620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
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Im Montafon, das im Süden des österreichischen Bundeslandes Vorarlberg liegt, befindet sich eines der ältesten kleinen Montanreviere. Zwischen St. Anton im Norden und St. Gallenkirch im Süden befinden sich an zahlreichen Stellen Hinweise auf alten Bergbau, wobei sich die umfangreichsten Relikte in den ehemaligen Bergbaurevieren in den Gewannen Knappagruaba und Worms am Bartholomäberg sowie auf dem Kristberg im Silbertal finden. Es handelt sich um verschiedene Hinterlassenschaften des historischen Bergbaus, meist sind es unterschiedlich große Halden mit Taubgestein, runde Schachtpingen und verstürzte Stollenmundlöcher, die in zwei Fällen – dem sog. Barbara Stollen und dem St. Anna Stollen – oberhalb von Bartholomäberg in der Knappagruaba, heute wieder freigelegt wurden und als Schaubergwerk zugänglich sind.
Der Kristberg liegt am Ostende des Davenna-Massivs, ein Bergmassiv, das zwischen dem Klostertal im Norden und der Ill im Montafon im Süden liegt. Als Kristberg wird ein 1465 m hoch gelegener Sattel zwischen dem Itonskopf (2100 m üNN) im Westen und dem Mutjöchle (2010 m üNN) im Osten bezeichnet. Südlich unterhalb des Sattels liegt die Bergknappenkirche St. Agatha und der Panoramagasthof Kristberg inmitten einer heute noch gut erhaltenen Haldenlandschaft des mittelalterlichen bis neuzeitlichen Bergbaus.
Understanding the physics of strongly correlated electronic systems has been a central issue in condensed matter physics for decades. In transition metal oxides, strong correlations characteristic of narrow d bands are at the origin of remarkable properties such as the opening of Mott gap, enhanced effective mass, and anomalous vibronic coupling, to mention a few. SrVO3 with V4+ in a 3d1 electronic configuration is the simplest example of a 3D correlated metallic electronic system. Here, the authors' focus on the observation of a (roughly) quadratic temperature dependence of the inverse electron mobility of this seemingly simple system, which is an intriguing property shared by other metallic oxides. The systematic analysis of electronic transport in SrVO3 thin films discloses the limitations of the simplest picture of e–e correlations in a Fermi liquid (FL); instead, it is shown show that the quasi-2D topology of the Fermi surface (FS) and a strong electron–phonon coupling, contributing to dress carriers with a phonon cloud, play a pivotal role on the reported electron spectroscopic, optical, thermodynamic, and transport data. The picture that emerges is not restricted to SrVO3 but can be shared with other 3d and 4d metallic oxides.
High shares of intermittent renewable power generation in a European electricity system will require flexible backup power generation on the dominant diurnal, synoptic, and seasonal weather timescales. The same three timescales are already covered by today’s dispatchable electricity generation facilities, which are able to follow the typical load variations on the intra-day, intra-week, and seasonal timescales. This work aims to quantify the changing demand for those three backup flexibility classes in emerging large-scale electricity systems, as they transform from low to high shares of variable renewable power generation. A weather-driven modelling is used, which aggregates eight years of wind and solar power generation data as well as load data over Germany and Europe, and splits the backup system required to cover the residual load into three flexibility classes distinguished by their respective maximum rates of change of power output. This modelling shows that the slowly flexible backup system is dominant at low renewable shares, but its optimized capacity decreases and drops close to zero once the average renewable power generation exceeds 50% of the mean load. The medium flexible backup capacities increase for modest renewable shares, peak at around a 40% renewable share, and then continuously decrease to almost zero once the average renewable power generation becomes larger than 100% of the mean load. The dispatch capacity of the highly flexible backup system becomes dominant for renewable shares beyond 50%, and reach their maximum around a 70% renewable share. For renewable shares above 70% the highly flexible backup capacity in Germany remains at its maximum, whereas it decreases again for Europe. This indicates that for highly renewable large-scale electricity systems the total required backup capacity can only be reduced if countries share their excess generation and backup power.
The transition to a future electricity system based primarily on wind and solar PV is examined for all regions in the contiguous US. We present optimized pathways for the build-up of wind and solar power for least backup energy needs as well as for least cost obtained with a simplified, lightweight model based on long-term high resolution weather-determined generation data. In the absence of storage, the pathway which achieves the best match of generation and load, thus resulting in the least backup energy requirements, generally favors a combination of both technologies, with a wind/solar PV (photovoltaics) energy mix of about 80/20 in a fully renewable scenario. The least cost development is seen to start with 100% of the technology with the lowest average generation costs first, but with increasing renewable installations, economically unfavorable excess generation pushes it toward the minimal backup pathway. Surplus generation and the entailed costs can be reduced significantly by combining wind and solar power, and/or absorbing excess generation, for example with storage or transmission, or by coupling the electricity system to other energy sectors.
Background: In general, the prevalence of work-related musculoskeletal disorders (WMSD) in dentistry is high, and dental assistants (DA) are even more affected than dentists (D). Furthermore, differentiations between the fields of dental specialization (e.g., general dentistry, endodontology, oral and maxillofacial surgery, or orthodontics) are rare. Therefore, this study aims to investigate the ergonomic risk of the aforementioned four fields of dental specialization for D and DA on the one hand, and to compare the ergonomic risk of D and DA within each individual field of dental specialization. Methods: In total, 60 dentists (33 male/27 female) and 60 dental assistants (11 male/49 female) volunteered in this study. The sample was composed of 15 dentists and 15 dental assistants from each of the dental field, in order to represent the fields of dental specialization. In a laboratory setting, all tasks were recorded using an inertial motion capture system. The kinematic data were applied to an automated version of the Rapid Upper Limb Assessment (RULA). Results: The results revealed significantly reduced ergonomic risks in endodontology and orthodontics compared to oral and maxillofacial surgery and general dentistry in DAs, while orthodontics showed a significantly reduced ergonomic risk compared to general dentistry in Ds. Further differences between the fields of dental specialization were found in the right wrist, right lower arm, and left lower arm in DAs and in the neck, right wrist, right lower arm, and left wrist in Ds. The differences between Ds and DAs within a specialist discipline were rather small. Discussion: Independent of whether one works as a D or DA, the percentage of time spent working in higher risk scores is reduced in endodontologists, and especially in orthodontics, compared to general dentists or oral and maxillofacial surgeons. In order to counteract the development of WMSD, early intervention should be made. Consequently, ergonomic training or strength training is recommended.
AttendAffectNet-emotion prediction of movie viewers using multimodal fusion with self-attention
(2021)
In this paper, we tackle the problem of predicting the affective responses of movie viewers, based on the content of the movies. Current studies on this topic focus on video representation learning and fusion techniques to combine the extracted features for predicting affect. Yet, these typically, while ignoring the correlation between multiple modality inputs, ignore the correlation between temporal inputs (i.e., sequential features). To explore these correlations, a neural network architecture—namely AttendAffectNet (AAN)—uses the self-attention mechanism for predicting the emotions of movie viewers from different input modalities. Particularly, visual, audio, and text features are considered for predicting emotions (and expressed in terms of valence and arousal). We analyze three variants of our proposed AAN: Feature AAN, Temporal AAN, and Mixed AAN. The Feature AAN applies the self-attention mechanism in an innovative way on the features extracted from the different modalities (including video, audio, and movie subtitles) of a whole movie to, thereby, capture the relationships between them. The Temporal AAN takes the time domain of the movies and the sequential dependency of affective responses into account. In the Temporal AAN, self-attention is applied on the concatenated (multimodal) feature vectors representing different subsequent movie segments. In the Mixed AAN, we combine the strong points of the Feature AAN and the Temporal AAN, by applying self-attention first on vectors of features obtained from different modalities in each movie segment and then on the feature representations of all subsequent (temporal) movie segments. We extensively trained and validated our proposed AAN on both the MediaEval 2016 dataset for the Emotional Impact of Movies Task and the extended COGNIMUSE dataset. Our experiments demonstrate that audio features play a more influential role than those extracted from video and movie subtitles when predicting the emotions of movie viewers on these datasets. The models that use all visual, audio, and text features simultaneously as their inputs performed better than those using features extracted from each modality separately. In addition, the Feature AAN outperformed other AAN variants on the above-mentioned datasets, highlighting the importance of taking different features as context to one another when fusing them. The Feature AAN also performed better than the baseline models when predicting the valence dimension.
Solar photovoltaics (PV) panels in combination with batteries are often proposed as a solution to provide stable power supply in rural areas. PV generation is mostly dominated by the solar diurnal cycle and has, in some countries, already started to have influence on the daily price distribution on the electricity market.
In this work, we study the performance and optimisation of rural PV-battery hybrid systems in a future renewable Polish power system. We use data on generation potentials to study PV and battery deployment. Together with a power system optimisation and dispatch model for the Polish power system, we study market values when selling at the national market for different CO2 price scenarios. We show that optimal orientations with respect to tilt/azimuth are subject to change as the PV share grows and that the benefit from batteries grows for higher shares of renewables.
High-temperature tolerant enzymes offer multiple advantages over enzymes from mesophilic organisms for the industrial production of sustainable chemicals due to high specific activities and stabilities towards fluctuations in pH, heat, and organic solvents. The production of molecular hydrogen (H2) is of particular interest because of the multiple uses of hydrogen in energy and chemicals applications, and the ability of hydrogenase enzymes to reduce protons to H2 at a cathode. We examined the activity of Hydrogen-Dependent CO2 Reductase (HDCR) from the thermophilic bacterium Thermoanaerobacter kivui when immobilized in a redox polymer, cobaltocene-functionalized polyallylamine (Cc-PAA), on a cathode for enzyme-mediated H2 formation from electricity. The presence of Cc-PAA increased reductive current density 340-fold when used on an electrode with HDCR at 40 °C, reaching unprecedented current densities of up to 3 mA·cm−2 with minimal overpotential and high faradaic efficiency. In contrast to other hydrogenases, T. kivui HDCR showed substantial reversibility of CO-dependent inactivation, revealing an opportunity for usage in gas mixtures containing CO, such as syngas. This study highlights the important potential of combining redox polymers with novel enzymes from thermophiles for enhanced electrosynthesis.
Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time
(2021)
Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based longitudinal discrete choice experiment in combination with a covariate-extended hierarchical Bayes logit estimator that allows one to test the statistical significance of changes. We showcase this method’s use in studies about preferences for electric vehicles over six years and empirically observe that preferences develop in an unpredictable, non-monotonous way. We also find that inspecting only the absolute differences in preferences between samples may result in misleading inferences. Moreover, surveying a new sample produced similar results as asking the same sample of respondents over time. Finally, we experimentally test how adding or removing an attribute affects preferences for the other attributes.
In this paper, we introduce an approach for future frames prediction based on a single input image. Our method is able to generate an entire video sequence based on the information contained in the input frame. We adopt an autoregressive approach in our generation process, i.e., the output from each time step is fed as the input to the next step. Unlike other video prediction methods that use “one shot” generation, our method is able to preserve much more details from the input image, while also capturing the critical pixel-level changes between the frames. We overcome the problem of generation quality degradation by introducing a “complementary mask” module in our architecture, and we show that this allows the model to only focus on the generation of the pixels that need to be changed, and to reuse those that should remain static from its previous frame. We empirically validate our methods against various video prediction models on the UT Dallas Dataset, and show that our approach is able to generate high quality realistic video sequences from one static input image. In addition, we also validate the robustness of our method by testing a pre-trained model on the unseen ADFES facial expression dataset. We also provide qualitative results of our model tested on a human action dataset: The Weizmann Action database.