AN ACTIVE LEARNING PROCEDURE FOR THE INTERAURAL TIME DIFFERENCE DISCRIMINATION THRESHOLD

Measuring the auditory lateralization elicited by interaural time difference (ITD) cues involves the estimation of a psychometric function (PF). The shape of this function usually follows from the analysis of the subjective data and models the probability of correctly localizing the angular position of a sound source. The present study describes and evaluates a procedure for progressively fitting a PF, using Gaussian process classification of the subjective responses produced during a binary decision experiment. The process refines adaptively an approximated PF, following Bayesian inference. At each trial, it suggests the most informative auditory stimulus for function refinement according to Bayesian active learning by disagreement (BALD) mutual information. In this paper, the procedure was modified to accommodate two-alternative forced choice (2AFC) experimental methods and then was compared with a standard adaptive “three-down, one-up” staircase procedure. Our process approximates the average threshold ITD 79.4% correct level of lateralization with a mean accuracy increase of 8.9% over the Weibull function fitted on the data of the same test. The final accuracy for the Just Noticeable Difference (JND) in ITD is achieved with only 37.6% of the trials needed by a standard lateralization test

The Role of Haptics in Training and Games for Hearing-Impaired Individuals: A Systematic Review

Sensory substitution and augmentation are pivotal concepts in multi-modal perception, particularly when confronting the challenges associated with impaired or missing sense rehabilitation. The present systematic review investigates the role of haptics for the hearing impaired in training or gamified activities. We applied a set of keywords to the Scopus® and PubMed® databases, obtaining a collection of 35 manuscripts spanning 23 years. Each article has been categorized following a documented procedure and thoroughly analyzed. Our findings reveal a rising number of studies in this field in the last five years, mostly testing the effectiveness of the developed rehabilitative method (77.14%). Despite a wide variety in almost every category we analyzed, such as haptic devices, body location, and data collection, we report a constant difficulty in recruitment, reflected in the low number of hearing-impaired participants (mean of 8.31). This review found that in all six papers reporting statistically significant positive results, the vibrotactile device in use generated vibrations starting from a sound, suggesting that some perceptual aspects connected to sound are transmittable through touch. This fact provides evidence that haptics and vibrotactile devices could be viable solutions for hearing-impaired rehabilitation and training

Investigations using Csiro Hi triaxal cells for measuring the stress state of rock masses subject to mining extraction: numerical modelling of in-situ extracted core samples

The measurement of the stress state of rock, carried out in-situ using the overcoring CSIro hI Cell technique, provides valuable information about the rock mass geo-structural and stress conditions. this is particularly useful for calibrating the numerical model of natural slopes and excavations fronts and for assessing their static conditions. thus, it allows to improve workplace safety conditions in both open-pit and underground quarries. During an in-situ CSIro test, the stress release strains are measured by 12 strain gauges differently oriented in the space and the stress tensor and the material elastic parameters are then computed. the classic interpretative procedure of stress release test refers to analytical formulations that assume an extracted sample of regular cylindrical shape. however, during overcoring, it may happen that a discontinuity is intercepted, causing the extracted core to break and to assume an irregular shape. to address this challenge, in this work, a Finite Element numerical simulation of stress release was conducted basing on a 3D digital model of the irregular sample resulting from a Photogrammetric Survey. this allowed for the computation of the stress tensor for both irregularly shaped and ideal cylindrical samples. the research proceeded as it follows: i) three-dimensional modelling of the irregularly shaped core using Photogrammetric techniques and mesh Editing, which enabled the accurate representation of complex geometries; ii) numerical modelling of the irregularly shaped core containing the CSIro hI Cell through Finite Element Analysis, providing insights about stress and deformation distributions; iii) stress State of the rock calculation using a multiple Linear regression Procedure by using the coefficient matrix as determined by the core numerical modelling. the implementation of this procedure may facilitate the determination of stress state for irregularly shaped cores, and it enhances to understand how shape and rock elastic properties may influence the stress release behaviour. this comprehensive approach could allow to address challenges associated to stress assessment for irregular shaped rock cores and to improve the accuracy and applicability of geotechnical engineering methods

Long-Short Term Memory for an Effective Short-Term Weather Forecasting Model Using Surface Weather Data

Part 7: Deep Learning - Convolutional ANNInternational audienceNumerical Weather Prediction (NWP) requires considerable computer power to solve complex mathematical equations to obtain a forecast based on current weather conditions. In this article, we propose a lightweight data-driven weather forecasting model by exploring state-of-the-art deep learning techniques based on Artificial Neural Network (ANN). Weather information is captured by time-series data and thus, we explore the latest Long Short-Term Memory (LSTM) layered model, which is a specialised form of Recurrent Neural Network (RNN) for weather prediction. The aim of this research is to develop and evaluate a short-term weather forecasting model using the LSTM and evaluate the accuracy compared to the well-established Weather Research and Forecasting (WRF) NWP model. The proposed deep model consists of stacked LSTM layers that uses surface weather parameters over a given period of time for weather forecasting. The model is experimented with different number of LSTM layers, optimisers, and learning rates and optimised for effective short-term weather predictions. Our experiment shows that the proposed lightweight model produces better results compared to the well-known and complex WRF model, demonstrating its potential for efficient and accurate short-term weather forecasting

Using Open Source Libraries in the Development of Control Systems Based on Machine Vision

The possibility of the boundaries detection in the images of crushed ore particles using a convolutional neural network is analyzed. The structure of the neural network is given. The construction of training and test datasets of ore particle images is described. Various modifications of the underlying neural network have been investigated. Experimental results are presented. © 2020, IFIP International Federation for Information Processing.Foundation for Assistance to Small Innovative Enterprises in Science and Technology, FASIEFunding. The work was performed under state contract 3170ΓC1/48564, grant from the FASIE

Stress–Strain Investigation of the Rock Mass Based on Overcoring with CSIRO HI Cell Test and Numerical Modeling: A Case Study from an Italian Underground Marble Quarry

The present research illustrates the application of a methodological approach to studying the stress–strain distribution in a marble quarry of the Apuan Alps mining area (Italy). This study has been carried out in the framework of a project involving the University of Siena and the UOC Ingegneria Mineraria—USL Toscana Nord-Ovest, Tuscany Region. This stress–strain analysis aims foremost to monitor the slope stability conditions to guarantee a safe workplace for the personnel involved in mining activities, and to enable more sustainable long-term planning for excavation and production. The involved survey activities are as follows: (i) terrestrial laser scanning; (ii) engineering–geological data mapping; and (iii) in situ marble stress measuring through four CSIRO-type cell tests executed in different locations and at various depths within the underground excavation walls. The gathered data converged into numerical models of the quarry, both in 2D (DEM) and 3D (FEM), calibrated by in situ stress results through a rigorous back analysis assessment using least squares procedures. The created models represent a valuable tool for the identification and securing of risk areas and for future excavation planning in respect of the site efficiency and safety

IgG cryoglobulinemia

OBJECTIVE: Mixed Cryoglobulinemia is the most well-known Hepatitis C Virus (HCV)-associated extrahepatic manifestation. MC is both an autoimmune and B-lymphoproliferative disorder. Cryoglobulins (CGs) are classified into three groups according to immunoglobulin (Ig) composition: type I is composed of one isotype or Ig class. Type II and type III mixed CGs are immune complexes composed of polyclonal IgGs acting as autoantigens and mono, polyclonal or oligoclonal IgM with rheumatoid factor activity. IgG1 and IgG3 are the predominant subclasses involved. This study shows the simultaneous presence of IgG-RF and IgG3, supporting the hypothesis of an involvement of this subclass in the initiation of early stages of CGs. PATIENTS AND METHODS: We describe a case series of six HCV-positive patients, all of whom had peripheral neuropathy and transient ischemic attacks, presenting cryoprecipitates formed by IgG3 and IgG1. Cryoprecipitate IgG subclass research was carried out by immunofixation electrophoresis by using antisera against IgG1, IgG2, IgG3, and IgG4. RESULTS: Our six patients presented with an immunochemical pattern characterized by the mere presence of IgG1 and IgG3 subclasses with probable RF activity and one of these six patients exhibited monoclonal IgG3 in his cerebrospinal fluid. CONCLUSIONS: We can hypothesize that the IgG passage through the blood-brain barrier could have contributed to the cause of TIAs, through a mechanism involving the precipitation of circulating immune complexes formed by the two subclasses in the intrathecal vessels

Cerebral Microbleeds in a Small Cohort of Patients with First Ever Lacunar Stroke. A 3Tesla MRI Longitudinal Case Series

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Immune dyscrasia in adult growth hormone deficiency: Evaluation of hemolytic complement activity (CH50) and IgG subclasses

CH50 is a screening assay for the activation of the classical complement pathway, the immunoglobulins-mediated one, activated in several inflammatory diseases. Adult growth hormone deficiency (aGHD) is recognized as a chronic inflammatory condition, although poorly evaluated under the profile of inflammatory biomarkers. The aim of this case-control observational study is to analyze CH50 and immunoglobulins G (IgG) subclasses production in aGHD, comparing this condition to healthy controls. 38 subjects were included and divided as follows: aGHD (n = 18, 6 females and 12 males); healthy controls (n = 20, 10 females and 10 males). GHD was diagnosed with dynamic test using Growth Hormone-Releasing Hormone (GHRH 50 \u3bcg i.v. + arginine 0,5 g/Kg), with a peak GH response < 9 \u3bcg/L when BMI was <30 kg/m2 or < 4 \u3bcg/L when BMI was >30 kg/m2. The two groups were evaluated for hormonal and metabolic parameters, CH50 and IgG subtypes. IgG1 and IgG2 were significantly higher in controls than in aGHD, while IgG3 and IgG4 showed a trend to higher levels in controls, although not significant. Furthermore, CH50 levels were significantly higher in aGHD. These data substantiate the hypothesis of a dyscrasia in IgG subclasses production in aGHD. As IgG levels decrease, CH50 levels do not