Italian adaptation of the Multilingual Assessment Instrument for Narratives.

This paper presents the Italian version of the Multilingual Assessment tool for Narratives (MAIN), describes how it was developed and reports on some recent uses of MAIN within the Italian context. The Italian MAIN has been used in different research projects and for clinical purposes; results have been presented at conferences and in peer reviewed papers. The results indicate that MAIN is an appropriate assessment tool for evaluating children’s narrative competence, in production and comprehension from preschool age (5 years) to school age (8 years) in typical language development, bilingual development and language delay/disorders

RHIP, a Radio-controlled High-Voltage Insulated Picoammeter and its usage in studying ion backflow in MPGD-based photon detectors

A picoammeter system has been developed and engineering. It consists in a current-voltage converter, based on an operational amplifier with very low input current, a high precision ADC, a radio controlled data acquisition unit and the computer-based control, visualization and storage. The precision is of the order of a tenth of picoampers and it can measure currents between electrodes at potentials up to 8 kV. The system is battery powered and a number of strategies have been implemented to limit the power consumption. The system is designed for multichannel applications, up to 256 parallel channels. The overall implementation is cost-effective to make the availability of multichannel setups easily affordable. The design, implementation and performance of the picoammeter system are described in detail as well as a an application: the measurement of ion backflow in MPGD-based photon detectors.Comment: 5th International Conference on Micro-Pattern Gas Detectors (MPGD2017), presentation by Silvia Dalla Torr

Study of MicroPattern Gaseous detectors with novel nanodiamond based photocathodes for single photon detection in EIC RICH

Identification of high momentum hadrons at the future EIC is crucial, gaseous RICH detectors are therefore viable option. Compact collider setups impose to construct RICHes with small radiator length, hence significantly limiting the number of detected photons. More photons can be detected in the far UV region, using a windowless RICH approach. QE of CsI degrades under strong irradiation and air contamination. Nanodiamond based photocathodes (PCs) are being developed as an alternative to CsI. Recent development of layers of hydrogenated nanodiamond powders as an alternative photosensitive material and their performance, when coupled to the THick Gaseous Electron Multipliers (THGEM)-based detectors, are the objects of an ongoing R\&D. We report about the initial phase of our studies.Comment: 3 pages, 5 figures, RICH2018 conference proceedin

Characterization of the water diffusion in GEM foil material

Systematic studies on the GEM foil material are performed to measure the moisture diffusion rate and saturation level.These studies are important because the presence of this compound inside the detector’s foil can possibly change its mechanical and electrical properties,and in such a way,the detector performance can be affected.To understand this phenomenon,a model is developed with COMSOL Multiphysicsv.4.3 which described the adsorption and diffusion within the geometry of GEM foil,the concentration profiles and the time required to saturate the foil.The COMSOL model is verified by experimental observations on a GEM foil sample.This note will describe the model and its experimental verification results

Context-Aware Stress Monitoring using Wearable and Mobile Technologies in Everyday Settings

Daily monitoring of stress is a critical component of maintaining optimal physical and mental health. Physiological signals and contextual information have recently emerged as promising indicators for detecting instances of heightened stress. Nonetheless, developing a real-time monitoring system that utilizes both physiological and contextual data to anticipate stress levels in everyday settings while also gathering stress labels from participants represents a significant challenge. We present a monitoring system that objectively tracks daily stress levels by utilizing both physiological and contextual data in a daily-life environment. Additionally, we have integrated a smart labeling approach to optimize the ecological momentary assessment (EMA) collection, which is required for building machine learning models for stress detection. We propose a three-tier Internet-of-Things-based system architecture to address the challenges. We utilized a cross-validation technique to accurately estimate the performance of our stress models. We achieved the F1-score of 70\% with a Random Forest classifier using both PPG and contextual data, which is considered an acceptable score in models built for everyday settings. Whereas using PPG data alone, the highest F1-score achieved is approximately 56\%, emphasizing the significance of incorporating both PPG and contextual data in stress detection tasks

Nanodiamond photocathodes for MPGD-based single photon detectors at future EIC

The design of a Ring Imaging CHerenkov (RICH) detector for the identification of high momentum particles at the future Electron Ion Collider (EIC) is extremely challenging by using current technology. Compact collider setups impose to construct RICH with short radiator length, hence limiting the number of generated photons. The number of detected photons can be increased by selecting the far UV region. As standard fused-silica windows is opaque below 165 nm, a windowless RICH can be a possible approach. CsI is widely used photocathode (PC) for photon detection in the far UV range. Due to its hygroscopic nature it is very delicate to handle. In addition, its Quantum Efficiency (QE) degrades in high intensity ion fluxes. These are the key reasons to quest for novel PC with sensitivity in the far UV region. Recent development of layers of hydrogenated nanodiamond powders as an alternative PC material and their performance, when coupled to the THick Gaseous Electron Multipliers (THGEM)-based detectors, are the objects of an ongoing R\&D. We report here some preliminary results on the initial phase of these studies.Comment: 6 pages, 5 figures, MPGD-2019 La Rochelle, Proceedin

HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT

The Internet of Things (IoT) paradigm holds significant promises for remote health monitoring systems. Due to their life-or mission-critical nature, these systems need to provide a high level of availability and accuracy. On the one hand, centralized cloud-based IoT systems lack reliability, punctuality and availability (e.g., in case of slow or unreliable Internet connection), and on the other hand, fully outsourcing data analytics to the edge of the network can result in diminished level of accuracy and adaptability due to the limited computational capacity in edge nodes. In this paper, we tackle these issues by proposing a hierarchical computing architecture, HiCH, for IoT-based health monitoring systems. The core components of the proposed system are 1) a novel computing architecture suitable for hierarchical partitioning and execution of machine learning based data analytics, 2) a closed-loop management technique capable of autonomous system adjustments with respect to patient's condition. HiCH benefits from the features offered by both fog and cloud computing and introduces a tailored management methodology for healthcare IoT systems. We demonstrate the efficacy of HiCH via a comprehensive performance assessment and evaluation on a continuous remote health monitoring case study focusing on arrhythmia detection for patients suffering from CardioVascular Diseases (CVDs)