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We report the case of a 64-year-old male with significant cardiac comorbidities who reported three episodes of gastrointestinal bleeding. In the third episode, he presented massive hematemesis, anaemia and hypotension. Despite a standard upper endoscopy, a computed tomography (CT) showed an infrarenal abdominal aortic aneurysm and densification of the aortic fat cover. A primary aortoenteric fistula, with acute bleeding and haemodynamic instability, was assumed, and an emergent endovascular repair was performed. Subsequent CT scans and endoscopies demonstrated control of the enteric lesion. After five months, there was no evidence of infection or rebleeding.

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Applying machine learning (ML), and especially deep learning, to understand visual content is becoming common practice in many application areas. However, little attention has been given to its use within the multimedia creative domain. It is true that ML is already popular for content creation, but the progress achieved so far addresses essentially textual content or the identification and selection of specific types of content. A wealth of possibilities are yet to be explored by bringing the use of ML into the multimedia creative process, allowing the knowledge inferred by the former to influence automatically how new multimedia content is created. The work presented in this article provides contributions in three distinct ways towards this goal: firstly, it proposes a methodology to re-train popular neural network models in identifying new thematic concepts in static visual content and attaching meaningful annotations to the detected regions of interest; secondly, it presents varied visual digital effects and corresponding tools that can be automatically called upon to apply such effects in a previously analyzed photo; thirdly, it defines a complete automated creative workflow, from the acquisition of a photograph and corresponding contextual data, through the ML region-based annotation, to the automatic application of digital effects and generation of a semantically aware multimedia story driven by the previously derived situational and visual contextual data. Additionally, it presents a variant of this automated workflow by offering to the user the possibility of manipulating the automatic annotations in an assisted manner. The final aim is to transform a static digital photo into a short video clip, taking into account the information acquired. The final result strongly contrasts with current standard approaches of creating random movements, by implementing an intelligent content- and context-aware video.

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BACKGROUND: Many species of snakes exhibit epidermal surface nanostructures that form complex motifs conferring self-cleaning properties, and sometimes structural iridescence, to their skin. RESULTS: Using confocal microscopy, we show that these specialised cells can be greatly elongated along their left-right axis and that different types of nanostructures are generated by cell borders and cell surface. To characterise the complexity and diversity of these surface gratings, we analysed scanning electron microscopy images of skin sheds from 353 species spanning 19 of the 26 families of snakes and characterised the observed nanostructures with four characters. The full character matrix, as well as one representative SEM image of each of the corresponding species, is available as a MySQL relational database at https://snake-nanogratings.lanevol.org . We then performed continuous-time Markov phylogenetic mapping on the snake phylogeny, providing an evolutionary dynamical estimate for the different types of nanostructures. These analyses suggest that the presence of cell border digitations is the ancestral state for snake skin nanostructures which was subsequently and independently lost in multiple lineages. Our analyses also indicate that cell shape and cell border shape are co-dependent characters whereas we did not find correlation between a simple life habit classification and any specific nanomorphological character. CONCLUSIONS: These results, compatible with the fact that multiple types of nanostructures can generate hydrophobicity, suggest that the diversity and complexity of snake skin surface nano-morphology are dominated by phylogenetic rather than habitat-specific functional constraints. The present descriptive study opens the perspective of investigating the cellular self-organisational cytoskeletal processes controlling the patterning of different skin surface nanostructures in snakes and lizards.

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