A Comparison of Three Different NeuroTag Visualization Media: Brain Visual Stimuli by Monitor, Augmented and Virtual Reality Devices

Brain-Computer Interfaces (BCIs) proved to overcome some limitations of other input modes (e.g., gestures, voice, haptic, etc.). BCIs are able to detect the brain activity, thus identifying searched patterns. When a specific brain activity is recognized, a well-defined action can be triggered, thus implementing a human-machine interaction paradigm. BCIs can be used in different domains ranging from industry to services for impaired people. This paper considers BCIs that can be designed and developed by the NextMind, which is a small and ergonomics device to capture the activity of the visual cortex. Objects called NeuroTags can be inserted in both 2D and 3D scenes; these objects act like switches when the user is able to focus on them. The aim of this work is to evaluate different NeuroTag configurations (varying in terms of size and distance) as well as different visualization devices: a monitor, a virtual reality head-mounted display, and an augmented reality head-mounted display. User tests outline that the best tradeoff between robustness and selection speed is obtained by medium-size and medium-spaced NeuroTags; on the other hand, monitor visualization outperforms the AR solution, whereas it is not possible to identify statistically significant differences between monitor-VR and AR-VR

On Old Age and Its Multiplicity: Exploring Discourses and Materialities about Getting Older

Old age is at the core of complex constellations composed by media discourses, care and mundane activities, and affective and technological practices that involve a wide range of human and non-human actors. While during the last years concepts such as “active” and “successful” ageing have more and more emphasised the individual responsibility of older adults in managing their own health, in the context of the Covid-19 pandemic elderly have been increasingly framed as vulnerable subjects. This Crossing Boundaries will explore the different instances assumed by the “old age” as an emerging object by the enactment of discourses and materialities. In doing so, this Crossing Boundaries mobilizes different theoretical perspectives, such as STS, media studies and sociology of health. The authors will explore three main issues: 1) the public discourse about the health status of older people; 2) the collective management of Alzheimer’s disease in and outside institutions; 3) the involvement of older adults in designing information and communication technologies

Chiral sulfoxides in the enantioselective allylation of aldehydes with allyltrichlorosilane: a kinetic study

The mechanism of the allylation of aldehydes in the presence of allyltrichlorosilane employing the commercially available (R)-methyl p-tolyl sulfoxide as a Lewis base has been investigated. The combination of kinetic measurements, conductivity analysis and quantum chemical calculations indicates that the reaction proceeds through a dissociative pathway in which an octahedral cationic complex with two sulfoxides is involved. The lack of turnover is ascribed to the formation of neutral sulfurane derivatives

A new dissimilarity measure for clustering seismic signals

Hypocenter and focal mechanism of an earthquake can be determined by the analysis of signals, named waveforms, related to the wave field produced and recorded by a seismic network. Assuming that waveform similarity implies the similarity of focal parameters, the analysis of those signals characterized by very similar shapes can be used to give important details about the physical phenomena which have generated an earthquake. Recent works have shown the effectiveness of cross-correlation and/or cross-spectral dissimilarities to identify clusters of seismic events. In this work we propose a new dissimilarity measure between seismic signals whose reliability has been tested on real seismic data by computing external and internal validation indices on the obtained clustering. Results show its superior quality in terms of cluster homogeneity and computational time with respect to the largely adopted cross correlation dissimilarity

What These Findings Tell Us. Reply to Kelly et al. What Do These Findings Tell Us? Comment on “Tinella et al. Cognitive Efficiency and Fitness-to-Drive along the Lifespan: The Mediation Effect of Visuospatial Transformations. Brain Sci. 2021, 11, 1028”

The study of the contribution of spatial transformation skills to driving behavior is a research topic substantiated by scarce evidence. In previous studies, we found that mental rotation and perspective-taking skills have an influence on performance in driving tasks by conveying the distal effects of the general cognitive efficiency on the execution of driving maneuvers. Studies have provided evidence on the relevance of the cognitive processes of encoding, imagined rotation, and spatial orientation in the accuracy of both the vehicle management during stressful driving situations and the acquisition of visual information on the traffic scenario. Results can find applications in both the training and the assessment of fitness to drive, as well as in the study of interaction between the drivers and in-vehicle devices. The lack of cross-validations in path analysis models cannot be assumed, a priori, to be capitalizing on chance and as an example of bad science. The non-replicability of a study should be demonstrated before it is proclaimed. The purpose of this reply was to address the questions raised by Kelly et al. (2022)—that is, “Do these results seem replicable?” and “How do these results advance our understanding of brain function and/or human behavior?”—by providing additional information on the study in question

ValenTo: Sentiment Analysis of Figurative Language Tweets with Irony and Sarcasm

This paper describes the system used by the ValenTo team in the Task 11, Sentiment Analysis of Figurative Language in Twitter, at SemEval 2015. Our system used a regression model and additional external resources to assign polarity values. A distinctive feature of our approach is that we used not only word-sentiment lexicons providing polarity annotations, but also novel resources for dealing with emotions and psycholinguistic information. These are important aspects to tackle in figurative language such as irony and sarcasm, which were represented in the dataset. The system also exploited novel and standard structural features of tweets. Considering the different kinds of figurative language in the dataset our submission obtained good results in recognizing sentiment polarity in both ironic and sarcastic tweets