From unstructured texts to semantic story maps

Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper presents a semi-automatic workflow to produce story maps from textual documents containing territory data. An expert first assembles one territory-contextual document containing text and images. Then, automatic processes use natural language processing and Wikidata services to (i) extract key concepts (entities) and geospatial coordinates associated with the territory, (ii) assemble a logically-ordered sequence of enriched story-map events, and (iii) openly publish online story maps and an interoperable Linked Open Data semantic knowledge base for event exploration and inter-story correlation analyses. Our workflow uses an Open Science-oriented methodology to publish all processes and data. Through our workflow, we produced story maps for the value chains and territories of 23 rural European areas of 16 countries. Through numerical evaluation, we demonstrated that territory experts considered the story maps effective in describing their territories, and appropriate for communicating with citizens and stakeholders

The Hypermedia Dante Network Project

In this paper, we present the Hypermedia Dante Network (HDN) project. First, we briefly introduce the relevant state of the art on Dante’s commentaries and their digital representation, and we outline the project goals. In the main section, we present the core features of the HDN ontology, an evolution of the DanteSources ontology that aims at representing knowledge about Dante’s primary sources as they are identified by a vast range of commentaries. Then, we describe the tool that has been developed to process Dante’s commentaries and populate the HDN ontology. Finally, we comment on the project’s usability and possible outcomes for both scholars and common users

The Hypermedia Dante Network Project

In this paper, we present the Hypermedia Dante Network (HDN) project. First, we briefly introduce the relevant state of the art on Dante’s commentaries and their digital representation, and we outline the project goals. In the main section, we present the core features of the HDN ontology, an evolution of the DanteSources ontology that aims at representing knowledge about Dante’s primary sources as they are identified by a vast range of commentaries. Then, we describe the tool that has been developed to process Dante’s commentaries and populate the HDN ontology. Finally, we comment on the project’s usability and possible outcomes for both scholars and common users

A formal representation of the Divine Comedy’s primary sources: The Hypermedia Dante Network ontology

Hypermedia Dante Network (HDN) is a 3-year Italian National Research Project, started in 2020, which aims to enrich the functionalities of the DanteSources Digital Library to efficiently represent knowledge about the primary sources of Dante’s Comedy. DanteSources allows users to retrieve and visualize the list and the distribution of Dante's primary sources that have been identified by recent commentaries of five of Dante’s minor works (i.e. Vita nova, De vulgari eloquentia, Convivio, De Monarchia, and Rime). The digital library is based on a formal ontology expressed in Resource Description Framework Schema (RDFS) language. Based on the DanteSources experience, the HDN project aims to formally represent the primary sources of the Divine Comedy whose identification is based on several commentaries included in the Dartmouth Dante Project corpus. To reach this goal, we restructured and extended the DanteSources ontology to provide a wider and more complete representation of the knowledge concerning the primary sources of the Comedy. In this article, we present the result of this effort, i.e. the HDN ontology. The ontology is expressed in OWL and has as reference ontologies the CIDOC CRM and its extension FRBRoo, including its in-progress reformulation LRMoo. We also briefly describe the semi-automatic tool that will be used by the scholars to populate the ontology

Cytotoxic Effect Induced by Sicilian Oregano Essential Oil in Human Breast Cancer Cells

Origanum vulgare L. is an aromatic plant that exerts antibacterial, antioxidant, anti-inflammatory, and antitumor activities, mainly due to its essential oil (EO) content. In this study, we investigated the possible mechanism underlying the in vitro antitumor activity of EO extracted by hydrodistillation of dried flowers and leaves of Origanum vulgare L. grown in Sicily (Italy) in MDA-MB-231 and MCF-7 breast cancer cell lines. Gas chromatography–mass spectrometry analysis of Oregano essential oil (OEO) composition highlighted the presence of twenty-six major phytocompounds, such as p-cymene, γ-terpinene, and thymoquinone p-acetanisole. OEO possesses strong antioxidant capacity, as demonstrated by the DPPH test. Our studies provided evidence that OEO reduces the viability of both MCF-7 and MDA-MB-231 cells. The cytotoxic effect of OEO on breast cancer cells was partially counteracted by the addition of z-VAD-fmk, a general caspase inhibitor. Caspases and mitochondrial dysfunction appeared to be involved in the OEO-induced death mechanism. Western blotting analysis showed that OEO-induced activation of pro-caspases-9 and -3 and fragmentation of PARP decreased the levels of Bcl-2 and Bcl-xL while increasing those of Bax and VDAC. In addition, fluorescence microscopy and cytofluorimetric analysis showed that OEO induces a loss of mitochondrial membrane potential in both cell lines. Furthermore, we tested the effects of p-cymene, γ-terpinene, thymoquinone, and p-acetanisole, which are the main components of OEO. Our findings highlighted that the effect of OEO on MDA-MB-231 and MCF-7 cells appears to be mainly due to the combination of different constituents of OEO, providing evidence of the potential use of OEO for breast cancer treatment

A Roadmap for Craft Understanding, Education, Training, and Preservation

A roadmap is proposed that defines a systematic approach for craft preservation and its evaluation. The proposed roadmap aims to deepen craft understanding so that blueprints of appropriate tools that support craft documentation, education, and training can be designed while achieving preservation through the stimulation and diversification of practitioner income. In addition to this roadmap, an evaluation strategy is proposed to validate the efficacy of the developed results and provide a benchmark for the efficacy of craft preservation approaches. The proposed contribution aims at the catalyzation of craft education and training with digital aids, widening access and engagement to crafts, economizing learning, increasing exercisability, and relaxing remoteness constraints in craft learning.ISSN:2571-940

Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-CoV-2 infection: a multicentre cohort study (PREDI-CO study)

Objectives: We aimed to develop and validate a risk score to predict severe respiratory failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19).Methods: We performed a multicentre cohort study among hospitalized (>24 hours) patients diagnosed with COVID-19 from 22 February to 3 April 2020, at 11 Italian hospitals. Patients were divided into derivation and validation cohorts according to random sorting of hospitals. SRF was assessed from admission to hospital discharge and was defined as: SpO(2) <93% with 100% FiO(2), respiratory rate >30 breaths/min or respiratory distress. Multivariable logistic regression models were built to identify predictors of SRF, beta-coefficients were used to develop a risk score. Trial Registration NCT04316949.Results: We analysed 1113 patients (644 derivation, 469 validation cohort). Mean (+/- SD) age was 65.7 (+/- 15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in the derivation and validation cohorts, respectively. At multivariate analysis, risk factors for SRF in the derivation cohort assessed at hospitalization were age >= 70 years (OR 2.74; 95% CI 1.66-4.50), obesity (OR 4.62; 95% CI 2.78-7.70), body temperature >= 38 degrees C (OR 1.73; 95% CI 1.30-2.29), respiratory rate >= 22 breaths/min (OR 3.75; 95% CI 2.01-7.01), lymphocytes <= 900 cells/mm(3) (OR 2.69; 95% CI 1.60-4.51), creatinine >= 1 mg/dL (OR 2.38; 95% CI 1.59-3.56), C-reactive protein >= 10 mg/dL (OR 5.91; 95% CI 4.88 -7.17) and lactate dehydrogenase >= 350 IU/L (OR 2.39; 95% CI 1.11-5.11). Assigning points to each variable, an individual risk score (PREDI-CO score) was obtained. Area under the receiver-operator curve was 0.89 (0.86-0.92). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 71.6% (65%-79%), 89.1% (86%-92%), 74% (67%-80%) and 89% (85%-91%), respectively. PREDI-CO score showed similar prognostic ability in the validation cohort: area under the receiver-operator curve 0.85 (0.81e0.88). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 80% (73%-85%), 76% (70%-81%), 69% (60%-74%) and 85% (80%-89%), respectively.Conclusion: PREDI-CO score can be useful to allocate resources and prioritize treatments during the COVID-19 pandemic. (c) 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved