Institution
University of Geneva
Education•Geneva, Switzerland•
About: University of Geneva is a education organization based out in Geneva, Switzerland. It is known for research contribution in the topics: Population & Planet. The organization has 26887 authors who have published 65265 publications receiving 2931373 citations. The organization is also known as: Geneva University & Universite de Geneve.
Topics: Population, Planet, Galaxy, Exoplanet, Stars
Papers published on a yearly basis
Papers
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TL;DR: The effect of the contamination of facial muscle activities on EEG signals is analyzed and it is found that most of the emotionally valuable content in EEG features are as a result of this contamination, however, the statistical analysis showed that EEG signals still carry complementary information in presence of facial expressions.
Abstract: Emotions are time varying affective phenomena that are elicited as a result of stimuli. Videos and movies in particular are made to elicit emotions in their audiences. Detecting the viewers’ emotions instantaneously can be used to find the emotional traces of videos. In this paper, we present our approach in instantaneously detecting the emotions of video viewers’ emotions from electroencephalogram (EEG) signals and facial expressions. A set of emotion inducing videos were shown to participants while their facial expressions and physiological responses were recorded. The expressed valence (negative to positive emotions) in the videos of participants’ faces were annotated by five annotators. The stimuli videos were also continuously annotated on valence and arousal dimensions. Long-short-term-memory recurrent neural networks (LSTM-RNN) and continuous conditional random fields (CCRF) were utilized in detecting emotions automatically and continuously. We found the results from facial expressions to be superior to the results from EEG signals. We analyzed the effect of the contamination of facial muscle activities on EEG signals and found that most of the emotionally valuable content in EEG features are as a result of this contamination. However, our statistical analysis showed that EEG signals still carry complementary information in presence of facial expressions.
423 citations
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TL;DR: The authors analyzes theoretically and empirically the relationship between trade and war and finds that countries more open to global trade have a higher probability of war because multilateral trade openness decreases bilateral dependence to any given country.
Abstract: This paper analyzes theoretically and empirically the relationship between trade and war. We show that the intuition that trade promotes peace is only partially true even in a model where trade is beneficial to all, war reduces trade and leaders take into account the costs of war. When war can occur because of the presence of asymmetric information, the probability of escalation is indeed lower for countries that trade more bilaterally because of the opportunity cost associated with the loss of trade gains. However, countries more open to global trade have a higher probability of war because multilateral trade openness decreases bilateral dependence to any given country. Using a theoretically-based econometric model, we test our predictions on a large dataset of military conflicts in the period 1948-2001. We find strong evidence for the contrasting effects of bilateral and multilateral trade. Our empirical results also confirm our theoretical prediction that multilateral trade openness increases more the probability of war between proximate countries. This may explain why military conflicts have become more localized and less global over time.
423 citations
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TL;DR: Analysis of speckles along dynamic GFP-CLIP170 stretches suggests that CLIP170 treadmills on growing microtubule ends, rather than being continuously transported toward these ends, according to the structure of a segment of newly polymerized tubulin.
423 citations
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TL;DR: The promoter of the mouse albumin gene contains at least six binding sites for specific DNA-binding proteins (A to F), and both of these competing binding sites are required for maximal in vitro transcription.
423 citations
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TL;DR: Data support the notion that ABI5 acts as the final common repressor of germination in response to changes in ABA and GA levels, and could be recapitulated by the addition of a SnRK2 protein kinase to the A BI5 overexpression line.
Abstract: Seed germination is antagonistically controlled by the phytohormones gibberellic acid (GA) and abscisic acid (ABA). GA promotes seed germination by enhancing the proteasome-mediated destruction of RGL2 (for RGA-LIKE2), a key DELLA factor repressing germination. By contrast, ABA blocks germination by inducing ABI5 (for ABA-INSENSITIVE5), a basic domain/leucine zipper transcription factor repressing germination. Decreased GA synthesis leads to an increase in endogenous ABA levels through a stabilized RGL2, a process that may involve XERICO, a RING-H2 zinc finger factor promoting ABA synthesis. In turn, increased endogenous ABA synthesis is necessary to elevate not only ABI5 RNA and protein levels but also, critically, those of RGL2. Increased ABI5 protein is ultimately responsible for preventing seed germination when GA levels are reduced. However, overexpression of ABI5 was not sufficient to repress germination, as ABI5 activity requires phosphorylation. The endogenous ABI5 phosphorylation and inhibition of germination could be recapitulated by the addition of a SnRK2 protein kinase to the ABI5 overexpression line. In sleepy1 mutant seeds, RGL2 overaccumulates; germination of these seeds can occur under conditions that produce low ABI5 expression. These data support the notion that ABI5 acts as the final common repressor of germination in response to changes in ABA and GA levels.
422 citations
Authors
Showing all 27203 results
Name | H-index | Papers | Citations |
---|---|---|---|
JoAnn E. Manson | 270 | 1819 | 258509 |
Joseph L. Goldstein | 207 | 556 | 149527 |
Kari Stefansson | 206 | 794 | 174819 |
David Baltimore | 203 | 876 | 162955 |
Mark I. McCarthy | 200 | 1028 | 187898 |
Michael S. Brown | 185 | 422 | 123723 |
Yang Gao | 168 | 2047 | 146301 |
Napoleone Ferrara | 167 | 494 | 140647 |
Marc Weber | 167 | 2716 | 153502 |
Alessandro Melchiorri | 151 | 674 | 116384 |
Andrew D. Hamilton | 151 | 1334 | 105439 |
David P. Strachan | 143 | 472 | 105256 |
Andrew Beretvas | 141 | 1985 | 110059 |
Rainer Wallny | 141 | 1661 | 105387 |
Josh Moss | 139 | 1019 | 89255 |