CorTexT platform

@article{McIlwaine2021,
title = {A state-of-the-art techno-economic review of distributed and embedded energy storage for energy systems},
author = {Neil McIlwaine and Aoife M. Foley and D. John Morrow and Dlzar Al Kez and Chongyu Zhang and Xi Lu and Robert J. Best},
url = {https://www.sciencedirect.com/science/article/pii/S0360544221007106},
doi = {https://doi.org/10.1016/j.energy.2021.120461},
issn = {0360-5442},
year = {2021},
date = {2021-08-15},
journal = {Energy},
volume = {229},
pages = {120461},
abstract = {Renewable energy is projected to play an important role in reducing greenhouse gas emissions and in realising the climate change goals. Large scale development of variable renewable energy, which is regarded as non-dispatchable, requires additional power system quality services such as voltage regulation, frequency regulation and inertial response. Energy storage provides an important means to supply these services but there are many uncertainties in terms of technology, market readiness, economics, and regulatory requirements. The aim of this study is to undertake a global state-of-the-art review of the techno-economic and regulatory status of energy storage and power quality services at the distribution level. The review will establish the global trends in electricity markets that have seen high levels of renewable energy penetration. The results of the investigation indicate that further research is required to qualify, quantify, and value the installation of mass energy storage particularly at the distribution level.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{León-Vargas2021,
title = {Two Decades of Research in Artificial Pancreas: Insights from a Bibliometric Analysis},
author = {Fabian León-Vargas and Jineth Andrea Arango Oviedo and Héctor Javier Luna Wandurraga},
url = {https://doi.org/10.1177/19322968211005500},
doi = {10.1177/19322968211005500},
year = {2021},
date = {2021-04-15},
journal = {Journal of Diabetes Science and Technology},
volume = {0},
number = {0},
pages = {19322968211005500},
abstract = {Artificial pancreas is a well-known research topic devoted to achieving better glycemic outcomes that has been attracting increasing attention over the years. However, there is a lack of systematic, chronological, and synthesizing studies that show the background of the knowledge generation in this field. This study implements a bibliometric analysis to recognize the main documents, type of publications, research categories, countries, keywords, organizations, and authors related to this topic.Methods:Web of Science core collection database was accessed from 2000 to 2020 in order to select high-quality scientific documents based on a specific search query. Bibexcel, MS Excel, Power BI, R-Studio, VOSviewer, and CorText software were used for a descriptive and network analysis based on the local database obtained. Bibliometric parameters as the h-index, frequencies, co-authorship and co-ocurrences were computed.Results:A total of 756 documents were included that show a growing scientific production on this topic with an increasing contribution from engineering. Outstanding authors, organizations, and countries were identified. An analysis of trends in research was conducted according to the scientific categories of the Web of Science database to identify the main research interests of the last 2 decades and the emerging areas with greater prominence in the coming years. A keyword network analysis allowed to identify the main stages in the development of the AP research over time.Conclusions:Results reveal a comprehensive background of the knowledge generation for the AP topic during the last 2 decades, which has been strengthened with international collaborations and a remarkable interdisciplinarity between endocrinology and engineering, giving rise to a growing number of research areas over time, where computer science and medical informatics stand out as the main emerging research areas.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Testoni2021,
title = {Whose shoulders is health research standing on? Determining the key actors and contents of the prevailing biomedical research agenda},
author = {Federico E. Testoni and Mercedes García Carrillo and Marc-André Gagnon and Cecilia Rikap and Matías Blaustein
},
editor = {Quinn Grundy, University of Toronto, CANADA},
url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249661},
doi = { https://doi.org/10.1371/journal.pone.0249661},
year = {2021},
date = {2021-04-07},
journal = {PLoS ONE},
abstract = {Conflicts of interest in biomedical research can influence research results and drive research agendas away from public health priorities. Previous agenda-setting studies share two shortfalls: they only account for direct connections between academic institutions and firms, as well as potential bias based on researchers’ personal beliefs. This paper’s goal is to determine the key actors and contents of the prevailing health and biomedical sciences (HBMS) research agenda, overcoming these shortfalls.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Kabudi2021,
title = {AI-enabled adaptive learning systems: A systematic mapping of the literature},
author = {Tumaini Kabudi and Ilias Pappas and Dag Håkon Olsen},
url = {https://www.sciencedirect.com/science/article/pii/S2666920X21000114},
doi = {https://doi.org/10.1016/j.caeai.2021.100017},
issn = {2666-920X},
year = {2021},
date = {2021-03-31},
journal = {Computers and Education: Artificial Intelligence},
volume = {2},
pages = {100017},
abstract = {Mobile internet, cloud computing, big data technologies, and significant breakthroughs in Artificial Intelligence (AI) have all transformed education. In recent years, there has been an emergence of more advanced AI-enabled learning systems, which are gaining traction due to their ability to deliver learning content and adapt to the individual needs of students. Yet, even though these contemporary learning systems are useful educational platforms that meet students’ needs, there is still a low number of implemented systems designed to address the concerns and problems faced by many students. Based on this perspective, a systematic mapping of the literature on AI-enabled adaptive learning systems was performed in this work. A total of 147 studies published between 2014 and 2020 were analysed. The major findings and contributions of this paper include the identification of the types of AI-enabled learning interventions used, a visualisation of the co-occurrences of authors associated with major research themes in AI-enabled learning systems and a review of common analytical methods and related techniques utilised in such learning systems. This mapping can serve as a guide for future studies on how to better design AI-enabled learning systems to solve specific learning problems and improve users’ learning experiences.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}