studies have shown that coated brake discs offer significant wear and emission reduction potential. Nevertheless, no studies are available that describe the specific particle formation process, the contact conditions, the structure of the friction layer and the differences compared to conventional grey cast iron discs. The aim of this study is to describe those differences. For this purpose, the tribological behaviour, the structure of the friction layer and the associated particle dynamics within the friction contact between a laser cladding coated disc and a conventional grey cast iron disc are compared. The required investigations are carried out both ex situ (stationary) and in situ (dynamic). Parallel to the tribological investigations, the particle emission behaviour is determined on an inertia dynamometer using a constant volume sampling system (CVS) and equipment for particle number and particle size distribution measurement. The results show that, for two different brake pads, the laser cladding brake disc has lower wear and less particulate emissions than the grey cast iron brake disc. The wear behaviour of the coating varies significantly for the two brake pads. By contrast, the grey cast iron brake disc shows a significantly lower influence.



https://doi.org/10.3390/met13020300
Kästner, Christian; Schneider, Julien David; Du Puits, Ronald
Evolution and features of dust devil-like vortices in turbulent Rayleigh-Bénard convection - an experimental study. - In: JGR, ISSN 2169-8996, Bd. 128 (2023), 2, e2022JD037466, S. 1-20

We present an experimental study simulating atmospheric dust devils in a controlled laboratory experiment. The experimental facility, called the “Barrel of Ilmenau” (www.ilmenauer-fass.de) represents a classical Rayleigh-Bénard set-up and is believed to model the phenomena in a convective atmospheric boundary layer fairly well. Our work complements and extends the numerical work of Giersch and Raasch (2021) https//doi.org/10.1029/2020jd034334 by experiments. Dust devils are thermal convective vortices with a vertical axis of rotation visualized by entrained soil particles. They evolve in the convective atmospheric boundary layer and are believed to substantially contribute to the aerosol transport into the atmosphere. Thus, their evolution, size, lifetime, and frequency of occurrence are of particular research interest. Extensive experimental studies have been conducted by field measurements and laboratory experiments so far. Beyond that, our study is the first attempt of Rayleigh-Bénard convection (RBC) in air to investigate dust devil-like vortices in a laboratory experiment. Up to now, this set-up mimics the natural process of dust devil evolution as closest to reality. The flow measurement was carried out by particle tracking velocimetry using neutrally buoyant soap bubbles. We initially identified dust devil-like vortices by eye from the Lagrangian velocity field, and in a later, more sophisticated analysis by a specific algorithm from the corresponding Eulerian velocity field. We analyzed their frequency of occurrence, observation time, and size. With our work, we could demonstrate that turbulent RBC is an appropriate model to mimic the natural process of the evolution of dust devils in the convective atmospheric boundary layer without artificial stimulation.



https://doi.org/10.1029/2022JD037466
Sachs, Sebastian; Ratz, Manuel; Mäder, Patrick; König, Jörg; Cierpka, Christian
Particle detection and size recognition based on defocused particle images: a comparison of a deterministic algorithm and a deep neural network. - In: Experiments in fluids, ISSN 1432-1114, Bd. 64 (2023), 2, 21, S. 1-16

The systematic manipulation of components of multimodal particle solutions is a key for the design of modern industrial products and pharmaceuticals with highly customized properties. In order to optimize innovative particle separation devices on microfluidic scales, a particle size recognition with simultaneous volumetric position determination is essential. In the present study, the astigmatism particle tracking velocimetry is extended by a deterministic algorithm and a deep neural network (DNN) to include size classification of particles of multimodal size distribution. Without any adaptation of the existing measurement setup, a reliable classification of bimodal particle solutions in the size range of 1.14 μm–5.03 μm is demonstrated with a precision of up to 99.9 %. Concurrently, the high detection rate of the particles, suspended in a laminar fluid flow, is quantified by a recall of 99.0 %. By extracting particle images from the experimentally acquired images and placing them on a synthetic background, semi-synthetic images with consistent ground truth are generated. These contain labeled overlapping particle images that are correctly detected and classified by the DNN. The study is complemented by employing the presented algorithms for simultaneous size recognition of up to four particle species with a particle diameter in between 1.14 μm and 5.03 μm. With the very high precision of up to 99.3 % at a recall of 94.8 %, the applicability to classify multimodal particle mixtures even in dense solutions is confirmed. The present contribution thus paves the way for quantitative evaluation of microfluidic separation and mixing processes.



https://doi.org/10.1007/s00348-023-03574-2
Hähnlein, Bernd; Honig, Hauke; Schaaf, Peter; Krischok, Stefan; Tonisch, Katja
Effect of poly-crystallinity on the magnetoelectric behavior of TiN/AlN/Ni MEMS cantilevers investigated by finite element methods. - In: Physica status solidi, ISSN 1862-6319, Bd. 220 (2023), 16, 2200839, S. 1-6

Herein, magnetoelectric microelectromechanical system (MEMS) cantilevers are investigated on basis of a TiN/AlN/Ni laminate derived from experimental sensors using finite-element simulations. With the anisotropic ΔE effect as an implication of the magnetocrystalline anisotropy, the lateral sensitivity of the sensor is studied for different nickel layer thicknesses and boundary conditions. It is found that above 60% of the cantilever length, the nickel is effectively not contributing to the sensor sensitivity anymore which is supported by the investigation of sensors with partial nickel coverage. The boundary condition of the magnetostrictive layer is found to affect the sensitivity of thick layers while it is negligible for thinning layers. Further investigations on basis of polycrystalline untextured nickel with slightly preferred orientations reveal a stronger effect on thin layers than on thicker ones. It is found to arise from relatively large crystals in the high-sensitivity region near the clamping of the sensor. For thicker polycrystalline layers, the ΔE effect reproduces a characteristic based mainly on the (110) and (111) orientations while the (100) orientation appears to be underrepresented.



https://doi.org/10.1002/pssa.202200839
Löffelholz, Martin;
[Rezension von: Störmer, Maja, 1990-, Krisenkommunikation in der digitalen Gesellschaft]. - In: Publizistik. - Wiesbaden : VS Verl. für Sozialwiss., 2000- , ISSN: 1862-2569 , ZDB-ID: 2273951-8, ISSN 1862-2569, Bd. 68 (2023), 1, S. 151-153

https://doi.org/10.1007/s11616-022-00775-3
Cheng, Pengfei; Döll, Joachim; Romanus, Henry; Wang, Hongguang; Aken, Peter Antonie van; Wang, Dong; Schaaf, Peter
Reactive magnetron sputtering of large-scale 3D aluminum-based plasmonic nanostructure for both light-induced thermal imaging and photo-thermoelectric conversion. - In: Advanced optical materials, ISSN 2195-1071, Bd. 11 (2023), 6, 2202664, S. 1-7

Plasmonic nanostructures have attracted tremendous interest due to their special capability to trap light, which is of great significance for many applications such as solar steam generation and desalination, electric power generation, photodetection, sensing, catalysis, cancer therapy, and photoacoustic imaging. However, the noble metal-based (Au, Ag, Pd) plasmonic nanostructures with expensive costs and limitations to large-scale fabrication restrict their practical applications. Here, a novel and noble-metal-free Al/AlN plasmonic nanostructure fabricated by a reactive magnetron sputtering at the elevated temperature of 200 ˚C is presented. The unique 3D Al/AlN plasmonic nanostructures show a highly efficient (96.8%) and broadband (full solar spectrum) absorption and a strong photothermal conversion effect on its surface, demonstrating the potential in applications in light-induced thermal imaging and photo-thermoelectric power generation. This simple fabrication method and the developed Al/AlN plasmonic nanostructure combine excellent light trapping performance, abundant and low-cost Al and N elements, good heat localization effect, and scalable fabrication method, suggesting a promising alternative to noble-metal plasmonic nanostructures for photonic applications.



https://doi.org/10.1002/adom.202202664
Xu, Changfan; Dong, Yulian; Shen, Yonglong; Zhao, Huaping; Li, Liqiang; Shao, Guosheng; Lei, Yong
Fundamental understanding of nonaqueous and hybrid Na-CO2 batteries: challenges and perspectives. - In: Small, ISSN 1613-6829, Bd. 19 (2023), 15, 2206445, S. 1-30

Alkali metal-CO2 batteries, which combine CO2 recycling with energy conversion and storage, are a promising way to address the energy crisis and global warming. Unfortunately, the limited cycle life, poor reversibility, and low energy efficiency of these batteries have hindered their commercialization. Li-CO2 battery systems have been intensively researched in these aspects over the past few years, however, the exploration of Na-CO2 batteries is still in its infancy. To improve the development of Na-CO2 batteries, one must have a full picture of the chemistry and electrochemistry controlling the operation of Na-CO2 batteries and a full understanding of the correlation between cell configurations and functionality therein. Here, recent advances in CO2 chemical and electrochemical mechanisms on nonaqueous Na-CO2 batteries and hybrid Na-CO2 batteries (including O2-involved Na-O2/CO2 batteries) are reviewed in-depth and comprehensively. Following this, the primary issues and challenges in various battery components are identified, and the design strategies for the interfacial structure of Na anodes, electrolyte properties, and cathode materials are explored, along with the correlations between cell configurations, functional materials, and comprehensive performances are established. Finally, the prospects and directions for rationally constructing Na-CO2 battery materials are foreseen.



https://doi.org/10.1002/smll.202206445