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description Publicationkeyboard_double_arrow_right Conference object , Preprint , Article 2024 FrancePublisher:IOP Publishing Funded by:EC | FCCISEC| FCCISAuthors: Dalena, Barbara; Da Silva, Tatiana; Chance, Antoine; Ghribi, Adnan;Dalena, Barbara; Da Silva, Tatiana; Chance, Antoine; Ghribi, Adnan;After the discovery of the Higgs boson at the LHC, particle physics community is exploring and proposing next accelerators, to address the remaining open questions on the underlying mechanisms and constituents of the present universe. One of the studied possibilities is FCC (Future Circular Collider), a 100 km long collider at CERN. The feasibility study of this future proposed accelerator implies the definition of tolerances on magnets imperfections and of the strategies of correction in order to guarantee the target performances of the High Energy Booster ring. The efficiency of the correction scheme, used to control the orbit, directly bounds the corrector needs and magnet tolerances. Analytic formulae give a first estimation of the average rms value of the required linear correctors' strengths and of the allowed magnets misalignments and field quality along the entire ring. The distribution of the correctors along the ring is simulated in order to verify the quality of the residual orbit after the proposed correction strategy and compared with the analytical predictions. First specifications of the orbit correctors strength and tolerances for the alignment of the main elements of the ring are presented. The limits of the studied correction scheme and method are also discussed. International audience
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2687/2/022004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 FinlandPublisher:Institute of Electrical and Electronics Engineers (IEEE) Zhilin Lu; Rongpeng Li; Kun Lu; Xianfu Chen; Ekram Hossain; Zhifeng Zhao; Honggang Zhang;Along with the springing up of the semantics-empowered communication (SemCom) research, it is now witnessing an unprecedentedly growing interest towards a wide range of aspects (e.g., theories, applications, metrics and implementations) in both academia and industry. In this work, we primarily aim to provide a comprehensive survey on both the background and research taxonomy, as well as a detailed technical tutorial. Specifically, we start by reviewing the literature and answering the "what" and "why" questions in semantic transmissions. Afterwards, we present the ecosystems of SemCom, including history, theories, metrics, datasets and toolkits, on top of which the taxonomy for research directions is presented. Furthermore, we propose to categorize the critical enabling techniques by explicit and implicit reasoning-based methods, and elaborate on how they evolve and contribute to modern content & channel semantics-empowered communications. Besides reviewing and summarizing the latest efforts in SemCom, we discuss the relations with other communication levels (e.g., conventional communications) from a holistic and unified viewpoint. Subsequently, in order to facilitate future developments and industrial applications, we also highlight advanced practical techniques for boosting semantic accuracy, robustness, and large-scale scalability, just to mention a few. Finally, we discuss the technical challenges that shed light on future research opportunities. This paper has been accepted for publication in the IEEE Communications Surveys and Tutorials
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/comst....Article . 2024 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/comst....Article . 2024 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/comst.2023.3333342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Conference object 2023 SwitzerlandPublisher:IEEE Funded by:EC | INODEEC| INODEAuthors: Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems. So far the majority of benchmarks rely on pattern-based SPARQL query generation approaches. The subsequent natural language (NL) question generation is conducted through crowdsourcing or other automated methods, such as rule-based paraphrasing or NL question templates. Although some of these datasets are of considerable size, their pitfall lies in their pattern-based generation approaches, which do not always generalize well to the vague and linguistically diverse questions asked by humans in real-world contexts. In this paper, we introduce Spider4SPARQL - a new SPARQL benchmark dataset featuring 9,693 previously existing manually generated NL questions and 4,721 unique, novel, and complex SPARQL queries of varying complexity. In addition to the NL/SPARQL pairs, we also provide their corresponding 166 knowledge graphs and ontologies, which cover 138 different domains. Our complex benchmark enables novel ways of evaluating the strengths and weaknesses of modern KGQA systems. We evaluate the system with state-of-the-art KGQA systems as well as LLMs, which achieve only up to 45\% execution accuracy, demonstrating that Spider4SPARQL is a challenging benchmark for future research. Comment: 10 pages, 5 figures, accepted at IEEE BigData Conference 2023, 8th IEEE Special Session on Machine Learning on Big Data (MLBD 2023)
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/bigdata59044.2023.10386182&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 IrelandPublisher:University Library J. C. Senckenberg Publicly fundedAuthors: Louis Mahon; Carl Vogel;Louis Mahon; Carl Vogel;handle: 2262/104231
This paper presents FASTFOOD, a rule-based natural language generation (NLG) program for cooking recipes. We consider the representation of cooking recipes as discourse representation, because the meaning of each sentence needs to consider the context of the others. Our discourse representation system is based on states of affairs and transtions between states of affairs, and does not use discourse referents. Recipes are generated by using an automated theorem-proving procedure to select the ingredients and instructions, with ingredients corresponding to axioms and instructions to implications. FASTFOOD also contains a temporal optimization module which can rearrange the recipe to make it more time efficient for the user, e.g. the recipe specifies to chop the vegetables while the rice is boiling. The system is described in detail, including the decision to forgo discourse referents and how plausible representations of nouns and verbs emerge purely as a by-product of the practical requirements of efficiently representing recipe content. A comparison is then made with existing recipe generation systems, NLG systems more generally, and automated theorem provers.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article 2023Publisher:IEEE Funded by:EC | OMINOEC| OMINOAuthors: Kocoń, Jan;Kocoń, Jan;Sentiment analysis involves using WordNets enriched with emotional metadata, which are valuable resources. However, manual annotation is time-consuming and expensive, resulting in only a few WordNet Lexical Units being annotated. This paper introduces two new techniques for automatically propagating sentiment annotations from a partially annotated WordNet to its entirety and to a WordNet in a different language: Multilingual Structured Synset Embeddings (MSSE) and Cross-Lingual Deep Neural Sentiment Propagation (CLDNS). We evaluated the proposed MSSE+CLDNS method extensively using Princeton WordNet and Polish WordNet, which have many inter-lingual relations. Our results show that the MSSE+CLDNS method outperforms existing propagation methods, indicating its effectiveness in enriching WordNets with emotional metadata across multiple languages. This work provides a solid foundation for large-scale, multilingual sentiment analysis and is valuable for academic research and practical applications. Comment: 6 pages, 1 figure, presented at ICDM Workshop: SENTIRE 2023
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/icdmw6...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icdmw60847.2023.00101&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/icdmw6...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icdmw60847.2023.00101&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 United KingdomPublisher:IOP Publishing Li, Haiwei; Zhao, Yongling; Bardhan, Ronita; Kubilay, Aytac; Derome, Dominique; Carmeliet, Jan;Nowadays, cities are frequently exposed to heatwaves, worsening the outdoor thermal comfort and increasing cooling energy demand in summer. Urban forestry is seen as one of the viable and preferable solutions to combating extreme heat events and urban heat island (UHI) in times of climate change. While many cities have initiated tree-planting programmes in recent years, the evolving impact of trees on street microclimate, in a time span of up to several decades, remains unclear. We investigate the cooling effects of linden trees in five groups, i.e., 10-20, 20-30, 30-40, 40-60, and 60-100 years old. The leaf area index (LAI) and leaf area density (LAD) vary nonlinearly as the trees grow, peaking at different ages. Computational fluid dynamics (CFD) simulations solving microclimate are performed for an idealized street canyon with trees of varied age groups. Turbulent airflow, heat and moisture transport, shortwave and longwave radiation, shading and transpiration are fully coupled and solved in OpenFOAM. The meteorological data, including air temperature, wind speed, moisture, and shortwave radiation of the heatwave in Zurich (June 2019), are applied as boundary conditions. The results show that young trees in the age group of 10-20 years old provide little heat mitigation at the pedestrian level in an extreme heat event. Optimal heat mitigation by trees is observed for the group of 30-60 years old trees. Finally, the potential impact of growing trees as a heat mitigation measure on air ventilation is evaluated. Comment: 4 figures, 8 pages
Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 GermanyPublisher:Springer Science and Business Media LLC Funded by:EC | PRODEMINFOEC| PRODEMINFOSegun Taofeek Aroyehun; Lukas Malik; Hannah Metzler; Nikolas Haimerl; Anna Di Natale; David Garcia;The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the quality of emotion identification methods due to training data size limitations and noise in the production of labels used in model development. We present LEIA, a model for emotion identification in text that has been trained on a dataset of more than 6 million posts with self-annotated emotion labels for happiness, affection, sadness, anger, and fear. LEIA is based on a word masking method that enhances the learning of emotion words during model pre-training. LEIA achieves macro-F1 values of approximately 73 on three in-domain test datasets, outperforming other supervised and unsupervised methods in a strong benchmark that shows that LEIA generalizes across posts, users, and time periods. We further perform an out-of-domain evaluation on five different datasets of social media and other sources, showing LEIA’s robust performance across media, data collection methods, and annotation schemes. Our results show that LEIA generalizes its classification of anger, happiness, and sadness beyond the domain it was trained on. LEIA can be applied in future research to provide better identification of emotions in text from the perspective of the writer. published
Konstanzer Online-Pu... arrow_drop_down Konstanzer Online-Publikations-SystemArticle . 2023Data sources: Konstanzer Online-Publikations-SystemarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Konstanzer Online-Pu... arrow_drop_down Konstanzer Online-Publikations-SystemArticle . 2023Data sources: Konstanzer Online-Publikations-SystemarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1140/epjds/s13688-023-00427-0&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Conference object 2023 GermanyPublisher:Stichting SciPost Funded by:UKRI | Plasma Functionalisation ...UKRI| Plasma Functionalisation of Recovered Carbon Black & Graphene for Multifunctional Elastomers (ElastoPlas)Carney, Daniel; Raj, Nirmal; Bai, Yang; Berger, Joshua; Blanco, Carlos; Bramante, Joseph; Cappiello, Christopher; Dutra, Mara; Ebadi, Reza; Engel, Kristi; Kolb, Edward; Harding, J. Patrick; Kumar, Jason; Krnjaic, Gordan; Lang, Rafael F.; Leane, Rebecca K.; Lehmann, Benjamin V.; Li, Shengchao; Long, Andrew J.; Mohlabeng, Gopolang; Olcina, Ibles; Pueschel, Elisa; Rodd, Nicholas L.; Rott, Carsten; Sengupta, Dipan; Shakya, Bibhushan; Walsworth, Ronald L.; Westerdale, Shawn;We outline the unique opportunities and challenges in the search for 'ultraheavy' dark matter candidates with masses between roughly $10~{\rm TeV}$ and the Planck scale $m_{\rm pl} \approx 10^{16}~{\rm TeV}$. This mass range presents a wide and relatively unexplored dark matter parameter space, with a rich space of possible models and cosmic histories. We emphasize that both current detectors and new, targeted search techniques, via both direct and indirect detection, are poised to contribute to searches for ultraheavy particle dark matter in the coming decade. We highlight the need for new developments in this space, including new analyses of current and imminent direct and indirect experiments targeting ultraheavy dark matter and development of new, ultra-sensitive detector technologies like next-generation liquid noble detectors, neutrino experiments, and specialized quantum sensing techniques. Snowmass 2021, Seattle, United States, 17 Jul 2022 - 26 Jul 2022; SciPost Physics Core 6(4), 075 (2023). doi:10.21468/SciPostPhysCore.6.4.075 Published by SciPost Foundation, Amsterdam
SciPost Physics Core arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert SciPost Physics Core arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21468/scipostphyscore.6.4.075&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object 2023 SwitzerlandPublisher:IOP Publishing Funded by:EC | OCAL, SNSF | NCCR Automation (phase I)EC| OCAL ,SNSF| NCCR Automation (phase I)Authors: Behrunani, Varsha; Zagorowska, Marta; Hudoba de Badyn, Mathias; id_orcid0000-0003-0955-2381; Ricca, Francesco; +2 AuthorsBehrunani, Varsha; Zagorowska, Marta; Hudoba de Badyn, Mathias; id_orcid0000-0003-0955-2381; Ricca, Francesco; Heer, Philipp; Lygeros, John; id_orcid0000-0002-6159-1962;Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a building, while posing the challenge of considering battery degradation during control operation. We demonstrate the performance of a data-enabled predictive control (DeePC) approach applied to a single multi- zone building and an energy hub comprising an electric heat pump and a battery. In a comparison with a standard rule-based controller, results demonstrate that the performance of DeePC is superior in terms of satisfaction of comfort constraints without increasing grid power consumption. Moreover, DeePC achieved two-fold decrease in battery degradation over one year, as compared to a rule-based controller. CISBAT International Conference 2023: Predictive & Adaptive Control Journal of Physics: Conference Series, 2600 (7) ISSN:1742-6596 ISSN:1742-6588
Research Collection arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Research Collection arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2600/7/072006&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article 2023Publisher:Oxford University Press (OUP) Qiao Jin; Won Kim; Qingyu Chen; Donald C Comeau; Lana Yeganova; W John Wilbur; Zhiyong Lu;Information retrieval (IR) is essential in biomedical knowledge acquisition and clinical decision support. While recent progress has shown that language model encoders perform better semantic retrieval, training such models requires abundant query-article annotations that are difficult to obtain in biomedicine. As a result, most biomedical IR systems only conduct lexical matching. In response, we introduce MedCPT, a first-of-its-kind Contrastively Pre-trained Transformer model for zero-shot semantic IR in biomedicine. To train MedCPT, we collected an unprecedented scale of 255 million user click logs from PubMed. With such data, we use contrastive learning to train a pair of closely-integrated retriever and re-ranker. Experimental results show that MedCPT sets new state-of-the-art performance on six biomedical IR tasks, outperforming various baselines including much larger models such as GPT-3-sized cpt-text-XL. In addition, MedCPT also generates better biomedical article and sentence representations for semantic evaluations. As such, MedCPT can be readily applied to various real-world biomedical IR tasks. Comment: The MedCPT code and API are available at https://github.com/ncbi/MedCPT
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/bioinformatics/btad651&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 4 citations 4 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Conference object , Preprint , Article 2024 FrancePublisher:IOP Publishing Funded by:EC | FCCISEC| FCCISAuthors: Dalena, Barbara; Da Silva, Tatiana; Chance, Antoine; Ghribi, Adnan;Dalena, Barbara; Da Silva, Tatiana; Chance, Antoine; Ghribi, Adnan;After the discovery of the Higgs boson at the LHC, particle physics community is exploring and proposing next accelerators, to address the remaining open questions on the underlying mechanisms and constituents of the present universe. One of the studied possibilities is FCC (Future Circular Collider), a 100 km long collider at CERN. The feasibility study of this future proposed accelerator implies the definition of tolerances on magnets imperfections and of the strategies of correction in order to guarantee the target performances of the High Energy Booster ring. The efficiency of the correction scheme, used to control the orbit, directly bounds the corrector needs and magnet tolerances. Analytic formulae give a first estimation of the average rms value of the required linear correctors' strengths and of the allowed magnets misalignments and field quality along the entire ring. The distribution of the correctors along the ring is simulated in order to verify the quality of the residual orbit after the proposed correction strategy and compared with the analytical predictions. First specifications of the orbit correctors strength and tolerances for the alignment of the main elements of the ring are presented. The limits of the studied correction scheme and method are also discussed. International audience
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2687/2/022004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2687/2/022004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 FinlandPublisher:Institute of Electrical and Electronics Engineers (IEEE) Zhilin Lu; Rongpeng Li; Kun Lu; Xianfu Chen; Ekram Hossain; Zhifeng Zhao; Honggang Zhang;Along with the springing up of the semantics-empowered communication (SemCom) research, it is now witnessing an unprecedentedly growing interest towards a wide range of aspects (e.g., theories, applications, metrics and implementations) in both academia and industry. In this work, we primarily aim to provide a comprehensive survey on both the background and research taxonomy, as well as a detailed technical tutorial. Specifically, we start by reviewing the literature and answering the "what" and "why" questions in semantic transmissions. Afterwards, we present the ecosystems of SemCom, including history, theories, metrics, datasets and toolkits, on top of which the taxonomy for research directions is presented. Furthermore, we propose to categorize the critical enabling techniques by explicit and implicit reasoning-based methods, and elaborate on how they evolve and contribute to modern content & channel semantics-empowered communications. Besides reviewing and summarizing the latest efforts in SemCom, we discuss the relations with other communication levels (e.g., conventional communications) from a holistic and unified viewpoint. Subsequently, in order to facilitate future developments and industrial applications, we also highlight advanced practical techniques for boosting semantic accuracy, robustness, and large-scale scalability, just to mention a few. Finally, we discuss the technical challenges that shed light on future research opportunities. This paper has been accepted for publication in the IEEE Communications Surveys and Tutorials
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/comst....Article . 2024 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/comst.2023.3333342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/comst....Article . 2024 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/comst.2023.3333342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Conference object 2023 SwitzerlandPublisher:IEEE Funded by:EC | INODEEC| INODEAuthors: Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems. So far the majority of benchmarks rely on pattern-based SPARQL query generation approaches. The subsequent natural language (NL) question generation is conducted through crowdsourcing or other automated methods, such as rule-based paraphrasing or NL question templates. Although some of these datasets are of considerable size, their pitfall lies in their pattern-based generation approaches, which do not always generalize well to the vague and linguistically diverse questions asked by humans in real-world contexts. In this paper, we introduce Spider4SPARQL - a new SPARQL benchmark dataset featuring 9,693 previously existing manually generated NL questions and 4,721 unique, novel, and complex SPARQL queries of varying complexity. In addition to the NL/SPARQL pairs, we also provide their corresponding 166 knowledge graphs and ontologies, which cover 138 different domains. Our complex benchmark enables novel ways of evaluating the strengths and weaknesses of modern KGQA systems. We evaluate the system with state-of-the-art KGQA systems as well as LLMs, which achieve only up to 45\% execution accuracy, demonstrating that Spider4SPARQL is a challenging benchmark for future research. Comment: 10 pages, 5 figures, accepted at IEEE BigData Conference 2023, 8th IEEE Special Session on Machine Learning on Big Data (MLBD 2023)
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/bigdata59044.2023.10386182&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 IrelandPublisher:University Library J. C. Senckenberg Publicly fundedAuthors: Louis Mahon; Carl Vogel;Louis Mahon; Carl Vogel;handle: 2262/104231
This paper presents FASTFOOD, a rule-based natural language generation (NLG) program for cooking recipes. We consider the representation of cooking recipes as discourse representation, because the meaning of each sentence needs to consider the context of the others. Our discourse representation system is based on states of affairs and transtions between states of affairs, and does not use discourse referents. Recipes are generated by using an automated theorem-proving procedure to select the ingredients and instructions, with ingredients corresponding to axioms and instructions to implications. FASTFOOD also contains a temporal optimization module which can rearrange the recipe to make it more time efficient for the user, e.g. the recipe specifies to chop the vegetables while the rice is boiling. The system is described in detail, including the decision to forgo discourse referents and how plausible representations of nouns and verbs emerge purely as a by-product of the practical requirements of efficiently representing recipe content. A comparison is then made with existing recipe generation systems, NLG systems more generally, and automated theorem provers.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article 2023Publisher:IEEE Funded by:EC | OMINOEC| OMINOAuthors: Kocoń, Jan;Kocoń, Jan;Sentiment analysis involves using WordNets enriched with emotional metadata, which are valuable resources. However, manual annotation is time-consuming and expensive, resulting in only a few WordNet Lexical Units being annotated. This paper introduces two new techniques for automatically propagating sentiment annotations from a partially annotated WordNet to its entirety and to a WordNet in a different language: Multilingual Structured Synset Embeddings (MSSE) and Cross-Lingual Deep Neural Sentiment Propagation (CLDNS). We evaluated the proposed MSSE+CLDNS method extensively using Princeton WordNet and Polish WordNet, which have many inter-lingual relations. Our results show that the MSSE+CLDNS method outperforms existing propagation methods, indicating its effectiveness in enriching WordNets with emotional metadata across multiple languages. This work provides a solid foundation for large-scale, multilingual sentiment analysis and is valuable for academic research and practical applications. Comment: 6 pages, 1 figure, presented at ICDM Workshop: SENTIRE 2023
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/icdmw6...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icdmw60847.2023.00101&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/icdmw6...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icdmw60847.2023.00101&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 United KingdomPublisher:IOP Publishing Li, Haiwei; Zhao, Yongling; Bardhan, Ronita; Kubilay, Aytac; Derome, Dominique; Carmeliet, Jan;Nowadays, cities are frequently exposed to heatwaves, worsening the outdoor thermal comfort and increasing cooling energy demand in summer. Urban forestry is seen as one of the viable and preferable solutions to combating extreme heat events and urban heat island (UHI) in times of climate change. While many cities have initiated tree-planting programmes in recent years, the evolving impact of trees on street microclimate, in a time span of up to several decades, remains unclear. We investigate the cooling effects of linden trees in five groups, i.e., 10-20, 20-30, 30-40, 40-60, and 60-100 years old. The leaf area index (LAI) and leaf area density (LAD) vary nonlinearly as the trees grow, peaking at different ages. Computational fluid dynamics (CFD) simulations solving microclimate are performed for an idealized street canyon with trees of varied age groups. Turbulent airflow, heat and moisture transport, shortwave and longwave radiation, shading and transpiration are fully coupled and solved in OpenFOAM. The meteorological data, including air temperature, wind speed, moisture, and shortwave radiation of the heatwave in Zurich (June 2019), are applied as boundary conditions. The results show that young trees in the age group of 10-20 years old provide little heat mitigation at the pedestrian level in an extreme heat event. Optimal heat mitigation by trees is observed for the group of 30-60 years old trees. Finally, the potential impact of growing trees as a heat mitigation measure on air ventilation is evaluated. Comment: 4 figures, 8 pages
Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 GermanyPublisher:Springer Science and Business Media LLC Funded by:EC | PRODEMINFOEC| PRODEMINFOSegun Taofeek Aroyehun; Lukas Malik; Hannah Metzler; Nikolas Haimerl; Anna Di Natale; David Garcia;The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the quality of emotion identification methods due to training data size limitations and noise in the production of labels used in model development. We present LEIA, a model for emotion identification in text that has been trained on a dataset of more than 6 million posts with self-annotated emotion labels for happiness, affection, sadness, anger, and fear. LEIA is based on a word masking method that enhances the learning of emotion words during model pre-training. LEIA achieves macro-F1 values of approximately 73 on three in-domain test datasets, outperforming other supervised and unsupervised methods in a strong benchmark that shows that LEIA generalizes across posts, users, and time periods. We further perform an out-of-domain evaluation on five different datasets of social media and other sources, showing LEIA’s robust performance across media, data collection methods, and annotation schemes. Our results show that LEIA generalizes its classification of anger, happiness, and sadness beyond the domain it was trained on. LEIA can be applied in future research to provide better identification of emotions in text from the perspective of the writer. published
Konstanzer Online-Pu... arrow_drop_down Konstanzer Online-Publikations-SystemArticle . 2023Data sources: Konstanzer Online-Publikations-SystemarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Konstanzer Online-Pu... arrow_drop_down Konstanzer Online-Publikations-SystemArticle . 2023Data sources: Konstanzer Online-Publikations-SystemarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1140/epjds/s13688-023-00427-0&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Conference object 2023 GermanyPublisher:Stichting SciPost Funded by:UKRI | Plasma Functionalisation ...UKRI| Plasma Functionalisation of Recovered Carbon Black & Graphene for Multifunctional Elastomers (ElastoPlas)Carney, Daniel; Raj, Nirmal; Bai, Yang; Berger, Joshua; Blanco, Carlos; Bramante, Joseph; Cappiello, Christopher; Dutra, Mara; Ebadi, Reza; Engel, Kristi; Kolb, Edward; Harding, J. Patrick; Kumar, Jason; Krnjaic, Gordan; Lang, Rafael F.; Leane, Rebecca K.; Lehmann, Benjamin V.; Li, Shengchao; Long, Andrew J.; Mohlabeng, Gopolang; Olcina, Ibles; Pueschel, Elisa; Rodd, Nicholas L.; Rott, Carsten; Sengupta, Dipan; Shakya, Bibhushan; Walsworth, Ronald L.; Westerdale, Shawn;We outline the unique opportunities and challenges in the search for 'ultraheavy' dark matter candidates with masses between roughly $10~{\rm TeV}$ and the Planck scale $m_{\rm pl} \approx 10^{16}~{\rm TeV}$. This mass range presents a wide and relatively unexplored dark matter parameter space, with a rich space of possible models and cosmic histories. We emphasize that both current detectors and new, targeted search techniques, via both direct and indirect detection, are poised to contribute to searches for ultraheavy particle dark matter in the coming decade. We highlight the need for new developments in this space, including new analyses of current and imminent direct and indirect experiments targeting ultraheavy dark matter and development of new, ultra-sensitive detector technologies like next-generation liquid noble detectors, neutrino experiments, and specialized quantum sensing techniques. Snowmass 2021, Seattle, United States, 17 Jul 2022 - 26 Jul 2022; SciPost Physics Core 6(4), 075 (2023). doi:10.21468/SciPostPhysCore.6.4.075 Published by SciPost Foundation, Amsterdam
SciPost Physics Core arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21468/scipostphyscore.6.4.075&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert SciPost Physics Core arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21468/scipostphyscore.6.4.075&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object 2023 SwitzerlandPublisher:IOP Publishing Funded by:EC | OCAL, SNSF | NCCR Automation (phase I)EC| OCAL ,SNSF| NCCR Automation (phase I)Authors: Behrunani, Varsha; Zagorowska, Marta; Hudoba de Badyn, Mathias; id_orcid0000-0003-0955-2381; Ricca, Francesco; +2 AuthorsBehrunani, Varsha; Zagorowska, Marta; Hudoba de Badyn, Mathias; id_orcid0000-0003-0955-2381; Ricca, Francesco; Heer, Philipp; Lygeros, John; id_orcid0000-0002-6159-1962;Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a building, while posing the challenge of considering battery degradation during control operation. We demonstrate the performance of a data-enabled predictive control (DeePC) approach applied to a single multi- zone building and an energy hub comprising an electric heat pump and a battery. In a comparison with a standard rule-based controller, results demonstrate that the performance of DeePC is superior in terms of satisfaction of comfort constraints without increasing grid power consumption. Moreover, DeePC achieved two-fold decrease in battery degradation over one year, as compared to a rule-based controller. CISBAT International Conference 2023: Predictive & Adaptive Control Journal of Physics: Conference Series, 2600 (7) ISSN:1742-6596 ISSN:1742-6588
Research Collection arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2600/7/072006&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Research Collection arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print ArchiveJournal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2600/7/072006&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article 2023Publisher:Oxford University Press (OUP) Qiao Jin; Won Kim; Qingyu Chen; Donald C Comeau; Lana Yeganova; W John Wilbur; Zhiyong Lu;Information retrieval (IR) is essential in biomedical knowledge acquisition and clinical decision support. While recent progress has shown that language model encoders perform better semantic retrieval, training such models requires abundant query-article annotations that are difficult to obtain in biomedicine. As a result, most biomedical IR systems only conduct lexical matching. In response, we introduce MedCPT, a first-of-its-kind Contrastively Pre-trained Transformer model for zero-shot semantic IR in biomedicine. To train MedCPT, we collected an unprecedented scale of 255 million user click logs from PubMed. With such data, we use contrastive learning to train a pair of closely-integrated retriever and re-ranker. Experimental results show that MedCPT sets new state-of-the-art performance on six biomedical IR tasks, outperforming various baselines including much larger models such as GPT-3-sized cpt-text-XL. In addition, MedCPT also generates better biomedical article and sentence representations for semantic evaluations. As such, MedCPT can be readily applied to various real-world biomedical IR tasks. Comment: The MedCPT code and API are available at https://github.com/ncbi/MedCPT
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/bioinformatics/btad651&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 4 citations 4 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/bioinformatics/btad651&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu