Analysis of residual dependencies of independent components extracted from fMRI data

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data can be employed as an exploratory method. The lack in the ICA model of strong a priori assumptions about the signal or about the noise leads to difficult interpretations of the results. Moreover, the statistical independence of the components is only approximated. Residual dependencies among the components can reveal informative structure in the data. A major problem is related to model order selection, that is, the number of components to be extracted. Specifically, overestimation may lead to component splitting. In this work, a method based on hierarchical clustering of ICA applied to fMRI datasets is investigated. The clustering algorithm uses a metric based on the mutual information between the ICs. To estimate the similarity measure, a histogram-based technique and one based on kernel density estimation are tested on simulated datasets. Simulations results indicate that the method could be used to cluster components related to the same task and resulting from a splitting process occurring at different model orders. Different performances of the similarity measures were found and discussed. Preliminary results on real data are reported and show that the method can group task related and transiently task related components

An automatic deep learning approach for coronary artery calcium segmentation

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed tomography (CT) images. The proposed system uses a supervised deep learning algorithm, i.e. convolutional neural network (CNN) for the segmentation and classification of candidate lesions as coronary or not, previously extracted in the region of the heart using a cardiac atlas. We trained our network with 45 CT volumes; 18 volumes were used to validate the model and 56 to test it. Individual lesions were detected with a sensitivity of 91.24%, a specificity of 95.37% and a positive predicted value (PPV) of 90.5%; comparing calcium score obtained by the system and calcium score manually evaluated by an expert operator, a Pearson coefficient of 0.983 was obtained. A high agreement (Cohen's k = 0.879) between manual and automatic risk prediction was also observed. These results demonstrated that convolutional neural networks can be effectively applied for the automatic segmentation and classification of coronary calcifications

Crossing Over from Attractive to Repulsive Interactions in a Tunneling Bosonic Josephson Junction

We explore the interplay between tunneling and interatomic interactions in the dynamics of a bosonic Josephson junction. We tune the scattering length of an atomic $^{39}$K Bose-Einstein condensate confined in a double-well trap to investigate regimes inaccessible to other superconducting or superfluid systems. In the limit of small-amplitude oscillations, we study the transition from Rabi to plasma oscillations by crossing over from attractive to repulsive interatomic interactions. We observe a critical slowing down in the oscillation frequency by increasing the strength of an attractive interaction up to the point of a quantum phase transition. With sufficiently large initial oscillation amplitude and repulsive interactions the system enters the macroscopic quantum self-trapping regime, where we observe coherent undamped oscillations with a self-sustained average imbalance of the relative well population. The exquisite agreement between theory and experiments enables the observation of a broad range of many body coherent dynamical regimes driven by tunable tunneling energy, interactions and external forces, with applications spanning from atomtronics to quantum metrology.Comment: 10 pages, 8 figures, supplemental materials are include

Quantitative analysis of the epithelial lining architecture in radicular cysts and odontogenic keratocysts

BACKGROUND: This paper describes a quantitative analysis of the cyst lining architecture in radicular cysts (of inflammatory aetiology) and odontogenic keratocysts (thought to be developmental or neoplastic) including its 2 counterparts: solitary and associated with the Basal Cell Naevus Syndrome (BCNS). METHODS: Epithelial linings from 150 images (from 9 radicular cysts, 13 solitary keratocysts and 8 BCNS keratocysts) were segmented into theoretical cells using a semi-automated partition based on the intensity of the haematoxylin stain which defined exclusive areas relative to each detected nucleus. Various morphometrical parameters were extracted from these "cells" and epithelial layer membership was computed using a systematic clustering routine. RESULTS: Statistically significant differences were observed across the 3 cyst types both at the morphological and architectural levels of the lining. Case-wise discrimination between radicular cysts and keratocyst was highly accurate (with an error of just 3.3%). However, the odontogenic keratocyst subtypes could not be reliably separated into the original classes, achieving discrimination rates slightly above random allocations (60%). CONCLUSION: The methodology presented is able to provide new measures of epithelial architecture and may help to characterise and compare tissue spatial organisation as well as provide useful procedures for automating certain aspects of histopathological diagnosis

Improving plastic management by means of people awareness

In past decades the usage of plastic has seen a tremendous increment. This raise is mainly caused by industrial development and by the spread of this material in every aspect of people life, from food package to aerospace application. For sure plastic has a key role in society and it is not possible to erase, nevertheless its overuse has a serious impact on the environment as well know. In particular, just a few percentage of the total amount of plastic is recycled, the rest has to be landfilled or burnt causing serious pollution side effect. This poor circularity in plastic value chain is mainly caused by difficulties in sorting processes and expensiveness of recycling. By the way a great part of plastic applications could be avoided without implying a reduction in life quality for the people. In addition, a better education in plastic objects shopping and plastic waste management could decrease the difficulties in sorting and recycling. One of the crucial reason why these applications and incorrect behaviour are still present is that the information on alternatives are not present or very hard to be found. In the present paper a novel platform to enhance a more plastic-free life is presented. First a detailed description of the problem is stated, then the process to achieve the proposed solution is described. Finally the platform prototype is analysed in details among its functionalities

Attachment forerunners, dyadic sensitivity and development of the child in families with a preterm born baby

Objective: The aim of this study is to explore attachment forerunners and dyadic sensitivity in the family with preterm born child. Methods: 89 families, 35 with preterm born children ( 2500 gr.) were studied from 3 months to 1 year corrected age (267 total subjects). Mother-child and father-child couples were subjected to CARE-Index and both parents to DAS, CES-D and STAI Y-2. The child\u2019s psychomotor development was assessed by Bayley Scales. Results: The mothers of preterm children presented high risk interactive behaviors at CARE-Index (low scores at Dyadic Sensitivity Scale, p = .000), high anxiety (p = .003) and depression (p = .03). Preterm fathers presented low scores at Dyadic Sensitivity Scale (p = .000) and high anxiety (p = .024). In interaction, attachment forerunners suggest an insecure attachment in preterm mothers (p = .001) and fathers (p = .000) and in preterm children in the interaction with the mother (p = .028). These risk factors were correlated, in both parents, with low performance of the child at Bayley Scales (p =.04). Fathers of preterm children presented also a negative perception of the child and an unsatisfied perception of the hospital care. Conclusions: The results show in the preterm family that 40% of mothers and 75% of fathers are in high risk area suggested by CARE-Index. In these cases, insecure attachment forerunners, low dyadic sensitivity and psychological difficulties (couple conflicts, anxiety, depression) seem to influence the psychomotor development of the preterm child