Classification of finite simple Lie conformal superalgebras

The notion of a Lie conformal superalgebra encodes an axiomatic descrption of singular parts of the operator product expansions of chiral fields in conformal field theory. In the paper we give a detailed proof of the classification of all finite simple Lie conformal superalgebras. We also classify all their central extensions.Comment: 29 pages, LaTe

Artefatti e inclusione organizzativa. Rappresentare simbolicamente la disabilità

L’inclusione delle persone con disabilità può essere osservata attraverso la sua rappresentazione. Le differenze tra il simbolo ISA (Wheelchair symbol) e le sue più recenti versioni diventano così un modo per esplorare come queste rappresentazioni nei contesti organizzativi possano avere un effetto inclusivo, guardando a questi simboli come artefatti organizzativi

RICKETS AT THE MEDICI COURT OF FLORENCE: THE CASE OF DON FILIPPINO (1577-1582)

Among the children found in the crypt of the Grand Duke Giangastone in S. Lorenzo Basilica (Florence), the skeletal remains of a 5-year-old child still wearing his fine high social status clothing were recovered. This child of the Medici family was identified as Don Filippino (1577-1582), son of the Grand Duke Francesco I (1541-1587) and Giovanna from Austria (1547-1578). The prince showed several pathological deformities of the cranial and post-cranial skeleton, including enlargement of the cranium, thinning of the cranial vault bones (craniotabes), platybasia and marked bending of femora, tibiae and fibulae. Differential diagnosis suggests that Don Filippino was affected by rickets. The occurrence of this metabolic disease related to vitamin D deficiency in a Renaissance high social class individual can be explained by the practice of very prolonged breast-feeding, up until to sunlight. Historical sources describe Don Filippino as frail and sickly, with frequent illnesses and persistent slight fevers, and it can be supposed that the child was frequently confined indoors, especially in the cold season. Integration of osteoarchaeological evidence with historical documentation suggests that bone lesions observed in the skeletal remains of Don Filippino are compatible with a diagnosis of rickets, caused by the custom of prolonged breast-feeding associated with inadequate sunlight exposure two years of age. Maternal milk contains insufficient vitamin D ratios and retarded weaning severely exposes children to a higher risk of developing rickets, especially if dietary habits are combined with inadequate exposure

Decoding sensorimotor information from superior parietal lobule of macaque via Convolutional Neural Networks

Despite the well-recognized role of the posterior parietal cortex (PPC) in processing sensory information to guide action, the differential encoding properties of this dynamic processing, as operated by different PPC brain areas, are scarcely known. Within the monkey's PPC, the superior parietal lobule hosts areas V6A, PEc, and PE included in the dorso-medial visual stream that is specialized in planning and guiding reaching movements. Here, a Convolutional Neural Network (CNN) approach is used to investigate how the information is processed in these areas. We trained two macaque monkeys to perform a delayed reaching task towards 9 positions (distributed on 3 different depth and direction levels) in the 3D peripersonal space. The activity of single cells was recorded from V6A, PEc, PE and fed to convolutional neural networks that were designed and trained to exploit the temporal structure of neuronal activation patterns, to decode the target positions reached by the monkey. Bayesian Optimization was used to define the main CNN hyper-parameters. In addition to discrete positions in space, we used the same network architecture to decode plausible reaching trajectories. We found that data from the most caudal V6A and PEc areas outperformed PE area in the spatial position decoding. In all areas, decoding accuracies started to increase at the time the target to reach was instructed to the monkey, and reached a plateau at movement onset. The results support a dynamic encoding of the different phases and properties of the reaching movement differentially distributed over a network of interconnected areas. This study highlights the usefulness of neurons' firing rate decoding via CNNs to improve our understanding of how sensorimotor information is encoded in PPC to perform reaching movements. The obtained results may have implications in the perspective of novel neuroprosthetic devices based on the decoding of these rich signals for faithfully carrying out patient's intentions.(C) 2022 Published by Elsevier Ltd

Motor decoding from the posterior parietal cortex using deep neural networks

Objective. Motor decoding is crucial to translate the neural activity for brain-computer interfaces (BCIs) and provides information on how motor states are encoded in the brain. Deep neural networks (DNNs) are emerging as promising neural decoders. Nevertheless, it is still unclear how different DNNs perform in different motor decoding problems and scenarios, and which network could be a good candidate for invasive BCIs. Approach. Fully-connected, convolutional, and recurrent neural networks (FCNNs, CNNs, RNNs) were designed and applied to decode motor states from neurons recorded from V6A area in the posterior parietal cortex (PPC) of macaques. Three motor tasks were considered, involving reaching and reach-to-grasping (the latter under two illumination conditions). DNNs decoded nine reaching endpoints in 3D space or five grip types using a sliding window approach within the trial course. To evaluate decoders simulating a broad variety of scenarios, the performance was also analyzed while artificially reducing the number of recorded neurons and trials, and while performing transfer learning from one task to another. Finally, the accuracy time course was used to analyze V6A motor encoding. Main results. DNNs outperformed a classic Naive Bayes classifier, and CNNs additionally outperformed XGBoost and Support Vector Machine classifiers across the motor decoding problems. CNNs resulted the top-performing DNNs when using less neurons and trials, and task-to-task transfer learning improved performance especially in the low data regime. Lastly, V6A neurons encoded reaching and reach-to-grasping properties even from action planning, with the encoding of grip properties occurring later, closer to movement execution, and appearing weaker in darkness. Significance. Results suggest that CNNs are effective candidates to realize neural decoders for invasive BCIs in humans from PPC recordings also reducing BCI calibration times (transfer learning), and that a CNN-based data-driven analysis may provide insights about the encoding properties and the functional roles of brain regions

Traumatic rupture of the thoracic aorta: Ten years of delayed management

ObjectiveTraumatic rupture of the thoracic aorta is a highly fatal condition in which patient outcome is strongly conditioned by other associated injuries. Delayed aortic treatment has been proposed to improve results.MethodsThe charts of 69 patients with traumatic rupture of the thoracic aorta observed between 1980 and 2003 were reviewed. Patients were grouped according the timing of repair: group I, immediate repair (21 patients); and group II, delayed repair (48 patients). In group II, 45 patients were treated surgically or by endovascular procedure.ResultsIn-hospital mortalities were 4 of 21 patients (19%) in group I and 2 of 48 patients (4.2%) in group II. There were 3 cases of paraplegia in group I and none in group II.ConclusionImprovement of patient outcome with traumatic rupture of the thoracic aorta can be achieved by delaying surgical repair until after management of major associated injuries if there are no signs of impending rupture. Endovascular treatment is feasible and safe and may represent a valid alternative to open surgery in selected cases

Preoperative rectal cancer staging with phased-array MR

<p>Abstract</p> <p>Background</p> <p>We retrospectively reviewed magnetic resonance (MR) images of 96 patients with diagnosis of rectal cancer to evaluate tumour stage (T stage), involvement of mesorectal fascia (MRF), and nodal metastasis (N stage).</p> <p>Our gold standard was histopathology.</p> <p>Methods</p> <p>All studies were performed with 1.5-T MR system (Symphony; Siemens Medical System, Erlangen, Germany) by using a phased-array coil. Our population was subdivided into two groups: the first one, formed by patients at T1-T2-T3, N0, M0 stage, whose underwent MR before surgery; the second group included patients at Tx N1 M0 and T3-T4 Nx M0 stage, whose underwent preoperative MR before neoadjuvant chemoradiation therapy and again 4-6 wks after the end of the treatment for the re-staging of disease.</p> <p>Our gold standard was histopathology.</p> <p>Results</p> <p>MR showed 81% overall agreement with histological findings for T and N stage prediction; for T stage, this rate increased up to 95% for pts of group I (48/96), while for group II (48/96) it decreased to 75%.</p> <p>Preoperative MR prediction of histologically involved MRF resulted very accurate (sensitivity 100%; specificity 100%) also after chemoradiation (sensitivity 100%; specificity 67%).</p> <p>Conclusions</p> <p>Phased-array MRI was able to clearly estimate the entire mesorectal fat and surrounding pelvic structures resulting the ideal technique for local preoperative rectal cancer staging.</p

A multidisciplinary approach to estimating wolf population size for long-term conservation

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Cold atoms in space: community workshop summary and proposed road-map

We summarise the discussions at a virtual Community Workshop on Cold Atoms in Space concerning the status of cold atom technologies, the prospective scientific and societal opportunities offered by their deployment in space, and the developments needed before cold atoms could be operated in space. The cold atom technologies discussed include atomic clocks, quantum gravimeters and accelerometers, and atom interferometers. Prospective applications include metrology, geodesy and measurement of terrestrial mass change due to, e.g., climate change, and fundamental science experiments such as tests of the equivalence principle, searches for dark matter, measurements of gravitational waves and tests of quantum mechanics. We review the current status of cold atom technologies and outline the requirements for their space qualification, including the development paths and the corresponding technical milestones, and identifying possible pathfinder missions to pave the way for missions to exploit the full potential of cold atoms in space. Finally, we present a first draft of a possible road-map for achieving these goals, that we propose for discussion by the interested cold atom, Earth Observation, fundamental physics and other prospective scientific user communities, together with the European Space Agency (ESA) and national space and research funding agencies.publishedVersio