Incorporation of Radio Frequency Identification Tag in Dentures to Facilitate Recognition and Forensic Human Identification

Forensic identification using odontology is based on the comparison of ante-mortem and post mortem dental records. The insertion of a radio frequency identification (RFId) tag into dentures could be used as an aid to identify decomposed bodies, by storing personal identification data in a small transponder that can be radio-transmitted to a reader connected to a computer. A small passive, 12 x 2,1 mm, read-only RFId-tag was incorporated into the manufacture of three trial complete upper dentures and tested for a signal. The aim of this article is to demonstrate the feasibility of manufacturing such a dental prosthesis, the technical protocols for its implantation in the denture resin and its working principles. Future research and tests are required in order to verify human compatibility of the tagged denture and also to evaluate any potential deterioration in strength when subjected to high temperatures, or for damage resulting from everyday wear and tear. It should also be able to withstand the extreme conditions resulting from major accidents or mass disasters and procedures used to perform a forensic identification

AI-KG: an Automatically Generated Knowledge Graph of Artificial Intelligence

Scientific knowledge has been traditionally disseminated and preserved through research articles published in journals, conference proceedings, and online archives. However, this article-centric paradigm has been often criticized for not allowing to automatically process, categorize, and reason on this knowledge. An alternative vision is to generate a semantically rich and interlinked description of the content of research publications. In this paper, we present the Artificial Intelligence Knowledge Graph (AI-KG), a large-scale automatically generated knowledge graph that describes 820K research entities. AI-KG includes about 14M RDF triples and 1.2M reified statements extracted from 333K research publications in the field of AI, and describes 5 types of entities (tasks, methods, metrics, materials, others) linked by 27 relations. AI-KG has been designed to support a variety of intelligent services for analyzing and making sense of research dynamics, supporting researchers in their daily job, and helping to inform decision-making in funding bodies and research policymakers. AI-KG has been generated by applying an automatic pipeline that extracts entities and relationships using three tools:DyGIE++, Stanford CoreNLP, and the CSO Classifier. It then integrates and filters the resulting triples using a combination of deep learning and semantic technologies in order to produce a high-quality knowledge graph. This pipeline was evaluated on a manually crafted gold standard, yielding competitive results. AI-KG is available under CC BY 4.0 and can be downloaded as a dump or queried via a SPARQL endpoint

Improving Editorial Workflow and Metadata Quality at Springer Nature

Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in online libraries. For this reason, Springer Nature, the world's largest academic book publisher, has traditionally entrusted this task to their most expert editors. These editors manually analyse all new books, possibly including hundreds of chapters, and produce a list of the most relevant topics. Hence, this process has traditionally been very expensive, time-consuming, and confined to a few senior editors. For these reasons, back in 2016 we developed Smart Topic Miner (STM), an ontology-driven application that assists the Springer Nature editorial team in annotating the volumes of all books covering conference proceedings in Computer Science. Since then STM has been regularly used by editors in Germany, China, Brazil, India, and Japan, for a total of about 800 volumes per year. Over the past three years the initial prototype has iteratively evolved in response to feedback from the users and evolving requirements. In this paper we present the most recent version of the tool and describe the evolution of the system over the years, the key lessons learnt, and the impact on the Springer Nature workflow. In particular, our solution has drastically reduced the time needed to annotate proceedings and significantly improved their discoverability, resulting in 9.3 million additional downloads. We also present a user study involving 9 editors, which yielded excellent results in term of usability, and report an evaluation of the new topic classifier used by STM, which outperforms previous versions in recall and F-measure

Development and implementation of the AIDA International Registry for patients with Periodic Fever, Aphthous stomatitis, Pharyngitis, and cervical Adenitis syndrome

Objective: Aim of this paper is to illustrate the methodology, design, and development of the AutoInflammatory Disease Alliance (AIDA) International Registry dedicated to patients with the Periodic Fever, Aphthous stomatitis, Pharyngitis, and cervical Adenitis (PFAPA) syndrome. Methods: This is a physician-driven, non-population- and electronic-based registry proposed to gather real-world demographics, clinical, laboratory, instrumental and socioeconomic data from PFAPA patients. Data recruitment is realized through the on-line Research Electronic Data Capture (REDCap) tool. This registry is thought to collect standardized information for clinical research leading to solid real-life evidence. The international scope and the flexibility of the registry will facilitate the realization of cutting-edge study projects through the constant updating of variables and the possible merging and transfer of data between current and future PFAPA registries. Results: A total of 112 centers have already been involved from 23 countries and 4 continents starting from August 24th, 2021, to April 6th, 2022. In total 56/112 have already obtained the formal approval from their local Ethics Committees. The platform counts 321 users (113 principal investigators, 203 site investigators, two lead investigators, and three data managers). The registry collects retrospective and prospective data using 3,856 fields organized into 25 instruments, including PFAPA patient's demographics, medical histories, symptoms, triggers/risk factors, therapies, and impact on the healthcare systems. Conclusions: The development of the AIDA International Registry for PFAPA patients will enable the on-line collection of standardized data prompting real-life studies through the connection of worldwide groups of physicians and researchers. This project can be found on NCT 05200715

Clinical and laboratory features associated with macrophage activation syndrome in Still’s disease: data from the international AIDA Network Still’s Disease Registry

To characterize clinical and laboratory signs of patients with Still's disease experiencing macrophage activation syndrome (MAS) and identify factors associated with MAS development. Patients with Still's disease classified according to internationally accepted criteria were enrolled in the AutoInflammatory Disease Alliance (AIDA) Still's Disease Registry. Clinical and laboratory features observed during the inflammatory attack complicated by MAS were included in univariate and multivariate logistic regression analysis to identify factors associated to MAS development. A total of 414 patients with Still's disease were included; 39 (9.4%) of them developed MAS during clinical history. At univariate analyses, the following variables were significantly associated with MAS: classification of arthritis based on the number of joints involved (p = 0.003), liver involvement (p = 0.04), hepatomegaly (p = 0.02), hepatic failure (p = 0.01), axillary lymphadenopathy (p = 0.04), pneumonia (p = 0.03), acute respiratory distress syndrome (p < 0.001), platelet abnormalities (p < 0.001), high serum ferritin levels (p = 0.009), abnormal liver function tests (p = 0.009), hypoalbuminemia (p = 0.002), increased LDH (p = 0.001), and LDH serum levels (p < 0.001). At multivariate analysis, hepatomegaly (OR 8.7, 95% CI 1.9-52.6, p = 0.007) and monoarthritis (OR 15.8, 95% CI 2.9-97.1, p = 0.001), were directly associated with MAS, while the decade of life at Still's disease onset (OR 0.6, 95% CI 0.4-0.9, p = 0.045), a normal platelet count (OR 0.1, 95% CI 0.01-0.8, p = 0.034) or thrombocytosis (OR 0.01, 95% CI 0.0-0.2, p = 0.008) resulted to be protective. Clinical and laboratory factors associated with MAS development have been identified in a large cohort of patients based on real-life data. © 2023, The Author(s)