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'THIS ISN'T ME!': the role of age-related self- and user images for robot acceptance by elders
(2020)
Although companion-type robots are already commercially available, little interest has been taken in identifying reasons for inter-individual differences in their acceptance. Elders’ age-related perceptions of both their own self (self-image) and of the general older robot user (user image) could play a relevant role in this context. Since little is known to date about elders’ companion-type robot user image, it is one aim of this study to investigate its age-related facets, concentrating on possibly stigmatizing perceptions of elder robot users. The study also addresses the association between elders’ age-related self-image and robot acceptance: Is the association independent of the user image or not? To investigate these research questions, N = 28 adults aged 63 years and older were introduced to the companion-type robot Pleo. Afterwards, several markers of robot acceptance were assessed. Actual and ideal self- and subjective robot user image were assessed by a study-specific semantic differential on the stereotype dimensions of warmth and competence. Results show that participants tended to stigmatize elder robot users. The self-images were not directly related to robot acceptance, but affected it in the context of the user image. A higher fit between self- and user image was associated with higher perceived usefulness, social acceptance, and intention to use the robot. To conclude, elders’ subjective interpretations of new technologies play a relevant role for their acceptance. Together with elders’ individual self-images, they need to be considered in both robot development and implementation. Future research should consider that associations between user characteristics and robot acceptance by elders can be complex and easily overlooked.
Organ-on-a-chip technology has the potential to accelerate pharmaceutical drug development, improve the clinical translation of basic research, and provide personalized intervention strategies. In the last decade, big pharma has engaged in many academic research cooperations to develop organ-on-a-chip systems for future drug discoveries. Although most organ-on-a-chip systems present proof-of-concept studies, miniaturized organ systems still need to demonstrate translational relevance and predictive power in clinical and pharmaceutical settings. This review explores whether microfluidic technology succeeded in paving the way for developing physiologically relevant human in vitro models for pharmacology and toxicology in biomedical research within the last decade. Individual organ-on-a-chip systems are discussed, focusing on relevant applications and highlighting their ability to tackle current challenges in pharmacological research.
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.
This paper explores the many interesting implications for oscillator design, with optimized phase-noise performance, deriving from a newly proposed model based on the concept of oscillator conjugacy. For the case of 2-D (planar) oscillators, the model prominently predicts that only circuits producing a perfectly symmetric steady-state can have zero amplitude-to-phase (AM-PM) noise conversion, a so-called zero-state. Simulations on standard industry oscillator circuits verify all model predictions and, however, also show that these circuit classes cannot attain zero-states except in special limit-cases which are not practically relevant. Guided by the newly acquired design rules, we describe the synthesis of a novel 2-D reduced-order LC oscillator circuit which achieves several zero-states while operating at realistic output power levels. The potential future application of this developed theoretical framework for implementation of numerical algorithms aimed at optimizing oscillator phase-noise performance is briefly discussed.
Nano-granular metals are materials that fall into the general class of granular electronic systems in which the interplay of electronic correlations, disorder and finite size effects can be studied. The charge transport in nano-granular metals is dominated by thermally-assisted, sequential and correlated tunneling over a temperature-dependent number of metallic grains. Here we study the frequency-dependent conductivity (AC conductivity) of nano-granular Platinum with Pt nano-grains embedded into amorphous carbon (C). We focus on the transport regime on the insulating side of the insulator metal transition reflected by a set of samples covering a range of tunnel-coupling strengths. In this transport regime polarization contributions to the AC conductivity are small and correlation effects in the transport of free charges are expected to be particularly pronounced. We find a universal behavior in the frequency dependence that can be traced back to the temperature-dependent zero-frequency conductivity (DC conductivity) of Pt/C within a simple lumped-circuit analysis. Our results are in contradistinction to previous work on nano-granular Pd/ZrO2ZrO2 in the very weak coupling regime where polarization contributions to the AC conductivity dominated. We describe possible future applications of nano-granular metals in proximity impedance spectroscopy of dielectric materials.
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.
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.
Consequences of minimal length discretization on line element, metric tensor, and geodesic equation
(2021)
When minimal length uncertainty emerging from a generalized uncertainty principle (GUP) is thoughtfully implemented, it is of great interest to consider its impacts on gravitational Einstein field equations (gEFEs) and to try to assess consequential modifications in metric manifesting properties of quantum geometry due to quantum gravity. GUP takes into account the gravitational impacts on the noncommutation relations of length (distance) and momentum operators or time and energy operators and so on. On the other hand, gEFE relates classical geometry or general relativity gravity to the energy–momentum tensors, that is, proposing quantum equations of state. Despite the technical difficulties, we intend to insert GUP into the metric tensor so that the line element and the geodesic equation in flat and curved space are accordingly modified. The latter apparently encompasses acceleration, jerk, and snap (jounce) of a particle in the quasi-quantized gravitational field. Finite higher orders of acceleration apparently manifest phenomena such as accelerating expansion and transitions between different radii of curvature and so on.
Variable renewable energy sources (VRES), such as solarphotovoltaic (PV) and wind turbines (WT), are starting to play a significant role in several energy systems around the globe. To overcome the problem of their non-dispatchable and stochastic nature, several approaches have been proposed so far. This paper describes a novel mathematical model for scheduling the operation of a wind-powered pumped-storage hydroelectricity (PSH) hybrid for 25 to 48 h ahead. The model is based on mathematical programming and wind speed forecasts for the next 1 to 24 h, along with predicted upper reservoir occupancy for the 24th hour ahead. The results indicate that by coupling a 2-MW conventional wind turbine with a PSH of energy storing capacity equal to 54 MWh it is possible to significantly reduce the intraday energy generation coefficient of variation from 31% for pure wind turbine to 1.15% for a wind-powered PSH The scheduling errors calculated based on mean absolute percentage error (MAPE) are significantly smaller for such a coupling than those seen for wind generation forecasts, at 2.39% and 27%, respectively. This is even stronger emphasized by the fact that, those for wind generation were calculated for forecasts made for the next 1 to 24 h, while those for scheduled generation were calculated for forecasts made for the next 25 to 48 h. The results clearly show that the proposed scheduling approach ensures the high reliability of the WT–PSH energy source
Surface plasmon polaritons on (silver) nanowires are promising components for future photonic technologies. Here, we study near-field patterns on silver nanowires with a scattering-type scanning near-field optical microscope that enables the direct mapping of surface waves. We analyze the spatial pattern of the plasmon signatures for different excitation geometries and polarization and observe a plasmon wave pattern that is canted relative to the nanowire axis, which we show is due to a superposition of two different plasmon modes, as supported by electromagnetic simulations including the influence of the substrate. These findings yield new insights into the excitation and propagation of plasmon polaritons for applications in nanoplasmonic devices.