Effects of Gender and Personality on First Impression.

The present study explores whether and to what extent individual differences (i.e., gender and personality traits of perceiver) predict inferences of trustworthiness from emotionally neutral unfamiliar faces and the related confidence in judgment. Four hundred and ten undergraduate students participated in the study. Personality was assessed using the Big Five model (i.e., Extraversion, Neuroticism, Conscientiousness, Agreeableness and Openness to experience) and measures of trait anxiety and aggression. The results suggest that trustworthiness judgments are affected by the gender of the perceiver, although this effect depends on the valence of the face. Women tend to judge trustworthy-looking faces as significantly more trustworthy than men do, and this is particularly pronounced for judgments of female faces. There were no gender differences for judgments of untrustworthy-looking or neutral faces. Gender also seems to affect the confidence in judgment. Specifically, women were generally less confident than men in judging trustworthiness of unfamiliar faces. Personality also affected judgment. Both low agreeable individuals and high trait aggressive individuals tend to perceive unfamiliar faces as less trustworthy. The present findings suggest that both gender and personality traits are relevant for understanding how people evaluate the trustworthiness of others. Whom we decide to trust is a function not only of their facial features but also of gender and individual differences in personality traits

Response of microchannel plates in ionization mode to single particles and electromagnetic showers

Hundreds of concurrent collisions per bunch crossing are expected at future hadron colliders. Precision timing calorimetry has been advocated as a way to mitigate the pileup effects and, thanks to their excellent time resolution, microchannel plates (MCPs) are good candidate detectors for this goal. We report on the response of MCPs, used as secondary emission detectors, to single relativistic particles and to electromagnetic showers. Several prototypes, with different geometries and characteristics, were exposed to particle beams at the INFN-LNF Beam Test Facility and at CERN. Their time resolution and efficiency are measured for single particles and as a function of the multiplicity of particles. Efficiencies between 50% and 90% to single relativistic particles are reached, and up to 100% in presence of a large number of particles. Time resolutions between 20ps and 30ps are obtained.Comment: 20 pages, 9 figures. Paper submitted to NIM

Executive functions in children with specific learning disorders: Shedding light on a complex profile through teleassessment

Executive Functions (EFs) are high-order cognitive processes relevant to learning and adaptation and frequently impaired in children with specific learning disorders (SLDs). This study aimed to investigate EFs in children with SLD and explore the role of specific EF-related subprocesses, such as stimuli processing and processing speed. Fifty-seven SLD and 114 typically developing (TD) children, matched for gender and age, completed four tasks measuring response inhibition, interference control, shifting, and updating on a web-based teleassessment platform. The results show that SLD children performed lower in all EF tasks than TD children, regardless of stimulus type and condition. Mediation analyses suggested that differences between the SLD and TD groups are mediated by EF-related subprocesses, offering an interpretative model of EF deficits in children with SLD

Plastic Representation of the Reachable Space for a Humanoid Robot

Reaching a target object requires accurate estimation of the object spatial position and its further transformation into a suitable arm-motor command. In this paper, we propose a framework that provides a robot with a capacity to represent its reachable space in an adaptive way. The location of the target is represented implicitly by both the gaze direction and the angles of arm joints. Two paired neural networks are used to compute the direct and inverse transformations between the arm position and the head position. These networks allow reaching the target either through a ballistic movement or through visually-guided actions. Thanks to the latter skill, the robot can adapt its sensorimotor transformations so as to reflect changes in its body configuration. The proposed framework was implemented on the NAO humanoid robot, and our experimental results provide evidences for its adaptative capabilities

Improving physics‐based aftershock forecasts during the 2016–2017 Central Italy earthquake cascade

The 2016–2017 Central Apennines earthquake sequence is a recent example of how damages from subsequent aftershocks can exceed those caused by the initial mainshock. Recent studies reveal that physics‐based aftershock forecasts present comparable skills to their statistical counterparts, but their performance remains a controversial subject. Here we employ physics‐based models that combine the elasto‐static stress transfer with rate‐and‐state friction laws, and short‐term statistical Epidemic Type Aftershock Sequence (ETAS) models to describe the spatiotemporal evolution of the earthquake cascade. We then track the absolute and relative model performance using log‐likelihood statistics for a 1‐year horizon after the 24 August 2016 Mw = 6.0 Amatrice earthquake. We perform a series of pseudoprospective experiments by producing seven classes of Coulomb rate‐state (CRS) forecasts with gradual increase in data input quality and model complexity. Our goal is to investigate the influence of data quality on the predictive power of physics‐based models and to assess the comparative performance of the forecasts in critical time windows, such as the period following the 26 October Visso earthquakes leading to the 30 October Mw = 6.5 Norcia mainshock. We find that (1) the spatiotemporal performance of the basic CRS models is poor and progressively improves as more refined data are used, (2) CRS forecasts are about as informative as ETAS when secondary triggering effects from M3+ earthquakes are included together with spatially variable slip models, spatially heterogeneous receiver faults, and optimized rate‐and‐state parameters. After the Visso earthquakes, the more elaborate CRS model outperforms ETAS highlighting the importance of the static stress transfer for operational earthquake forecasting

Contrasting deficits on executive functions between ADHD and reading disabled children

BACKGROUND. The object of this study was to analyze the executive functioning of children with attention deficit hyperactivity disorder (ADHD) or reading disability (RD) independent of their non-executive deficits. METHODS: Three carefully diagnosed groups of children, aged between 7 and 12 years (35 ADHD, 22 RD and 30 typically developing children), were tested on a wide range of tasks related to five major domains of executive functioning (EF): inhibition, visual working memory, planning, cognitive flexibility, and verbal fluency. Additional tasks were selected for each domain to control for non-executive processing. RESULTS: ADHD children were impaired on interference control, but not on prepotent and ongoing response suppression. ADHD showed deficits on visual working memory, planning, cognitive flexibility and phonetic fluency. RD children were impaired on phonetic fluency. The only EF measure that differentiated ADHD from RD was planning. CONCLUSIONS: The present sample of ADHD children showed several EF deficits, whereas RD children were almost spared executive dysfunction, but exhibited deficits in phonetic fluency

Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features

The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients’ clinical outcome. Patient’s prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition high- from low-risk patients, preventing the reliable recognition of early relapsing/refractory patients. By a dimensionality reduction approach, here we dissect the genomic landscape of a large cohort of newly diagnosed MM patients, modelling all the possible interactions between any MM chromosomal alterations. We highlight the presence of a distinguished cluster of patients in the low-dimensionality space, with unfavorable clinical behavior, whose biology was driven by the co-occurrence of chromosomes 1q CN gain and 13 CN loss. Presence or absence of these alterations define MM patients overexpressing either CCND2 or CCND1, fostering the implementation of biology-based patients’ classification models to describe the different MM clinical behaviors