Workshop to review and progress the reported lists of eu msfd descriptor 3 ( (WKD3LISTS)

info:eu-repo/semantics/publishedVersio

Wishing you a Formidable Christmas

1. O holy night, 2. Por Ti Sere (You raise me up

Tosca the technopera /

"Tosca goes techno...an opera using techno/dance music as the main musical medium ... Set: Nightclub. Rome 2006 - a tragic lover's tale of a rave diva (Tosca) and lighting designer caught up in protecting a Vietnamese prostitute"--Bakk Studios website

Tosca: The technopera: Highlights

"Tosca goes techno...an opera using techno/dance music as the main musical medium ... Set: Nightclub. Rome 2006 - a tragic lover's tale of a rave diva (Tosca) and lighting designer caught up in protecting a Vietnamese prostitute"--Bakk Studios website

Digitalizing and Upgrading Severe Acute Respiratory Infections Surveillance in Malta: System Development

BackgroundIn late 2020, the European Centre for Disease Prevention and Control and Epiconcept started implementing a surveillance system for severe acute respiratory infections (SARI) across Europe. ObjectiveWe sought to describe the process of digitizing and upgrading SARI surveillance in Malta, an island country with a centralized health system, during the COVID-19 pandemic from February to November 2021. We described the characteristics of people included in the surveillance system and compared different SARI case definitions, including their advantages and disadvantages. This study also discusses the process, output, and future for SARI and other public health surveillance opportunities. MethodsMalta has one main public hospital where, on admission, patient data are entered into electronic records as free text. Symptoms and comorbidities are manually extracted from these records, whereas other data are collected from registers. Collected data are formatted to produce weekly and monthly reports to inform public health actions. From October 2020 to February 2021, we established an analogue incidence-based system for SARI surveillance. From February 2021 onward, we mapped key stakeholders and digitized most surveillance processes. ResultsBy November 30, 2021, 903 SARI cases were reported, with 380 (42.1%) positive for SARS-CoV-2. Of all SARI hospitalizations, 69 (7.6%) were admitted to the intensive care unit, 769 (85.2%) were discharged, 27 (3%) are still being treated, and 107 (11.8%) died. Among the 107 patients who died, 96 (89.7%) had more than one underlying condition, the most common of which were hypertension (n=57, 53.3%) and chronic heart disease (n=49, 45.8%). ConclusionsThe implementation of enhanced SARI surveillance in Malta was completed by the end of May 2021, allowing the monitoring of SARI incidence and patient characteristics. A future shift to register-based surveillance should improve SARI detection through automated processes

Annotated corpora and tools of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions (edition 1.0)

The PARSEME shared task aims at identifying verbal MWEs in running texts. Verbal MWEs include idioms (let the cat out of the bag), light verb constructions (make a decision), verb-particle constructions (give up), and inherently reflexive verbs (se suicider 'to suicide' in French). VMWEs were annotated according to the universal guidelines in 18 languages. The corpora are provided in the parsemetsv format, inspired by the CONLL-U format. For most languages, paired files in the CONLL-U format - not necessarily using UD tagsets - containing parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training and test data, tools and the universal guidelines file

PARSEME corpora annotated for verbal multiword expressions (version 1.3)

This multilingual resource contains corpora in which verbal MWEs have been manually annotated. VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). This is the first release of the corpora without an associated shared task. Previous version (1.2) was associated with the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). The data covers 26 languages corresponding to the combination of the corpora for all previous three editions (1.0, 1.1 and 1.2) of the corpora. VMWEs were annotated according to the universal guidelines. The corpora are provided in the cupt format, inspired by the CONLL-U format. Morphological and syntactic information, ­­­­including parts of speech, lemmas, morphological features and/or syntactic dependencies, are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). All corpora are split into training, development and test data, following the splitting strategy adopted for the PARSEME Shared Task 1.2. The annotation guidelines are available online: https://parsemefr.lis-lab.fr/parseme-st-guidelines/1.3 The .cupt format is detailed here: https://multiword.sourceforge.net/cupt-format