Accurate and reliable segmentation of the optic disc in digital fundus images

We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE)

Detecting an immersed body in a fluid. Stability and reconstruction

We consider the inverse problem of the detection of a single body, immersed in a bounded container filled with a fluid which obeys the stationary Stokes or Navier Stokes equations, from a single measurement of force and velocity on a portion of the boundary. Under appropriate a priori hypotheses we obtain an estimate of stability of log-log type for both cases. We then present a numerical method for the reconstruction of the body using a boundary elements representation of the solutions, combined with the iteratively regularized Gauss-Newton method, and present some partial numerical results in this direction

Understanding Autism in Schizophrenia

Detachment from external reality, distancing from others, closure into a sort of virtual hermitage, and prevalence of inner fantasies, are the descriptive aspects of autism. However, from an anthropological-phenomenological point of view, in schizophrenia, the autistic mode of life can arise from a person's being confronted with a pathological crisis in the obviousness of the intersubjective world, essentially a crisis in the intersubjective foundation of human presence. The “condition of possibility” of the autistic way of being is the deficiency of the operation that phenomenology call empathetic-intuitive constitution of the Other, an Other which is the naturalness of evidence of being a subject like me. The theme of the Other, of intersubjectivity, has become so central in the psychopathological analysis of schizophrenic disorders because the modifications of interhuman encounter cannot be seen as the secondary consequences of symptoms but constitute the fundamental disorder of schizophrenic alienation. Revision of the concept of autism from the original definition, centered on the prevalence of inner fantasies, leads to the profound change with the vision of autism as “loss” and “void.” I call attention to possibility of phenomenological research to understand autistic world starting from this “void.

Bridging Multiple Levels of Exploration: Towards a Neuroengineering-Based Approach to Physiological and Pathological Problems in Neuroscience

Neuroengineering is a rapidly growing discipline that takes its lymph from the increasing cross-fertilization of many areas of technology and science. For example, by means of neuroengineering, advances in diverse technologies and in cellular and molecular biology converge into powerful tools to improve our understanding and treatment of neural (dis)functions. Recently such a discipline has gone beyond the concept of a simple application of engineering principles to central nervous system (CNS) comprehension, leading to the emergence of one of the more exciting interdisciplinary research fields in modern neuroscience

Improving the predictability of take-off times with Machine Learning : a case study for the Maastricht upper area control centre area of responsibility

The uncertainty of the take-off time is a major contribution to the loss of trajectory predictability. At present, the Estimated Take-Off Time (ETOT) for each individual flight is extracted from the Enhanced Traffic Flow Management System (ETFMS) messages, which are sent each time there is an event triggering a recalculation of the flight data by the Network Man- ager Operations Centre. However, aircraft do not always take- off at the ETOTs reported by the ETFMS due to several factors, including congestion and bad weather conditions at the departure airport, reactionary delays and air traffic flow management slot improvements. This paper presents two machine learning models that take into account several of these factors to improve the take- off time prediction of individual flights one hour before their estimated off-block time. Predictions performed by the model trained on three years of historical flight and weather data show a reduction on the take-off time prediction error of about 30% as compared to the ETOTs reported by the ETFMS.Peer ReviewedPostprint (published version

Diverse inflammatory threats modulate astrocytes Ca2+ signaling via connexin43 hemichannels in organotypic spinal slices

Neuroinflammation is an escalation factor shared by a vast range of central nervous system (CNS) pathologies, from neurodegenerative diseases to neuropsychiatric disorders. CNS immune status emerges by the integration of the responses of resident and not resident cells, leading to alterations in neural circuits functions. To explore spinal cord astrocyte reactivity to inflammatory threats we focused our study on the effects of local inflammation in a controlled micro-environment, the organotypic spinal slices, developed from the spinal cord of mouse embryos. These organ cultures represent a complex in vitro model where sensory-motor cytoarchitecture, synaptic properties and spinal cord resident cells, are retained in a 3D fashion and we recently exploit these cultures to model two diverse immune conditions in the CNS, involving different inflammatory networks and products. Here, we specifically focus on the tuning of calcium signaling in astrocytes by these diverse types of inflammation and we investigate the mechanisms which modulate intracellular calcium release and its spreading among astrocytes in the inflamed environment. Organotypic spinal cord slices are cultured for two or three weeks in vitro (WIV) and exposed for 6 h to a cocktail of cytokines (CKs), composed by tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1 β) and granulocyte macrophage-colony stimulating factor (GM-CSF), or to lipopolysaccharide (LPS). By live calcium imaging of the ven- tral horn, we document an increase in active astrocytes and in the occurrence of spontaneous calcium oscillations displayed by these cells when exposed to each inflammatory threat. Through several pharmacological treatments, we demonstrate that intracellular calcium sources and the activation of connexin 43 (Cx43) hemichannels have a pivotal role in increasing calcium intercellular communication in both CKs and LPS conditions, while the Cx43 gap junction communication is apparently reduced by the inflammatory treatments