Finding Strong Gravitational Lenses in the Kilo Degree Survey with Convolutional Neural Networks

The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyze sources. Indeed, this is the case for the search for strong gravitational lenses, where the population of the detectable lensed sources is only a very small fraction of the full source population. We apply for the first time a morphological classification method based on a Convolutional Neural Network (CNN) for recognizing strong gravitational lenses in $255$ square degrees of the Kilo Degree Survey (KiDS), one of the current-generation optical wide surveys. The CNN is currently optimized to recognize lenses with Einstein radii $\gtrsim 1.4$ arcsec, about twice the $r$-band seeing in KiDS. In a sample of $21789$ colour-magnitude selected Luminous Red Galaxies (LRG), of which three are known lenses, the CNN retrieves 761 strong-lens candidates and correctly classifies two out of three of the known lenses. The misclassified lens has an Einstein radius below the range on which the algorithm is trained. We down-select the most reliable 56 candidates by a joint visual inspection. This final sample is presented and discussed. A conservative estimate based on our results shows that with our proposed method it should be possible to find $\sim100$ massive LRG-galaxy lenses at z\lsim 0.4 in KiDS when completed. In the most optimistic scenario this number can grow considerably (to maximally $\sim$2400 lenses), when widening the colour-magnitude selection and training the CNN to recognize smaller image-separation lens systems.Comment: 24 pages, 17 figures. Published in MNRA

Magnetic resonance tumor regression grade (MR-TRG) to assess pathological complete response following neoadjuvant radiochemotherapy in locally advanced rectal cancer

This study aims to evaluate the feasibility of a magnetic resonance (MR) automatic method for quantitative assessment of the percentage of fibrosis developed within locally advanced rectal cancers (LARC) after neoadjuvant radiochemotherapy (RCT). A total of 65 patients were enrolled in the study and MR studies were performed on 3.0 Tesla scanner; patients were followed-up for 30 months. The percentage of fibrosis was quantified on T2-weighted images, using automatic K-Means clustering algorithm. According to the percentage of fibrosis, an optimal cut-off point for separating patients into favorable and unfavorable pathologic response groups was identified by ROC analysis and tumor regression grade (MR-TRG) classes were determined and compared to histopathologic TRG. An optimal cut-off point of 81% of fibrosis was identified to differentiate between favorable and unfavorable pathologic response groups resulting in a sensitivity of 78.26% and a specificity of 97.62% for the identification of complete responders (CRs). Interobserver agreement was good (0.85). The agreement between P-TRG and MR-TRG was excellent (0.923). Significant differences in terms of overall survival (OS) and disease free survival (DFS) were found between favorable and unfavorable pathologic response groups. The automatic quantification of fibrosis determined by MR is feasible and reproducible

Effects of Mindfulness Practice on Performance and Factors Related to Performance in Long-Distance Running: A Systematic Review

Fatigue, boredom, pain, performance anxiety, and negative thoughts are challenges characteristic of competitive running. One psychological technique that is gaining support and has been successfully implemented in sport is the practice of mindfulness. Where conventional psychological skills training interventions aim to change dysfunctional thoughts and emotions, mindfulness focuses on altering the relationship to physiological and psychological states. This could help in dealing with the demands of distance running but this has yet to be examined. This article was focused on reviewing mindfulness interventions on performance and performance-based factors in long distance running, assessing (a) mindfulness scores, (b) physiological performance-related factors, (c) psychological performance-related factors, and (d) performance outcomes. A search of relevant electronic databases yielded seven studies which met the inclusion criteria. The review provided some tentative support for the use of mindfulness interventions regarding: reducing competitive anxiety, attenuating immune responses to high-intensity running, and increasing state mindfulness. However, due to the methodological weaknesses of studies more research is required using high-quality randomized controlled trial designs

From the emotional integration to the cognitive construction: the developmental approach of Turtle Project in children with autism spectrum disorder

Background: Children with autism spectrum disorder show a deficit in neurobiological processes. This deficit hinders the development of intentional behavior and appropriate problem-solving, leading the child to implement repetitive and stereotyped behaviors and to have difficulties in reciprocal interactions, empathy and in the development of a theory of mind. The objective of this research is to verify the effectiveness of a relationship-based approach on the positive evolution of autistic symptoms. Method: A sample of 80 children with autism spectrum disorder was monitored during the first four years of therapy, through a clinical diagnostic assessment at the time of intake and then in two follow-up. Results: The results showed that through the Autism Diagnostic Observation Schedule it is possible to assess the socio-relational key elements on which the therapy is based. There was evidence, in fact, of significant improvements after two and four years of therapy, both for children with severe autistic symptoms and for those in autistic spectrum. Conclusions: Socio-relational aspects represent the primary element on which work in therapy with autistic children and can be considered as indicators of a positive evolution and prognosis that will produce improvements even in the cognitive are