CAT-CAD: A Computer-Aided Diagnosis Tool for Cataplexy

Narcolepsy with cataplexy is a severe lifelong disorder characterized, among others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). A recent approach for the diagnosis of the disease is based on a completely manual analysis of video recordings of patients undergoing emotional stimulation made on-site by medical specialists, looking for specific facial behavior motor phenomena. We present here the CAT-CAD tool for automatic detection of cataplexy symptoms, with the double aim of (1) supporting neurologists in the diagnosis/monitoring of the disease and (2) facilitating the experience of patients, allowing them to conduct video recordings at home. CAT-CAD includes a front-end medical interface (for the playback/inspection of patient recordings and the retrieval of videos relevant to the one currently played) and a back-end AI-based video analyzer (able to automatically detect the presence of disease symptoms in the patient recording). Analysis of patients’ videos for discovering disease symptoms is based on the detection of facial landmarks, and an alternative implementation of the video analyzer, exploiting deep-learning techniques, is introduced. Performance of both approaches is experimentally evaluated using a benchmark of real patients’ recordings, demonstrating the effectiveness of the proposed solutions

ALDO: An Innovative Digital Framework for Active E-Learning

In this paper, we propose ALDO (Active e-Learning by DOing), a novel, advanced digital framework supporting integrated facilities for effective, active e-Learning. The ALDO framework includes an active repository for collecting/sharing relevant materials, collaborative editing services for enriching so collected “raw” materials, and advanced data visualization tools (e.g., interactive maps, graphs, and timelines) to explore the spatial and temporal dimension of specific data contexts. Although the present research was carried out within the European Horizon 2020 Project DETECt (Detecting Transcultural Identity in European Popular Crime Narratives), focusing on the specific data context of European crime narrative, the generality of ALDO technological framework makes it suitable for any type of study/teaching activity. More in details, ALDO consists of a multi-functional digital infrastructure (back-end) for the integration of collaborative editing and e-Learning activities in formal and informal educational contexts. The platform supports effective services for collecting, sharing, retrieving, and analyzing data, together with advanced online collaboration tools, an e-Learning platform and advanced data visualization tools, all made available to teachers/students through a dedicated Web portal (front-end). The design and creation of above tools and services for teaching, together with their uses, are presented and discussed through a series of real examples taken from DETECt

Cataplexy Detection: Neurologists, You Are Not Alone!

Narcolepsy with cataplexy is a severe lifelong disorder characterized, among the others, by the sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). In this extended abstract, we present two methodologies for the automatic analysis of patients’ videos able to assist neurologists in diagnosing the disease and/or detecting attacks. Indeed, recent findings demonstrated that the detection of abnormal motor behaviors in video recordings of patients undergoing emotional stimulation is effective in characterizing the disease symptoms. Such motor behaviors (ptosis, mouth opening, head drop) are however to be discovered by neurologists through manual inspection of patients’ videos. Automatic content-based video analysis is clearly of immediate help here. Experimental results conducted on real data support the effectiveness of the presented automated techniques

New study practices. Survey on the use of new and old technologies among university students

In a context of “widespread communication”, supported by new tools and work environments, study practices also change, profoundly transforming students’ habits and behaviors. The research in question intends to investigate and describe, through a narrative inquiry process, the study practices of university students, making reference to the integrated use they make of old and new modes of communication, of traditional texts and of digital platforms and tools among the most famous and widespread. The research focuses in particular on the relationship that, through the new tools, is established between the student and the teacher, between the student and colleagues and between the student and the study texts. The analysis aimed at describing new habits, will try to demarcate advantages and difficulties related to the use of digital and to analyze, specifically, how the use of new communication methods or new forms of textuality can favor or inhibit communication within the university environment

Efficient and effective similarity-based video retrieval

The retrieval of videos of interest from large video collections is a main open problem which calls for the definition of new video content characterization techniques in term of both visual descriptors and semantic annotations. In this paper, we present an efficient and effective video retrieval system which profitably exploits the functionalities offered by a semantic-based automatic video annotator using video shots similarity to suggest relevant labels for the videos to be annotated. Similarity queries based on semantic labels and/or visual features are implemented and experimentally compared on real data in order to measure the retrieval contribution of each type of video content information

Pilot Scale Fermentations of Sangiovese: An Overview on the Impact of Saccharomyces and Non-Saccharomyces Wine Yeasts

none6openRomani, Cristina; Lencioni, Livio; Biondi Bartolini, Alessandra; Ciani, Maurizio; Mannazzu, Ilaria; Domizio, PaolaRomani, Cristina; Lencioni, Livio; Biondi Bartolini, Alessandra; Ciani, Maurizio; Mannazzu, Ilaria; Domizio, Paol

Search and comparison of (epi)genomic feature patterns in multiple genome browser tracks

Background: Genome browsers are widely used for locating interesting genomic regions, but their interactive use is obviously limited to inspecting short genomic portions. An ideal interaction is to provide patterns of regions on the browser, and then extract other genomic regions over the whole genome where such patterns occur, ranked by similarity. Results: We developed SimSearch, an optimized pattern-search method and an open source plugin for the Integrated Genome Browser (IGB), to find genomic region sets that are similar to a given region pattern. It provides efficient visual genome-wide analytics computation in large datasets; the plugin supports intuitive user interactions for selecting an interesting pattern on IGB tracks and visualizing the computed occurrences of similar patterns along the entire genome. SimSearch also includes functions for the annotation and enrichment of results, and is enhanced with a Quickload repository including numerous epigenomic feature datasets from ENCODE and Roadmap Epigenomics. The paper also includes some use cases to show multiple genome-wide analyses of biological interest, which can be easily performed by taking advantage of the presented approach. Conclusions: The novel SimSearch method provides innovative support for effective genome-wide pattern search and visualization; its relevance and practical usefulness is demonstrated through a number of significant use cases of biological interest. The SimSearch IGB plugin, documentation, and code are freely available at https://deibgeco.github.io/simsearch-app/ and https://github.com/DEIB-GECO/simsearch-app/

WARP: accurate retrieval of shapes using phase of fourier descriptors and time warping distance

Abstract-Effective and efficient retrieval of similar shapes from large image databases is still a challenging problem in spite of the high relevance that shape information can have in describing image contents. In this paper, we propose a novel Fourier-based approach, called WARP, for matching and retrieving similar shapes. The unique characteristics of WARP are the exploitation of the phase of Fourier coefficients and the use of the Dynamic Time Warping (DTW) distance to compare shape descriptors. While phase information provides a more accurate description of object boundaries than using only the amplitude of Fourier coefficients, the DTW distance permits us to accurately match images even in the presence of (limited) phase shiftings. In terms of classical precision/recall measures, we experimentally demonstrate that WARP can gain, say, up to 35 percent in precision at a 20 percent recall level with respect to Fourier-based techniques that use neither phase nor DTW distance

Distinct MRI pattern of "pseudoresponse" in recurrent glioblastoma multiforme treated with regorafenib: Case report and literature review

: Antiangiogenic agents can induce a distinct MRI pattern in glioblastoma, characterized by a decrease in the contrast enhancement on T1-weighted images and a simultaneous hyperintensity on T2-weighted or fluid-attenuated inversion recovery images