cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/ac0c-8043
title: Traffic Flow Prediction and program codes

description: This dataset mainly consists 1) source codes of wide-attention and deep model (WADC); 2) datasets to evaluate the performance of the proposed model. Datasets are obtained from the Caltrans Performance Measurement System (CPeMS) http://pems.doc.ca.gov; and Fremont Bridge Bicycle Counter (FBBC), https://data.seattle.gov.For more details, please refer to our paper entitled "Wide-Attention and Deep-Composite Model for Traffic Flow Prediction in Transportation Cyber-Physical Systems", accepted to appear in IEEE Transactions on Industrial Informatics and githubhttps://github.com/zhoujunhao/wadc.
DOI: 10.21227/mjy8-fz43
title: Traffic Flow Prediction and program codes

description: This dataset mainly consists 1) source codes of wide-attention and deep model (WADC); 2) datasets to evaluate the performance of the proposed model. Datasets are obtained from the Caltrans Performance Measurement System (CPeMS) http://pems.doc.ca.gov; and Fremont Bridge Bicycle Counter (FBBC), https://data.seattle.gov.For more details, please refer to our paper entitled "Wide-Attention and Deep-Composite Model for Traffic Flow Prediction in Transportation Cyber-Physical Systems", accepted to appear in IEEE Transactions on Industrial Informatics and githubhttps://github.com/zhoujunhao/wadc.
DOI: 10.21227/w3f0-nr98
title: NSL-KDD in JSON Format

description: NSL-KDD is a benchmark dataset available in a comma-separated text file. Many advance analytics tools prefer data set in a JSON format due to its ability to self describe. We converted the benchmark dataset to a JSON format as a part of our research work. This dataset in a JSON format will be very useful for researchers doing analysis using advance analytics tools.
DOI: 10.5281/zenodo.3402868
title: Supplementary Material for the paper "Efficient Strategies for CEGAR-based Model Checking"

description: Supplementary material for the paper "Efficient Strategies for CEGAR-based Model Checking" by Akos Hajdu and Zoltan Micskei. The material includes a detailed report (report.html) and all artifacts to replicate our measurements and analysis (artifact.tar.gz). <em>This is the version that corresponds to the final, published paper.</em>
DOI: 10.5281/zenodo.3893955
title: Supplementary Material for the paper "Efficient Strategies for CEGAR-based Model Checking"

description: Supplementary material for the paper "Efficient Strategies for CEGAR-based Model Checking" by Akos Hajdu and Zoltan Micskei. The material includes a detailed report (report.html) and all artifacts to replicate our measurements and analysis (artifact.tar.gz). <em>Version 1.2.0 corresponds to the final, published paper. This version (1.2.1) is a minor update that added two new plots.</em>
DOI: 10.5281/zenodo.1252784
title: Supplementary Material for the paper "Efficient Strategies for CEGAR-based Model Checking"

description: Supplementary material for the paper "Efficient Strategies for CEGAR-based Model Checking" by Akos Hajdu and Zoltan Micskei. The material includes a detailed report (report.html) and all artifacts to replicate our measurements and analysis (artifact.tar.gz). <em>Version 1.2.0 corresponds to the final, published paper. This version (1.2.1) is a minor update that added two new plots.</em>
DOI: 10.21227/134f-7171
title: NSL-KDD in AVRO Format

description: NSL-KDD is a benchmark dataset in security available in a comma-separated text format. Many big data analytics tools like Google BigQuery, Hadoop, Spark etc. prefer dataset in AVRO format for its advantages of lightweight and fast data serialisation and deserialization. This, in turn, results in delivering very good data ingestion performance. We have converted comma-separated values into AVRO format as a part of our research work. This dataset in AVRO format will be very useful for researchers working with cloud-based big data analytics tools.
DOI: 10.5281/zenodo.3894005
title: Dataset for paper "Two-dimensional particle-in-cell simulations of magnetosonic waves in the dipole magnetic field: On a constant L-shell"

description: * Reduced datasets for figures in the manuscript. * Code for producing the simulation data.
DOI: 10.5281/zenodo.3894004
title: Dataset for paper "Two-dimensional particle-in-cell simulations of magnetosonic waves in the dipole magnetic field: On a constant L-shell"

description: * Reduced datasets for figures in the manuscript. * Code for producing the simulation data.
DOI: 10.5281/zenodo.3893846
title: Development and validation of a machine learning model for use as an automated artificial intelligence tool to predict mortality risk in patients with COVID-19

description: <strong>Background</strong> New York City quickly became an epicenter of the COVID-19 pandemic. Due to a sudden and massive increase in patients during COVID-19 pandemic, healthcare providers incurred an exponential increase in workload which created a strain on the staff and limited resources. As this is a new infection, predictors of morbidity and mortality are not well characterized. <strong>Methods</strong> We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3000 hospital admissions with COVID-19. A variable importance algorithm was used for interpretability and understanding of performance and predictors. <strong>Findings</strong> We built a model with 84-97% accuracy to identify predictors and patients with high risk of mortality, and developed an automated artificial intelligence (AI) notification tool that does not require manual calculation by the busy clinician. Oximetry, respirations, blood urea nitrogen, lymphocyte percent, calcium, troponin and neutrophil percentage were important features and key ranges were identified that contributed to a 50% increase in patients’ mortality prediction score. With an increasing negative predictive value (NPV) starting 0.90 after the second day of admission, we are able more confidently able identify likely survivors. This study serves as a use case of a model with visualizations to aide clinicians with a better understanding of the model and predictors of mortality. Additionally, an example of the operationalization of the model via an AI notification tool is illustrated.
DOI: 10.5281/zenodo.3893845
title: Development and validation of a machine learning model for use as an automated artificial intelligence tool to predict mortality risk in patients with COVID-19

description: <strong>Background</strong> New York City quickly became an epicenter of the COVID-19 pandemic. Due to a sudden and massive increase in patients during COVID-19 pandemic, healthcare providers incurred an exponential increase in workload which created a strain on the staff and limited resources. As this is a new infection, predictors of morbidity and mortality are not well characterized. <strong>Methods</strong> We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3000 hospital admissions with COVID-19. A variable importance algorithm was used for interpretability and understanding of performance and predictors. <strong>Findings</strong> We built a model with 84-97% accuracy to identify predictors and patients with high risk of mortality, and developed an automated artificial intelligence (AI) notification tool that does not require manual calculation by the busy clinician. Oximetry, respirations, blood urea nitrogen, lymphocyte percent, calcium, troponin and neutrophil percentage were important features and key ranges were identified that contributed to a 50% increase in patients’ mortality prediction score. With an increasing negative predictive value (NPV) starting 0.90 after the second day of admission, we are able more confidently able identify likely survivors. This study serves as a use case of a model with visualizations to aide clinicians with a better understanding of the model and predictors of mortality. Additionally, an example of the operationalization of the model via an AI notification tool is illustrated.
DOI: 10.5281/zenodo.3893424
title: Food security in ASEAN countries: an overview of rice self-sufficiency amidst the COVID-19 pandemic

description: Data for analysis in the study on <strong>Food security in ASEAN countries: an overview of rice self-sufficiency amidst the COVID-19 pandemic</strong>
DOI: 10.5281/zenodo.3893423
title: Food security in ASEAN countries: an overview of rice self-sufficiency amidst the COVID-19 pandemic

description: Data for analysis in the study on <strong>Food security in ASEAN countries: an overview of rice self-sufficiency amidst the COVID-19 pandemic</strong>
DOI: 10.5281/zenodo.3893789
title: Supplementary Information for Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

description: Supplementary information for<br> Páll, S., Zhmurov, A., Bauer, P., Abraham, M., Lundborg, M., Gray, A., Hess, B, & Lindahl, E.. (2020). Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS. The Journal of Chemical Physics, 2020 Contains benchmark methodology description as well as all inputs used in the application performance benchmarks included the paper.
DOI: 10.5281/zenodo.3893788
title: Supplementary Information for Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

description: Supplementary information for<br> Páll, S., Zhmurov, A., Bauer, P., Abraham, M., Lundborg, M., Gray, A., Hess, B, & Lindahl, E.. (2020). Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS. The Journal of Chemical Physics, 2020 Contains benchmark methodology description as well as all inputs used in the application performance benchmarks included the paper.
DOI: 10.15161/oar.it/30428
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.3866196
title: Artificial Intelligence (AI), in the Breast Cancer Screening Programme Questionnaire and Data

description: The goal of this study is to gain insight into the level of trust of women in the Netherlands, in the decisions made by radiologists with the support of different applications of Artificial Intelligence (AI), in the Breast Cancer Screening Programme. Gaining insight into your level of trust in the decisions made by radiologists and AI regarding whether you have breast cancer or not, is of high importance, as this will help to anticipate which steps can be taken by hospitals and software developers, in the near future. The survey consists of 10 introductory questions and 42 statements and takes approximately 10 minutes to complete.
DOI: 10.5281/zenodo.3866195
title: Artificial Intelligence (AI), in the Breast Cancer Screening Programme Questionnaire and Data

description: The goal of this study is to gain insight into the level of trust of women in the Netherlands, in the decisions made by radiologists with the support of different applications of Artificial Intelligence (AI), in the Breast Cancer Screening Programme. Gaining insight into your level of trust in the decisions made by radiologists and AI regarding whether you have breast cancer or not, is of high importance, as this will help to anticipate which steps can be taken by hospitals and software developers, in the near future. The survey consists of 10 introductory questions and 42 statements and takes approximately 10 minutes to complete.
DOI: 10.1285/i22840753n16p1
title: Frontespizio
DOI: 10.1285/i22840753n16p3
title: Indice
DOI: 10.1285/i22840753n16p5
title: Emozioni
DOI: 10.1285/i22840753n16p7
title: Media empatici, emozioni e gamification: dalla quarta rivoluzione industriale alla società postpandemica = Empathic media, emotions and gamification: from the Fourth Industrial Revolution to the postpandemic society

description: The Fourth Industrial Revolution represents the most advanced frontier of technological innovation that will transform the economy of the future in a disruptive way, introducing new devices such as: self-guided vehicles, 3D printing, advanced robotics, new materials, digital platforms, gene editing etc. The expression "empathic media" means not only the platforms and devices that develop forms of "emotional artificial intelligence", but also all those innovations who have been able to enhance the emotional nature of the human being in commercial terms. The ever closer relationship between emotions, artificial intelligence and creativity represents a dominant trend of our time that can be examined, for example, by comparing the recent cinematographic imagination with some innovations on the market. Through this comparison we can understand the way in which new technologies enhance the emotional dimension that has become a central aspect not only in human-machine interaction but also more generally of a new concept of design, communication and consumption. By analyzing the social context created as a consequence of the coronavirus, we discuss a classification based on three scenarios that it seems they can work as interpretative models of the relation between technology and everyday life: 1) Isolation, 2) Integration and 3) Co-design. Each of them is expressed as a form of experience in which the media are the medium and therefore the environment capable of creating, nurturing and hosting particular feelings and emotions. The media are transfigured as empathic tools because they allow "suffering together", as the etymology of the term prefigures, producing different types of experiential sharing
DOI: 10.1285/i22840753n16p27
title: Entertainment Highway in Cina. Il ruolo delle piattaforme online nell'analisi della reputazione sociale = Entertainment Highway in China. The role of online platforms in shaping the social credit system

description: This article provides an analysis on the history of the Chinese Social System taking into account three directions: first, it refers to policy documents issued by the State Council of PRC; second, it refers to the experience of Sina Weibo Credit System; third, it focuses on the failed experience of the Sesame Credit System. The present research has a double aim. First, it highlights the importance of the media history to frame relevant Chinese Internet dynamics; second, it suggests an alternative to study the Chinese Social Credit System going beyond to the dichotomy vision state – citizens and its preconditions mainly based on state surveillance and Confucianism traditions. Whereas, the present article, in line with the rationale of the special issue, highlights the role played by Chinese private companies and more importantly, their attitude to shape the structure and the management of their platforms and services boosting the importance of entertainment.
DOI: 10.1285/i22840753n16p49
title: Football Re(me)mediation: i meme e l’estetizzazione dell'emozione calcistica nelle community social = Football Re(me)mediation: Memes and The Aestheticization of Football Emotions in Social Newtorks Communities

description: The relationship between sport, emotions and media is immediate. Football has a strong ability to emotionally involve huge masses of fans, thanks to the dramaturgical and ritualistic qualities of each match and thanks to the collective identification in footballer-heroes (Bifulco e Tirino, 2018). These qualities are further reinvigorated by media stories, which transform fans into media users (Gau, James e Kim, 2009). Due to the emergence of the SMS triangle (Sport, Media, Sponsor) (Martelli 2011, 2014) the figure of the fan is increasingly indistinguishable from the figures of the user and the consumer. However, football fans increasingly have the opportunity to participate in contemporary cultural production, for example by generating UGC to be disseminated in media environments such as social networks. Through the concept of “radical mediation”, Grusin argues that the media are configured as emotional environments. On the other hand, social networks constitute a privileged territory of exteriorization of one’s emotional commitment (Boccia Artieri et al. 2017). Starting from these sociological and mediological perspectives, the aim of our paper is to investigate media modalities and processes by which football fans’ emotions are remediated, on social networks, through the production and dissemination of meme. Meme are relevant examples of user-generated content (Boccia Artieri, 2012, Jenkins, Ford e Green, 2013), and also are central media objects to understand the participatory cultures of web 2.0 and the typical logic of remix cultures. Our paper will try to highlight how these grassroots practices, within a new participatory aesthetic, elaborate the connection between mediation and affection (Grusin 2017), (social) media and emotions, football communication (mainstream and bottom-top) and fans.
DOI: 10.1285/i22840753n16p81
title: Gli elementi nostalgici dei punta-e-clicca italiani degli Anni Dieci = Nostalgic elements in Italian point-and-click video games of the 2010s

description: This paper inquiries the insertion of nostalgic elements in Italian point-and-click video games of the 2010s, highlighting those elements that still survive in spite of being out-of-date from the points of view of technology and gameplay. After having clarified the notions of "point-and-click" and nostalgia, the paper presents the corpus of titles considered in the analysis, that is, thirty-seven Italian point-and-click video games of the last decade. The choice of such corpus is based on three reasons: limiting the size of the corpus to make it manageable; maintaining an adequate temporal distance from the classic and post-classic point-and-click video games, such a lapse of time being a precondition of nostalgia; focussing on video games "indie", a label including all the corpus's titles. Three categories of nostalgic insertion were detected: "technical", "thematically dense" and "thematically rarefied". The first includes titles technically similar to the classics (1990-1995), which they idealise and emulate by an explicit interface (e.g. SCUMM v. 4). The second comprises games whose inspiration is rather that of the second half of the Nineties, when new technological solutions were introduced (e.g. pseudo-3D). The third contains products more innovative than nostalgic, still interspersed with quotations. Three case studies are presented to testimony of these categories, respectively: Chronicle of Innsmouth (PsychoDev, 2017), Detective Gallo (Footprints Games, 2018) and The Wardrobe (C.I.N.I.C. Games, 2017).
DOI: 10.1285/i22840753n16p99
title: Niente sarà più come prima. Il Covid-19 come narrazione apocalittica di successo = Nothing will ever be the same: COVID 19, an apocalyptic narrative of success

description: The paper aims to investigate the interactions between public, media and authorities that emerged during the Covid-19 emergency as variables of a state of systemic anxiety, characteristic of information societies. The Coronavirus crisis involved around four billion individuals. No pandemic or traumatic event on a global scale, however serious or risky, had ever managed to lead authorities and multitudes to such a resolution. The measures prescribed for the containment of the pandemic implied maximum physical confinement and the widest freedom guaranteed to our digital avatars. That was the opportunity for an unprecedented and massive transhumance in digital territories. Using the paradigms of fear as a latent and functional emotional constant in advanced information society, (Beck, 1986; Bauman, 2006), the investigation makes a comparison between some mechanisms of defense against states of shock and some of the media narratives of the emergency by which the italian public constructed its own mediated experience of the pandemic during the quarantine. In particular, the theme of the apocalyptic/millennial narrative is studied in more detail, in the light of various literary theories that describe its characteristics and dynamics. The aim is to demonstrate how the collective anxiety state can be traced back to a constant oscillation on different semantic clusters, rather than a variable consequence of concrete events.
DOI: 10.1285/i22840753n16p123
title: Percorsi di Ricerca
DOI: 10.1285/i22840753n16p125
title: Beyond screens, beyond borders. Il caso SKAM = Beyond screens, beyond borders. SKAM, a case study

description: The Norwegian series SKAM is one of the most interesting products of contemporary television, as a match between the structure of transmedia storytelling and the established tv genre of the teen-drama. In 2018 SKAM became an international success.The series is firstly published in real time, in the form of short clips on the dedicated website, and it is later assembled on television or on the streaming platform in weekly episodes. This format has trascended the borders between screens and between states as no other product before. If the transmedial structure of SKAM perfectly fits a media consumption practice linked to the briefness of contents shared on social media, the intrinsic power of this format allowed the original series to find a huge following in many countries thanks to appropriation experiences like fan subbing or fan art. The temporality of the series’ fruition is integrated in the daily routine of the viewers, thus cementing the parasocial bonds with the characters
DOI: 10.1285/i22840753n16p136
title: Colophon
DOI: 10.5281/zenodo.3894431
title: Extended Data for "Area-based conservation in the 21st century"

description: Source Data for Figs. 1 and 2 and all data tables found in the Supplementary Information for "Area-based conservation in the 21st century"
DOI: 10.5281/zenodo.3750498
title: Extended Data for "Area-based conservation in the 21st century"

description: Source Data for Figs. 1 and 2 and all data tables found in the Supplementary Information for "Area-based conservation in the 21st century"