440 research outputs found
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The effect of facial feedback on the evaluation of statements describing everyday situations and the role of awareness
According to theories of embodiment enacting a smile or a frown can positively or negatively influence one’s evaluations, even without awareness of one’s facial activity. While some previous studies found evidence for facial feedback effects, recent replication attempts could not confirm these findings. Are our decisions throughout the day amenable to the state of our facial muscles? We tested the effect of smiling and frowning on the evaluation of emotional sentences describing everyday situations. While most previous studies based their assessment of awareness on verbal debriefing interviews without explicitly defined criteria, we employed a written debriefing questionnaire in order to avoid potential bias when identifying participants’ awareness. Our results indicate that smiling/frowning increased/decreased sentence ratings only for participants aware of their expressions. This emphasizes the importance of more rigorous awareness tests in facial feedback studies. Our results support the view that facial feedback cannot necessarily influence us without conscious mediation
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Embodiment in affective evaluations: the case of the facial feedback effect
Theories of embodiment propose that our bodily states can influence affective processing. This thesis investigated the possibility that facial feedback (i.e., afferent signals from facial muscles) can influence the interpretation of affective stimuli. One study tested the effect of overt smiling and frowning on the interpretation of short descriptions of everyday events. Smiling, as compared to frowning, led to more positive evaluations, but only for participants who were aware of the emotional relevance of their expressions. A second study tested whether subtle changes in facial activation (elicited by unconsciously presented happy/angry facial expressions) led to changes in evaluations of ambiguous target symbols. While angry prime faces, as compared to happy prime faces, induced more frowning (as measured via electromyography), this change in facial activation did not translate into a behavioural effect on subsequent evaluations. A third study investigated the relation between naturally occurring facial reactions and interpretations of both clearly valenced and ambiguous facial expressions. Results indicate that facial reactivity predicts participants’ self-reports of their own emotional reactions towards others’ expressions (Experiment 1). A relation between facial reactions and interpretations of the expression senders’ emotional states was only found in cases in which participants with high sensitivity towards their own bodily states (as measured with a test of interoceptive accuracy) tried to interpret ambiguous expressions (Experiment 2). In a last experiment, prolonged presentation of emotional prime faces led to expression-congruent facial reactions, but resulted in expression-incongruent behavioural reactions in both classification speed and interpretative tendency of emotional target faces. Overall, this thesis suggests that facial feedback is not generally involved in the interpretation of affective stimuli, but that it might contribute to evaluative processes only under special circumstances
Multisensory Integration of Anticipated Cardiac Signals with Visual Targets Affects Their Detection among Multiple Visual Stimuli
Many studies have elucidated the multisensory processing of different exteroceptive signals (e.g., auditory-visual stimuli), but less is known about the multisensory integration of interoceptive signals with exteroceptive information. Here, we investigated the perceptual outcomes and electrophysiological brain mechanisms of cardio-visual integration by using participants’ electrocardiogram signals to control the color change of a visual target in dynamically changing displays. Reaction times increased when the target change coincided with strong cardiac signals
concerning the state of cardiovascular arousal (i.e., presented at the end of ventricular systole), compared to when the target change occurred at a time when cardiac arousal was relatively low (i.e., presented at the end of ventricular diastole). Moreover, the concurrence of the target change
and cardiac arousal signals modulated the event-related potentials and the beta power in an early period (~100 ms after stimulus onset), and decreased the N2pc and the beta lateralization in a later period (~200 ms after stimulus onset). Our results suggest that the multisensory integration of anticipated cardiac signals with a visual target negatively affects its detection among multiple visual stimuli, potentially by suppressing sensory processing and reducing attention toward the
visual target. This finding highlights the role of cardiac information in visual processing and furthers our understanding of the brain dynamics underlying multisensory perception involving both interoception and exteroception
Attention Is All You Need
The dominant sequence transduction models are based on complex recurrent or
convolutional neural networks in an encoder-decoder configuration. The best
performing models also connect the encoder and decoder through an attention
mechanism. We propose a new simple network architecture, the Transformer, based
solely on attention mechanisms, dispensing with recurrence and convolutions
entirely. Experiments on two machine translation tasks show these models to be
superior in quality while being more parallelizable and requiring significantly
less time to train. Our model achieves 28.4 BLEU on the WMT 2014
English-to-German translation task, improving over the existing best results,
including ensembles by over 2 BLEU. On the WMT 2014 English-to-French
translation task, our model establishes a new single-model state-of-the-art
BLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction
of the training costs of the best models from the literature. We show that the
Transformer generalizes well to other tasks by applying it successfully to
English constituency parsing both with large and limited training data.Comment: 15 pages, 5 figure
Simulation-based Inference for Model Parameterization on Analog Neuromorphic Hardware
The BrainScaleS-2 (BSS-2) system implements physical models of neurons as
well as synapses and aims for an energy-efficient and fast emulation of
biological neurons. When replicating neuroscientific experiment results, a
major challenge is finding suitable model parameters. This study investigates
the suitability of the sequential neural posterior estimation (SNPE) algorithm
for parameterizing a multi-compartmental neuron model emulated on the BSS-2
analog neuromorphic hardware system. In contrast to other optimization methods
such as genetic algorithms or stochastic searches, the SNPE algorithms belongs
to the class of approximate Bayesian computing (ABC) methods and estimates the
posterior distribution of the model parameters; access to the posterior allows
classifying the confidence in parameter estimations and unveiling correlation
between model parameters. In previous applications, the SNPE algorithm showed a
higher computational efficiency than traditional ABC methods. For our
multi-compartmental model, we show that the approximated posterior is in
agreement with experimental observations and that the identified correlation
between parameters is in agreement with theoretical expectations. Furthermore,
we show that the algorithm can deal with high-dimensional observations and
parameter spaces. These results suggest that the SNPE algorithm is a promising
approach for automating the parameterization of complex models, especially when
dealing with characteristic properties of analog neuromorphic substrates, such
as trial-to-trial variations or limited parameter ranges
Die Entstehung und Entwicklung devianten und delinquenten Verhaltens im Lebensverlauf und ihre Bedeutung fĂĽr soziale Ungleichheitsprozesse: Fragebogendokumentation der SchĂĽlerbefragung in Dortmund und NĂĽrnberg. Band 1: Itemdokumentation. Erste Erhebungswelle, 2012.
Meinert J, Kaiser F, Guzy J. Die Entstehung und Entwicklung devianten und delinquenten Verhaltens im Lebensverlauf und ihre Bedeutung fĂĽr soziale Ungleichheitsprozesse: Fragebogendokumentation der SchĂĽlerbefragung in Dortmund und NĂĽrnberg. Band 1: Itemdokumentation. Erste Erhebungswelle, 2012. SFB 882 Technical Report Series. Vol 7. Bielefeld: DFG Research Center (SFB) 882 From Heterogeneities to Inequalities; 2014
Social acceptance of green hydrogen in Germany: building trust through responsible innovation
Background
Social acceptance presents a major challenge for Germany’s transition to green energy. As a power-to-x technology, green hydrogen is set to become a key component of a future sustainable energy system. With a view to averting conflicts like those surrounding wind energy, we have investigated social acceptance of green hydrogen at an early stage in its implementation, before wider rollout. Our study uses a mixed-method approach, wherein semi-structured interviews (n = 24) and two participatory workshops (n = 51) in a selected region in central Germany serve alongside a representative survey (n = 2054) as the basis for both understanding social attitudes and reaching generalisable conclusions.
Results
Overall, it is possible to observe both a marked lack of knowledge and a large degree of openness towards green hydrogen and its local use, along with high expectations regarding environmental and climate protection. We reach three key conclusions. First, acceptance of green hydrogen relies on trust in science, government, the media, and institutions that uphold distributive justice, with consideration for regional values playing a vital role in establishing said trust. Second, methodologically sound participatory processes can promote acceptance, and active support in particular. Third, recurrent positive participatory experiences can effectively foster trust.
Conclusions
Accordingly, we argue that trust should be strengthened on a structural level, and that green hydrogen acceptance should be understood as a matter of responsible innovation. As the first empirical investigation into social acceptance of green hydrogen, and by conceptually interlinking acceptance research and responsible innovation, this study constitutes an important contribution to existing research
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