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43 Research products, page 1 of 5

  • Digital Humanities and Cultural Heritage
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  • Other research product . Other ORP type . 2021
    Open Access English
    Publisher: Sarajevo : INSAM Institute for Contemporary Artistic Music
    Country: Serbia

    We have before us the sixth issue of INSAM Journal of Contemporary Music, Art and Technology. This is the second issue in a row dedicated to the global crisis caused by the Covid-19 pandemic. After the overwhelming response from all over the world to the call for papers and provocative inspections that ensued, here we wanted to discuss the ways in which technology shapes and enables work in the areas of music, arts, humanities, and the education process, this time inviting our collaborators to discuss the shortcomings and struggles of the working processes in these fields. The main theme, “Music, Art and Humanities in the Time of Global Crisis”, expanded from the Main Theme section into the interviews as well.

  • Other research product . Other ORP type . 2021
    Open Access
    Authors: 
    Caselli, Tommaso (University of Groningen); Egger, Clara (University of Groningen); Tziafas, Georgios (University of Groningen); De Saint-Phalle, Eugenie (University of Groningen);
    Publisher: DataverseNL

    EXCEPTIUS Corpus v1.0, containing the following data: - raw documents for 21 countries at national level - pre-processed data with spacy-udpipe v1.0 - automatically annotated documents for the identification of exceptional measures at sentence level Country list (ISO 3166-1 alpha-2): AT, BE, HR, CY, CZ, DK, FR, DE, HU, IE, IT, LV, LT, NL, NO, PL, SI, SE, CH, UK Folder structure: each country has a dedicated folder. Inside each folder you will find the following subfolders: - raw_text: the raw text data (.txt format) - processed: the output of the spacy-udpipe v1.0 - each line is a sentence, containing the following info: tokens, lemma, POS, UD dependency relations - model: the predictions of the trained model (XML pre@36 as reported in Table 4 of the paper). Each line is a sentence, separate by 9 tab - each for a exceptional measure class. 1: signals presence of a class. The Italy and Norway folder misses the predictions of the models.

  • Open Access English
    Authors: 
    Chatterjee, Avishek; Nardi, Cosimo; Oberije, Cary; Lambin, Philippe;

    Background: Searching through the COVID-19 research literature to gain actionable clinical insight is a formidable task, even for experts. The usefulness of this corpus in terms of improving patient care is tied to the ability to see the big picture that emerges when the studies are seen in conjunction rather than in isolation. When the answer to a search query requires linking together multiple pieces of information across documents, simple keyword searches are insufficient. To answer such complex information needs, an innovative artificial intelligence (AI) technology named a knowledge graph (KG) could prove to be effective. Methods: We conducted an exploratory literature review of KG applications in the context of COVID-19. The search term used was "covid-19 knowledge graph". In addition to PubMed, the first five pages of search results for Google Scholar and Google were considered for inclusion. Google Scholar was used to include non-peer-reviewed or non-indexed articles such as pre-prints and conference proceedings. Google was used to identify companies or consortiums active in this domain that have not published any literature, peer-reviewed or otherwise. Results: Our search yielded 34 results on PubMed and 50 results each on Google and Google Scholar. We found KGs being used for facilitating literature search, drug repurposing, clinical trial mapping, and risk factor analysis. Conclusions: Our synopses of these works make a compelling case for the utility of this nascent field of research.

  • Open Access
    Authors: 
    White, Luke A.; Maxey, Benjamin S.; Solitro, Giovanni F.; Takei, Hidehiro; Conrad, Steven A.; Alexander, J. Steven;
    Publisher: figshare

    Additional file 13. Combine Pressures Python Script. Custom Python script used to combine pressure waveforms recorded from pressure sensors placed at the inspiratory and expiratory limbs during FALCON ventilation.

  • Open Access
    Authors: 
    Vicens P; Heredia L; Bustamante E; Pérez Y; Domingo JL; Torrente M;

    The petrochemical industry has made the economic development of many local communities possible, increasing employment opportunities and generating a complex network of closely-related secondary industries. However, it is known that petrochemical industries emit air pollutants, which have been related to different negative effects on mental health. In addition, many people around the world are being exposed to highly stressful situations deriving from the COVID-19 pandemic and the lockdowns adopted by national and regional governments. The present study aims to analyse the possible differential effects on various psychological outcomes (stress, anxiety, depression and emotional regulation strategies) stemming from the COVID-19 pandemic and consequent lockdown experienced by individuals living near an important petrochemical complex and subjects living in other areas, nonexposed to the characteristic environmental pollutants emitted by these kinds of complex. The sample consisted of 1607 subjects who answered an ad hoc questionnaire on lockdown conditions, the Perceived Stress Scale (PSS), the Hospital Anxiety and Depression Scale (HADS), the Barratt Impulsivity Scale (BIS) and the Emotional Regulation Questionnaire (ERQ). The results indicate that people living closer to petrochemical complexes reported greater risk perception [K = 73.42, p < 0.001, with a medium size effect (η = 0.061)]. However, no significant relationship between psychological variables and proximity to the focus was detected when comparing people living near to or far away from a chemical/petrochemical complex. Regarding the adverse psychological effects of the first lockdown due to COVID-19 on the general population in Catalonia, we can conclude that the conditions included in this survey were mai

  • Open Access Dutch; Flemish
    Authors: 
    Van Damme, Ilja;
    Country: Belgium
  • Open Access Spanish; Castilian
    Authors: 
    Gudiño Rosero, Jairo Fernando;
    Publisher: Universidad del Rosario
    Country: Colombia

    Using a novel database of 189,000+ Colombian firms and 500,000+ firm executives' names, I study the effect of financial factors, CEOs' centrality (corporate power), and political connections on access to a government bailouts program launched to subsidy wages in the first stages of COVID 19 crisis. Natural Language Processing algorithms and complex networks metrics are used to unveil ownership and control links of politic/economic elites and gauge their closeness to the Colombian President. I find that firm size factors and firm age, instead of political-connections or being run by prominent CEOs/shareholders, explain access to the program. In addition, I find that impacts of the program are positive in terms of salaries and liquidity, but they do not increase with firm size and age. These findings suggest a preference for protecting systemically-important firms (without ex-post economic efficiency) rather than special interests of elites.

  • Open Access Spanish
    Authors: 
    Carbonetti, Adrián;
    Publisher: Casa de Oswaldo Cruz, Fundação Oswaldo Cruz

    Resumen Se comparan los escenarios que se generaron en las pandemias de gripe española de 1918-1919 y de covid-19 en Argentina. Se analizan las políticas gubernamentales y desequilibrios estructurales en esa pandemia tomando como casos la ciudad de Buenos Aires y la provincia de Salta. Posteriormente se estudian los mismos tópicos para la pandemia de covid-19. Se describen las políticas nacionales y se analiza la provincia de Jujuy donde el sistema de salud se saturó. Se concluye que a fin de administrar la pandemia es necesario la elaboración de políticas de consenso y solución de los desequilibrios estructurales del país. Abstract This article compares the scenarios generated in the Spanish flu pandemic of 1918-1919 and covid-19 in Argentina. It analyzes governmental policies and structural imbalances in the earlier pandemic based on case studies of the city of Buenos Aires and the province of Salta. It then studies those same topics for the covid-19 pandemic. It describes national policies and analyzes the province of Jujuy, where the health care system was overwhelmed. It concludes that in order to manage the pandemic it is necessary to create consensus policies to solve the structural imbalanaces in the country.

  • Other research product . Other ORP type . 2021
    Open Access English
    Publisher: Sarajevo : INSAM Institute for Contemporary Artistic Music
    Country: Serbia

    In the seventh issue of INSAM Journal of Contemporary Music, Art and Technology, we are continuing our series on themes dedicated to art, music, and humanities in times of global crisis. After dealing with more general questions regarding these areas of creation, in this volume we are thinking about the issue of mental and bodily health during the Covid-19 pandemic and its possible ties and representations in music and art.

  • Open Access English
    Authors: 
    Giovanni Spitale; Federico Germani; Nikola Biller - Andorno;
    Publisher: Zenodo

    The purpose of this tool is performing NLP analysis on Telegram chats. Telegram chats can be exported as .json files from the official client, Telegram Desktop (v. 2.9.2.0). The files are parsed, the content is used to populate a message dataframe, which is then anonymized. The software calculates and displays the following information: user count (n of users, new users per day, removed users per day); message count (n and relative frequency of messages, messages per day); autocoded messages (anonymized message dataframe with code weights assigned to each message based on a customizable set of regex rules); prevalence of codes (n and relative frequency); prevalence of lemmas (n and relative frequency); prevalence of lemmas segmented by autocode (n and relative frequency); mean sentiment per day; mean sentiment segmented by autocode. The software outputs: messages_df_anon.csv - an anonymized file containing the progressive id of the message, the date, the univocal pseudonym of the sender, and the text; usercount_df.csv - user count dataframe; user_activity_df.csv - user activity dataframe; messagecount_df.csv - message count dataframe; messages_df_anon_coded.csv - an anonymized file containing the progressive id of the message, the date, the univocal pseudonym of the sender, the text, the codes, and the sentiment; autocode_freq_df.csv - general prevalence of codes; lemma_df.csv - lemma frequency; autocode_freq_df_[rule_name].csv - lemma frequency in coded messages, one file per rule; daily_sentiment_df.csv - daily sentiment; sentiment_by_code_df.csv - sentiment segmented by code; messages_anon.txt - anonymized text file generated from the message data frame, for easy import in other software for text mining or qualitative analysis; messages_anon_MaxQDA.txt - anonymized text file generated from the message data frame, formatted specifically for MaxQDA (to track speakers and codes). Dependencies: pandas (1.2.1) json random os re tqdm (4.62.2) datetime (4.3) matplotlib (3.4.3) Spacy (3.1.2) + it_core_news_md wordcloud (1.8.1) Counter feel_it (1.0.3) torch (1.9.0) numpy (1.21.1) transformers (4.3.3) This code is optimized for Italian, however: Lemma analysis is based on spaCy, which provides several other models for other languages ( https://spacy.io/models ) so it can easily be adapted. Sentiment analysis is performed using FEEL-IT: Emotion and Sentiment Classification for the Italian Language (Kudos to Federico Bianchi <f.bianchi@unibocconi.it>; Debora Nozza <debora.nozza@unibocconi.it>; and Dirk Hovy <dirk.hovy@unibocconi.it>). Their work is specific for Italian. To perform sentiment analysis in other languages one could consider nltk.sentiment The code is structured in a Jupyter-lab notebook, heavily commented for future reference. The software comes with a toy dataset comprised of Wikiquotes copy-pasted in a chat created by the research group. Have fun exploring it. {"references": ["Bianchi F, Nozza D, Hovy D. FEEL-IT: Emotion and Sentiment Classification for the Italian Language. In: Proceedings of the 11th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics; 2021. https://github.com/MilaNLProc/feel-it"]}