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131 results on '"Science Foundation Ireland (SFI)"'

1. Heat dissipation plays critical role for longevity of polymer-based 3D-printed inserts for plastics injection moulding

Author

Vicente F. Moritz, Gilberto S. N. Bezerra, Michael Hopkins Jnr, Evert Fuenmayor, Suzan Günbay, Conor Hayes, John G. Lyons, Declan M. Devine, Technological University of the Shannon Midlands Midwest, and This publication has results from research conducted with the financial support of Enterprise Ireland under the Technology Gateway Programme, Grant Number TG-2017-0114 (APT Ireland), and Science Foundation Ireland (SFI), Grant Number SFI 16/RC/3918, cofunded by the European Regional Development Fund. The APC was funded by Science Foundation Ireland (SFI), Grant Number SFI 16/RC/3918.

Subjects
3D printed moulds, injection moulding, additive manufacturing, stereolithography, polypropylene, Stereolithography, Injection moulding, Mechanics of Materials, Additive manufacturing, Mechanical Engineering, Polymer, Recycling, Industrial, Sustainability and Manufacturing Institute TUS:MM [PRISM], Polypropylene, Industrial and Manufacturing Engineering
Abstract

Injection moulding is a polymer processing method of choice for making plastic parts on industrial scale, but its traditional mould is made from tooling steel with time-consuming and costly production. Additive manufacturing technologies arise as an alternative for creating mould inserts at lower costs and shorter lead times. In this context, this study describes a series of stereolithography (SLA)-printed injection mould inserts fabricated from two photopolymer resins, utilised to mould standard tensile specimens of a commercial-grade polypropylene, aiming to evaluate effects on the polymer’s thermal and mechanical properties. Our results demonstrated that the glass fibre-filled resin inserts withstood more moulding cycles before failure, had superior mechanical properties, higher Tg and greater thermal conductivity. Calorimetric data revealed that PP thermal properties and degree of crystallinity were little affected, while mechanical testing suggests a significant effect in the elongation at break. Thus, these findings highlight the importance of adequate heat extraction during injection moulding and endorse further application of SLA mould inserts for the manufacturing of injection-moulded plastic parts in the case of prototypes or small batches, provided suitable cooling is made available, contributing to the feasibility and affordability of employing this approach for an industrial setting. This paper is an extended version of conference paper by M. Hopkins, S. Gunbay, C. Hayes, V.F. Moritz, E. Fuenmayor, J.G. Lyons, D.M. Devine “Stereolithography (SLA) utilised to print injection mould tooling in order to evaluate thermal and mechanical properties of commercial polypropylene”. Procedia Manuf. 2021, 55, 205–212. 10.1016/j.promfg.2021.10.029. yes

Published
2022

2. Self-assembly of porphyrin nanostructures at the interface between two immiscible liquids

Author

Manuel Dossot, David L. Cheung, Andrew Stewart, Colm O'Dwyer, Grégoire Herzog, Andrés F. Molina-Osorio, Micheál D. Scanlon, Bernal Institute [Limerick, Ireland], University of Limerick (UL), School of Chemistry, National University of Ireland Galway, National University of Ireland [Galway] (NUI Galway), University College Cork (UCC), Advanced Materials and BioEngineering Research - AMBER (IRELAND), Laboratoire de Chimie Physique et Microbiologie pour les Matériaux et l'Environnement (LCPME), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), European Research Council Starting Grant (agreement no. 716792), Science Foundation Ireland (SFI) (grant number 13/SIRG/2137), Science Foundation Ireland (SFI) under Grant Numbers 13/TIDA/E2761, 14/IA/2581 and 15/TIDA/2893, ANR-15-IDEX-0004,LUE,Isite LUE(2015), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), ERC, SFI, IRC, Irish Centre for High-End Computing, and French Programme Investissement d’Avenir

Subjects
Materials science, Nanostructure, Porphyrins, soft interface, Interface (Java), engineering, Nanotechnology, 02 engineering and technology, 010402 general chemistry, 01 natural sciences, chemistry.chemical_compound, interface between two immiscible liquids, Light energy, Energy transformation, Molecule, molecular antennas, Physical and Theoretical Chemistry, ComputingMilieux_MISCELLANEOUS, Light-harvesting antennas, Artificial photosynthesis technologies, self-assembly, [CHIM.MATE]Chemical Sciences/Material chemistry, Self-assembly, 021001 nanoscience & nanotechnology, Porphyrin, Energy conversion, 0104 chemical sciences, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials, Nanostructures, [CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry, General Energy, chemistry, X-ray crystallography, 0210 nano-technology, porphyrin nanostructures
Abstract

peer-reviewed The full text of this article will not be available in ULIR until the embargo expires on the 06/03/2021 One of the many evolved functions of photosynthetic organisms is to synthesize light harvesting nanostructures from photoactive molecules such as porphyrins. Engineering synthetic analogues with optimized molecular order necessary for the efficient capture and harvest of light energy remains challenging. Here, we address this challenge by reporting the self-assembly of zinc(II) meso-tetrakis(4-carboxyphenyl)porphyrins into films of highly ordered nanostructures. The self-assembly process takes place selectively at the interface between two immiscible liquids (water|organic solvent), with kinetically stable interfacial nanostructures formed only at pH values close to the pKa of the carboxyphenyl groups. Molecular dynamics simulations suggest that the assembly process is driven by an interplay between the hydrophobicity gradient at the interface and hydrogen bonding in the formed nanostructure. Ex situ XRD analysis and in situ UV/vis and steady state fluorescence indicates the formation of chlathrate type nanostructures that retain the emission properties of their monomeric constituents. The self-assembly method presented here avoids the use of acidic conditions, additives such as surfactants and external stimuli, offering an alternative for the realization of light-harvesting antennas in artificial photosynthesis technologies.

Published
2020
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3. The duality of e-participation - a model and technical infrastructure to study and harness social media-based participation

Author

Porwol, Lukasz, Breslin, John, Ojo, Adegboyega, Science Foundation Ireland (SFI) under DERI-Líon–II project (SFI/08/CE/I1380), Science Foundation Ireland (SFI) - Insight (SFI/12/RC/2289), and European Commision Grant 256261 (Puzzled by Policy – CIP-ICT-PSP- 2009-3bis), Grant 645860 (ROUTE-TO-PA — H2020-INSO-2014-2015/H2020- INSO-2014), Grant 645372 (ARCADIA — H2020-ICT-2014/H2020-ICT-2014-1), Grant 645886 (YDS — H2020-INSO-2014-2015/H2020-INSO-2014)

Subjects
Social media, e-Government, Data analytics, Citizen participation, e-Participation
Abstract

Despite the proliferation of e-Participation initiatives, overall efforts towards mainstreaming social media-based and citizen-led political deliberations are still limited. Consequently, there is a paucity of research on expected mutual re-shaping of deliberations on traditional e-Participation platforms and spontaneous citizen discussions on social media platforms. This mutual re- shaping phenomenon also referred to as the “duality of e-Participation” has been identified by Macintosh et al. in 2009, however up to date there is lack of methods and tools to study or enabling to harness the duality. In particular, the duality requires a specific, e-Participation-aligned, technical infrastructure to enable decision makers in government to access relevant information about ongoing citizen discussions on social media platforms. In this dissertation, we investigate the nature of the duality of e-Participation phenomenon; we construct a design inter alia of a Social Software Infrastructure (SSI), as a tool to study this duality. The design has been based upon e-Participation domain structuration and analysis leading to specific infrastructure requirements. Specifically, we combine the Structuration Theory complemented by Dynamic Capabilities Theory in an integrated model for e-Participation – an essential theoretical lens for generation of the SSI requirements. Also, we conduct a set of semi-structured interviews with politicians and decision-makers in relation to the duality. We investigate with politicians the nature of duality, we discuss possible ways of harnessing the duality and we 4 attempt to evaluate the feasibility of applying specific technologies, in the context of SSI, to enable effective social media-based e-Participation. The consolidated, structured results from the interviews inform a comprehensive analysis of the phenomenon of duality of e-Participation. From our results, we identify the essential technical capabilities that need to be obtained by governments to harness the duality. Finally, based on the knowledge acquired throughout the study, and considering all the challenges identified, we elaborate on the revised technical infrastructure implementation realising en evolved SSI design. We conclude with recommendations for governments to realise this SSI and some proposals for future work.

Published
2016

4. An evaluation of a computational technique for measuring the embeddedness of sustainability in the curriculum aligned to AASHE-STARS and the United Nations Sustainable Development Goals

Author

Lemarchand, Philippe, MacMahon, Cormac H., Dr, McKeever, Mick, Owende, Philip, and This research was funded under the Student Transformative Learning Record Project (Transform-EDU) of the Higher Education Authority of Ireland (HEA) Ireland, under the Innovation and Transformation Programme 2018. It was also supported by MaREI, the Science Foundation Ireland (SFI) Research Centre for Energy, Climate, and Marine (Grant No: 12/RC/2302_P2) and the European University of Technology (EUt+), a European University Alliance under the Erasmus programme (Grant No: 101004088).

Subjects
Psychiatry and Mental health, Sustainability Lexica, Artificial Intelligence, Validation, TF-IDF, Higher Education, Electrical and Computer Engineering, SDGs, Natural Language Processing
Abstract

IntroductionSDG 4.7 mandates university contributions to the United Nations (UN) Sustainable Development Goals (SDGs) through their education provisions. Hence, universities increasingly assess their curricular alignment to the SDGs. A common approach to the assessment is to identify keywords associated with specific SDGs and to analyze for their presence in the curriculum. An inherent challenge is associating the identified keywords as used in the diverse set of curricular contexts to relevant sustainability indicators; hence, the urgent need for more systematic assessment as SDG implementation passes its mid-cycle.MethodIn this study, a more nuanced technique was evaluated with notable capabilities for: (i) computing the importance of keywords based on the term frequency-inverse document frequency (TF-IDF) method; (ii) extending this computation to the importance of courses to each SDG and; (iii) correlating such importance to a statistical categorization based on the Association for the Advancement of Sustainability in Higher Education (AASHE) criteria. Application of the technique to analyze 5,773 modules in a university's curriculum portfolio facilitated categorization of the modules/courses to be “sustainability-focused” or “sustainability-inclusive.” With the strategic objective of systematically assessing the sustainability content of taught curricula, it is critical to evaluate the precision and accuracy of the computed results, in order to attribute text with the appropriate SDGs and level of sustainability embeddedness. This paper evaluates this technique, comparing its results against a manual and labor-intensive interpretation of expert informed assessment of sustainability embeddedness on a random sample of 306 modules/courses.Results and discussionExcept for SDGs 1 and 17, the technique exhibited a reasonable degree of accuracy in predicting module/course alignment to SDGs and in categorizing them using AASHE criteria. Whilst limited to curricular contexts from a single university, this study indicates that the technique can support curricular transformation by stimulating enhancement and reframing of module/course contexts through the lens of the SDGs.

Published
2023
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5. Prehensile and Non-Prehensile Robotic Pick-and-Place of Objects in Clutter Using Deep Reinforcement Learning

Author

Imtiaz, Muhammad Babar, Qiao, Yuansong, Lee, Brian, Technological University of the Shannon: Midlands Midwest, and Science Foundation Ireland (SFI)

Subjects
Deep reinforcement learning, fully convolutional network, Prehensile, deep reinforcement learning, Fully convolutional network, non-prehensile, robotic manipulation, Biochemistry, Atomic and Molecular Physics, and Optics, Analytical Chemistry, deep Q-network, Non-prehensile, Robotic manipulation, TUS MIdlands [Software Research Institute], prehensile, Deep Q-network, Electrical and Electronic Engineering, Instrumentation, Markov decision process, DenseNet-121
Abstract

In this study, we develop a framework for an intelligent and self-supervised industrial pick-and-place operation for cluttered environments. Our target is to have the agent learn to perform prehensile and non-prehensile robotic manipulations to improve the efficiency and throughput of the pick-and-place task. To achieve this target, we specify the problem as a Markov decision process (MDP) and deploy a deep reinforcement learning (RL) temporal difference model-free algorithm known as the deep Q-network (DQN). We consider three actions in our MDP; one is ‘grasping’ from the prehensile manipulation category and the other two are ‘left-slide’ and ‘right-slide’ from the non-prehensile manipulation category. Our DQN is composed of three fully convolutional networks (FCN) based on the memory-efficient architecture of DenseNet-121 which are trained together without causing any bottleneck situations. Each FCN corresponds to each discrete action and outputs a pixel-wise map of affordances for the relevant action. Rewards are allocated after every forward pass and backpropagation is carried out for weight tuning in the corresponding FCN. In this manner, non-prehensile manipulations are learnt which can, in turn, lead to possible successful prehensile manipulations in the near future and vice versa, thus increasing the efficiency and throughput of the pick-and-place task. The Results section shows performance comparisons of our approach to a baseline deep learning approach and a ResNet architecture-based approach, along with very promising test results at varying clutter densities across a range of complex scenario test cases.

Published
2023
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6. Liquid-Based 4D printing of shape memory nanocomposites: A Review

Author

Mohamad Alsaadi, Eoin P. Hinchy, Conor T. McCarthy, Vicente F. Moritz, Shuo Zhuo, Evert Fuenmayor, Declan M. Devine, Technological University of the Shannon: Midlands Midwest, and This research project is funded by Marie Skłodowska-Curie grant agreement No. 847577 cofounded by the European Regional Development Fund and Science Foundation Ireland (SFI) under Grant Number SFI/16/RC/3918 (Smart Manufacturing, Confirm Centre, UL).

Subjects
digital light processing, shape memory, Direct ink writing (DIW), Mechanical Engineering, Polymer nanocomposites, Additive manufacturing (AM), Industrial and Manufacturing Engineering, Stereolithography (SLA), polymer nanocomposites, Shape memory (SM), Material jetting (MJ), Engineering, Digital light processing (DLP), Mechanics of Materials, Polymer, Recycling, Industrial, Sustainability and Manufacturing Institute TUS:MM [PRISM], material jetting, additive manufacturing, 40 Engineering
Abstract

Significant advances have been made in recent years in the materials development of liquid-based 4D printing. Nevertheless, employing additive materials such as nanoparticles for enhancing printability and shape memory characteristics is still challenging. Herein, we provide an overview of recent developments in liquid-based 4D printing and highlights of novel 4D-printable polymeric resins and their nanocomposite components. Recent advances in additive manufacturing technologies that utilise liquid resins, such as stereolithography, digital light processing, material jetting and direct ink writing, are considered in this review. The effects of nanoparticle inclusion within liquid-based resins on the shape memory and mechanical characteristics of 3D-printed nanocomposite components are comprehensively discussed. Employing various filler-modified mixture resins, such as nanosilica, nanoclay and nanographene, as well as fibrous materials to support various properties of 3D printing components is considered. Overall, this review paper provides an outline of liquid-based 4D-printed nanocomposites in terms of cutting-edge research, including shape memory and mechanical properties.

Published
2023
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7. ECE: Exactly-Once-Computation for Collaborative Edge in IoT using Information Centric Networking

Author

Qian Wang, Brian Lee, Niall Murray, Yuansong Qiao, Technological University of the Shannon: Midlands Midwest, and Technological University of the Shannon under the Staff Development Programme, and Science Foundation Ireland (SFI) under Grant Number SFI 16/RC/3918, co-funded by the European Regional Development Fund. R

Subjects
Computer Networks and Communications, Hardware and Architecture, Collaborative edge computing, Signal Processing, Exactly-once-computation, Information Centric Networking (ICN), MM [Software Research Institute TUS], Computer Science Applications, Information Systems, Internet of Things (IoT)
Abstract

—Exactly-once data processing/delivery can be guaranteed in traditional big data processing systems, e.g. Apache Flink. Checkpoint is commonly used as the solution. Each operator in these systems can restart from the last successfully saved state whenever a failure happens. It is not necessary to restore the logical job graph onto the same device(s) in traditional datacentre scenarios with powerful servers close to each other. However, the datacentre oriented solutions are not suitable for IoT collaborative edge computing scenarios. The logical job graph is tightly coupled to the physical topology in IoT networks. Data processing task(s) cannot be placed at a random edge device to recover from a network failure as it needs to evaluate the benefits of transmitting data versus processing/aggregating the data. To address the above challenges, this paper proposes an Information Centric Networking based solution and correspondent protocols to provide Exactly-oncecomputation for the Collaborative Edge in IoT (ECE). It contains a job execution scheme to deliver IoT jobs with exactly once data computation guarantee and a recovery procedure to dynamically change the IoT job execution graph while experiencing link failures. The protocol also provides a checking procedure on data state (received/un-received and computed/un-computed) to prevent any data loss or duplicated data processing due to the updated job graph. A data identification approach based on the job graph is devised to support the ECE functionality. A testbed has been developed on ndnSIM and the simulation results have verified the feasibility and scalability of ECE design. It also evaluates the overhead incurred by the ECE protocol to guarantee exactly once data computation. yes

Published
2023

8. Near-Field Propagation Analysis for Vivaldi Antenna Design: Insight into the propagation process for optimizing the directivity, integrity of signal transmission, and efficiency

Author

Max J. Ammann, Patrick McEvoy, Matthias John, Ha Hoang, Science Foundation Ireland (SFI), and European Regional Development Fund

Subjects
Clustering algorithms, Computer science, Acoustics, Near and far field, 02 engineering and technology, 01 natural sciences, Directivity, law.invention, Time-domain analysis, law, Systems and Communications, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Impulse response, Multiple signal classification, Classification algorithms, Computer Sciences, 010401 analytical chemistry, Process (computing), Pattern classification, 020206 networking & telecommunications, Condensed Matter Physics, 0104 chemical sciences, Time–frequency analysis, Time-frequency analysis, Vivaldi antennas, Antenna (radio), Vivaldi antenna, Energy (signal processing)
Abstract

Refined optimization of complex curve–linear-shaped radiators, such as traveling-wave Vivaldi antennas, can be achieved by considering simulated near fields to interpret in detail the structural influences of a design. The relationships between the space and time distributions of electromagnetic (EM) energy clusters and the geometric features are revealed with appropriate use of impulse response analysis combined with the multiple signal classification (MUSIC) algorithm. This article reports a deeper approach when applied to the adjustment of the geometric features of a traveling-wave antenna based on an analysis of near-field propagation features.

Published
2021
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9. Converging technologies: targeting the hallmarks of cancer using ultrasound and microbubbles

Author

Patrick J. Cullen, Janith Wanigasekara, Brijesh K. Tiwari, Andressa Maria Aguiar de Carvalho, James F. Curtin, James F. Curtin, Science Foundation Ireland (SFI), and Walsh Scholar Programme

Subjects
Cancer Research, Microbubbles, business.industry, medicine.medical_treatment, Ultrasound, Cancer, medicine.disease, Biochemistry, microbubbles, Biological materials, Targeted therapy, The Hallmarks of Cancer, Ultrasonic Waves, Oncology, Neoplasms, Medicine and Health Sciences, medicine, Humans, Ultrasonic sensor, business, Biomedical engineering
Abstract

Various complex biological effects occur when ultrasonic compression waves travel through biological material. The myriad of biological outcomes instigated by ultrasound are evident when viewed through the lens of the hallmarks of cancer. Herein, we summarise the therapeutic potential of ultrasound, enhanced by microbubbles, for the treatment of cancer.

Published
2021
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10. Delay-Based Network Utility Maximization Modelling for Congestion Control in Named Data Networking

Author

Jin Xu, Ronan Flynn, Yuansong Qiao, Guiming Fang, Yuhang Ye, Brian Lee, Athlone Institute of Technology, and This work was supported in part by Irish Research Council under ID GOIPD/2019/874, Science Foundation Ireland (SFI) under Grant Number 16/RC/3918 and 13/SIRG/2178, co-funded by the European Regional Development Fund, National Natural Science Foundation of China under Grant Number 61671126, Science and Technology Program of Sichuan Province of China under Grant Number 2019JDR0022

Subjects
Queueing theory, Computer Networks and Communications, Computer science, business.industry, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, Congestion control, 020206 networking & telecommunications, 02 engineering and technology, Computer Science Applications, Network congestion, Connectionless communication, Multi-source, Transmission (telecommunications), Multipath, Packet loss, Control system, 0202 electrical engineering, electronic engineering, information engineering, Bandwidth (computing), Electrical and Electronic Engineering, business, Software, Multipath propagation, Named data networking, Software Research Institute AIT, Computer network
Abstract

Content replication and name-based routing lead to a natural multi-source and multipath transmission paradigm in NDN. Due to the unique connectionless characteristic of NDN, current end-to-end multipath congestion control schemes (e.g. MPTCP) cannot be used directly on NDN. This paper proposes a Network Utility Maximization (NUM) model to formulate multi-source and multipath transmission in NDN with in-network caches. From this model, a family of receiver-driven transmission solutions can be derived, named as path-specified congestion control. The path-specified congestion control enables content consumers to separate the traffic control on each path, which consequently facilitates fair and efficient bandwidth sharing amongst all consumers. As a specific instance, a Delay-based Path-specified Congestion Control Protocol (DPCCP) is presented, which utilizes queuing delays as signals to measure and control congestion levels of different bottlenecks. In addition, a set of high-performance congestion control laws are designed to accelerate bandwidth and fairness convergence towards the optimum defined by the NUM model. Finally, DPCCP is compared with state-of-the-art solutions. The experimental evaluations show that DPCCP outperforms existing solutions in terms of bandwidth utilization, convergence time and packet loss. yes

Published
2021
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11. Thermodynamic Modelling of Harsh Environments on the Solid Phase Assemblage of Hydrating Cements Using PHREEQC

Author

Niall Holmes, Mark Tyrer, Denis Kelliher, and National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
Fluid Flow and Transfer Processes, Thermodynamic Modelling of Harsh Environments on the Solid Phase Assemblage of Hydrating Cements Using PHREEQC, Engineering, Process Chemistry and Technology, cement, hydration, durability, carbonation, sulfate, seawater, thermodynamics, General Engineering, General Materials Science, Instrumentation, Computer Science Applications
Abstract

Poor durability of reinforced concrete structures can lead to serious structural failures. An accurate model to observe the effects of aggressive agents like carbonation, sulfate ingress, and seawater solutions on the solid phase assemblage will help designers and specifiers better understand how cement behaves in these environments. This paper presents the first steps in developing such a model using the PHREEQC geochemical software by accounting for alkali binding and dissolution. It also presents the use of discrete solid phases (DSPs) to account for the solid-solution behaviour of siliceous hydrogarnet and magnesium silicate hydrate (M-S-H). A new thermodynamic description of the vaterite phase has also been developed for this work using the cemdata18 thermodynamic database. The predicted phase assemblages of cements in these environments here agree with previously published findings using a different thermodynamic model supported with experimental data.

Published
2022
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12. Defective activation and regulation of type I interferon immunity is associated with increasing COVID-19 severity

Author

Nikaïa Smith, Céline Possémé, Vincent Bondet, Jamie Sugrue, Liam Townsend, Bruno Charbit, Vincent Rouilly, Violaine Saint-André, Tom Dott, Andre Rodriguez Pozo, Nader Yatim, Olivier Schwartz, Minerva Cervantes-Gonzalez, Jade Ghosn, Paul Bastard, Jean Laurent Casanova, Tali-Anne Szwebel, Benjamin Terrier, Niall Conlon, Cliona O’Farrelly, Clíona Ní Cheallaigh, Nollaig M. Bourke, Darragh Duffy, Immunologie Translationnelle - Translational Immunology lab, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Trinity College Dublin, Saint James Hospital (SJH), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Datactix, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Virus et Immunité - Virus and immunity (CNRS-UMR3569), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, CHU Necker - Enfants Malades [AP-HP], Human genetics of infectious diseases : Mendelian predisposition (Equipe Inserm U1163), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Rockefeller University [New York], Howard Hughes Medical Institute (HHMI), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This study was supported by the 'URGENCE COVID-19' fundraising campaign of the Institut Pasteur (CoVarImm and Steroid Response), from the Agence Nationale de la Recherche (ANR-flash COVID-19), by the Laboratoire d’Excellence ‘Milieu Intérieur’ (grant no. ANR-10-LABX-69-01) (D.D.), the Fonds IMMUNOV for Innovation in Immunopathology (B.T.), and Science Foundation Ireland (C.O.F., C.N.C., and N.B.). We thank the STTAR-Bioresource of TCD-SJH-TUH COVID-19 bioresource which supported the collection of patient samples. N.S. is a recipient of the Pasteur–Roux–Cantarini Fellowship. C.O.F., N.C., and C.N.C. are part-funded by a Science Foundation Ireland (SFI) grant, Grant Code 20/SPP/3685. L.T. is supported by the Irish Clinical Academic Training (ICAT) Program, supported by the Wellcome Trust and the Health Research Board (Grant Number 203930/B/16/Z), the Health Service Executive, National Doctors Training and Planning and the Health and Social Care, Research and Development Division, Northern Ireland. N.B. is funded under the Science Foundation Ireland Phase 2 COVID-19 Rapid Response Call (20/COV/8487) and the Health Research Board COVID-19 Rapid Response Call (COV19e2020e053). The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI088364 and R01AI163029), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Award (CTSA) program (UL1 TR001866), a Fast Grant from Emergent Ventures, Mercatus Center at George Mason University, the Fisher Center for Alzheimer’s Research Foundation, the Meyer Foundation, the JPB Foundation, the French National Research Agency (ANR) under the 'Investments for the Future' program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM) (EQU201903007798), the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), ANR AABIFNCOV (ANR-20-CO11-0001) and ANR GenMISC (ANR-21-COVR-0039) projects, the European Union’s Horizon 2020 research and innovation program under grant agreement No. 824110 (EASI-genomics), the Square Foundation, Grandir—Fonds de solidarité pour l’enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, The French Ministry of Higher Education, Research, and Innovation (MESRI-COVID-19), Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM and the University of Paris (J.L.C.). P.B. was supported by the MD–Ph.D. program of the Imagine Institute (with the support of the Fondation Bettencourt-Schueller)., We thank the UTechS CB of the Center for Translational Research, Institut Pasteur for supporting Luminex and Nanostring analysis. We thank Quanterix for the provision of IFNα multi-subtype prototype assays. We acknowledge all healthcare workers involved in the diagnosis and treatment of patients in Hopital Cochin, Hopital Bichat, and St James’s Hospital Dublin., ANR-20-COVI-0053,CoVarImm,Variation de la réponse immune systémique et muqueuse pendant l'infection par le SRAS-CoV-2 et la convalescence(2020), ANR-10-LABX-0069,MILIEU INTERIEUR,GENETIC & ENVIRONMENTAL CONTROL OF IMMUNE PHENOTYPE VARIANCE: ESTABLISHING A PATH TOWARDS PERSONALIZED MEDICINE(2010), ANR-10-IAHU-0001,Imagine,Institut Hospitalo-Universitaire Imagine(2010), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-20-CE93-0003,GENVIR,Analyse multi-omique de l'immunité anti-virale: de l'identification des circuits biologiques pertinents à la découverte de défauts monogéniques héréditaires de l'immunité chez les patients avec infections virales sévères(2020), ANR-20-CO11-0001,AABIFNCOV,Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19.(2020), ANR-21-COVR-0039,GenMIS-C,Recherche des Déficits immunitaires innées monogéniques prédisposant au syndrome inflammatoire multisystémique chez l'enfant.(2021), and European Project: 824110,H2020-INFRAIA-2018-1,EASI-Genomics(2019)

Subjects
Proteomics, Multidisciplinary, SARS-CoV-2, [SDV]Life Sciences [q-bio], Interferon Type I, General Physics and Astronomy, Humans, COVID-19, Interferon-alpha, General Chemistry, Antiviral Agents, General Biochemistry, Genetics and Molecular Biology, Autoantibodies
Abstract

Host immunity to infection with SARS-CoV-2 is highly variable, dictating diverse clinical outcomes ranging from asymptomatic to severe disease and death. We previously reported reduced type I interferon in severe COVID-19 patients preceded clinical worsening. Further studies identified genetic mutations in loci of the TLR3- or TLR7-dependent interferon-I pathways, or neutralizing interferon-I autoantibodies as risk factors for development of COVID-19 pneumonia. Here we show in patient cohorts with different severities of COVID-19, that baseline plasma interferon α measures differ according to the immunoassay used, timing of sampling, the interferon α subtype measured, and the presence of autoantibodies. We also show a consistently reduced induction of interferon-I proteins in hospitalized COVID-19 patients upon immune stimulation, that is not associated with detectable neutralizing autoantibodies against interferon α or interferon ω. Intracellular proteomic analysis shows increased monocyte numbers in hospitalized COVID-19 patients but impaired interferon-I response after stimulation. We confirm this by ex vivo whole blood stimulation with interferon-I which induces transcriptomic responses associated with inflammation in hospitalized COVID-19 patients, that is not seen in controls or non-hospitalized moderate cases. These results may explain the dichotomy of the poor clinical response to interferon-I based treatments in late stage COVID-19, despite the importance of interferon-I in early acute infection and may guide alternative therapeutic strategies.

Published
2022
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13. Comparing the measured and thermodynamically predicted AFm phases in a hydrating cement

Author

Niall Holmes, Mark Russell, Geoff Davis, Mark Tyrer, Yoo, Doo-Yeol, Niall Holmes, and This research is supported through a US-Ireland grant tri-funded by the National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
Fluid Flow and Transfer Processes, cement, Process Chemistry and Technology, PHREEQC, General Engineering, Civil Engineering, Article, Computer Science Applications, hydration, thermodynamics, mineralogy, General Materials Science, Instrumentation
Abstract

In hydrating Portland cements, more than one of the AFm family of calcium aluminates may exist. Depending on the amount of carbonate and sulfate present in the cement, the most common phase to precipitate is monosulfate, monocarbonate and/or hemicarbonate. It has been reported in the literature that hemicarbonate often appears in measurements such as XRD but not predicted to form/equilibrate in thermodynamic models. With the ongoing use of commercial cements such as CEM I and CEM II containing more and more limestone, it is important to understand which hydrate solids physically precipitate and numerically predict over time. Using 27 cement samples with three w/c ratios analysed at 1, 3 and 28 days, this paper shows that although hemicarbonate was observed in a hydrating commercial Portland cement, as well as being predicted based on its carbonate (CO2/Al2O3) and sulfate (SO3/Al2O3) ratios, thermodynamic analysis did not predict it to equilibrate and form as a solid hydrate. Regardless of the w/c ratio, thermodynamic analysis did predict hemicarbonate to form for calcite contents < 2 wt.%. It appears that the dominant stability of monocarbonate in thermodynamic models leads to it precipitating and remaining as a persistent phase.

Published
2022
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14. Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

Author

Saeed H. Alsamhi, Brian Lee, Hatem Al-Dois, Hager Saleh, Soufiene Ben Othman, Jahan Hassan, Faris A. Almalki, Ammar Hawbani, Radyah Sahal, Athlone Institute of Technology, and Science Foundation Ireland (SFI) under grant no. SFI/16/RC/3918 (CONFIRM) and Marie Skłodowska-Curie grant agreement no. 847577 co-funded by the European Regional Development Fund. Taif University Researchers Supporting Project (no. TURSP-2020/265).

Subjects
General Computer Science, Computer science, General Mathematics, Internet of Things, Computer applications to medicine. Medical informatics, R858-859.7, QoS, Neurosciences. Biological psychiatry. Neuropsychiatry, Review Article, Machine learning, computer.software_genre, Machine Learning, B5G Networks, Smart environments, Dynamism, Cities, Connectivity, business.industry, General Neuroscience, Quality of service, Provisioning, General Medicine, Energy consumption, Variety (cybernetics), Smart environment, The Internet, Artificial intelligence, business, Delivery of Health Care, computer, Software Research Institute AIT, RC321-571
Abstract

The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.

Published
2021
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15. Modelling the thermoelectric properties of cement-based materials using finite element method and effective medium theory

Author

Stella, Lorenzo, Johnston, Conrad, Troncoso, Javier F., Chudzinski, Piotr, Orisakwe, Esther, Kohanoff, Jorge, Jani, Ruchita, Holmes, Niall, Norton, Brian, Liu, Xiaoli, Qu, Ming, Yin, Hongxi, Yazawa, Kazuaki, Niall Holmes, and This research is supported through a US-Ireland grant tri-funded by the National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
Thermoelectrics, Seebeck Coefficient, Thermal Conductivity, Electrical Conductivity, Civil Engineering, Cement composites
Abstract

Because of the thermoelectric (TE) effect (or Seebeck effect), a difference of potential is generated as a consequence of a temperature gradient across a sample. The TE effect has been mostly studied and engineered in semiconducting materials and it already finds several commercial applications. Only recently the TE effect in cement-based materials has been demonstrated and there is a growing interest in its potential. For instance, a temperature gradient across the external walls of a building can be used to generate electricity. By the inverse of the TE effect (or Peltier effect), one can also seek to control the indoor temperature of a building by biasing TE elements embedded in its external walls. In designing possible applications, the TE properties of cement-based materials must be determined as a function of their chemical composition. For instance, the TE properties of cement paste can be enhanced by the addition of metal oxide (e.g., Fe2O3) powder. In this paper, a single thermoelectric leg is studied using the finite element method. Metal oxide additives in the cement paste are modelled as spherical inhomogeneities. The thermoelectric properties of the single components are based on experimental data, while the overall thermoelectric properties of the composites are obtained from the numerical model. The results of this numerical study are interpreted according to the effective medium theory (EMT) and its generalisation (GEMT).

Published
2022

16. Experimental performance evaluation of a convective thermoelectric building envelope for building heating and cooling

Author

Xiaoli Liu, Kazuaki Yazawa, Ming Qu, Orkan Kurtulus, Brian Norton, Niall Holmes, Ruchita Jani, Jorge Kohanoff, Lorenzo Stella, Conrad Johnston, Hongxi Yin, Niall Holmes, and This research is supported through a US-Ireland grant tri-funded by the National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
Prototype evaluation, Experiment, Mechanical Engineering, Heating and cooling, Building and Construction, Electrical and Electronic Engineering, Thermoelectric building envelope, Civil Engineering, Civil and Structural Engineering
Abstract

The thermoelectric building envelope (TBE) integrates thermoelectric materials with the building envelope for active space heating and cooling. The advantage of TBE heating and cooling includes its significantly low-profile design and no refrigerant use. Although there are existing studies evaluating TBE performance, they were based on limited operating conditions. The study aims to experimentally evaluate the heating and cooling performance of a TBE prototype under various operating conditions. The TBE prototype was installed between two psychrometric chambers, which simulated indoor and outdoor conditions. The prototype was tested at an indoor temperature of around 22.35–23.58 degrees C and outdoor temperatures from about 7.35 degrees C and 16.99 degrees C for heating and from 28.36 degrees C to 40.95 degrees C for cooling, with varied power inputs and fan conditions. The maximum coefficient of performance (COP) of TBE in heating mode is 3.2. The average heating COP of TBE with a current of 1.5 A in four winter scenarios is 1.37. The average heating COP of TBE operating with the current of 0.3–1.5 A at an outdoor temperature of 12 degrees C is 2.27. The TBE system demonstrates a better heating efficiency than an auxiliary electric heater for the heat pump system. The experimental results and evaluation obtained provide critical guidance for the deployment of TBE applications.

Published
2022

17. Defective type I interferon immunity is associated with increasing COVID-19 severity

Author

Darragh Duffy, Nikaïa SMITH, Céline Possémé, Vincent Bondet, Jamie Sugrue, Liam Townsend, Bruno Charbit, Vincent Rouilly, Violaine Saint-André, Tom Dott, Andre Rodriguez Pozo, Nader Yatim, Olivier Schwartz, Minerva Cervantes-Gonzales, Jade Ghosn, Paul Bastard, Jean-Laurent Casanova, Tali-Anne Szwebel, Benjamin Terrier, Niall Conlon, Cliona O'Farrelly, Cliona Ni Cheallaigh, Nollaig Bourke, Immunologie Translationnelle - Translational Immunology lab, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Institut Pasteur [Paris] (IP), Trinity College Dublin, Datactix, AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Hôpital Cochin [AP-HP], St James' Hospital, This study was supported by the 'URGENCE COVID-19' fundraising campaign the Institut Pasteur (CoVarImm and Steroid Response), from the Agence Nationale de la Recherche (ANR-flash COVID-19), by the Laboratoire d’Excellence ‘Milieu Intérieur’ (grant no. ANR-10-LABX-69-01), the Fonds IMMUNOV for Innovation in Immunopathology, and Science Foundation Ireland. We thank the STTAR-Bioresource of TCD-SJH-TUH COVID-19 bioresource which supported collection of patient samples. NS is a recipient of the Pasteur-Roux-Cantarini Fellowship. COF, NC and CNC are part-funded by a Science Foundation Ireland (SFI) grant, Grant Code 20/SPP/3685. LT is supported by the Irish Clinical Academic Training (ICAT) Programme, supported by the Wellcome Trust and the Health Research Board (Grant Number 203930/B/16/Z), the Health Service Executive, National Doctors Training and Planning and the Health and Social Care, Research and Development Division, Northern Ireland. N.B. is funded under the Science Foundation Ireland Phase 2 COVID-19 Rapid Response Call (20/COV/8487) and the Health Research Board COVID-19 Rapid Response Call (COV19e2020e053). The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI088364 and R01AI163029), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Award (CTSA) program (UL1 TR001866), a Fast Grant from Emergent Ventures, Mercatus Center at George Mason University, the Fisher Center for Alzheimer’s Research Foundation, the Meyer Foundation, the JPB Foundation, the French National Research Agency (ANR) under the 'Investments for the Future' program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM) (EQU201903007798), the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), ANR AABIFNCOV (ANR-20-CO11-0001) and ANR GenMISC (ANR-21-COVR-0039) projects, the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824110 (EASI-genomics), the Square Foundation, Grandir - Fonds de solidarité pour l’enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, The French Ministry of Higher Education, Research, and Innovation (MESRI-COVID-19), Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM and the University of Paris. PB was supported by the MD-PhD program of the Imagine Institute (with the support of the Fondation Bettencourt-Schueller)., We thank the UTechS CB of the Center for Translational Research, Institut Pasteur for supporting Luminex and Nanostring analysis. We acknowledge all health-care workers involved in the diagnosis and treatment of patients in Hopital Cochin, Hopital Bichat, and St James’s Hospital Dublin., ANR-10-LABX-0069,MILIEU INTERIEUR,GENETIC & ENVIRONMENTAL CONTROL OF IMMUNE PHENOTYPE VARIANCE: ESTABLISHING A PATH TOWARDS PERSONALIZED MEDICINE(2010), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-10-IAHU-0001,Imagine,Institut Hospitalo-Universitaire Imagine(2010), ANR-20-CE93-0003,GENVIR,Analyse multi-omique de l'immunité anti-virale: de l'identification des circuits biologiques pertinents à la découverte de défauts monogéniques héréditaires de l'immunité chez les patients avec infections virales sévères(2020), ANR-20-CO11-0001,AABIFNCOV,Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19.(2020), ANR-21-COVR-0039,GenMIS-C,Recherche des Déficits immunitaires innées monogéniques prédisposant au syndrome inflammatoire multisystémique chez l'enfant.(2021), European Project: 824110,H2020-INFRAIA-2018-1,EASI-Genomics(2019), Institut Pasteur [Paris]-Université Paris Cité (UPC), Institut Pasteur [Paris], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPC)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

Host immunity to infection with SARS-CoV-2 is highly variable, dictating diverse clinical outcomes ranging from asymptomatic to severe disease and death. We previously reported that reduced blood type I interferon (IFN-I) in severe COVID-19 patients preceded clinical worsening. These results were supported by studies which identified genetic mutations in loci of the TLR3- or TLR7-dependent IFN-I pathways, or autoantibodies neutralizing IFNα or IFNω, as major risk factors for development of severe and critical COVID-19 pneumonia. Here, we analyzed a range of IFN-I associated responses in patient cohorts with different severities of COVID-19, showing that baseline plasma IFNα measures differed significantly according to the immunoassay used, as well as timing of sampling, the IFNα subtype measured, and the presence of autoantibodies. We then compared immune responses induced by ex vivo stimulation between non-hospitalized moderate cases (n=27) and hospitalized (n=17) adult patients that required oxygen supplementation. This showed a consistently reduced induction of IFN-I proteins in hospitalized COVID-19 patients upon stimulation, that was not associated with detectable neutralizing autoantibodies against IFNα or IFNω. We confirmed the poor induction of IFN-I in an independent patient cohort (n=33), and showed it was more pronounced with severe disease. Intracellular proteomic analysis showed that while monocyte numbers were increased in hospitalized COVID-19 patients, they did not secrete IFN-I in response to stimulation. This was further confirmed by ex vivo whole blood stimulation with IFN-I which induced a transcriptomic response associated with inflammation in hospitalized COVID-19 patients, that was not seen in controls or non-hospitalized moderate cases. These results may explain the dichotomy of the poor clinical response to IFN-I based treatments in late stage COVID-19, despite the critical importance of IFN-I in early acute infection. An improved understanding of such variable responses to treatment may help to identify potential alternative therapeutic strategies.

Published
2022

18. Characterization and Performance Enhancement of Cement-Based Thermoelectric Materials

Author

Ruchita Jani, Niall Holmes, Roger West, Kevin Gaughan, Xiaoli Liu, Ming Qu, Esther Orisakwe, Lorenzo Stella, Jorge Kohanoff, Hongxi Yin, Bartlomiej Wojciechowski, Niall Holmes, and This research is supported through a US-Ireland grant tri-funded by the National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
Polymers and Plastics, electrical conductivity, Física, Seebeck coefficient, General Chemistry, Civil Engineering, Ingeniería Civil y de la Construcción, cement composites, thermoelectrics, thermal conductivity, SDG 7 - Affordable and Clean Energy, Other Engineering
Abstract

Thermoelectric materials enable the direct conversion of thermal to electrical energy. One application of this is ambient heat energy harvesting where relatively stable temperature gradients existing between the inside and outside of a building could be utilized to produce electricity. Buildings can thus change from energy consumers to energy generators. This could ultimately help reduce the surface temperatures and energy consumption of buildings, especially in urban areas. In this paper, research work carried out on developing and characterizing a cement-based thermoelectric material is presented. Cement-based samples are doped with different metal oxides (Bi2O3 and Fe2O3) to enhance their thermoelectric properties, which are defined through their Seebeck coefficient, electrical conductivity and thermal conductivity. The study also discusses the positive impact of moisture content on the electrical conductivity

Published
2022
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19. Self-Photopolymerizable Hydrogel-Ceramic Composites with Scavenger Properties

Author

Maria Canillas, Gabriel Goetten de Lima, Marcelo J. C. de Sá, Michael J. D. Nugent, Miguel A. Rodríguez, Declan M. Devine, Technological University of the Shannon Midlands Midwest, and This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001, and Science Foundation Ireland (SFI), Grant Number SFI 16/RC/3918, cofunded by the European Regional Development Fund.

Subjects
MM [Materials Research Institute TUS], Photoinitiator, photoinitiator, hydrogels, photo-Kolbe reaction, Polymers and Plastics, Hydrogels, General Chemistry, Photinitiator
Abstract

The photocatalytic behaviours of semiconductive ceramic nanoparticles such as TiO2, ZnO, Fe2O3, and Fe3O4, have been extensively studied in photocatalysis and photopolymerization, due to their ability to produce radical species under ultraviolet–visible light, and even in dark conditions. In addition, in the form of microparticles, TiO2 and its Magnéli phases are capable of neutralizing radical species, and a heterogeneous catalytic process has been suggested to explain this property, as it is well known as scavenging activity. Thus, in this study, we demonstrate that these ceramic powders, in the form of microparticles, could be used as photoinitiators in UV polymerization in order to synthesize a hydrogel matrix. Them, embedded ceramic powders could be able to neutralize radical species of physiological media once implanted. The hydrogel matrix would regulate the exchange of free radicals in any media, while the ceramic particles would neutralize the reactive species. Therefore, in this work, the scavenger activities of TiO2, ZnO, Fe2O3, and Fe3O4 microparticles, along with their photoinitiation yield, were evaluated. After photopolymerization, the gel fraction and swelling behaviour were evaluated for each hydrogel produced with different ceramic initiators. Gel fractions were higher than 60%, exhibiting variation in their scavenging activity. Therefore, we demonstrate that ceramic photoinitiators of TiO2, ZnO, Fe2O3, and Fe3O4 can be used to fabricate implantable devices with scavenger properties in order to neutralize radical species involved in inflammatory processes and degenerative diseases.

Published
2022

20. Ultrasound 96 Probe Device Protocol for cancer cell treatment

Author

Field, Aisling, Tiwari, Brijesh K, Curtin, James F, Mondala, Julie R M, Wanigasekara, Janith, Prof. James F. Curtin, Science Foundation Ireland (SFI), and Walsh Scholar Programme

Subjects
3D cell culture, Ultrasound, Medical Biophysics, Cell Biology, Medical Biochemistry, Biochemistry, 2D cell culture, Cancer, Cancer Biology
Abstract

Ultrasound is a sound wave with frequencies ranging between 20 kHz and 20 MHz. Ultrasound is able to temporarily and repeatedly open the BBB safely and enhance chemotherapeutic delivery without adverse effects. This novel technique in drug delivery benefits from the powerful ability of ultrasound to produce cavitation activity. Cavitation is the generation and activity of gas-filled bubbles in a medium exposed to ultrasound. As the pressure wave passes through the media, gas bubbles expand at low pressure and contract at high pressure. This leads to oscillation which produces a circulating fluid flow known as microstreaming around the bubble with velocities and shear rates proportional to the amplitude of the oscillation. At high amplitudes the associated shear forces can cut open liposomes

Published
2022

21. Plasma induced reactive oxygen species-dependent cytotoxicity in glioblastoma 3D tumourspheres

Author

Janith Wanigasekara, Carlos Barcia, Patrick J. Cullen, Brijesh Tiwari, James F. Curtin, James F. Curtin, Science Foundation Ireland (SFI), and Teagasc Walsh Fellowship

Subjects
Polymers and Plastics, glioblastoma, Cell Biology, cold atmospheric plasma, Condensed Matter Physics, Biochemistry, 3D tumourspheres, Cell and Developmental Biology, ROS dependent, Oncology, Medical Specialties, Medicine and Health Sciences, cytotoxicity, epidermoid, Molecular Biology, reactive oxygen and nitrogen species, Biochemistry, Biophysics, and Structural Biology, Cancer Biology
Abstract

The aim of this study was to determine the effects of a pin‐to‐plate cold atmospheric plasma (CAP) on U‐251 MG three‐dimensional (3D) glioblastoma spheroids under different conditions. 3D tumorspheres showed higher resistance to the CAP treatment compared to 2D monolayer cells. A single CAP treatment was able to induce cytotoxicity, while multiple CAP treatments augmented this effect. CAP was also able to induce cytotoxicity throughout the tumoursphere, and we identified that reactive oxygen species(ROS) plays a major role, while H2O2plays a partial role in CAP‐induced cytotoxicity in tumour-spheres. We conclude that ROS‐dependent cytotoxicity is induced uniformly throughout glioblastoma and epidermoid tumourspheres by direct CAP treatment.

Published
2022

22. Shape memory alloy-based wearables: a review, and conceptual frameworks on HCI and HRI in Industry 4.0

Author

Rupal Srivastava, Saeed Hamood Alsamhi, Niall Murray, Declan Devine, Technological University of the Shannon Midlands Midwest, and Marie Skłodowska-Curie grant agreement No. 847577 cofunded by the European Regional Development Fund and Science Foundation Ireland (SFI) under Grant Number SFI/16/RC/3918

Subjects
Robotics, Biochemistry, Atomic and Molecular Physics, and Optics, Human-computer interaction, Analytical Chemistry, shape memory alloys, smart wearables, hand exoskeletons, human-robot interaction, human-computer interaction, Shape Memory Alloys, Wearable Electronic Devices, MM [Materials Research Institute TUS], Shape memory alloys, Alloys, Humans, Hand exoskeletons, Smart wearables, Electrical and Electronic Engineering, Human-robot interaction, Plastics, Instrumentation
Abstract

Ever since its discovery, the applications of Shape Memory Alloys (SMA) can be found across a range of application domains, from structural design to medical technology. This is based upon the unique and inherent characteristics such as thermal Shape Memory Effect (SME) and Superelasticity (or Pseudoelasticity). While thermal SME is used for shape morphing applications wherein temperature change can govern the shape and dimension of the SMA, Superelasticity allows the alloy to withstand a comparatively very high magnitude of loads without undergoing plastic deformation at higher temperatures. These unique properties in wearables have revolutionized the field, and from fabrics to exoskeletons, SMA has found its place in robotics and cobotics. This review article focuses on the most recent research work in the field of SMA-based smart wearables paired with robotic applications for human-robot interaction. The literature is categorized based on SMA property incorporated and on actuator or sensor-based concept. Further, use-cases or conceptual frameworks for SMA fiber in fabric for ‘Smart Jacket’ and SMA springs in the shoe soles for ‘Smart Shoes’ are proposed. The conceptual frameworks are built upon existing technologies; however, their utility in a smart factory concept is emphasized, and algorithms to achieve the same are proposed. The integration of the two concepts with the Industrial Internet of Things (IIoT) is discussed, specifically regarding minimizing hazards for the worker/user in Industry 5.0. The article aims to propel a discussion regarding the multi-faceted applications of SMAs in human-robot interaction and Industry 5.0. Furthermore, the challenges and the limitations of the smart alloy and the technological barriers restricting the growth of SMA applications in the field of smart wearables are observed and elaborated.

Published
2022

23. An Ensemble Machine Learning Method for Microplastics Identification with Ftir Spectrum

Author

Xinyu Yan, Zhi Cao, Alan Murphy, Yuansong Qiao, Technological University of the Shannon Midlands Midwest, and Technological University of the Shannon (TUS), Ireland under President’s Doctoral Scholarship 2020, and Science Foundation Ireland (SFI) under Grant Number SFI 16/RC/3918, co funded by the European Regional Develop

Subjects
History, Data pre-processing, Polymers and Plastics, Process Chemistry and Technology, Deep learning, Pollution, Industrial and Manufacturing Engineering, FTIR, Machine learning, Chemical Engineering (miscellaneous), Microplastics identification, Business and International Management, Waste Management and Disposal, MM [Software Research Institute TUS]
Abstract

Microplastics (MPs) (size < 5 mm) marine pollution have been investigated and monitored by many researchers and found in many coasts around the world. These toxic chemicals make their way into human diet through food chain when aquatic organisms ingest MPs. Attenuated Total Reflection Fourier transform infrared spectroscopy (ATR-FTIR) is a very effective method to detect MPs. To provide the automatic detecting method for MPs, Numerous studies have proposed Machine Learning (ML) based methods, such as Support Vector Machines, K Nearest Neighbours, and Random Forests, for identification and classification of MPs through using the ATR FTIR data. The evaluations of these ML based methods primarily focus on the average scores across all types of MPs. However, the existing FTIR datasets are normally imbalanced. Furthermore, some MPs contain the identical functional group, and some MPs may be fouled or contaminated, which will reduce the quality of FTIR data samples (e.g. lacking of peaks or creating noises). These factors will interfere the ML classification algo rithms and cause the algorithms to perform differently while identifying different MPs. Hence, this work pro poses an ensemble learning algorithm to exploit the advantage of different ML algorithms based on a systematic evaluation of the existing ML based MP identification approaches. A neural network is employed to fuse the outputs of chosen ML algorithms to improve the overall metrics. The evaluation results show that the proposed algorithm outperforms existing single ML based approaches. no

Published
2022
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24. Performance Modeling and Analysis of a Thermoelectric Building Envelope for Space Heating

Author

Liu, Xiaoli, Qu, Ming, Yazawa, Kazuaki, Kohanoff, Jorge, Chudzinski, Piotr, Stella, Lorenzo, Norton, Brian, Holmes, Niall, Dr., Jani, Ruchita, Yin, Hongxi, Niall Holmes, and This research is supported through a US-Ireland grant tri-funded by the National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
building, modeling, heating, thermoelectric, Civil Engineering, performance
Abstract

To provide energy-efficient space heating and cooling, a thermoelectric building envelope (TBE) embeds thermoelectric devices in building walls. The thermoelectric device in the building envelope can provide active heating and cooling without requiring refrigerant use and energy transport among subsystems. Thus, the TBE system is energy and environmentally friendly. A few studies experimentally investigated the TBE under limited operating conditions, and only simplified models for the commercial thermoelectric module (TEM) were developed to quantify its performance. A holistic approach to optimum system performance is needed for the optimal system design and operation. The study developed a holistic TBE-building system model in Modelica for system simulation and performance analysis. A theoretical model for a single TEM was first established based on energy conversion and thermoelectric principles. Subsequently, a TBE prototype model combining the TEM model was constructed. The prototype model employing a feedback controller was used in a whole building system simulation for a residential house. The system model computed the overall building energy efficiency and dynamic indoor conditions under varying operating conditions. Simulation results indicate the studied TBE system can meet a heating demand to maintain the desired room temperature at 20 °C when the lowest outdoor temperature is at -26.3 degrees C, with a seasonal heating COP near 1.1, demonstrating a better heating performance than electric heaters. It suggests a potential energy-efficient alternative to the traditional natural gas furnaces and electric heaters for space heating.

Published
2022
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25. Regulated IRE1 alpha-dependent decay (RIDD)-mediated reprograming of lipid metabolism in cancer

Author

Aitor Almanza, Katarzyna Mnich, Arnaud Blomme, Claire M. Robinson, Giovanny Rodriguez-Blanco, Sylwia Kierszniowska, Eoghan P. McGrath, Matthieu Le Gallo, Eleftherios Pilalis, Johannes V. Swinnen, Aristotelis Chatziioannou, Eric Chevet, Adrienne M. Gorman, Afshin Samali, National University of Ireland [Galway] (NUI Galway), Cancer Research UK Cambridge Institute [Cambridge, Royaume-Uni] (CRUK), University of Cambridge [UK] (CAM), Oncogenesis, Stress, Signaling (OSS), Université de Rennes (UR)-CRLCC Eugène Marquis (CRLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM), CRLCC Eugène Marquis (CRLCC), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Biomedical Research Foundation of the Academy of Athens (BRFAA), NUI Galway, Science Foundation Ireland, Irish Government's Program for Research in Third Level Institutions, Cycle 5, European Regional Development Fund, Precision Oncology Ireland - Science Foundation Ireland (SFI) Strategic Partnership Program [18/SPP/3522], EU H2020 MSCA [RISE-734749, ITN-675448], SFI Industry Fellowship [18/IF/6247], Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-CRLCC Eugène Marquis (CRLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
EXPRESSION, X-Box Binding Protein 1, GENES, General Physics and Astronomy, [SDV.CAN]Life Sciences [q-bio]/Cancer, IRE1, Protein Serine-Threonine Kinases, General Biochemistry, Genetics and Molecular Biology, ENDOPLASMIC-RETICULUM STRESS, Neoplasms, Endoribonucleases, Humans, RNA, Messenger, Science & Technology, MESSENGER-RNA DECAY, Multidisciplinary, UNFOLDED PROTEIN RESPONSE, General Chemistry, ER STRESS, Endoplasmic Reticulum Stress, Lipid Metabolism, NEGATIVE BREAST-CANCER, XBP1, Multidisciplinary Sciences, Science & Technology - Other Topics, CELL FATE, Transcription Factors
Abstract

International audience; IRE1 alpha cleaves several mRNAs upon accumulation of misfolded proteins. Here the authors show that active IRE1 alpha cleaves DGAT2 mRNA encoding the rate-limiting enzyme in the synthesis of triacylglycerols, suggesting a role of IRE1 alpha in reprogramming lipid metabolism in cancer cells. IRE1 alpha is constitutively active in several cancers and can contribute to cancer progression. Activated IRE1 alpha cleaves XBP1 mRNA, a key step in production of the transcription factor XBP1s. In addition, IRE1 alpha cleaves select mRNAs through regulated IRE1 alpha-dependent decay (RIDD). Accumulating evidence implicates IRE1 alpha in the regulation of lipid metabolism. However, the roles of XBP1s and RIDD in this process remain ill-defined. In this study, transcriptome and lipidome profiling of triple negative breast cancer cells subjected to pharmacological inhibition of IRE1 alpha reveals changes in lipid metabolism genes associated with accumulation of triacylglycerols (TAGs). We identify DGAT2 mRNA, encoding the rate-limiting enzyme in TAG biosynthesis, as a RIDD target. Inhibition of IRE1 alpha, leads to DGAT2-dependent accumulation of TAGs in lipid droplets and sensitizes cells to nutritional stress, which is rescued by treatment with the DGAT2 inhibitor PF-06424439. Our results highlight the importance of IRE1 alpha RIDD activity in reprograming cellular lipid metabolism.

Published
2022
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26. Anomalous distributed traffic: detecting cyber security attacks amongst microservices using graph convolutional networks

Author

Stephen Jacob, Yuansong Qiao, Yuhang Ye, Brian Lee, Technological University of the Shannon Midlands Midwest, and f Athlone Institute of Technology under its Presidents Seed Fund (2021) and Science Foundation Ireland (SFI)

Subjects
General Computer Science, Microservices, Traffic forecasting, Graph convolutional network, Anomaly detection, Cyber security, Law, Distributed tracing, MM [Software Research Institute TUS]
Abstract

Currently, microservices are trending as the most popular software application design architecture. Software organisations are also being targeted by more cyber-attacks every day and newer security measures are in high demand. One available measure is the application of anomaly detection, which is defined as the discovery of irregular or unusual activity that occurs to a greater or lesser degree than normal occurrences in a data series. In this paper, we continue existing work where various real-world cyber-attacks are executed against a running microservices application, and the application traffic is logged and returned in the form of distributed traces. A Diffusion Convolutional Recurrent Neural Network is used to model the set of distributed traces and learn the spatial and temporal dependencies of the application traffic. Subsequently, the model is used to make predictions for ongoing microservice activity and threshold-based anomaly detection is applied to detect irregular microservice activity indicating the presence of seeded cyber security attacks, or anomalies. The cyber-attacks used to evaluate this approach include a brute force attack, a batch registration of bot accounts and a distributed denial of service attack. yes

Published
2022

27. A two phase escarpment evolution of the Red Sea margin of southwestern Saudi Arabia. Insights from low-temperature apatite thermochronology

Author

Syed Ali Turab, Kurt Stüwe, Finlay M. Stuart, Nathan Cogne, David M. Chew, Jörg Robl, Karl-Franzens-Universität Graz, University of Peshawar (UOP), Scottish Universities Environmental Research Centre (SUERC), University of Glasgow-University of Edinburgh, Géosciences Rennes (GR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Trinity College Dublin, University of Salzburg, Higher Education Commission (HEC) of Pakistan, FWF Project (P22351-N22), Saudi Geological Survey, and Science Foundation Ireland (SFI) under grant numbers 13/RC/2092_P2 and 13/RC/2092_P2 (iCRAG - the SFI Research Centre in Applied Geosciences)

Subjects
Geophysics, escarpment evolution, [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry, Space and Planetary Science, Geochemistry and Petrology, orographic precipitation, Saudi Arabia, geomorphic analysis, Earth and Planetary Sciences (miscellaneous), low-temperature thermochronology, [SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology
Abstract

International audience; Rifting of the Red Sea resulted in the formation of one of the highest escarpments on our planet: the Great Escarpment of southwestern Saudi Arabia. Published low-temperature geochronology ages are around the Paleogene-Neogene transition, but geomorphic features like the height, the steepness and the preservation of the escarpment may indicate a younger aspect to the exhumation history. Here we use apatite fission track (AFT) and (U-Th-Sm)/He (AHe) cooling ages in combination with a geomorphic analysis of the region from Jeddah to Jizan to test this idea. Pooled AFT ages range from to Ma (1σ). The base of the AFT partial annealing zone prior to rock uplift is at ∼200 m elevation in most of the studied area, but track length data show that the amount of exhumation is insufficient to affect all coastal plain samples. Consistent with earlier estimates in the literature, the total amount of rock uplift is estimated to be ∼4 km. Single grain AHe ages range from to Ma (1σ) and do not have a clear trend with distance from the escarpment. Overall, the distribution of data appears to indicate widespread downwearing of the elevated topography around the rift flank. In contrast, geomorphic analysis that indicates escarpment retreat including a flexural uplift response. We suggest that the conflict between geomorphological and geochronological data can be resolved by invoking a two-stage erosion model. The first stage involved dome-shaped rift flank uplift since initiation of the Afar plume, downwearing of this topography and cooling recorded by the AFT ages. The second stage involved the massive erosion that excavated the present day Saudi escarpment and reset the AHe ages. We suggest that this second stage is related to the formation of oceanic lithosphere since 13 Ma in the Red Sea, associated downwarping of the margin and flexural updoming of the eastern rift flank. The consequential orographic precipitation initiated asymmetric erosion and formation of a retreating escarpment. This model is consistent with the large age difference between Miocene AFT and Pliocene AHe ages and the geomorphic metrics.

Published
2023
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28. Maximum depth sequencing reveals an ON/OFF replication slippage switch and apparent in vivo selection for bifidobacterial pilus expression

Author

Christophe Penno, Mary O’Connell Motherway, Yuan Fu, Virag Sharma, Fiona Crispie, Paul D. Cotter, Benoit Houeix, Lokesh Joshi, Francesca Bottacini, Aoife O’Dwyer, Gary Loughran, John F. Atkins, Douwe van Sinderen, Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), University College Cork (UCC), Aberystwyth University, University of Limerick (UL), National University of Ireland [Galway] (NUI Galway), National University of Ireland Maynooth (Maynooth University), MTU - Munster Technological University, and This work was supported by Science Foundation Ireland (SFI) through the Irish Government’s National Development Plan [grant numbers SFI/12/RC/2273-P1, SFI/12/RC/2273-P2], and an HRB postdoctoral fellowship [grant no. PDTM/20011/9] awarded to MOCM. AD was supported by an internal APC summer studentship. GL and JFA were supported by Irish Research Council Advanced Laureate award IRCLA/2019/74 to J.F.A.

Subjects
Mice, Multidisciplinary, Host Microbial Interactions, Fimbriae, Bacterial, Animals, Humans, Bifidobacterium, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Bifidobacterium breve, Gastrointestinal Microbiome
Abstract

The human gut microbiome, of which the genus Bifidobacterium is a prevalent and abundant member, is thought to sustain and enhance human health. Several surface-exposed structures, including so-called sortase-dependent pili, represent important bifidobacterial gut colonization factors. Here we show that expression of two sortase-dependent pilus clusters of the prototype Bifidobacterium breve UCC2003 depends on replication slippage at an intragenic G-tract, equivalents of which are present in various members of the Bifidobacterium genus. The nature and extent of this slippage is modulated by the host environment. Involvement of such sortase-dependent pilus clusters in microbe-host interactions, including bacterial attachment to the gut epithelial cells, has been shown previously and is corroborated here for one case. Using a Maximum Depth Sequencing strategy aimed at excluding PCR and sequencing errors introduced by DNA polymerase reagents, specific G-tract sequences in B. breve UCC2003 reveal a range of G-tract lengths whose plasticity within the population is functionally utilized. Interestingly, replication slippage is shown to be modulated under in vivo conditions in a murine model. This in vivo modulation causes an enrichment of a G-tract length which appears to allow biosynthesis of these sortase-dependent pili. This work provides the first example of productive replication slippage influenced by in vivo conditions. It highlights the potential for microdiversity generation in “beneficial” gut commensals.

Published
2021
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29. Domain Wall Dynamics in a Ferroelastic Spin Crossover Complex with Giant Magnetoelectric Coupling

Author

Vibe Boel Jakobsen, Elzbieta Trzop, Emiel Dobbelaar, Laurence C. Gavin, Shalinee Chikara, Xiaxin Ding, Minseong Lee, Kane Esien, Helge Müller-Bunz, Solveig Felton, Eric Collet, Michael A. Carpenter, Vivien S. Zapf, Grace G. Morgan, University College Dublin [Dublin] (UCD), Institut de Physique de Rennes (IPR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Auburn University (AU), Los Alamos National Laboratory (LANL), Queen's University [Belfast] (QUB), University of Cambridge [UK] (CAM), Science Foundation Ireland (SFI) Science Foundation Ireland [19/FFP/6909], Irish Research CouncilIrish Research Council for Science, Engineering and Technology [GOIPG/2016/73], Augustinus Fonden [18-0338], Oticon Fonden [17-3813], Reinholdt W. Jorck og Hustrus Fond [18-JI-0573], P. A. Fiskers Fond, A. P. MOller og Hustru Chastine Mc-Kinney MOllers Fond til almene Formaal, Christian og Ottilia Brorsons Rejselegat for yngre videnskabsmaend og-kvinder, Natural Environment Research Council of Great Britain [NE/B505738/1, NE/F17081/1], Engineering and Physical Sciences Research CouncilUK Research and Innovation (UKRI) Engineering and Physical Sciences Research Council (EPSRC) [EP/I036079/1], U.S. National Science FoundationNational Science Foundation (NSF) [DMR-1157490], State of Florida, U.S. Department of Energy United States Department of Energy (DOE), Laboratory-Directed Research and Development program (LDRD), U.S. Department of Energy, Office of Science, Basic Energy Sciences United States Department of Energy (DOE) [DE SC0019330], Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[PHYS]Physics [physics], Colloid and Surface Chemistry, Phase transitions, Polarization, Order, General Chemistry, Transition metals, Biochemistry, Quantum mechanics, Catalysis, Article
Abstract

International audience; Pinned and mobile ferroelastic domain walls are detected in response to mechanical stress in a Mn3+ complex with two-step thermal switching between the spin triplet and spin quintet forms. Single-crystal X-ray diffraction and resonant ultrasound spectroscopy on [Mn-III(3,5-diCl-sal(2)(323))]BPh4 reveal three distinct symmetry-breaking phase transitions in the polar space group series Cc -> Pc -> P1 -> P1((1/2)). The transition mechanisms involve coupling between structural and spin state order parameters, and the three transitions are Landau tricritical, first order, and first order, respectively. The two first-order phase transitions also show changes in magnetic properties and spin state ordering in the Jahn-Teller-active Mn3+ complex. On the basis of the change in symmetry from that of the parent structure, Cc, the triclinic phases are also ferroelastic, which has been confirmed by resonant ultrasound spectroscopy. Measurements of magnetoelectric coupling revealed significant changes in electric polarization at both the Pc -> P1 and P1 -> P1((1/2)) transitions, with opposite signs. All these phases are polar, while P1 is also chiral. Remanent electric polarization was detected when applying a pulsed magnetic field of 60 T in the P1 -> P1((1/2)) region of bistability at 90 K. Thus, we showcase here a rare example of multifunctionality in a spin crossover material where the strain and polarization tensors and structural and spin state order parameters are strongly coupled.

Published
2021
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30. Kinetics of the Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Response and Serological Estimation of Time Since Infection

Author

Pelleau, Stéphane, Woudenberg, Tom, Rosado, Jason, Donnadieu, Françoise, Garcia, Laura, Obadia, Thomas, Gardais, Soazic, Elgharbawy, Yasmine, Velay, Aurelie, Gonzalez, Maria, Nizou, Jacques Yves, Khelil, Nizar, Zannis, Konstantinos, Cockram, Charlotte, Merkling, Sarah Hélène, Meola, Annalisa, Kerneis, Solen, Terrier, Benjamin, de Seze, Jerome, Planas, Delphine, Schwartz, Olivier, Dejardin, François, Petres, Stéphane, von Platen, Cassandre, Pellerin, Sandrine Fernandes, Arowas, Laurence, de Facci, Louise Perrin, Duffy, Darragh, Cheallaigh, Clíona Ní, Dunne, Jean, Conlon, Niall, Townsend, Liam, Duong, Veasna, Auerswald, Heidi, Pinaud, Laurie, Tondeur, Laura, Backovic, Marija, Hoen, Bruno, Fontanet, Arnaud, Mueller, Ivo, Fafi-Kremer, Samira, Bruel, Timothée, White, Michael, Epidémiologie et Analyse des Maladies Infectieuses - Infectious Disease Epidemiology and Analytics, Institut Pasteur [Paris] (IP), Malaria : parasites et hôtes - Malaria : parasites and hosts, Santé publique : épidémiologie & sciences de l'information biomédicale (ED 393), Sorbonne Université (SU), Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Immuno-Rhumatologie Moléculaire, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Strasbourg, Institut Mutualiste de Montsouris (IMM), Régulation spatiale des Génomes - Spatial Regulation of Genomes, Interactions Virus-Insectes - Insect-Virus Interactions (IVI), Virologie Structurale - Structural Virology, Epidémiologie et modélisation de la résistance aux antimicrobiens - Epidemiology and modelling of bacterial escape to antimicrobials (EMAE), Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Department of Internal Medicine, National Referral Center for Rare Systemic Autoimmune Diseases, Assistance Publique Hôpitaux de Paris-Centre (APHP-CUP), Université de Paris, Paris, France, Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), CIC Strasbourg (Centre d’Investigation Clinique Plurithématique (CIC - P) ), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nouvel Hôpital Civil de Strasbourg-Hôpital de Hautepierre [Strasbourg], Virus et Immunité - Virus and immunity (CNRS-UMR3569), Plateforme technologique Production et purification de protéines recombinantes – Production and Purification of Recombinant Proteins Technological Platform (PPR), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Investigation Clinique et d’Accès aux Ressources Biologiques (Plate-forme) - Clinical Investigation and Access to BioResources (ICAReB), Immunologie Translationnelle - Translational Immunology lab, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Trinity College Dublin, Institut Pasteur du Cambodge, Réseau International des Instituts Pasteur (RIIP), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Direction de la recherche médicale de l'Institut Pasteur, Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), The Walter and Eliza Hall Institute of Medical Research (WEHI), University of Melbourne, Vaccine Research Institute [Créteil, France] (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), This work was supported by the European Research Council (MultiSeroSurv ERC Starting Grant 852373, MW), l’Agence Nationale de la Recherche and Fondation pour la Recherche Médicale (CorPopImm, MW), and the Institut Pasteur International Network (CoronaSeroSurv, MW). JR was supported by the Pasteur Paris University (PPU) International PhD Program. CC was supported by the European Research Council 771813. MB, AL and HA were supported by the « URGENCE COVID-19 » fundraising campaign of Institut Pasteur. HA is supported by Centre for International Migration and Development. NC and CNC are part-funded by a Science Foundation Ireland (SFI) grant, Grant Code 20/SPP/3685. LT has been awarded the Irish ClinicalAcademic Training (ICAT) Programme, supported by the Wellcome Trust and the Health Research Board (Grant Number 203930/B/16/Z), the Health Service Executive, National Doctors Training and Planning and the Health and Social Care, Research and Development Division, Northern Ireland (https://icatprogramme.org/). MB and AM were supported by Institut Pasteur TaskForce funding (TooLab project). IM is supported by a NHMRC Principal Research Fellowship. SFK lab is funded by Strasbourg University Hospitals (SeroCoV-HUS, PRI 7782), the Agence Nationale de la Recherche (ANR-18-CE17-0028), Laboratoire d'Excellence TRANSPLANTEX (ANR-11-LABX-0070_TRANSPLANTEX), and Institut National de la Santé et de la Recherche Médicale (UMR_S1109)., ANR-20-COVI-0052,CorPopImm,Évaluer l'immunité contre SARS-CoV-2 à l'échelle de la population grâce aux tests sérologiques(2020), ANR-18-CE17-0028,HuMABK,Les anticorps monoclonaux humains : une Nouvelle approche thérapeutique contre l'infection par le virus BK et les maladies associées(2018), ANR-11-LABX-0070,TRANSPLANTEX,Nouveaux loci d'histocompatibilité/biomarqueurs en transplantation humaine: de la découverte à l'app(2011), European Project: 852373,ERC-2019-STG,MultiSeroSurv(2020), European Project: 771813,ERC-2017-COG,SynarchiC(2018), Institut Pasteur [Paris], Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), Virus et Immunité - Virus and immunity, Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université (HESAM)-HESAM Université (HESAM), HESAM Université (HESAM), Vaccine Research Institute (VRI), and HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)

Subjects
Male, Aucun, Antibodies, Viral, time since infection, MESH: Aged, 80 and over, Antibody Specificity, Seroepidemiologic Studies, MESH: COVID-19, Aged, 80 and over, MESH: Immunoglobulin G, MESH: Aged, MESH: Middle Aged, seroprevalence, MESH: Kinetics, Middle Aged, MESH: Antibody Formation, AcademicSubjects/MED00290, MESH: Young Adult, surveillance, [SDV.IMM]Life Sciences [q-bio]/Immunology, Female, France, Adult, antibody kinetics, Adolescent, SARS-SoV-2, Sensitivity and Specificity, Young Adult, Major Article, Humans, Serologic Tests, MESH: SARS-CoV-2, MESH: Antibody Specificity, Aged, MESH: Adolescent, MESH: Humans, MESH: Seroepidemiologic Studies, SARS-CoV-2, MESH: Serologic Tests, COVID-19, MESH: Adult, MESH: Male, MESH: Sensitivity and Specificity, MESH: France, Kinetics, sero-prevalence, Immunoglobulin G, Antibody Formation, MESH: Female, MESH: Antibodies, Viral
Abstract

Background Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. Methods We developed a multiplex serological test for measuring antibodies to 5 SARS-CoV-2 antigens and the spike proteins of seasonal coronaviruses. We measured antibody responses in cohorts of hospitalized patients and healthcare workers followed for up to 11 months after symptoms. A mathematical model of antibody kinetics was used to quantify the duration of antibody responses. Antibody response data were used to train algorithms for estimating time since infection. Results One year after symptoms, we estimate that 36% (95% range, 11%–94%) of anti-Spike immunoglobulin G (IgG) remains, 31% (95% range, 9%–89%) anti-RBD IgG remains, and 7% (1%–31%) of anti-nucleocapsid IgG remains. The multiplex assay classified previous infections into time intervals of 0–3 months, 3–6 months, and 6–12 months. This method was validated using data from a seroprevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey. Conclusions In addition to diagnosing previous SARS-CoV-2 infection, multiplex serological assays can estimate the time since infection, which can be used to reconstruct past epidemics., Longitudinal follow-up of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reveals differences in the duration of antibodies to multiple antigens. Mathematical models of antibody waning and statistical algorithms can estimate an individual’s time since SARS-CoV-2 infection, and previous transmission waves in a population.

Published
2021
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31. Early IFNβ secretion determines variable downstream IL-12p70 responses upon TLR4 activation

Author

Celine Posseme, Alba Llibre, Bruno Charbit, Vincent Bondet, Vincent Rouilly, Violaine Saint-André, Jeremy Boussier, Jacob Bergstedt, Nikaïa Smith, Liam Townsend, Jamie A. Sugrue, Clíona Ní Cheallaigh, Niall Conlon, Maxime Rotival, Michael S. Kobor, Estelle Mottez, Stanislas Pol, Etienne Patin, Matthew L. Albert, Lluis Quintana-Murci, Darragh Duffy, Laurent Abel, Andres Alcover, Hugues Aschard, Philippe Bousso, Nollaig Bourke, Petter Brodin, Pierre Bruhns, Nadine Cerf-Bensussan, Ana Cumano, Caroline Demangel, null Christophe d’Enfert, Ludovic Deriano, Marie-Agnès Dillies, James Di Santo, Françoise Dromer, Gérard Eberl, Jost Enninga, Jacques Fellay, Ivo Gomperts-Boneca, Milena Hasan, Magnus Fontes, Gunilla Karlsson Hedestam, Serge Hercberg, Molly A. Ingersoll, Rose Anne Kenny, Olivier Lantz, Mickael Ménager, Frédérique Michel, Hugo Mouquet, Cliona O'Farrelly, Sandra Pellegrini, Antonio Rausell, Frédéric Rieux-Laucat, Lars Rogge, Anavaj Sakuntabhai, Olivier Schwartz, Benno Schwikowski, Spencer Shorte, Frédéric Tangy, Antoine Toubert, Mathilde Touvier, Marie-Noëlle Ungeheuer, Christophe Zimmer, Immunologie Translationnelle - Translational Immunology lab, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Ecole Doctorale Frontiere de l’Innovation en Recherche et Education (ED 474 FIRE), Université Paris Cité (UPCité)-Université Paris sciences et lettres (PSL), Cytometrie et Biomarqueurs – Cytometry and Biomarkers (UTechS CB), Datactix, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Génétique Evolutive Humaine - Human Evolutionary Genetics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), St James’s Hospital [Dublin, Ireland], Trinity College Dublin, University of British Columbia [Vancouver], Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), HIBIO [South San Francisco], Collège de France - Chaire Génomique humaine et évolution, Collège de France (CdF (institution)), This study was funded with support from the French Governments Investissement dAvenir Program, Laboratoire Excellence Milieu Interieur Grant ANR-10-LABX-69-01 and by an Agence National de Recherche foundation grant (CE17001002)., The Milieu Intérieur Consortium is composed of the following team leaders: Laurent Abel (Hôpital Necker), Andres Alcover, Hugues Aschard, Philippe Bousso, Nollaig Bourke (Trinity College Dublin), Petter Brodin (Karolinska Institutet), Pierre Bruhns, Nadine Cerf-Bensussan (INSERM UMR 1163 – Institut Imagine), Ana Cumano, Caroline Demangel, Christophe d’Enfert, Ludovic Deriano, Marie-Agnès Dillies, James Di Santo, Françoise Dromer, Gérard Eberl, Jost Enninga, Jacques Fellay (EPFL, Lausanne), Ivo Gomperts-Boneca, Milena Hasan, Magnus Fontes (Institut Roche), Gunilla Karlsson Hedestam (Karolinska Institutet), Serge Hercberg (Université Paris 13), Molly Ingersoll, Rose Anne Kenny (Trinity College Dublin), Olivier Lantz (Institut Curie), Frédérique Michel, Hugo Mouquet, Cliona O'Farrelly (Trinity College Dublin), Etienne Patin, Sandra Pellegrini, Stanislas Pol (Hôpital Côchin), Antonio Rausell (INSERM UMR 1163 – Institut Imagine), Frédéric Rieux-Laucat (INSERM UMR 1163 – Institut Imagine), Lars Rogge, Anavaj Sakuntabhai, Olivier Schwartz, Benno Schwikowski, Spencer Shorte, Frédéric Tangy, Antoine Toubert (Hôpital Saint-Louis), Mathilde Touvier (Université Paris 13), Marie-Noëlle Ungeheuer, Christophe Zimmer, Matthew L. Albert (In Sitro), Darragh Duffy, Lluis Quintana-Murci, ANR-10-LABX-0069,MILIEU INTERIEUR,GENETIC & ENVIRONMENTAL CONTROL OF IMMUNE PHENOTYPE VARIANCE: ESTABLISHING A PATH TOWARDS PERSONALIZED MEDICINE(2010), ANR-20-CE17-0010,ELECTRO,Inhibition de l'Exchange Protein directly activated by cAMP -1 pour traiter la Fibrillation Atrial(2020), Institut Pasteur [Paris] (IP), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute-University of British Columbia (UBC), University of Cape Town, Département d'hépatologie [CHU Cochin], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Insitro [San Francisco], St James's University Hospital, Leeds Teaching Hospitals NHS Trust, University of British Columbia (UBC), This study was funded with support from the French Government’s Investissement d’Avenir Program, Laboratoire d’Excellence 'Milieu Intérieur' grant ANR-10-LABX-69-01, and by an Agence National de Recherche Foundation grant (CE17001002). We thank the UTechS CB of the Center for Translational Research, Institut Pasteur for supporting data generation, Pierre-Henri Commere for help with flow cytometry sorting, Aurelie Bisiaux for flow cytometry advice, and Dr. Molly Ingersoll for scientific advice and critical reading of the manuscript. D.D. thanks Immunoqure for provision of the mAbs under an MTA for the Simoa IFNα assay. We thank the STTAR-Bioresource of TCD-SJH-TUH COVID-19 bioresource, which supported collection of COVID-19 patient samples, and the 'URGENCE COVID-19' fundraising campaign of the Institut Pasteur (CoVarImm and Steroid Response) for supporting data generation of COVID-19 samples. N.S. is a recipient of the Pasteur-Roux-Cantarini Fellowship. N.C. and C.N.C. are part funded by a Science Foundation Ireland (SFI) grant, grant code 20/SPP/3685. L.T. is supported by the Irish Clinical Academic Training (ICAT) Program, supported by the Wellcome Trust and the Health Research Board (grant number 203930/B/16/Z), the Health Service Executive, National Doctors Training and Planning, and the Health and Social Care, Research and Development Division, Northern Ireland., Milieu Intérieur Consortium: Laurent Abel, Andres Alcover, Hugues Aschard, Philippe Bousso, Nollaig Bourke, Petter Brodin, Pierre Bruhns, Nadine Cerf-Bensussan, Ana Cumano, Caroline Demangel, Christophe d'Enfert, Ludovic Deriano, Marie-Agnès Dillies, James Di Santo, Françoise Dromer, Gérard Eberl, Jost Enninga, Jacques Fellay, Ivo Gomperts-Boneca, Milena Hasan, Magnus Fontes, Gunilla Karlsson Hedestam, Serge Hercberg, Molly A Ingersoll, Rose Anne Kenny, Olivier Lantz, Mickael Ménager, Frédérique Michel, Hugo Mouquet, Cliona O'Farrelly, Etienne Patin, Sandra Pellegrini, Stanislas Pol, Antonio Rausell, Frédéric Rieux-Laucat, Lars Rogge, Anavaj Sakuntabhai, Olivier Schwartz, Benno Schwikowski, Spencer Shorte, Frédéric Tangy, Antoine Toubert, Mathilde Touvier, Marie-Noëlle Ungeheuer, Christophe Zimmer, Matthew L Albert, Darragh Duffy, Lluis Quintana-Murci, and ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010)

Subjects
Lipopolysaccharides, Proteomics, History, Polymers and Plastics, [SDV]Life Sciences [q-bio], medicine.medical_treatment, Disease, systems immunology, Biology, General Biochemistry, Genetics and Molecular Biology, Industrial and Manufacturing Engineering, Immune system, medicine, Humans, Secretion, Epigenetics, Business and International Management, Epigenomics, TLR4 immune responses, Systems immunology, SARS-CoV-2, COVID-19, CP: Immunology, Interferon-beta, Interleukin-12, Toll-Like Receptor 4, Cytokine, IL-12p70, type I interferons, Immunology, TLR4, Cytokine variability, [SDV.IMM]Life Sciences [q-bio]/Immunology, Cytokines
Abstract

International audience; The interleukin-12 (IL-12) family comprises the only heterodimeric cytokines mediating diverse functional effects. We previously reported a striking bimodal IL-12p70 response to lipopolysaccharide (LPS) stimulation in healthy donors. Herein, we demonstrate that interferon β (IFNβ) is a major upstream determinant of IL-12p70 production, which is also associated with numbers and activation of circulating monocytes. Integrative modeling of proteomic, genetic, epigenomic, and cellular data confirms IFNβ as key for LPS-induced IL-12p70 and allowed us to compare the relative effects of each of these parameters on variable cytokine responses. Clinical relevance of our findings is supported by reduced IFNβ-IL-12p70 responses in patients hospitalized with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or chronically infected with hepatitis C (HCV). Importantly, these responses are resolved after viral clearance. Our systems immunology approach defines a better understanding of IL-12p70 and IFNβ in healthy and infected persons, providing insights into how common genetic and epigenetic variation may impact immune responses to bacterial infection.

Published
2021
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32. Polyesters with main and side chain phosphoesters as structural motives for biocompatible electrospun fibres

Author

Brian Gorey, Viviane Chiaradia, Claudia Sayer, Débora de Oliveira, Cathal J. Kearney, Pedro Henrique Hermes de Araújo, José Vladimir de Oliveira, Andreas Heise, André E. Polloni, Ronaldo J F C do Amaral, Science Foundation Ireland (SFI), CAPES, and CNPq

Subjects
Polymers and Plastics, Biocompatibility, Double bond, Bioengineering, 02 engineering and technology, polyesters, Conjugated system, 010402 general chemistry, 01 natural sciences, Biochemistry, Coupling reaction, Materials Chemistry, Side chain, Other Chemistry, Polymer, chemistry.chemical_classification, tunable biomaterials, Chemistry, Organic Chemistry, phophoester, Polymer Chemistry, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Polyester, Chemical engineering, 0210 nano-technology, Hybrid material
Abstract

Phosphoester containing polymers are promising materials in biomedical applications due to their biocompatibility and biodegradability. Utilising thiol-ene chemistry, the synthesis of two novel structural polymer motives combining polyesters and phophoester groups was explored. The first polymer was obtained by coupling ene-functional poly(thioether-phosphoester) with thiol functional poly(pentadecalactone). While the coupling reaction was successful, yields remained low presumably due to inadequate endgroup stoichiometry. The second polymer comprised phosphoester side groups conjugated to unsaturated poly(globalide). Double bond conversions up to 84% were achieved depending of the type of phosphoester thiol and relative reactant ratios. The resulting polymers transitioned from solid semicrystaline to liquid amorphous with increasing degree of phosphoester conjugation. Electrospun fibres from polymers with 14% phosphoester conjugation allowed attachment and survival of human dermal fibroblasts, indicating their biocompatibility. These polymers represent a new class of easily accessible biocompatible polyester-phosphoester hybrid materials as potential building blocks for tunable biomaterials.

Published
2020
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33. Employing Discrete Solid Phases to Represent C-S-H Solid Solutions in the Cemdata07 Thermodynamic Database to Model Cement Hydration Using the PHREEQC Geochemical Software

Author

Niall Holmes, Mark Tyrer, Denis Kelliher, Niall Holmes, and This research is supported through a US-Ireland grant tri-funded by the National Science Foundation (NSF, 1805818), Science Foundation Ireland (SFI, 17/US/3424), and the Department for the Economy of Northern Ireland (DfE, USI 127).

Subjects
cement, modelling, Fluid Flow and Transfer Processes, thermodynamics, solid solutions, Process Chemistry and Technology, General Engineering, General Materials Science, hydration, Civil Engineering, Instrumentation, Computer Science Applications
Abstract

This paper presents a cement hydration model over time using the cemdata07 thermodynamic database and a series of derived discrete solid phases (DSPs) to represent calcium silicate hydrate (C-S-H) as a binary solid solution with two end-members. C-S-H in cement is amorphous and poorly crystalline with a range of molar Ca/Si ratios from 0.6 to 1.7. It displays strongly incongruent dissolution behaviour, where the release of calcium into solution is several orders of magnitude greater than silicon. It is, therefore, important that any cement hydration model provides a credible account of this behaviour. C-S-H has been described in the cemdata07 thermodynamic database as a number of solid solutions using different end-members with differing levels of complexity. While solid solutions can be included in most modern geochemical software programs, they often lead to a significant increase in computation time. This paper presents how an incongruent solid solution between two C-S-H end-members may be represented as a number of DSPs to model cement hydration over time using the PHREEQC geochemical software. By using DSPs rather than modelling C-S-H as a nonideal solid solution, this gives the user full control of the input for the model, reducing the computational demand and analysis time with no loss in accuracy in predicting stable-phase assemblages and their associated pore chemistry over time.

Published
2022
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34. Karst modelling challenge 1: Results of hydrological modelling

Author

Dominique Thiéry, Naomi Mazzilli, Guillaume Artigue, Yong Chang, Yan Liu, Philip Schuler, Tanja Liesch, Pierre-Yves Jeannin, Eulogio Pardo-Igúzquiza, Hervé Jourde, Martin P. Lüthi, Laurence Gill, Jean-Baptiste Charlier, Thomas Wöhling, Andreas Wunsch, Arnauld Malard, Lea Duran, Anne Johannet, Thomas Reimann, Andreas Hartmann, Christoph Butscher, Alireza Kavousi, Swiss Institute for Speleology and Karst Studies (SISKA), Centre for Hydrogeology and Geothermics [Switzerland], Université de Neuchâtel (UNINE), IMT Mines Alès - ERT (ERT), IMT - MINES ALES (IMT - MINES ALES), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), HYTAKE : Hydrogéologie et Transferts dans les Aquifères Karstiques (HYTAKE), Hydrosciences Montpellier (HSM), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Technishe Universität Bergakademie Freiberg (TU Bergakademie Freiberg), Nanjing University (NJU), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Gestion de l'Eau, Acteurs, Usages (UMR G-EAU), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Trinity College Dublin, University of Freiburg [Freiburg], Service National d'Observation sur le KARST (SNO Karst), Institut national des sciences de l'Univers (INSU - CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Karlsruhe Institute of Technology (KIT), Universität Zürich [Zürich] = University of Zurich (UZH), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Instituto Geológico y Minero de España (IGME), Lincoln Agritech Ltd, Swiss National Research Foundation (SNF) for Swisskarst and Thermokarst projects (Grant Numbers 406140-125962 and 200021_188636), the Deutsche Forschungsgemeinschaft, DFG for the iKarst project (Grant Numbers: LI 727/31-1 and RE 4001/2-1). The work of E. Pardo-Igúzquiza was supported by research project PID2019-106435 GB-I00 of the Ministerio de Ciencia e Innovación of Spain. This TCD-Dublin was conducted within the Irish Centre for Research in Applied Geosciences (ICRAG), supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number 13/RC/2092. The authors would like to thank the French Karst National Observatory Service (SNO KARST) initiative at the INSU/CNRS for their diffusion of KarstMod platform., University of Zurich, Jeannin, Pierre-Yves, Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
010504 meteorology & atmospheric sciences, Groundwater flow, Calibration (statistics), Geography & travel, Hydrological modelling, 0207 environmental engineering, Karst, Hydrograph, 02 engineering and technology, Comparison, 01 natural sciences, Modelling, 2312 Water Science and Technology, Statistics, 910 Geography & travel, 020701 environmental engineering, 0105 earth and related environmental sciences, ddc:910, Water Science and Technology, Baseflow, Computational model, Recharge, Data set, 10122 Institute of Geography, 13. Climate action, [SDE]Environmental Sciences, Environmental science, Efficiency criteria, Groundwater model
Abstract

International audience; The complexity of karst groundwater flow modelling is reflected by the amount of simulation approaches. The goal of the Karst Modelling Challenge (KMC) is comparing different approaches on one single system using the same data set. Thirteen teams with different computational models for simulating discharge variations at karst springs have applied their respective models on one single data set coming from the Milandre Karst Hydrogeological System (MKHS). The approaches include neural networks, reservoir models, semi-distributed models and fully distributed groundwater models. Four and a half years of hourly or daily meteorological input and hourly discharge data were provided for model calibration. The validation comprised forecasting one year of discharge, without the observed discharge data. The model performance was evaluated using the volume conservation, Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) applied on the total discharge and individual flow components. As a result, the comparison of model performances is a challenging task due to the differences in the model architecture but also required time steps: some of the models require aggregated daily steps while others could be run using hourly data, which provided some interesting differences depending on how the data was transformed. The use of instantaneous data (e.g. value at noon) produces less bias that averaging hourly data over one day. The transformation of hourly into daily data produces a decrease of Nash and KGE of 0.05 to 0.08 (i.e. from 1 to ~0.93). The resulting simulations (forecasted values for year 2016) produced KGEs ranging between 0.83 and 0.37 (0.83 to −0.24 for NSE). Although the simulations matched the monitored flows reasonably well, most models struggled to simulate baseflow conditions accurately. In general, the models that performed the best for this exercise were the global ones (Gardenia and Varkarst), with a limited number of parameters, which can be calibrated using automatic calibration procedures. The neural network models also showed a fair potential, with one providing reasonable results despite the relatively short dataset available for warming-up (4.5 years). Semi-and fully distributed models also suggested that with some more effort they could perform well. The accuracy of model predictions does not seem to increase by using models with more than 9–12 calibration parameters. An evaluation of the relative errors between the forecasted and the observed values revealed that for most models, 50% of the forecasted values contained more than 50% of difference against the observed discharge rate, with 25% having a difference larger than 100%. A significant part of the poorly forecasted values corresponded to base-flow which was surprising given that as base-flow is generally much easier to predict than peak flow. Hence, this shows that modelling approaches and criteria for the calibration are too oriented towards peak-flow sections of the hydrographs, and that improvements could be gained by more focus on the base-flow.

Published
2021
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35. Kinetics of the SARS-CoV-2 antibody response and serological estimation of time since infection

Author

Pelleau, Stéphane, Woudenberg, Tom, Rosado, Jason, Donnadieu, Françoise, Garcia, Laura, Obadia, Thomas, Gardais, Soazic, Elgharbawy, Yasmine, Velay, Aurelie, Gonzalez, Maria, Nizou, Jacques Yves, Khelil, Nizar, Zannis, Konstantinos, Cockram, Charlotte, Merkling, Sarah Hélène, Meola, Annalisa, Kerneis, Solen, Terrier, Benjamin, de Seze, Jerome, Planas, Delphine, schwartz, olivier, Dejardin, François, Petres, Stéphane, von Platen, Cassandre, Pellerin, Sandrine Fernandes, Arowas, Laurence, de Facci, Louise Perrin, Duffy, Darragh, Cheallaigh, Clíona Ní, Dunne, Jean, Conlon, Niall, Townsend, Liam, Duong, Veasna, Auerswald, Heidi, Pinaud, Laurie, Tondeur, Laura, Backovic, Marija, Hoen, Bruno, Fontanet, Arnaud, Mueller, Ivo, Fafi-Kremer, Samira, Bruel, Timothée, White, Michael, Epidémiologie et Analyse des Maladies Infectieuses - Infectious Disease Epidemiology and Analytics, Institut Pasteur [Paris], Malaria : parasites et hôtes - Malaria : parasites and hosts, Santé publique : épidémiologie & sciences de l'information biomédicale (ED 393), Sorbonne Université (SU), Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Immuno-Rhumatologie Moléculaire, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Strasbourg, Institut Mutualiste de Montsouris (IMM), Régulation spatiale des Génomes - Spatial Regulation of Genomes, Interactions Virus-Insectes - Insect-Virus Interactions (IVI), Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris], Virologie Structurale - Structural Virology, Epidémiologie et modélisation de la résistance aux antimicrobiens - Epidemiology and modelling of bacterial escape to antimicrobials (EMAE), Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Department of Internal Medicine, National Referral Center for Rare Systemic Autoimmune Diseases, Assistance Publique Hôpitaux de Paris-Centre (APHP-CUP), Université de Paris, Paris, France, Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), CIC Strasbourg (Centre d’Investigation Clinique Plurithématique (CIC - P) ), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Strasbourg (UNISTRA)-Hôpital de Hautepierre [Strasbourg]-Nouvel Hôpital Civil de Strasbourg, Virus et Immunité - Virus and immunity, Plateforme technologique Production et purification de protéines recombinantes – Production and Purification of Recombinant Proteins Technological Platform (PPR), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Investigation Clinique et d’Accès aux Ressources Biologiques (Plate-forme) - Clinical Investigation and Access to BioResources (ICAReB), Immunologie Translationnelle - Translational Immunology lab, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Trinity College Dublin, Institut Pasteur du Cambodge, Réseau International des Instituts Pasteur (RIIP), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Direction de la recherche médicale de l'Institut Pasteur, Conservatoire National des Arts et Métiers [CNAM] (CNAM), The Walter and Eliza Hall Institute of Medical Research (WEHI), University of Melbourne, Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), This work was supported by the European Research Council (MultiSeroSurv ERC Starting Grant 852373, MW), l’Agence Nationale de la Recherche and Fondation pour la Recherche Médicale (CorPopImm, MW), and the Institut Pasteur International Network (CoronaSeroSurv, MW). JR was supported by the Pasteur Paris University (PPU) International PhD Program. CC was supported by the European Research Council 771813. MB, AL and HA were supported by the « URGENCE COVID-19 » fundraising campaign of Institut Pasteur. HA is supported by Centre for International Migration and Development. NC and CNC are part-funded by a Science Foundation Ireland (SFI) grant, Grant Code 20/SPP/3685. LT has been awarded the Irish ClinicalAcademic Training (ICAT) Programme, supported by the Wellcome Trust and the Health Research Board (Grant Number 203930/B/16/Z), the Health Service Executive, National Doctors Training and Planning and the Health and Social Care, Research and Development Division, Northern Ireland (https://icatprogramme.org/). MB and AM were supported by Institut Pasteur TaskForce funding (TooLab project). IM is supported by a NHMRC Principal Research Fellowship. SFK lab is funded by Strasbourg University Hospitals (SeroCoV-HUS, PRI 7782), the Agence Nationale de la Recherche (ANR-18-CE17-0028), Laboratoire d'Excellence TRANSPLANTEX (ANR-11-LABX-0070_TRANSPLANTEX), and Institut National de la Santé et de la Recherche Médicale (UMR_S1109)., ANR-20-COVI-0052,CorPopImm,Évaluer l'immunité contre SARS-CoV-2 à l'échelle de la population grâce aux tests sérologiques(2020), ANR-18-CE17-0028,HuMABK,Les anticorps monoclonaux humains : une Nouvelle approche thérapeutique contre l'infection par le virus BK et les maladies associées(2018), ANR-11-LABX-0070,TRANSPLANTEX,Nouveaux loci d'histocompatibilité/biomarqueurs en transplantation humaine: de la découverte à l'app(2011), European Project: 852373,ERC-2019-STG,MultiSeroSurv(2020), European Project: 771813,SynarchiC, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Pasteur [Paris], and HESAM Université (HESAM)

Subjects
antibody kinetics, time since infection, sero-prevalence, surveillance, [SDV.IMM]Life Sciences [q-bio]/Immunology, SARS-SoV-2
Abstract

All data and code used for reproducing the results is freely available on GitHub: https://github.com/MWhite-InstitutPasteur/SARSCoV2_AB_kinetics.; International audience; Background Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. Methods We developed a multiplex serological test for measuring antibodies to five SARS-CoV-2 antigens and the Spike proteins of seasonal coronaviruses. We measured antibody responses in cohorts of hospitalized patients and healthcare workers followed for up to eleven months after symptoms. A mathematical model of antibody kinetics was used to quantify the duration of antibody responses. Antibody response data were used to train algorithms for estimating time since infection. Results One year after symptoms, we estimate that 36% (95% range: 11%, 94%) of anti-Spike IgG remains, 31% (9%, 89%) anti-RBD IgG remains, and 7% (1%, 31%) anti-Nucleocapsid IgG remains. The multiplex assay classified previous infections into time intervals of 0–3 months, 3–6 months, and 6–12 months. This method was validated using data from a sero-prevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey. Conclusions In addition to diagnosing previous SARS-CoV-2 infection, multiplex serological assays can estimate the time since infection which can be used to reconstruct past epidemics.

Published
2021
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36. Bayesian Adaptive Path Allocation Techniques for Intra-Datacenter Workloads

Author

Chih-Heng Ke, Ali Malik, Hasanen Alyasiri, Ruairi de Frein, Obinna Izima, Science Foundation Ireland (SFI), and EOLAS

Subjects
Computer and Systems Architecture, Computer science, business.industry, probability, Cloud computing, Bayesian, SDN, traffic workloads, Packet loss, Systems and Communications, Path (graph theory), Benchmark (computing), The Internet, Data center, datacenter, Routing (electronic design automation), business, Dijkstra's algorithm, Computer network
Abstract

Data center networks (DCNs) are the backbone of many cloud and Internet services. They are vulnerable to link failures, that occur on a daily basis, with a high frequency. Service disruption due to link failure may incur financial losses, compliance breaches and reputation damage. Performance metrics such as packet loss and routing flaps are negatively affected by these failure events. We propose a new Bayesian learning approach towards adaptive path allocation that aims to improve DCN performance by reducing both packet loss and routing flaps ratios. The proposed approach incorporates historical information about link failure and usage probabilities into its allocation procedure, and updates this information on-the-fly during DCN operational time. We evaluate the proposed framework using an experimental platform built with the POX controller and the Mininet emulator. Compared with a benchmark shortest path algorithm, the results show that the proposed methods perform better in terms of reducing the packet loss and routing flaps.

Published
2021

37. Grammatical Evolution for Detecting Cyberattacks in Internet of Things Environments

Author

Ruairi de Frein, Ali Malik, John A. Clark, Hasanen Alyasiri, Science Foundation Ireland (SFI), and EOLAS

Subjects
IoT Security, Electrical and Electronics, business.industry, Computer science, Computer security, computer.software_genre, Unknown Attacks, Modern life, Evolutionary computation, Domain (software engineering), Grammatical Evolution, Grammatical evolution, Systems and Communications, Internet of Things, business, computer
Abstract

The Internet of Things (IoT) is revolutionising nearly every aspect of modern life, playing an ever greater role in both industrial and domestic sectors. The increasing frequency of cyber-incidents is a consequence of the pervasiveness of IoT. Threats are becoming more sophisticated, with attackers using new attacks or modifying existing ones. Security teams must deal with a diverse and complex threat landscape that is constantly evolving. Traditional security solutions cannot protect such sys- tems adequately and so researchers have begun to use Machine Learning algorithms to discover effective defence systems. In this paper, we investigate how one approach from the domain of evolutionary computation - grammatical evolution - can be used to identify cyberattacks in IoT environments. The experiments were conducted on up-to-date datasets and compared with state- of-the-art algorithms. The potential application of evolutionary computation-based approaches to detect unknown attacks is also examined and discussed

Published
2021
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38. Health-ID: a blockchain-based decentralized identity management for remote healthcare

Author

Badr Bellaj, Kashif Naseer Qureshi, Tiziana Margaria, Noel Crespi, Fares F Alharbi, Ibrahim Tariq Javed, Science Foundation Ireland (SFI Lero), Shaqra University, Institut Polytechnique de Paris (IP Paris), Département Réseaux et Services Multimédia Mobiles (RS2M), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Réseaux, Systèmes, Services, Sécurité (R3S-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Health Research Institute (HRI), University of Limerick (UL), and Bahria University

Subjects
Smart contract, Leadership and Management, Computer science, 0211 other engineering and technologies, Health Informatics, Digital identity, 02 engineering and technology, Telehealth, Computer security, computer.software_genre, Article, Identity management, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Ethereum, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Blockchain, Health Information Management, 0202 electrical engineering, electronic engineering, information engineering, eHealth, 021110 strategic, defence & security studies, Authentication, Health Policy, Hhealthcare, healthcare, Service provider, 3. Good health, Identity management system, Medicine, Decentralized identity, 020201 artificial intelligence & image processing, computer
Abstract

COVID-19 has made eHealth an imperative. The pandemic has been a true catalyst for remote eHealth solutions such as teleHealth. Telehealth facilitates care, diagnoses, and treatment remotely, making them more efficient, accessible, and economical. However, they have a centralized identity management system that restricts the interoperability of patient and healthcare provider identification. Thus, creating silos of users that are unable to authenticate themselves beyond their eHealth application’s domain. Furthermore, the consumers of remote eHealth applications are forced to trust their service providers completely. They cannot check whether their eHealth service providers adhere to the regulations to ensure the security and privacy of their identity information. Therefore, we present a blockchain-based decentralized identity management system that allows patients and healthcare providers to identify and authenticate themselves transparently and securely across different eHealth domains. Patients and healthcare providers are uniquely identified by their health identifiers (healthIDs). The identity attributes are attested by a healthcare regulator, indexed on the blockchain, and stored by the identity owner. We implemented smart contracts on an Ethereum consortium blockchain to facilities identification and authentication procedures. We further analyze the performance using different metrics, including transaction gas cost, transaction per second, number of blocks lost, and block propagation time. Parameters including block-time, gas-limit, and sealers are adjusted to achieve the optimal performance of our consortium blockchain.

Published
2021
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39. Event-driven ECG classification using an open-source, LC-ADC based non-uniformly sampled dataset

Author

Deepu John, Maryam Saeed, Qingyuan Wang, Antoine Frappe, Benoit Larras, Olev Martens, Barry Cardiff, University College Dublin [Dublin] (UCD), Tallinn University of Technology (TTÜ), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Microélectronique Silicium - IEMN (MICROELEC SI - IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Schlumberger Foundation, Science Foundation Ireland, SFI: 18/CRT/6183, Irish Research Council, This work is supported by 1) JEDAI project under the Chist-Era Program, 2)Schlumberger Foundation’s Faculty for the Future Program 3) Irish ResearchCouncil under the New Foundations Scheme and 4) Science FoundationIreland through the SFI Centre for Research Training in Machine Learning(18/CRT/6183), ANR-19-CHR3-0005,JEDAI,Event Driven Artificial Intelligence Hardware for Biomedical Sensors(2019), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), and Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA)

Subjects
Artificial neural network, Artificial neural networks, business.industry, Computer science, 020208 electrical & electronic engineering, Event-driven data, Signal compression, Cardiac arrhythmia, Pattern recognition, 02 engineering and technology, Converters, Reduction (complexity), [SPI]Engineering Sciences [physics], Signal-to-noise ratio, ComputingMethodologies_PATTERNRECOGNITION, Cardiac arrhythmia classification, Distortion, 0202 electrical engineering, electronic engineering, information engineering, Wearable sensors, ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS, Artificial intelligence, Quantization (image processing), business, LC-ADC
Abstract

The open-source event-driven ECG dataset is available at https://github.com/jedaiproject/Open-Source-Event-Driven-ECG-Dataset; International audience; In this article, non-uniformly sampled electrocardiogram (ECG) signals obtained from level-crossing analog-to-digital converters (LC-ADCs) are analyzed for event-driven classification and compression performance. The signal compression results show that it is important to assess the distortion in event-driven signals when simulating LC-ADC models, especially at lower resolutions and larger quantization steps. The effects of varying the LC-ADC parameters for the application of cardiac arrhythmia classifiers are also assessed using an artificial neural network (ANN) and the MIT-BIH Arrhythmia Database. In comparison with uniformly-sampled data, it is possible to achieve comparable classification accuracy at a much lower complexity with event-driven ECG signals. The results show the best event-driven model achieves over 97% accuracy with 79% reduction in ANN complexity with signal-to-distortion ratio (S/D)≥21dB. For S/D

Published
2021
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40. U-251MG Spheroid generation using a scaffold based method protocol

Author

Carroll, Lara J, Tiwari, Brijesh K, Curtin, James F, Wanigasekara, Janith, Prof. James F. Curtin, Science Foundation Ireland (SFI), and Walsh Scholar Programme

Subjects
3D cell culture, Scaffold, Cell and Developmental Biology, Engineering, Protocol, Cell Biology, Other Cell and Developmental Biology, Cancer Biology
Abstract

3D cell culture is a technique that is used to grow cells in vitro that will mimic an in vivo environment. 3D cell models are a helpful learning tool for researchers to better understand disease mechanisms and to explore different therapeutic properties of drugs. 3D cell cultures can be developed using patient derived cancer cells. Once they have been grown, these 3D cells can be used to screen for small molecule drugs or for genetic modification in for analysis of disease pathways or to predict drug treatments toxicity or efficacy. 3D cell cultures are a big step towards the more ethical testing of drug toxicity and efficacy as they decrease the need to use animals in research as well as providing more reliable results as the cells used are of human physiology. Cellusponge are 3D porous hydroxipropylcellulose scaffolds that are designed for use with cells that do not require specific ligands. As well as the standard non-coated cellusponge, there are two more of the same type of scaffold available for use that are made with two different coatings to allow for improved adaptation of different cell types, these are called Cellusponge-Gal and Cellusponge-Col. Cellusponge is a no-coating approach that is intended for use in the development of general soft tissue 3D culture. It has been used as soft matrix for 3D cell culture and 3D tumour model.

Published
2021

41. U-251MG Spheroid Generation Using Hanging Drop Method Protocol

Author

Carroll, Lara J, Tiwari, Brijesh K, Curtin, James F, Wanigasekara, Janith, Prof. James F. Curtin, Science Foundation Ireland (SFI), and Walsh Scholar Programme

Subjects
3D cell culture, Cell and Developmental Biology, Hanging drop plate method, Protocol, Cell Biology, Other Cell and Developmental Biology, Cancer Biology
Abstract

The use of 3D cell culture has been a major step in developing cellular models that can mimic physiological tissues. Traditional 2D cell cultures are often unable to accurately represent the cellular functions and responses that are present in tissues, as a result, research findings based on 2D cultures tend to be skewed with limited predictive capability. 3D cell cultures can be grown from cells obtained from cancer organoids in patients. These models are useful for understanding disease mechanisms and exploring drug therapeutics in areas such as toxicity and efficacy. In order to gather more physiologically relevant data, a variety of 3D cell culture techniques have been developed to mimic the in vivo characteristics of physiological tissues. This protocol describes in vitro generation of U-251MG spheroids using the hanging drop method. Advantages of using hanging drop plate method are, able to produce uniform size spheroids, low cost, comfortable to handling and suitable for short term culture. The main downside of this method is medium change, different drug treatment at different time points are impossible and labor intensive. This method uses the Perfecta3D hanging drop plate, a novel cell culture device that simplifies the process of spheroid formation, testing and analysis. Rather than having to invert the plates which often results in spillage or detachment, these plates are designed to create hanging drops using a plateau structure at the bottom of the plate.

Published
2021

42. U-251MG Spheroid generation using low attachment plate method protocol

Author

Carroll, Lara J, Tiwari, Brijesh K, Curtin, James F, Wanigasekara, Janith, Prof. James F Curtin, Science Foundation Ireland (SFI), and Teagasc Walsh Fellowship

Subjects
3D cell culture, Cell and Developmental Biology, Medical Sciences, protocol, Cell Biology, Other Cell and Developmental Biology, low attachment, Cancer Biology, Medical Cell Biology
Abstract

3D cell culture is a process used to grow cells in vitro to mimic an in vivo environment. 3D cell models are very useful for understanding disease mechanisms and exploring drug therapeutics. 3D cultures can be grown from cells taken from cancer organoids in patients. Once grown, they can be used to screen for small molecule drugs or they can be genetically modified in order to analyse disease pathways or predict the toxicity or efficacy of a drug treatment. These cultures decrease the need to use animals in research and provides more reliable results as it uses human physiology. This protocol describes the in vitro generation of spheroids using the low attachment plate method. This method uses low-adhesion plates that are coated with hydrophilic polymer to allow cells to cluster together, forming their own extracellular matrix, rather than sticking to the plate surface. The scaffold-free 3D cell culture models produced can more accurately reflect an in vivo microenvironment making them useful in the study of oncology, hepatotoxicity, neurology, nephrology and stem cell biology.

Published
2021

43. Giant Magnetoelectric Coupling and Magnetic-Field-Induced Permanent Switching in a Spin Crossover Mn(III) Complex

Author

Grace G. Morgan, Xiaxin Ding, Vivien Zapf, Hai-Ping Cheng, Jie-Xiang Yu, Shalinee Chikara, Conor T. Kelly, Franziska Weickert, Elzbieta Trzop, Vibe B. Jakobsen, Emiel Dobbelaar, Eric Collet, University College Dublin [Dublin] (UCD), Los Alamos National Laboratory (LANL), University of Florida [Gainesville] (UF), Institut de Physique de Rennes (IPR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), The scientific work by V.S.Z., H.P.C. and J.Y. was funded by the Center for Molecular Magnetic Quantum Materials (M2QM), an Energy Frontier Research Center funded by the U.S. Depart-ment of Energy, Office of Science, Basic Energy Sciences under Award DE SC0019330. G.G.M. would like to thank Science Foundation Ireland (SFI) for support via an Investigator Project Award (19/FFO/6909). V.B.J. was supported by the Irish Re-search Council GOIPG/2016/73 fellowship. Travel grants for V.B.J.’s research visits to LANL and IPR were funded by Augusti-nus Fonden (grant no. 18-0338), Oticon Fonden (grant no. 17-3813), Reinholdt W. Jorck og Hustrus Fond (grant no. 18-JI-0573), P.A. Fiskers Fond, A.P. Møller og Hustru Chastine Mc-Kinney Møllers Fond til almene Formaal and Christian og Ot-tilia Brorsons Rejselegat for yngre videnskabsmænd og -kvinder. C.T.K was supported by the Irish Research Council GOIPG/2018/2510 and UCD Advance PhD Scheme Supple-mental Award. The NHMFL experimental facility at LANL is funded by the U.S. National Science Foundation through Coop-erative Grant No. DMR-1157490, the State of Florida, and the U.S. Department of Energy., and Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[PHYS]Physics [physics], Phase transition, Field (physics), Condensed matter physics, 010405 organic chemistry, Chemistry, Magnetoelectric effect, 010402 general chemistry, 01 natural sciences, 0104 chemical sciences, Magnetic field, Inorganic Chemistry, Polarization density, Spin crossover, Phase (matter), [CHIM.COOR]Chemical Sciences/Coordination chemistry, Physical and Theoretical Chemistry, Spin-½
Abstract

International audience; We investigate giant magnetoelectric coupling at a Mn spin crossover in [MnL]BPh (L = (3,5-diBr-sal)323) with a field-induced permanent switching of the structural, electric, and magnetic properties. An applied magnetic field induces a first-order phase transition from a high spin/low spin (HS-LS) ordered phase to a HS-only phase at 87.5 K that remains after the field is removed. We observe this unusual effect for DC magnetic fields as low as 8.7 T. The spin-state switching driven by the magnetic field in the bistable molecular material is accompanied by a change in electric polarization amplitude and direction due to a symmetry-breaking phase transition between polar space groups. The magnetoelectric coupling occurs due to a γη coupling between the order parameter γ related to the spin-state bistability and the symmetry-breaking order parameter η responsible for the change of symmetry between polar structural phases. We also observe conductivity occurring during the spin crossover and evaluate the possibility that it results from conducting phase boundaries. We perform ab initio calculations to understand the origin of the electric polarization change as well as the conductivity during the spin crossover. Thus, we demonstrate a giant magnetoelectric effect with a field-induced electric polarization change that is 1/10 of the record for any material.

Published
2021
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44. Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

Author

John G. Breslin, Muhammad Intizar Ali, Saeed H. Alsamhi, Kenneth N. Brown, Radhya Sahal, Athlone Institute of Technology, and Science Foundation Ireland (SFI) under Grant Number SFI/16/RC/3918 (Confirm), and Marie SkłodowskaCurie grant agreement No. 847577 co-funded by the European Regional Development Fund.

Subjects
0209 industrial biotechnology, Industry 4.0, Computer science, auto-detection, Operational data, 02 engineering and technology, computer.software_genre, lcsh:Technology, Digital twins, digital twins, lcsh:Chemistry, 020901 industrial engineering & automation, Synchronization (computer science), 0202 electrical engineering, electronic engineering, information engineering, General Materials Science, cyber-physical, lcsh:QH301-705.5, Instrumentation, Fluid Flow and Transfer Processes, Wind power, lcsh:T, business.industry, Process Chemistry and Technology, operational data, General Engineering, Cyber-physical system, production system, Auto-detection, lcsh:QC1-999, Computer Science Applications, Product (business), Production systems, Information extraction, lcsh:Biology (General), lcsh:QD1-999, Conceptual framework, lcsh:TA1-2040, Systems engineering, 020201 artificial intelligence & image processing, Cyber-physical, lcsh:Engineering (General). Civil engineering (General), business, computer, lcsh:Physics, Change detection, Software Research Institute AIT
Abstract

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

Published
2021
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45. PI Regulation of a Reaction-Diffusion Equation with Delayed Boundary Control

Author

Christophe Prieur, Hugo Lhachemi, Emmanuel Trélat, University College Dublin [Dublin] (UCD), GIPSA - Infinite Dimensional Dynamics (GIPSA-INFINITY), GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), Laboratoire Jacques-Louis Lions (LJLL (UMR_7598)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Control And GEometry (CaGE ), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jacques-Louis Lions (LJLL (UMR_7598)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under grant number 16/RC/3872 and is co-funded under the European Regional Development Fund and byI-Form industry partners., Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Lyapunov function, 0209 industrial biotechnology, 1-D reaction-diffusion equation, Partial Differential Equations (PDEs), 1-D Reaction-diffusion equation, PID controller, Boundary (topology), 02 engineering and technology, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Setpoint, Tracking error, symbols.namesake, 020901 industrial engineering & automation, Control theory, Neumann trace, Reaction–diffusion system, FOS: Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY], Electrical and Electronic Engineering, Mathematics - Optimization and Control, Delay boundary control, Mathematics, Computer Science Applications, PI regulation control, Control and Systems Engineering, Optimization and Control (math.OC), Time derivative, symbols, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Numerical stability
Abstract

The general context of this work is the feedback control of an infinite-dimensional system so that the closed-loop system satisfies a fading-memory property and achieves the setpoint tracking of a given reference signal. More specifically, this paper is concerned with the Proportional Integral (PI) regulation control of the left Neumann trace of a one-dimensional reaction-diffusion equation with a delayed right Dirichlet boundary control. In this setting, the studied reaction-diffusion equation might be either open-loop stable or unstable. The proposed control strategy goes as follows. First, a finite-dimensional truncated model that captures the unstable dynamics of the original infinite-dimensional system is obtained via spectral decomposition. The truncated model is then augmented by an integral component on the tracking error of the left Neumann trace. After resorting to the Artstein transformation to handle the control input delay, the PI controller is designed by pole shifting. Stability of the resulting closed-loop infinite-dimensional system, consisting of the original reaction-diffusion equation with the PI controller, is then established thanks to an adequate Lyapunov function. In the case of a time-varying reference input and a time-varying distributed disturbance, our stability result takes the form of an exponential Input-to-State Stability (ISS) estimate with fading memory. Finally, another exponential ISS estimate with fading memory is established for the tracking performance of the reference signal by the system output. In particular, these results assess the setpoint regulation of the left Neumann trace in the presence of distributed perturbations that converge to a steady-state value and with a time-derivative that converges to zero. Numerical simulations are carried out to illustrate the efficiency of our control strategy., Comment: Preprint

Published
2021
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46. Blockchain for decentralized multi-drone to combat COVID-19

Author

Alsamhi, S. H., Lee, B., Guizani, M., Kumar, N., Qiao, Y., Liu, Xuan, Athlone Institute of Technology, This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 847577, and and a research grant from Science Foundation Ireland (SFI) under Grant Number 16/RC/3918 (Ireland’s European Structural and Investment Funds Programmes and the European Regional Development Fund 2014-2020)

Subjects
FOS: Computer and information sciences, Swarm drones, Monitoring COVID-19, Pandemic, COVID-19, Systems and Control (eess.SY), Smart healthcare, Electrical Engineering and Systems Science - Systems and Control, Blockchain, E2E delivery system, Computer Science - Distributed, Parallel, and Cluster Computing, Quarantine, Decentralized, FOS: Electrical engineering, electronic engineering, information engineering, Distributed, Parallel, and Cluster Computing (cs.DC), Software Research Institute AIT
Abstract

Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak. Drone missions will increasingly rely on drone collaboration, which requires the drones to reduce communication complexity and be controlled in a decentralized fashion. Blockchain technology becomes a must in industrial applications because it provides decentralized data, accessibility, immutability, and irreversibility. Therefore, Blockchain makes data public for all drones and enables drones to log information concerning world states, time, location, resources, delivery data, and drone relation to all neighbors drones. This paper introduces decentralized independent multi-drones to accomplish the task collaboratively. Improving blockchain with a consensus algorithm can improve network partitioning and scalability in order to combat COVID-19. The multi-drones task is to combat COVID-19 via monitoring and detecting, social distancing, sanitization, data analysis, delivering goods and medical supplies, and announcement while avoiding collisions with one another. We discuss End to End (E2E) delivery application of combination blockchain and multi-drone in combating COVID-19 and beyond future pandemics. Furthermore, the challenges and opportunities of our proposed framework are highlighted. yes

Published
2021

47. Green IoT for eco-friendly and sustainable smart cities: future directions and opportunities

Author

Jeff Morgan, Saeed H. Alsamhi, Faris A. Almalki, John G. Breslin, Jahan Hassan, Abdu Saif, Radhya Sahal, Ammar Hawbani, N. S. Rajput, Athlone Institute of Technology, and Science Foundation Ireland (SFI) under Grant Number SFI/16/RC/3918 (Confirm), and Marie Skłodowska-Curie grant agreement No. 847577 co-funded by the European Regional Development Fund.

Subjects
Smart city, Eco-friendly, Computer Networks and Communications, Computer science, Cost accounting, Green IoT, Faculty of Engineering & Informatics AIT, Energy consumption, Environmental economics, Environmentally friendly, Pollution, Resource (project management), Energy efficiency, Work (electrical), Sustainability, Hardware and Architecture, Software, Information Systems, Efficient energy use
Abstract

The development of the Internet of Things (IoT) technology and their integration in smart cities have changed the way we work and live, and enriched our society. However, IoT technologies present several challenges such as increases in energy consumption, and produces toxic pollution as well as E-waste in smart cities. Smart city applications must be environmentally-friendly, hence require a move towards green IoT. Green IoT leads to an eco-friendly environment, which is more sustainable for smart cities. Therefore, it is essential to address the techniques and strategies for reducing pollution hazards, traffic waste, resource usage, energy consumption, providing public safety, life quality, and sustaining the environment and cost management. This survey focuses on providing a comprehensive review of the techniques and strategies for making cities smarter, sustainable, and eco-friendly. Furthermore, the survey focuses on IoT and its capabilities to merge into aspects of potential to address the needs of smart cities. Finally, we discuss challenges and opportunities for future research in smart city applications.

Published
2021

48. The Galactic Anticentre

Author

Vincenzo Ripepi, A. de Torres, Annie C. Robin, Mariateresa Crosta, C. Diener, L. Noval, Daniel Michalik, P. J. Richards, L. Karbevska, K. Kruszyńska, E. Fraile, André Moitinho, Michał Pawlak, P. Panuzzo, M. Riello, Benoit Carry, A. Yoldas, Harry Enke, N. Tonello, P. Gavras, M. Vaillant, Rosanna Sordo, E. del Pozo, Lorenzo Rimoldini, M. Bernet, G. Orrù, W. van Reeven, J. M. Martín-Fleitas, S. Diakite, P. Burgess, P. Osborne, Derek W. Morris, M. I. Carnerero, Amina Helmi, Mike Smith, Iain A. Steele, Alessandro Sozzetti, M. Kontizas, A. Sagristà Sellés, Roberto Molinaro, B. Holl, D. Baines, D. Molina, J. Fernández-Hernández, S. Marinoni, Michele Bellazzini, Maria Süveges, Teresa Antoja, D. Barbato, Uwe Lammers, Isabella Pagano, Davide Massari, G. Plum, P. Ramos, G. Jevardat de Fombelle, M. Biermann, C. Crowley, Mathias Schultheis, D. W. Evans, P. A. Palicio, Paolo Montegriffo, Ramachrisna Teixeira, R. Blomme, Elmé Breedt, T. A. Lister, F. A. Jansen, Ruth Carballo, Marcella Marconi, A. Abreu Aramburu, J. M. Carrasco, F. Royer, S. Accart, A. Burlacu, S. Regibo, Andrej Prsa, M. Sarasso, Nicolas Rambaux, A. F. Mulone, Ana Ulla, Eric Gosset, Alessandra Mastrobuono-Battisti, George M. Seabroke, H. E. Delgado, Federico Marocco, C. Nicolas, T. Lebzelter, Nami Mowlavi, C. Barache, Nicoletta Sanna, G. Gracia-Abril, R. Santoveña, R. Haigron, N. Unger, Silvio Leccia, A. Jean-Antoine Piccolo, A. F. Lanza, Alberto Vecchiato, Thomas Wevers, F. Figueras, G. Busso, C. Fabre, P. Di Matteo, F. Riclet, F. Solitro, Eric Slezak, N. Samaras, João Alves, Emese Plachy, Timo Prusti, F. van Leeuwen, J. Osinde, O. Marchal, M. Ajaj, C. Ducourant, Tatiana Muraveva, Shay Zucker, H. Steidelmüller, Alberto Riva, D. Semeux, N. Cheek, Laurent Galluccio, Martin A. Barstow, Alex Bombrun, S. Liao, M. van Leeuwen, R. E. de Souza, P. de Laverny, T. Roegiers, Paul J. McMillan, G. Holland, Alexey Mints, G. Giuffrida, L. M. Sarro, Juan Zorec, G. Sadowski, P. Yvard, Carme Jordi, J. L. Halbwachs, Laurent Chemin, Ludovic Delchambre, M. Garcia-Reinaldos, Ugo Becciani, Diego Bossini, Ángel Gómez, Sergi Blanco-Cuaresma, Rossella Cancelliere, C. Fabricius, J. De Ridder, L. Eyer, L. Pulone, Simon Hodgkin, Ennio Poretti, F. De Angeli, M. Haywood, E. Anglada Varela, Antonella Vallenari, F. X. Pineau, D. Garabato, A. Guerrier, H. E. P. Lindstrøm, Thomas Hilger, I. Bellas-Velidis, Frédéric Arenou, Paolo Giacobbe, Ilaria Musella, Tristan Cantat-Gaudin, L. Palaversa, Pedro García-Lario, David Hobbs, C. Turon, E. Balbinot, P. de Teodoro, Sébastien Lambert, D. Katz, Angela Bragaglia, Anthony G. A. Brown, Paolo Tanga, P. Castro Sampol, J. C. Segovia, Alejandra Recio-Blanco, Yves Fremat, Jon Marchant, Jose M Hernandez, S. Ragaini, Sofia Randich, P. Re Fiorentin, J. F. Le Campion, Gisella Clementini, M. Segol, P. David, R. Drimmel, F. Crifo, J. Guiraud, M. David, R. L. Smart, M. Fabrizio, I. Gonzalez-Santamaria, D. Eappachen, M. G. Lattanzi, Miguel García-Torres, Andreas Korn, S. Voutsinas, László Molnár, Simchon Faigler, A. Mora, Nicholas Rowell, Antti Penttilä, R. Geyer, Sanjeev Khanna, Aldo Dell'Oro, H. E. Huckle, C. Dolding, N. Leclerc, Monica Rainer, R. Mor, J. Bakker, Maroussia Roelens, Douglas J. Marshall, A. G. Butkevich, Nigel Hambly, A. Masip, Laia Casamiquela, R. Messineo, Martin Altmann, A. M. Piersimoni, Alessandro Spagna, Gerry Gilmore, Stefano Bertone, Patrick Charlot, O. Vanel, Daniel Hestroffer, Marco Castellani, Sebastian L. Hidalgo, W. Roux, Łukasz Wyrzykowski, Krzysztof A. Rybicki, M. M. S. Marcos Santos, Raphael Guerra, Alberto Cellino, E. Poggio, Gérard Jasniewicz, J. J. González-Vidal, S. Cowell, Peter G. Jonker, C. M. Raiteri, S. Bartolomé, J. Álvarez Cid-Fuentes, Elisabetta Caffau, J. J. Aguado, N. R. Millar, Ulrike Heiter, Federica Spoto, Felix Franke, A. Baudesson-Stella, M. Barros, Tsevi Mazeh, A. Panahi, E. Brugaletta, R. Buzzi, Elena Pancino, G. Altavilla, E. Racero, Enrique Solano, Mikael Granvik, Minia Manteiga, C. Robin, Tomaz Zwitter, Deborah Busonero, Alberto Krone-Martins, Marc Audard, Kevin Benson, Christos Siopis, L. Balaguer-Núñez, C. A. L. Bailer-Jones, E. Poujoulet, O. L. Creevey, E. Szegedi-Elek, C. Fouron, Michael Davidson, E. Licata, Despina Hatzidimitriou, Mark Cropper, Z. Kostrzewa-Rutkowska, S. Managau, A. Dapergolas, Sergio Messina, Laszlo Szabados, H. I. Siddiqui, W. Löffler, Mario Gai, J.-B. Delisle, Leanne P. Guy, S. G. Baker, W. J. Cooper, Alfred Castro-Ginard, Conny Aerts, A. Lorca, Xavier Luri, Damien Ségransan, Grigori Fedorets, A. Garofalo, J. Juaristi Campillo, F. De Luise, F. Pailler, F. Taris, L. Bramante, Thierry Morel, T. Cornez, L. Martin Polo, M. Ramos-Lerate, Jordi Portell, E. Salguero, Sergei A. Klioner, K. Janßen, Ulrich Bastian, Stefan Jordan, P. Esquej, A. C. Lanzafame, Beatrice Bucciarelli, C. Panem, Y. Lebreton, Carlos Dafonte, S. Girona, D. Munoz, Dimitri Pourbaix, William Thuillot, J. H. J. de Bruijne, N. Brouillet, L. Chaoul, F. Torra, Alex Lobel, J.-L. Bassilana, Francesca Fragkoudi, M. Romero-Gómez, C. A. Stephenson, T. Pauwels, Eva Sciacca, Alessandro Bressan, Morgan Fouesneau, E. Livanou, E. Gerlach, X. Peñalosa Esteller, Roberto Morbidelli, L. Rohrbasser, Johannes Sahlmann, Elisa Distefano, P. Sartoretti, Karri Muinonen, Zoltan Balog, Y. Viala, J. Torra, H. Zhao, L. Siltala, G. Tauran, D. Souami, P. Madrero Pardo, David Teyssier, Jesus Salgado, J. Souchay, C. P. Murphy, Maria-Rosa L. Cioni, N. A. Walton, S. Bouquillon, Andrea Chiavassa, Agnes Fienga, Giovanni Comoretto, F. Julbe, A. Hutton, Yassine Damerdji, Richard I. Anderson, Pierre Fernique, Céline Reylé, M. Hauser, E. Utrilla, Pierre Kervella, C. Zurbach, Robert G. Mann, Ummi Abbas, Hector Canovas, D. L. Harrison, Y. Lasne, Mark Taylor, Y. Le Fustec, E. F. del Peloso, N. Bauchet, E. van Dillen, Jan Rybizki, N. Hładczuk, T. Boch, J. González-Núñez, Carine Babusiaux, C. Pagani, Krzysztof Nienartowicz, Eduard Masana, G. Kordopatis, N. Robichon, Luciana Bianchi, R. Gutiérrez-Sánchez, Arnaud Siebert, A. Kochoska, T. Carlucci, Jérôme Berthier, J. Castañeda, D. Vicente, R. De March, A. Garcia-Gutierrez, M. Weiler, F. Thévenin, Lennart Lindegren, Isabelle Lecoeur-Taïbi, Guy Rixon, Francois Mignard, P. M. Marrese, M. A. Álvarez, Caroline Soubiran, Rene Andrae, C. Ordénovic, A. Delgado, V. Sanchez Gimenez, Ministerio de Economía y Competitividad (España), Ministerio de Ciencia, Innovación y Universidades (España), Universidad de Barcelona, Xunta de Galicia, European Commission, Centros de Excelencia Severo Ochoa, BARCELONA SUPERCOMPUTING CENTER (BSC), SEV2015-0493, Krone Martins, A. [0000-0002-2308-6623], McMillan, P. [0000-0002-8861-2620], Carrasco Martínez, J. P. [0000-0002-3029-5853], Sozzetti, A. [0000-0002-7504-365X], Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MINECO/ICTI2013-2016/MDM-2014-0369, Centrode Excelencia Científica Instituto de Ciencias del Cosmos Universidad de Barcelona, MINECO/ICTI2013-2016/SEV2015-0493, Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), National Natural Science Foundation of China (NSFC), Estonian Ministry of Education and Research, Centre National D'Etudes Spatiales (CNES), Agence Nationale de la Recherche (ANR), Centre National de la Recherche Scientifique (CNRS), European Commission (EC), European Research Council (ERC), Institut des Sciences de l'Univers (INSU), Institut National Polytechnique (INP), Institut National de Physique nucleaire et de Physique des Particules (IN2P3), Deutsches Zentrum für Luft- und Raumfahrt (DLR), Hungarian Academy of Sciences, Hungarian National Research, Development, and Innovation Office (NKFIH), Science Foundation Ireland (SFI), Israel Science Foundation (ISF), Agenzia Spaziale Italiana (ASI), Italian Istituto Nazionale di Astrofisica (INAF), Netherlands Organisation for Scientific Research (NWO), Polish National Science Centre, Ministry of Science and Higher Education (MNiSW), Fundacao para a Ciencia e a Tecnologia (FCT), Slovenian Research Agency, Agencia Estatal de Investigación (AEI), Generalitat de Catalunya, United Kingdom Science and Technology Facilities Council (STFC), United Kingdom Space Agency (UKSA), Gaia Collaboration, Universidad de Cantabria, Astronomy, Kapteyn Astronomical Institute, Institut de Ciencies del Cosmos (ICCUB), Universitat de Barcelona (UB), Joseph Louis LAGRANGE (LAGRANGE), Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Kapteyn Astronomical Institute [Groningen], University of Groningen [Groningen], INAF - Osservatorio Astronomico di Padova (OAPD), Istituto Nazionale di Astrofisica (INAF), Institut de recherches sur la catalyse et l'environnement de Lyon (IRCELYON), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), M2A 2021, Laboratoire d'Astrophysique de Bordeaux [Pessac] (LAB), Université de Bordeaux (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'études spatiales et d'instrumentation en astrophysique (LESIA (UMR_8109)), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut de Physique de Rennes (IPR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Planetary-system research, Department of Physics, Particle Physics and Astrophysics, Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'études spatiales et d'instrumentation en astrophysique = Laboratory of Space Studies and Instrumentation in Astrophysics (LESIA), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Université Nice Sophia Antipolis (... - 2019) (UNS), and Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
trigonometric parallaxes, SOLAR NEIGHBORHOOD, Astronomy, SAGITTARIUS DWARF GALAXY, Astrophysics, 01 natural sciences, sagittarius dwarf galaxy, 010303 astronomy & astrophysics, Physics, [SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph], solar neighborhood, Astrophysics::Instrumentation and Methods for Astrophysics, Astrometry, Gelexy: kinematics and dynamics, Kinematics and Dynamics, Open clusters and asssociations: individual: Berkeley 29, sky survey, Disk, Physical Sciences, kinematics and dynamics [Gelexy], old open clusters, MILKY-WAY, Astrophysics::Earth and Planetary Astrophysics, open clusters and associations: individual: Berkeley 29, Galaxy: kinematics and dynamics, disk [Galaxy], individual: Berkeley 29 [open clusters and associations], Astrometria, Berkeley 29, EXPLORING HALO SUBSTRUCTURE, LOCAL KINEMATICS, Milky Way, FOS: Physical sciences, Open Clusters and Associations, Individual, exploring halo substructure, Astrophysics::Cosmology and Extragalactic Astrophysics, Astronomy & Astrophysics, Computer Science::Digital Libraries, stellar structure, Galaxy: disk, Open clusters and associations: individual: Saurer 1, Galactic halo, Halo, Settore FIS/05 - Astronomia e Astrofisica, individual: Berkeley 29 [Open clusters and asssociations], 0103 physical sciences, distances [stars], halo [Galaxy], Disc, Stars: distances, milky-way, Saurer 1, Astrophysics::Galaxy Astrophysics, canis-major, Science & Technology, 010308 nuclear & particles physics, TRIGONOMETRIC PARALLAXES, Galaxy: halo, stars: distances, open clusters and associations: individual: Saurer 1, Astrophysics - Astrophysics of Galaxies, Astronomy and Astrophysics, Galactic plane, kinematics and dynamics [Galaxy], 115 Astronomy, Space science, CANIS-MAJOR, Stars, Galaxy, Physics::History of Physics, Estels, individual: Saurer 1 [open clusters and associations], Distances, local kinematics, OLD OPEN CLUSTERS, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), SKY SURVEY, Open cluster, STELLAR STRUCTURE
Abstract

Aims. We aim to demonstrate the scientific potential of the Gaia Early Data Release 3 (EDR3) for the study of different aspects of the Milky Way structure and evolution and we provide, at the same time, a description of several practical aspects of the data and examples of their usage., Methods. We used astrometric positions, proper motions, parallaxes, and photometry from EDR3 to select different populations and components and to calculate the distances and velocities in the direction of the anticentre. In this direction, the Gaia astrometric data alone enable the calculation of the vertical and azimuthal velocities; also, the extinction is relatively low compared to other directions in the Galactic plane. We then explore the disturbances of the current disc, the spatial and kinematical distributions of early accreted versus in situ stars, the structures in the outer parts of the disc, and the orbits of open clusters Berkeley 29 and Saurer 1., Results. With the improved astrometry and photometry of EDR3, we find that: (i) the dynamics of the Galactic disc are very complex with oscillations in the median rotation and vertical velocities as a function of radius, vertical asymmetries, and new correlations, including a bimodality with disc stars with large angular momentum moving vertically upwards from below the plane, and disc stars with slightly lower angular momentum moving preferentially downwards; (ii) we resolve the kinematic substructure (diagonal ridges) in the outer parts of the disc for the first time; (iii) the red sequence that has been associated with the proto-Galactic disc that was present at the time of the merger with Gaia-Enceladus-Sausage is currently radially concentrated up to around 14 kpc, while the blue sequence that has been associated with debris of the satellite extends beyond that; (iv) there are density structures in the outer disc, both above and below the plane, most probably related to Monoceros, the Anticentre Stream, and TriAnd, for which the Gaia data allow an exhaustive selection of candidate member stars and dynamical study; and (v) the open clusters Berkeley 29 and Saurer 1, despite being located at large distances from the Galactic centre, are on nearly circular disc-like orbits., Conclusions. Even with our simple preliminary exploration of the Gaia EDR3, we demonstrate how, once again, these data from the European Space Agency are crucial for our understanding of the different pieces of our Galaxy and their connection to its global structure and history.

Published
2021
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49. Big Data Testing Techniques: Taxonomy, Challenges and Future Trends

Author

Arshad, Iram, Alsamhi, Saeed Hamood, Afzal, Wasif, Technological University of the Shannon: Midlands Midwest, This research was supported by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/16/RC/3918 (Confirm) and Marie Sklodowska Curie Grant agreement No. 847577 co-funded by the European Regional Development Fund. Wasif Afzal has received funding from the European Union’s Horizon 2020 research and innovation program under Grant agreement Nos. 871319, 957212, and and from the ECSEL Joint Undertaking (JU) under Grant agreement No 101007350

Subjects
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Testing techniques, Computer Science Applications, Biomaterials, Software Engineering (cs.SE), Computer Science - Software Engineering, Big data, Artificial Intelligence (cs.AI), Mechanics of Materials, Modeling and Simulation, Testing process, Electrical and Electronic Engineering, MM [Bioscience Research Institute TUS]
Abstract

Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques evidence occurring in the period 2010-2021. This paper discusses testing data processing by highlighting the techniques used in every processing phase. Furthermore, we discuss the challenges and future directions. Our findings show that diverse functional, non-functional and combined (functional and non-functional) testing techniques have been used to solve specific problems related to Big Data. At the same time, most of the testing challenges have been faced during the MapReduce validation phase. In addition, the combinatorial testing technique is one of the most applied techniques in combination with other techniques (i.e., random testing, mutation testing, input space partitioning and equivalence testing) to find various functional faults through Big Data testing., Comment: 32 pages

Published
2021
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50. An LPC Pole Processing Method for Enhancing the Identification of Dominant Spectral Features

Author

Mark Davis, Jin Xu, Ruairi de Frein, Mark Davis and Ruairí de Fréin, and Science Foundation Ireland (SFI)

Subjects
Signal processing, business.industry, Computer science, Linear prediction coding, Pattern recognition, TK1-9971, Processing methods, Identification (information), Engineering, Computer Science::Sound, Signal Processing, Electrical engineering. Electronics. Nuclear engineering, Artificial intelligence, Linear Prediction Coding, Electrical and Electronic Engineering, business
Abstract

This paper proposes a new time-resolved spectral analysis method based on a modification to the Linear Predictive Coding (LPC) method for enhancing the identification of the dominant frequencies of a signal. The method described here is based on a z-plane analysis of the LPC poles. These poles are used to produce a series of reduced order filter transfer functions which can accurately identify and estimate the frequency of the dominant spectral features. The standard LPC method has been shown to suffer from a sensitivity to noise and its performance is dependent on the filter order. The proposed method can accurately identify the dominant frequency components over a range of filter orders and is shown to be robust in the presence of noise. Compared with traditional time-resolved methods, it is a parameterized method where the identification of the dominant frequency changes can be directly obtained in the form of frequency measurements. In a series of 10,000 Monte Carlo experiments on a single component and multiple component signals, this LPC Pole Processing (LPC-PP) method outperforms the standard LPC method by accurately identifying the dominant frequency components in the signals.

Published
2021

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