Search results for "Mach"

2015

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminat…

Accurate Wound and Lice Detection in Atlantic Salmon Fish Using a Convolutional Neural Network

2022

The population living in the coastal region relies heavily on fish as a food source due to their vast availability and low cost. This need has given rise to fish farming. Fish farmers and the fishing industry face serious challenges such as lice in the aquaculture ecosystem, wounds due to injuries, early fish maturity, etc. causing millions of fish deaths in the fish aquaculture ecosystem. Several measures, such as cleaner fish and anti-parasite drugs, are utilized to reduce sea lice, but getting rid of them entirely is challenging. This study proposed an image-based machine-learning technique to detect wounds and the presence of lice in the live salmon fish farm ecosystem. A new equally di…

Survey on the innovation in the Sicilian grapevine nurseries

2012

This paper deals with quality innovation in the grapevine nursery sector. The vegetative propagation of grapevines, scarcely considered by economic research, is the first step in the wine production chain as it influences both the type and the quality of wines as well as the quality and quantity of the performance of farm investments.This paper gives the results of a study carried out through a structural analysis of both national and regional grapevine nurseries and then through a direct survey of the largest Sicilian nurseries. The survey covers the main structural and productive issues as well as the commercial aspects of eight Sicilian grapevine nurseries and their innovative investment…

Pancreas aberrante: una causa rara di epigastralgia

2004

Objective: The Authors report their experience about a case of aberrant pancreas that lead epigastralgia. Design: Report of 1 case and endoscopic treatment (upper endoscopy + EUS + endoscopic polipectomy + endoscopic biopsy of the base. Surgical effectiveness evaluation. Setting: Section of General and Thoracic Surgery. Department of General Surgery; Emergency and Organ Transplantation. Policlinico "Paolo GiacconePalermo. Intervention: After correct and sure diagnosis, the patient was submitted to endoscopic polipectomy with radical and curative intention. Results: Complete recovery. Hematochemical and endoscopic follow-up (1 months) negative. Conclusions: Diagnosis of aberrant pancreas is …

Atrial Fibrosis Hampers Non-invasive Localization of Atrial Ectopic Foci From Multi-Electrode Signals: A 3D Simulation Study

2018

[EN] Introduction: Focal atrial tachycardia is commonly treated by radio frequency ablation with an acceptable long-term success. Although the location of ectopic foci tends to appear in specific hot-spots, they can be located virtually in any atrial region. Multi-electrode surface ECG systems allow acquiring dense body surface potential maps (BSPM) for non-invasive therapy planning of cardiac arrhythmia. However, the activation of the atria could be affected by fibrosis and therefore biomarkers based on BSPM need to take these effects into account. We aim to analyze the effect of fibrosis on a BSPM derived index, and its potential application to predict the location of ectopic foci in the …

Control and design for efficiency improvement of permanent-magnet synchronous motor drives in household appliances

2011

This paper deals with some aspects of efficiency improvement of PMSMD (Permanent Magnet Synchronous Motor Drives). Particularly two aspects are focused: the control algorithm for the PMSMD, which allows to reduce the power losses of the electric drive without penalty on its dynamic performances and the optimization of an IPMSM (Interior Permanent Magnet Synchronous Motor) rotor configuration capable to increase the performances in terms of shaft torque production, limiting at the same time the rotor leakage flux. The loss minimization algorithm is here briefly analyzed, a test bed for experimental validation is presented and the data are analyzed. Experimental tests have been performed aimi…

Vibrations of a continuous web on elastic supports

2017

We consider an infinite, homogenous linearly elastic beam resting on a system of linearly elastic supports, as an idealized model for a paper web in the middle of a cylinder-based dryer section. We obtain closed-form analytical expressions for the eigenfrequencies and the eigenmodes. The frequencies increase as the support rigidity is increased. Each frequency is bounded from above by the solution with absolutely rigid supports, and from below by the solution in the limit of vanishing support rigidity. Thus in a real system, the natural frequencies will be lower than predicted by commonly used models with rigid supports. peerReviewed

Regularized extreme learning machine for regression problems

2011

Extreme learning machine (ELM) is a new learning algorithm for single-hidden layer feedforward networks (SLFNs) proposed by Huang et al. [1]. Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This paper proposes an algorithm for pruning ELM networks by using regularized regression methods, thus obtaining a suitable number of the hidden nodes in the network architecture. Beginning from an initial large number of hidden nodes, irrelevant nodes are then pruned using ridge regression, elastic net and lasso methods; hence, the architectural design of ELM network can be automated. Empirical studies…

An entropy-based machine learning algorithm for combining macroeconomic forecasts

2019

This paper applies a Machine Learning approach with the aim of providing a single aggregated prediction from a set of individual predictions. Departing from the well-known maximum-entropy inference methodology, a new factor capturing the distance between the true and the estimated aggregated predictions presents a new problem. Algorithms such as ridge, lasso or elastic net help in finding a new methodology to tackle this issue. We carry out a simulation study to evaluate the performance of such a procedure and apply it in order to forecast and measure predictive ability using a dataset of predictions on Spanish gross domestic product.

A machine learning application to predict early lung involvement in scleroderma: A feasibility evaluation

2021

Introduction: Systemic sclerosis (SSc) is a systemic immune-mediated disease, featuring fibrosis of the skin and organs, and has the greatest mortality among rheumatic diseases. The nervous system involvement has recently been demonstrated, although actual lung involvement is considered the leading cause of death in SSc and, therefore, should be diagnosed early. Pulmonary function tests are not sensitive enough to be used for screening purposes, thus they should be flanked by other clinical examinations