Specific Effects of Spatial-frequency Uncertainty and Different Cue Types on Contrast Detection: Data and Models**Parts of this research were presented at the 17th ECVP (European Conference on Visual Perception) held 1994 at Eindhoven, The Netherlands.

AbstractIf the spatial-frequency of sinusoidal signals in a contrast-detection experiment varies randomly from trial to trial, then performance is decreased compared with that in a situation where it remains constant. This spatial-frequency uncertainty effect can more or less be compensated by presenting informative cues shortly before each trial. Single-band, as well as multiple-band models, have been proposed to explain the uncertainty and cuing effects. While the latter assume that under uncertainty multiple channels are monitored simultaneously, the former propose that in each trial a single, but sometimes inappropriate, channel is selected for monitoring. Until now it is open which of these models is valid. Therefore, psychometric functions were collected under different conditions of spatial-frequency uncertainty. It appears that the size of the uncertainty effect varies with spatial-frequency. This result can be explained by a multiple-band model, as computational analysis reveals. Copyright © 1996 Elsevier Science Ltd

Effects of Stimulus Type and Level Repetition on Content-Level Binding in Global/Local Processing

The processing and representation of hierarchical objects not only involves the identification of information at the different levels, but also the binding of the identified content to its respective level. Whereas identification is well understood, little is known about content-level binding (CLB). In a recent study, however, it has been shown that attentional priming of certain spatial frequencies is advantageous for this binding. Therefore, the present study investigated effects of related factors on the binding process, namely stimulus type (filled or outlined hierarchical letters), stimulus-type repetition, and target-level repetition. The results show that CLB was improved for outlined stimuli and after target-level repetition, whereas stimulus-type repetition had no effect. The data suggest that hierarchical stimuli are mentally represented by abstract level categories and that content is linked to these categories by means of level-specific and identity-specific spatial-frequency information

On attentional control as a source of residual shift costs: Evidence from two-component task shifts.

It is widely assumed that supervisory or attentional control plays a role only in the preparatory reconfiguration of the mental system in task shifting. The well-known fact that residual shift costs are still present even after extensive preparation is usually attributed to passive mechanisms such as cross talk. The authors question this view and suggest that attentional control is also responsible for residual shift costs. The authors hypothesize that, under shift conditions, tasks are executed in a controlled mode to guarantee reliable performance. Consequently, the control of 2 task components should require more resources than the control of only 1. A series of 4 experiments with 2-component tasks was conducted to test this hypothesis. As expected, more residual shift costs were observed when 2 components rather than 1 varied across trials. Interference effects and sequential effects could not account for these results

Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature

“3,058 people like this.” In the digital age, people very commonly indicate their preferences by clicking a Like button. The data generated on the photo-sharing platform Instagram potentially represents a vast, freely accessible resource for research in the field of visual experimental aesthetics. Therefore, we compiled a photo database using images of five different Instagram accounts that fullfil several criteria (e.g., large followership, consistent content). The final database consists of about 700 architectural photographs with the corresponding liking data generated by the Instagram community. First, we aimed at validating Instagram Likes as a potential measure of aesthetic appeal. Second, we checked whether previously studied low-level features of “good” image composition also account for the number of Instagram Likes that architectural photographs received. We considered two measures of visual balance and the preference for curvature over angularity. In addition, differences between images with “2D” vs. “3D” appearance became obvious. Our findings show that visual balance predicts Instagram Likes in more complex “3D” photographs, with more balance meaning more Likes. In the less complex “2D” photographs the relation is reversed, more balance led to fewer Likes. Moreover, there was a general preference for curvature in the Instagram database. Together, our study illustrates the potential of using Instagram Likes as a measure of aesthetic appeal and provides a fruitful methodological basis for future research

Privacy for Peer Profiling in Collective Adaptive Systems

Part 5: Project Workshops and Tutorial PapersInternational audienceIn this paper, we introduce a privacy-enhanced Peer Manager, which is a fundamental building block for the implementation of a privacy-preserving collective adaptive systems computing platform. The Peer Manager is a user-centered identity management platform that keeps information owned by a user private and is built upon an attribute-based privacy policy. Furthermore, this paper explores the ethical, privacy and social values aspects of collective adaptive systems and their extensive capacity to transform lives. We discuss the privacy, social and ethical issues around profiles and present their legal privacy requirements from the European legislation perspective

Increased risk of severe clinical course of COVID-19 in carriers of HLA-C*04:01

Background: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing urgency to identify pathophysiological characteristics leading to severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors that affect individual immune response to SARS-CoV-2. We sought to evaluate this hypothesis by conducting a multicenter study using HLA sequencing. Methods: We analyzed the association between COVID-19 severity and HLAs in 435 individuals from Germany (n = 135), Spain (n = 133), Switzerland (n = 20) and the United States (n = 147), who had been enrolled from March 2020 to August 2020. This study included patients older than 18 years, diagnosed with COVID19 and representing the full spectrum of the disease. Finally, we tested our results by meta-analysing data from prior genome-wide association studies (GWAS). Findings: We describe a potential association of HLA-C*04:01 with severe clinical course of COVID-19. Carriers of HLA-C*04:01 had twice the risk of intubation when infected with SARS-CoV-2 (risk ratio 1.5 [95% CI 1.1-2.1], odds ratio 3.5 [95% CI 1.9-6.6], adjusted p-value = 0.0074). These findings are based on data from four countries and corroborated by independent results from GWAS. Our findings are biologically plausible, as HLA-C*04:01 has fewer predicted bindings sites for relevant SARS-CoV-2 peptides compared to other HLA alleles. Interpretation: HLA-C*04:01 carrier state is associated with severe clinical course in SARS-CoV-2. Our findings suggest that HLA class I alleles have a relevant role in immune defense against SARS-CoV-2. Funding: Funded by Roche Sequencing Solutions, Inc