Tridimensional reconstruction of cerebral volumetry in schizophrenia

Address: 1Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, Italy, 2Verona-Udine Brain Imaging Program, Inter-University Center for Behavioural Neurosciences, University of Udine and *University of Verona, Italy, 3Department of Morphological and Biomedical Sciences, Section of Radiology, University of Verona, Italy and 4Department of Pathology and Experimental and Clinical Medicine, Section of Psychiatry, University of Udine, Italy * Corresponding autho

MicroRNA expression is associated with auditory dysfunction in workers exposed to ototoxic solvents and noise

This study is part of a project on early hearing dysfunction induced by combined exposure to volatile organic compounds (VOCs) and noise in occupational settings. In a previous study, 56 microRNAs were found differentially expressed in exposed workers compared to controls. Here, we analyze the statistical association of microRNA expression with audiometric hearing level (HL) and distortion product otoacoustic emission (DPOAE) level in that subset of differentially expressed microRNAs. The highest negative correlations were found; for HL, with miR-195-5p and miR-122-5p, and, for DPOAEs, with miR-92b-5p and miR-206. The homozygous (mut) and heterozygous (het) variants of the gene hOGG1 were found disadvantaged with respect to the wild-type (wt), as regards the risk of hearing impairment due to exposure to VOCs. An unsupervised artificial neural network (auto contractive map) was also used to detect and show, using graph analysis, the hidden connections between the explored variables. These findings may contribute to the formulation of mechanistic hypotheses about hearing damage due to co-exposure to noise and ototoxic solvents

Attenuation of peak sound pressure levels of shooting noise by hearing protective earmuffs

Transmission losses (TL) to highly impulsive signals generated by three firearms have been measured for two ear muffs, using both a head and torso simulator and a miniature microphone located at the ear canal entrance (MIRE technique). Peak SPL TL have been found to be well approximated by 40 ms short-L eq TL. This has allowed the use of transmissibilities and correction factors for bone conduction and physiological masking appropriate for continuous noise, for the calculation of REAT-type peak insertion losses (IL). Results indicate that peak IL can be well predicted by estimates based on one-third octave band 40 ms short L eq and manufacturer-declared (nominal) IL measured for continuous noise according to test standards. Such predictions tend to be more accurate at the high end of the range, while they are less reliable when the attenuation is lower. A user-friendly simplified prediction algorithm has also been developed, which only requires nominal IL and one-third octave sound exposure level spectra. Separate predictions are possible for IL in direct and diffuse sound fields, albeit with higher uncertainties, due to the smaller number of experimental data comprising the two separate datasets on which such predictions are based

Remotizing and Virtualizing Chips and Circuits for Hardware-based Capture-the-Flag Challenges

In the very rapid digital revolution we are experiencing, the availability of cybersecurity experts becomes critical in every organization and at multiple levels. However, classical and theory-oriented training seems to lack effectiveness and power of attraction, while professional selection and training processes based on cybersecurity gamification are being successfully experimented, among which Capture-the-Flag (CTF) competitions certainly stand out. Nevertheless, careful analysis reveals that such initiatives have a major shortcoming in addressing security issues when training people to tackle hardware-related security issues. Several motivations can be identified, including the inadequate technical knowledge of the White Teams charged of the challenges preparations, and the evident logistic problems posed by the availability of real hardware devices when the numbers of trainees significantly scales up. This paper presents a platform able to provide as a service hardware-based CTF challenges and exercises, involving circuits and chips that can be physically connected to a server or simulated, to deal with topics such as hardware bugs, flaws and backdoors, vulnerabilities in test infrastructures, and side-channel attacks. The platform is presented from a technical perspective, and data for deducting related efficiency, stability and scalability are offered

Chimica metallorganici a basso impatto ambientale: Sintesi e Coordinazione di leganti Ciclopentadienilici plurifunzionalizzati

none4[RIASSUNTO (ABSTRACT)]noneS. BORDONI; L. BUSETTO; S. CERINI; P. NATANTIS., Bordoni; L., Busetto; S., Cerini; Natanti, Paol

A howling success or a working sea? Testing what BERT knows about metaphors

Metaphor is a widespread linguistic and cognitive phenomenon that is ruled by mechanisms which have received attention in the literature. Transformer Language Models such as BERT have brought improvements in metaphor-related tasks. However, they have been used only in application contexts, while their knowledge of the phenomenon has not been analyzed. To test what BERT knows about metaphors, we challenge it on a new dataset that we designed to test various aspects of this phenomenon such as variations in linguistic structure, variations in conventionality, the boundaries of the plausibility of a metaphor and the interpretations that we attribute to metaphoric expressions. Results bring out some tendencies that suggest that the model can reproduce some human intuitions about metaphors

A howling success or a working sea? Testing what BERT knows about metaphors

Metaphor is a widespread linguistic and cognitive phenomenon that is ruled by mechanisms which have received attention in the literature. Transformer Language Models such as BERT have brought improvements in metaphor-related tasks. However, they have been used only in application contexts, while their knowledge of the phenomenon has not been analyzed. To test what BERT knows about metaphors, we challenge it on a new dataset that we designed to test various aspects of this phenomenon such as variations in linguistic structure, variations in conventionality, the boundaries of the plausibility of a metaphor and the interpretations that we attribute to metaphoric expressions. Results bring out some tendencies that suggest that the model can reproduce some human intuitions about metaphors