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Kerren, Andreas, Dr.-Ing.ORCID iD iconorcid.org/0000-0002-0519-2537
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Simaki, V., Paradis, C. & Kerren, A. (2019). A two-step procedure to identify stance constructions in discourse from political blogs. Corpora
Open this publication in new window or tab >>A two-step procedure to identify stance constructions in discourse from political blogs
2019 (English)In: Corpora, ISSN 1749-5032, E-ISSN 1755-1676Article in journal (Refereed) Accepted
Abstract [en]

The Brexit Blog Corpus (BBC) is a collection of texts extracted from political blogs, which, in a recent study, was annotated according to a cognitive-functional stance framework by two independent annotators (Annotator A and B) using semantic criteria (Simaki et al. 2017). The goal was to label the stance or stances taken based on the overall meaning of a set of utterances. The annotators were not instructed to identify the lexical forms that were used to express the stances. In this study, we make use of those stance labelled utterances as a springboard to approach stance-taking in text from the opposite point of view, namely from how stance is realised through language. Our aim is to provide a description of the specific lexical elements used to express six stance categories, i.e., CONTRARIETY, HYPOTHETICALITY,  NECESSITY, PREDICTION, SOURCE OF KNOWLEDGE, and UNCERTAINTY. To this end, we followed a two-step experimental procedure. First, we performed a quantitative analysis of the stance labelled utterances in order to identify the lexical realisations of each stance category. Second, we carried out a meta-annotation of the data. Annotator B was instructed to single out the actual lexical forms of the constructions that triggered his semantic stance category decisions. This meta-annotation procedure made it possible for us to sift out the most salient lexical realisations of the constructions of each of the six category types on the basis of the qualitative assessments made by Annotator B. We then compared the results of the quantitative and the qualitative approaches, and we present a list of shared stance expressions for each stance category type.

Keywords
stance-taking, social media text analysis, stance construction, meta-annotation, corpus annotation, Brexit, Blogs
National Category
General Language Studies and Linguistics
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-79384 (URN)
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Note

TO BE PUBLISHED!!

Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-03-06
Chatzimparmpas, A., Bibi, S., Zozas, I. & Kerren, A. (2019). Analyzing the Evolution of JavaScript Applications. In: 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019): . Paper presented at 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019), May 4-5, 2019, Heraklion, Greece.
Open this publication in new window or tab >>Analyzing the Evolution of JavaScript Applications
2019 (English)In: 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019), 2019Conference paper, Published paper (Refereed)
Abstract [en]

Software evolution analysis can shed light on various aspects of software development and maintenance. Up to date, there is little empirical evidence on the evolution of JavaScript (JS) applications in terms of maintainability and changeability, even though JavaScript is among the most popular scripting languages for front-end web applications. In this study, we investigate JS applications’ quality and changeability trends over time by examining the relevant Laws of Lehman. We analyzed over 7,500 releases of JS applications and reached some interesting conclusions. The results show that JS applications continuously change and grow, there are no clear signs of quality degradation while the complexity remains the same over time, despite the fact that the understandability of the code deteriorates.

Keywords
Software Evolution, Lehman’s Laws, JavaScript, Maintenance, Software Quality
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-80639 (URN)
Conference
14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019), May 4-5, 2019, Heraklion, Greece
Note

To be published!

Available from: 2019-02-18 Created: 2019-02-18 Last updated: 2019-03-06
Kerren, A., Hurter, C. & Braz, J. (Eds.). (2019). Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019, Prague, Czech Republic, February 25-27, 2019: Volume 3: IVAPP. Paper presented at International Conference on Information Visualization Theory and Applications (IVAPP '19), Prague, Czech Republic, February 25-27, 2019. SciTePress
Open this publication in new window or tab >>Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019, Prague, Czech Republic, February 25-27, 2019: Volume 3: IVAPP
2019 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

This book contains the proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) which was organized and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC), in cooperation with ACM SIGCHI, ACM SIGGRAPH, AFIG, Eurographics and UXPA International.

The proceedings here published demonstrate new and innovative solutions and highlight technical problems in each field that are challenging and worthwhile being disseminated to the interested research audiences.

VISIGRAPP 2019 was organized to promote a discussion forum about the conference’s research topics be- tween researchers, developers, manufacturers and end-users, and to establish guidelines in the development of more advanced solutions.

We received a high number of paper submissions for this edition of VISIGRAPP, 396 in total, with contribu- tions from all five continents. This attests to the success and global dimension of VISIGRAPP. To evaluate each submission, we used a double-blind evaluation method where each paper was reviewed by two to six experts from the International Program Committee (IPC).

The IPC selected for oral presentation and for publication as full papers 12 papers from GRAPP, 6 for HUCAPP, 12 papers for IVAPP, and 36 papers for VISAPP, which led to a result for the full-paper accep- tance ratio of 17% and a high-quality program. Apart from the above full papers, the conference program also features 88 short papers and 115 poster presentations. We hope that these conference proceedings, which are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index, SCOPUS, DBLP, Semantic Scholar, Google Scholar and EI, will help the Computer Vision, Imaging, Visualization and Computer Graphics communities to find interesting research work. Moreover, we are proud to inform that the program also includes four plenary keynote lectures, given by internationally distinguished researchers, namely Daniel McDuff (Microsoft, United States), Diego Gutierrez (Universidad de Zaragoza, Spain), Jiri Matas (Czech Technical University in Prague, Faculty of Electrical Engineering, Czech Republic) and Dima Damen (University of Bristol, United Kingdom), thus contributing to increase the overall quality of the con- ference and to provide a deeper understanding of the conference’s interest fields.

Furthermore, a short list of the presented papers will be selected to be expanded into a forthcoming book of VISIGRAPP Selected Papers to be published by Springer during 2019 in the CCIS series. Also, a short list of presented papers will be selected for publication of extended and revised versions in a special issue of the Open Access Information Science Journal (IVAPP) and in a special issue of the Pattern Recognition and Artificial Intelligence Journal (VISAPP). All papers presented at this conference will be available at the SCITEPRESS Digital Library. Three awards are delivered at the closing session, to recognize the best conference paper, the best student paper and the best poster for each of the four conferences.

We would like to express our thanks, first of all, to the authors of the technical papers, whose work and dedication made possible to put together a program that we believe to be very exciting and of high technical quality. Next, we would like to thank the Area Chairs, all the members of the program committee and auxiliary reviewers, who helped us with their expertise and time. We would also like to thank the invited speakers for their invaluable contribution and for sharing their vision in their talks. Special thanks should be addressed to the INSTICC Steering Committee whose invaluable work made this event possible.

We wish you all an exciting conference and an unforgettable stay in Prague, Czech Republic. We hope to meet you again for the next edition of VISIGRAPP, details of which are available at http://www.visigrapp.org.

Place, publisher, year, edition, pages
SciTePress, 2019. p. 355
Keywords
Information Visualization
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-81078 (URN)978-989-758-354-4 (ISBN)
Conference
International Conference on Information Visualization Theory and Applications (IVAPP '19), Prague, Czech Republic, February 25-27, 2019
Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-03-21Bibliographically approved
Kucher, K., Martins, R. M. & Kerren, A. (2018). Analysis of VINCI 2009–2017 Proceedings. In: Karsten Klein, Yi-Na Li, and Andreas Kerren (Ed.), Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden: . Paper presented at 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden (pp. 97-101). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Analysis of VINCI 2009–2017 Proceedings
2018 (English)In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 97-101Conference paper, Published paper (Refereed)
Abstract [en]

Both the metadata and the textual contents of scientific publications can provide us with insights about the development and the current state of the corresponding scientific community. In this short paper, we take a look at the proceedings of VINCI from the previous years and conduct several types of analyses. We summarize the yearly statistics about different types of publications, identify the overall authorship statistics and the most prominent contributors, and analyze the current community structure with a co-authorship network. We also apply topic modeling to identify the most prominent topics discussed in the publications. We hope that the results of our work will provide insights for the visualization community and will also be used as an overview for researchers previously unfamiliar with VINCI.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018
Keywords
meta-analysis, survey, overview, visualization, scientific literature, topic modeling
National Category
Computer Sciences Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-75857 (URN)10.1145/3231622.3231641 (DOI)978-1-4503-6501-7 (ISBN)
Conference
11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden
Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-09-11Bibliographically approved
Kucher, K., Skeppstedt, M. & Kerren, A. (2018). Application of Interactive Computer-Assisted Argument Extraction to Opinionated Social Media Texts. In: Karsten Klein, Yi-Na Li, and Andreas Kerren (Ed.), Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18): . Paper presented at 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden (pp. 102-103). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Application of Interactive Computer-Assisted Argument Extraction to Opinionated Social Media Texts
2018 (English)In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18) / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 102-103Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The analysis of various opinions and arguments in textual data can be facilitated by automatic topic modeling methods; however, the exploration and interpretation of the resulting topics and terms may prove to be difficult to the analysts. Opinions, stances, arguments, topics, terms, and text documents are usually connected with many-to-many relationships for such tasks. Exploratory visual analysis with interactive tools can help the analysts to get an overview of the topics and opinions, identify particularly interesting documents, and describe main themes of various arguments. In our previous work, we introduced an interactive tool called Topics2Themes that was used for topic and theme analysis of vaccination-related discussion texts with a limited set of stance categories. In this poster paper, we describe an application of Topics2Themes to a different genre of data, namely, political comments from Reddit, and multiple sentiment and stance categories detected with automatic classifiers.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018
Keywords
visualization, interaction, topic modeling, argument extraction, text visualization, sentiment analysis, sentiment visualization, stance analysis, stance visualization, annotation
National Category
Computer Sciences Language Technology (Computational Linguistics) Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-75856 (URN)10.1145/3231622.3232505 (DOI)978-1-4503-6501-7 (ISBN)
Conference
11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden
Funder
Swedish Research Council, 2016-06681
Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-09-11Bibliographically approved
Simaki, V., Panagiotis, S., Paradis, C. & Kerren, A. (2018). Detection of Stance-Related Characteristics in Social Media Text. In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence (SETN '18): . Paper presented at The 10th Hellenic Conference on Artificial Intelligence (SETN '18), 9-15 July 2018, Patras, Greece. ACM Publications, Article ID 38.
Open this publication in new window or tab >>Detection of Stance-Related Characteristics in Social Media Text
2018 (English)In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence (SETN '18), ACM Publications, 2018, article id 38Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a study for the identification of stance-related features in text data from social media. Based on our previous work on stance and our findings on stance patterns, we detected stance-related characteristics in a data set from Twitter and Facebook. We extracted various corpus-, quantitative- and computational-based features that proved to be significant for six stance categories (contrariety, hypotheticality, necessity, prediction, source of knowledge, and uncertainty), and we tested them in our data set. The results of a preliminary clustering method are presented and discussed as a starting point for future contributions in the field. The results of our experiments showed a strong correlation between different characteristics and stance constructions, which can lead us to a methodology for automatic stance annotation of these data.

Place, publisher, year, edition, pages
ACM Publications, 2018
Keywords
stance-taking, text clustering, feature extraction, social media text
National Category
Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-71735 (URN)10.1145/3200947.3201017 (DOI)978-1-4503-6433-1 (ISBN)
Conference
The 10th Hellenic Conference on Artificial Intelligence (SETN '18), 9-15 July 2018, Patras, Greece
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2018-03-22 Created: 2018-03-22 Last updated: 2018-11-29Bibliographically approved
Kucher, K., Paradis, C. & Kerren, A. (2018). DoSVis: Document Stance Visualization. In: Alexandru C. Telea, Andreas Kerren, and José Braz (Ed.), Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '18): . Paper presented at International Conference on Information Visualization Theory and Applications (IVAPP), Funchal-Madeira, Portugal, 27-29 January, 2018 (pp. 168-175). SciTePress, 3
Open this publication in new window or tab >>DoSVis: Document Stance Visualization
2018 (English)In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '18) / [ed] Alexandru C. Telea, Andreas Kerren, and José Braz, SciTePress, 2018, Vol. 3, p. 168-175Conference paper, Published paper (Refereed)
Abstract [en]

Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer’s attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature. 

Place, publisher, year, edition, pages
SciTePress, 2018
Keywords
Stance Visualization, Sentiment Visualization, Text Visualization, Stance Analysis, Sentiment Analysis, Text Analytics, Information Visualization, Interaction
National Category
Computer Sciences Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-68428 (URN)10.5220/0006539101680175 (DOI)978-989-758-289-9 (ISBN)
Conference
International Conference on Information Visualization Theory and Applications (IVAPP), Funchal-Madeira, Portugal, 27-29 January, 2018
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2018-04-12Bibliographically approved
Martins, R. M. & Kerren, A. (2018). Efficient Dynamic Time Warping for Big Data Streams. In: Proceedings of the IEEE International Conference on Big Data (Big Data '18): Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management. Paper presented at 3rd Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management at IEEE Big Data '18, 10-13 December, 2018, Seattle, USA (pp. 2924-2929). IEEE
Open this publication in new window or tab >>Efficient Dynamic Time Warping for Big Data Streams
2018 (English)In: Proceedings of the IEEE International Conference on Big Data (Big Data '18): Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management, IEEE, 2018, p. 2924-2929Conference paper, Published paper (Refereed)
Abstract [en]

Many common data analysis and machine learning algorithms for time series, such as classification, clustering, or dimensionality reduction, require a distance measurement between pairs of time series in order to determine their similarity. A variety of measures can be found in the literature, each with their own strengths and weaknesses, but the Dynamic Time Warping (DTW) distance measure has occupied an important place since its early applications for the analysis and recognition of spoken word. The main disadvantage of the DTW algorithm is, however, its quadratic time and space complexity, which limits its practical use to relatively small time series. This issue is even more problematic when dealing with streaming time series that are continuously updated, since the analysis must be re-executed regularly and with strict running time constraints. In this paper, we describe enhancements to the DTW algorithm that allow it to be used efficiently in a streaming scenario by supporting an append operation for new time steps with a linear complexity when an exact, error-free DTW is needed, and even better performance when either a Sakoe-Chiba band is used, or when a sliding window is the desired range for the data. Our experiments with one synthetic and four natural data sets have shown that it outperforms other DTW implementations and the potential errors are, in general, much lower than another state-of-the-art approximated DTW technique.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
time series, dynamic time warping, streaming
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-78735 (URN)10.1109/BigData.2018.8621878 (DOI)978-1-5386-5035-6 (ISBN)978-1-5386-5036-3 (ISBN)
Conference
3rd Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management at IEEE Big Data '18, 10-13 December, 2018, Seattle, USA
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-01-29
Simaki, V., Paradis, C. & Kerren, A. (2018). Evaluating stance-annotated sentences from the Brexit Blog Corpus: A quantitative linguistic analysis. ICAME Journal/International Computer Archive of Modern English, 42(1), 133-166
Open this publication in new window or tab >>Evaluating stance-annotated sentences from the Brexit Blog Corpus: A quantitative linguistic analysis
2018 (English)In: ICAME Journal/International Computer Archive of Modern English, ISSN 0801-5775, E-ISSN 1502-5462, Vol. 42, no 1, p. 133-166Article in journal (Refereed) Published
Abstract [en]

This paper offers a formally driven quantitative analysis of stance-annotated sentences in the Brexit Blog Corpus (BBC). Our goal is to highlight linguistic features that determine the formal profiles of six stance categories (contrariety, hypotheticality, necessity, prediction, source of knowledge and uncertainty) in a subset of the BBC. The study has two parts: firstly, it examines a large number of formal linguistic features that occur in the sentences in order to describe the specific characteristics of each category, and secondly, it compares characteristics in the entire data set in order to determine linguistic similarities throughout the data set. We show that among the six stance categories in the corpus, contrariety and necessity are the most discriminative ones, with the former using longer sentences, more conjunctions, more repetitions and shorter forms than the sentences expressing other stances. The latter has longer lexical forms but shorter sentences, which are syntactically more complex. We show that stance in our data set is expressed in sentences with around 21 words per sentence. The sentences consist mainly of alphabetical characters forming a varied vocabulary without special forms, such as digits or special characters.

Place, publisher, year, edition, pages
De Gruyter Open, 2018
Keywords
stance-taking, corpus annotation, political blog text, statistical analysis, formal features
National Category
Language Technology (Computational Linguistics) Specific Languages
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-70768 (URN)10.1515/icame-2018-0007 (DOI)
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-10-17Bibliographically approved
Biedl, T. & Kerren, A. (Eds.). (2018). Graph Drawing and Network Visualization: 26th International Symposium, GD 2018, Barcelona, Spain, September 26-28, 2018, Proceedings. Paper presented at The 26th International Symposium on Graph Drawing and Network Visualization (GD '18), Barcelona, Spain, September 26-28, 2018. Springer
Open this publication in new window or tab >>Graph Drawing and Network Visualization: 26th International Symposium, GD 2018, Barcelona, Spain, September 26-28, 2018, Proceedings
2018 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

This book constitutes the refereed proceedings of the 26th International Symposium on Graph Drawing and Network Visualization, GD 2018, held in Barcelona, Spain, in September 2018. 

The 41 full papers presented in this volume were carefully reviewed and selected from 85 submissions. They were organized in topical sections named: planarity variants; upward drawings; RAC drawings; orders; crossings; crossing angles; contact representations; specialized graphs and trees; partially fixed drawings, experiments; orthogonal drawings; realizability; and miscellaneous. The book also contains one invited talk in full paper length and the Graph Drawing contest report.

Place, publisher, year, edition, pages
Springer, 2018. p. xviii, 666
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 11282
Keywords
graph drawing, visualization, computational geometry, graph algorithms, design and analysis of algorithms, empirical studies in visualization, graphs and surfaces, engineering of network visualization algorithms and systems, geometric graph theory, cognitive studies on graph drawing readability and user interaction
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-78301 (URN)10.1007/978-3-030-04414-5 (DOI)978-3-030-04413-8 (ISBN)978-3-030-04414-5 (ISBN)
Conference
The 26th International Symposium on Graph Drawing and Network Visualization (GD '18), Barcelona, Spain, September 26-28, 2018
Available from: 2018-10-13 Created: 2018-10-13 Last updated: 2018-12-11Bibliographically approved
Projects
Advances in the description and explanation of stance in discourse using visual and computational text analytics - StaViCTA [2012-05659_VR]; Linnaeus University; Publications
Simaki, V., Paradis, C. & Kerren, A. (2019). A two-step procedure to identify stance constructions in discourse from political blogs. CorporaSimaki, V., Panagiotis, S., Paradis, C. & Kerren, A. (2018). Detection of Stance-Related Characteristics in Social Media Text. In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence (SETN '18): . Paper presented at The 10th Hellenic Conference on Artificial Intelligence (SETN '18), 9-15 July 2018, Patras, Greece. ACM Publications, Article ID 38.
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0519-2537

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