From time-series to complex networks: Application to the cerebrovascular flow patterns in atrial fibrillation

A network-based approach is presented to investigate the cerebrovascular flow patterns during atrial fibrillation (AF) with respect to normal sinus rhythm (NSR). AF, the most common cardiac arrhythmia with faster and irregular beating, has been recently and independently associated with the increased risk of dementia. However, the underlying hemodynamic mechanisms relating the two pathologies remain mainly undetermined so far; thus the contribution of modeling and refined statistical tools is valuable. Pressure and flow rate temporal series in NSR and AF are here evaluated along representative cerebral sites (from carotid arteries to capillary brain circulation), exploiting reliable artificially built signals recently obtained from an in silico approach. The complex network analysis evidences, in a synthetic and original way, a dramatic signal variation towards the distal/capillary cerebral regions during AF, which has no counterpart in NSR conditions. At the large artery level, networks obtained from both AF and NSR hemodynamic signals exhibit elongated and chained features, which are typical of pseudo-periodic series. These aspects are almost completely lost towards the microcirculation during AF, where the networks are topologically more circular and present random-like characteristics. As a consequence, all the physiological phenomena at microcerebral level ruled by periodicity - such as regular perfusion, mean pressure per beat, and average nutrient supply at cellular level - can be strongly compromised, since the AF hemodynamic signals assume irregular behaviour and random-like features. Through a powerful approach which is complementary to the classical statistical tools, the present findings further strengthen the potential link between AF hemodynamic and cognitive decline.Comment: 12 pages, 10 figure

Real-time gaze estimation via pupil center tracking

Automatic gaze estimation not based on commercial and expensive eye tracking hardware solutions can enable several applications in the fields of human computer interaction (HCI) and human behavior analysis. It is therefore not surprising that several related techniques and methods have been investigated in recent years. However, very few camera-based systems proposed in the literature are both real-time and robust. In this work, we propose a real-time user-calibration-free gaze estimation system that does not need person-dependent calibration, can deal with illumination changes and head pose variations, and can work with a wide range of distances from the camera. Our solution is based on a 3-D appearance-based method that processes the images from a built-in laptop camera. Real-time performance is obtained by combining head pose information with geometrical eye features to train a machine learning algorithm. Our method has been validated on a data set of images of users in natural environments, and shows promising results. The possibility of a real-time implementation, combined with the good quality of gaze tracking, make this system suitable for various HCI applications

Severe asthma features in children: a case-control online survey

BACKGROUND: Very few studies have explored the distinguishing features of severe asthma in childhood in Europe, and only one study was conducted in Southern Europe. The aim of this study was to provide a detailed characterization of children with severe asthma treated in specialized pediatric asthma centers across Italy. METHODS: We conducted a web-based data collection of family, environmental, clinical and laboratory characteristics of 41 patients aged 6-17 years with severe asthma, defined according to the recent guidelines of the European Respiratory Society and the American Thoracic Society, and 78 age-matched peers with non-severe persistent asthma. The patients have been enrolled from 16 hospital-based pediatric pulmonology and allergy centers in Northern, Central, and Southern Italy. Logistic regression analysis assessed the relationship between patients' characteristics and severe asthma or non-severe persistent asthma. RESULTS: Features independently and significantly associated with severe asthma included lifetime sensitization to food allergens [Odds ratio (OR), 4.73; 95 % Confidence Interval (CI), 1.21-18.53; p = 0.03], lifetime hospitalization for asthma (OR, 3.71; 95 % CI, 1.11-12.33; p = 0.03), emergency-department visits for asthma during the past year (OR = 11.98; 95 % CI, 2.70-53.11; p = 0.001), and symptoms triggered by physical activity (OR = 12.78; 95 % CI, 2.66-61.40; p = 0.001). Quality-of-life score was worse in patients with severe asthma than in subjects with non-severe persistent asthma (5.9 versus 6.6, p = 0.005). Self-perception of wellbeing was compromised in more than 40 % of patients in both groups. Children with severe asthma had lower spirometric z scores than non-severe asthmatic peers (all p < 0.001), although 56 % of them had a normal forced expiratory volume in 1 s. No differences were found between the two groups for parental education, home environment, patients' comorbidities, adherence to therapy, exhaled nitric oxide values, and serum eosinophils and IgE . CONCLUSIONS: As expected, children with severe asthma had more severe clinical course and worse lung function than peers with non-severe persistent asthma. Unlike previous reports, we found greater sensitization to food allergens and similar environmental and personal characteristics in patients with severe asthma compared to those with non-severe persistent asthma. Psychological aspects are compromised in a large number of cases and deserve further investigation

Severe asthma features in children: A case–control online survey

Background: Very few studies have explored the distinguishing features of severe asthma in childhood in Europe, and only one study was conducted in Southern Europe. The aim of this study was to provide a detailed characterization of children with severe asthma treated in specialized pediatric asthma centers across Italy. Methods: We conducted a web-based data collection of family, environmental, clinical and laboratory characteristics of 41 patients aged 6–17 years with severe asthma, defined according to the recent guidelines of the European Respiratory Society and the American Thoracic Society, and 78 age-matched peers with non-severe persistent asthma. The patients have been enrolled from 16 hospital-based pediatric pulmonology and allergy centers in Northern, Central, and Southern Italy. Logistic regression analysis assessed the relationship between patients’ characteristics and severe asthma or non-severe persistent asthma. Results: Features independently and significantly associated with severe asthma included lifetime sensitization to food allergens [Odds ratio (OR), 4.73; 95% Confidence Interval (CI), 1.21–18.53; p = 0.03], lifetime hospitalization for asthma (OR, 3.71; 95% CI, 1.11–12.33; p = 0.03), emergency-department visits for asthma during the past year (OR = 11.98; 95% CI, 2.70–53.11; p = 0.001), and symptoms triggered by physical activity (OR = 12.78; 95% CI, 2.66–61.40; p = 0.001). Quality-of-life score was worse in patients with severe asthma than in subjects with non-severe persistent asthma (5.9 versus 6.6, p = 0.005). Self-perception of wellbeing was compromised in more than 40% of patients in both groups. Children with severe asthma had lower spirometric z scores than non-severe asthmatic peers (all p < 0.001), although 56% of them had a normal forced expiratory volume in 1 s. No differences were found between the two groups for parental education, home environment, patients’ comorbidities, adherence to therapy, exhaled nitric oxide values, and serum eosinophils and IgE. Conclusions: As expected, children with severe asthma had more severe clinical course and worse lung function than peers with non-severe persistent asthma. Unlike previous reports, we found greater sensitization to food allergens and similar environmental and personal characteristics in patients with severe asthma compared to those with non-severe persistent asthma. Psychological aspects are compromised in a large number of cases and deserve further investigation

Multicentre Italian study of SARS-CoV-2 infection in children and adolescents, preliminary data as at 10 April 2020

Data on features of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in children and adolescents are scarce. We report preliminary results of an Italian multicentre study comprising 168 laboratory-confirmed paediatric cases (median: 2.3 years, range: 1 day-17.7 years, 55.9% males), of which 67.9% were hospitalised and 19.6% had comorbidities. Fever was the most common symptom, gastrointestinal manifestations were frequent; two children required intensive care, five had seizures, 49 received experimental treatments and all recovered

Caratterizzazione della dinamica produttiva di pascoli naturali italiani

This work studies herbage production and its seasonal distribution in indigenous pastures, and analyses the relationship between the environmental factors (soil, clima, vegetation) and the productivity of these resources. The investigations have been carried on during the period 1983-90 by the joint activity of 10 different University Istitutions in 23 different environments distributed along the Italian peninsula and the main islands. For each environment, pasture production has been measured with the Corrall and Fenlon method, analysing the more important vegetational and ecological conditions; altogether the total yearly production and the seasonal pattern of herbage production have been detected on 104 pastures. The total herbage yield is not significantly influenced by the latitudinal gradient, and the overall regional (alps, central Appenine, south Apennine and islands) production is about 2.3 t ha-1 year-1 The wide range (0.5-6.3 t ha-1 year-1) of herbage production, on small or medium scale, seems to be due to evident changeof environmental or management factors. Five types of seasonal distribution of herbage growth are evidenced with multivariate analysis methods, based on the growing season and the amplitude of the growth. With mean temperature above 12°C and total rainfall below 800 mm, herbage distribution shows a standstill during summer period and an evident regrowth in autumn. On the contrary, for the 4 other distribution types, the winter standstill become important, and the types are distinct by summer growth amplitude and by the growing season lenght. With cluster analysis method, for each type of herbage distribution, have been pointed out under-types characterized by interannual herbage production variation. Among the environmental factors, vegetation characheristics, expressed as Pasture Value following Daget and Poissonet seems to be strictly correlated with total production. The comparative poor role played by the soil and climatic factor, may be due to the strong past and present antropic influence, related with management and utilization techniques. Il presente lavoro ha come scopo l'approfondimento delle conoscenze sulla produzione e sulla distribuzione stagionale della crescita dell'erba dei pascoli naturali, nonché l'analisi delle interazioni tra i fattori ambientali, pedo-climatici e vegetazionali, e la risposta produttiva di queste risorse. La ricerca è stata condotta nel periodo 1983-90 da 10 diverse Istituzioni Universitarie, in 23 ambienti differenti, distribuiti lungo tutta la penisola e le isole maggiori. Per ogni ambiente, con il metodo di rilievo di Corrall e Fenlon, è stata saggiata la risposta produttiva di pascoli rappresentativi delle principali situazioni vegetazionali e di giacitura; complessivamente sono state rilevate la produzione totale annua e la curva di produttività media pluriennale di 104 pascoli. Riguardo la produzione annua complessiva si è osservato che essa non presenta variazioni significative lungo il gradiente latitudinale, collocandosi tra le diverse regioni (alpina, centro appenninica, suq, appenninica e insulare) attorno a 2.3 t ha-1 anno-1. La fitomassa raccolta è soggetta invece a variazioni sensibili (0.5-6.3 t ha-1 anno-1) riconducibili a fattori ambientali e gestionali che si esprimono su piccola e media scala. Con metodi di analisi multivariata si sono individuate 5 tipologie distributive della crescita dell'erba, in rapporto alla stagione vegetativa e alle variazioni dell'intensità di crescita nel corso della stagione stessa. Con temperature medie e precipitazioni annue rispettivamente maggiori di 12°C e minori di 800 mm, risulta evidente la stasi vegetativa nel trimestre estivo e la ripresa vegetativa autunnale. Nel caso opposto la stasi è invernale e le 4 tipologie afferenti a questo modello, sono distinguibili dall'entità della crescita nei mesi estivi e dalla durata della stagione vegetativa. Per ogni tipologia produttiva, sono state evidenziate, tramite l'analisi cluster, sotto-tipologie distinte per la variabilità produttiva interannuale. Tra i fattori ambientali, la vegetazione, espressa attraverso l'indice del valore pastorale di Daget e Poissonet, presenta una buona capacità predittiva nei confronti del livello produttivo dei pascoli. Il contributo comparativamente modesto offerto dai fattori pedoclimatici sembra attribuibile alla forte influenza antropica, pregressa e attuale, attraverso le cure colturali e l'utilizzazione

Real-time gaze estimation via pupil center tracking

Automatic gaze estimation not based on commercial and expensive eye tracking hardware solutions can enable several applications in the fields of human computer interaction (HCI) and human behavior analysis. It is therefore not surprising that several related techniques and methods have been investigated in recent years. However, very few camera-based systems proposed in the literature are both real-time and robust. In this work, we propose a real-time user-calibration-free gaze estimation system that does not need person-dependent calibration, can deal with illumination changes and head pose variations, and can work with a wide range of distances from the camera. Our solution is based on a 3-D appearance-based method that processes the images from a built-in laptop camera. Real-time performance is obtained by combining head pose information with geometrical eye features to train a machine learning algorithm. Our method has been validated on a data set of images of users in natural environments, and shows promising results. The possibility of a real-time implementation, combined with the good quality of gaze tracking, make this system suitable for various HCI applications

Real-time gaze estimation via pupil center tracking

Abstract Automatic gaze estimation not based on commercial and expensive eye tracking hardware solutions can enable several applications in the fields of human computer interaction (HCI) and human behavior analysis. It is therefore not surprising that several related techniques and methods have been investigated in recent years. However, very few camera-based systems proposed in the literature are both real-time and robust. In this work, we propose a real-time user-calibration-free gaze estimation system that does not need person-dependent calibration, can deal with illumination changes and head pose variations, and can work with a wide range of distances from the camera. Our solution is based on a 3-D appearance-based method that processes the images from a built-in laptop camera. Real-time performance is obtained by combining head pose information with geometrical eye features to train a machine learning algorithm. Our method has been validated on a data set of images of users in natural environments, and shows promising results. The possibility of a real-time implementation, combined with the good quality of gaze tracking, make this system suitable for various HCI applications