In the context of the Industry 4.0 and of the digital factory, digital twin and virtual reality represent key technologies to design, simulate and optimize cyber-physical production system and ...interact with it remotely or in a collaborative way. Moreover, these technologies open up new possibilities which can be involved in the co-design and ergonomics studies of workstations, based on Industry 4.0 components like cobots. In order to satisfy these needs and to create dynamic and immersive virtual environment, it is therefore necessary to combine the capacities of the digital twin to perform simulation of the production system with the capacities of the immersive virtual environment in term of interactions. This paper proposes a co-simulation and communication architecture between digital twin and virtual reality software, then it presents a use case on a human-robot collaborative workplace design and assessment.
In recent years, the use of digital twins (DT) to improve maintenance procedures has increased in various industrial sectors (e.g., manufacturing, energy industry, aerospace) but is more limited in ...the construction industry. However, the operation and maintenance (O&M) phase of a building’s life cycle is the most expensive. Smart buildings already use BIM (Building Information Modeling) for facility management, but they lack the predictive capabilities of DT. On the other hand, the use of extended reality (XR) technologies to improve maintenance operations has been a major topic of academic research in recent years, both through data display and remote collaboration. In this context, this paper focuses on reviewing projects using a combination of these technologies to improve maintenance operations in smart buildings. This review uses a combination of at least three of the terms “Digital Twin”, “Maintenance”, “BIM” and “Extended Reality”. Results show how a BIM can be used to create a DT and how this DT use combined with XR technologies can improve maintenance operations in a smart building. This paper also highlights the challenges for the correct implementation of a BIM-based DT combined with XR devices. An example of use is also proposed using a diagram of the possible interactions between the user, the DT and the application framework during maintenance operations.
Patients on therapeutic immunosuppressants for immune-mediated inflammatory diseases were excluded from COVID-19 vaccine trials. We therefore aimed to evaluate humoral and cellular immune responses ...to COVID-19 vaccine BNT162b2 (Pfizer-BioNTech) in patients taking methotrexate and commonly used targeted biological therapies, compared with healthy controls. Given the roll-out of extended interval vaccination programmes to maximise population coverage, we present findings after the first dose.
In this cohort study, we recruited consecutive patients with a dermatologist-confirmed diagnosis of psoriasis who were receiving methotrexate or targeted biological monotherapy (tumour necrosis factor TNF inhibitors, interleukin IL-17 inhibitors, or IL-23 inhibitors) from a specialist psoriasis centre serving London and South East England. Consecutive volunteers without psoriasis and not receiving systemic immunosuppression who presented for vaccination at Guy's and St Thomas' NHS Foundation Trust (London, UK) were included as the healthy control cohort. All participants had to be eligible to receive the BNT162b2 vaccine. Immunogenicity was evaluated immediately before and on day 28 (±2 days) after vaccination. The primary outcomes were humoral immunity to the SARS-CoV-2 spike glycoprotein, defined as neutralising antibody responses to wild-type SARS-CoV-2, and spike-specific T-cell responses (including interferon-γ, IL-2, and IL-21) 28 days after vaccination.
Between Jan 14 and April 4, 2021, 84 patients with psoriasis (17 on methotrexate, 27 on TNF inhibitors, 15 on IL-17 inhibitors, and 25 on IL-23 inhibitors) and 17 healthy controls were included. The study population had a median age of 43 years (IQR 31–52), with 56 (55%) males, 45 (45%) females, and 85 (84%) participants of White ethnicity. Seroconversion rates were lower in patients receiving immunosuppressants (60 78%; 95% CI 67–87 of 77) than in controls (17 100%; 80–100 of 17), with the lowest rate in those receiving methotrexate (seven 47%; 21–73 of 15). Neutralising activity against wild-type SARS-CoV-2 was significantly lower in patients receiving methotrexate (median 50% inhibitory dilution 129 IQR 40–236) than in controls (317 213–487, p=0·0032), but was preserved in those receiving targeted biologics (269 141–418). Neutralising titres against the B.1.1.7 variant were similarly low in all participants. Cellular immune responses were induced in all groups, and were not attenuated in patients receiving methotrexate or targeted biologics compared with controls.
Functional humoral immunity to a single dose of BNT162b2 is impaired by methotrexate but not by targeted biologics, whereas cellular responses are preserved. Seroconversion alone might not adequately reflect vaccine immunogenicity in individuals with immune-mediated inflammatory diseases receiving therapeutic immunosuppression. Real-world pharmacovigilance studies will determine how these findings reflect clinical effectiveness.
UK National Institute for Health Research.
A completely automatic near-field mapping system has been developed within the Research Institute for Electronic Embedded Systems (IRSEEM) in order to determine the electromagnetic field created by ...electronic systems and components. This test bench uses a 3-D positioning system of the probe to make accurate measurements. This paper presents some applications of the near-field techniques in EMC investigations. In the first part, near-field measurements are used to locate precisely the electromagnetic sources of a limiter device. In the second part, we present an equivalent model of the radiated emission of an integrated circuit. In the last part, the near-field test bench is used to characterize faults in a cable.
EXtended Reality (XR) alongside the Digital Twin (DT) in Industrial Internet of Things (IIoT) emerges as a promising next-generation technology. Its diverse applications hod the potential to ...revolutionize multiple facets of Industry 4.0 and serve as a cornerstone for the rise of Industry 5.0. However, current systems are still not effective in providing a high-quality experience for users due to various factors, one of which is their limited resources for processing and transmitting complex data and big data. To overcome these challenges, this paper presents an in-depth analysis of performance optimization techniques for resource-constrained Augmented Reality (AR) and/or Virtual Reality (VR) environments operating with DT, with a specific focus on Quality of Service (QoS), Quality of Experience (QoE), Edge-Cloud architectures and future research directions. Furthermore, this study delves into the intricate complex trade-off relationships involving optimization factors, including system quality, information quality, and QoE. In addition, it also explores potential solutions based on powerful emerging technological tools, including data compression, blockchain, cloud computing, quantum computing, Artificial Intelligence (AI) / Machine Learning (ML), and cybersecurity in the Cyber-Physical Systems (CPS). The insights provided in this comprehensive survey can inspire and guide researchers and industrial practitioners in optimizing performance for XR with DT applications in resource-constrained Smart Manufacturing System (SMS).
The construction of a building comprises several phases and involves many stakeholders. As projects have become more and more complex, the Building Information Modeling (BIM) methodology was proposed ...to unify projects around a Digital Twin of the information necessary for collaboration. In recent years, Augmented Reality (AR) and Virtual Reality (VR) have shown their relevance in assisting in various construction activities. However, their use requires additional refinement for them to be integrated into the BIM process. This literature review is an analysis of the cutting-edge applications of AR and VR in Architecture Engineering Construction (AEC) projects and prevailing trends in their usage. This review focuses on publications related to BIM's safety applications (such as risk prevention and site operations during construction phase), as well as on data flow architectures between BIM and AR or VR applications.
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•Meta-analysis of 401 papers on Augmented/Virtual Reality(AR/VR) usage in construction.•A pluridisciplinary analysis between Building Information Modeling and AR/VR.•A detailed review of 74 papers on AR/VR according to the execution phase.•Synthesis of architectures for BIM to AR/VR tools and related trends.
Targeted biologic therapies can elicit an undesirable host immune response characterized by the development of antidrug antibodies (ADA), an important cause of treatment failure. The most widely used ...biologic across immune-mediated diseases is adalimumab, a tumor necrosis factor inhibitor. This study aimed to identify genetic variants that contribute to the development of ADA against adalimumab, thereby influencing treatment failure. In patients with psoriasis on their first course of adalimumab, in whom serum ADA had been evaluated 6-36 months after starting treatment, we observed a genome-wide association with ADA against adalimumab within the major histocompatibility complex (MHC). The association signal mapped to the presence of tryptophan at position 9 and lysine at position 71 of the HLA-DR peptide-binding groove, with both residues conferring protection against ADA. Underscoring their clinical relevance, these residues were also protective against treatment failure. Our findings highlight antigenic peptide presentation via MHC class II as a critical mechanism in the development of ADA against biologic therapies and downstream treatment response.
The recognition of human actions based on artificial intelligence methods to enable Human–Robot Collaboration (HRC) inside working environments remains a challenge, especially because of the ...necessary huge training datasets needed. Meanwhile, Digital Twins (DTs) of human centered productions are increasingly developed and used in the design and operation phases. As instance, DTs are already helping industries to design, visualize, monitor, manage, and maintain their assets more effectively. However, few works are dealing with using DTs as a dataset generator tool. Therefore, this paper explores the use of a DT of a real industrial workstation involving assembly tasks with a robotic arm interfaced with Virtual Reality (VR) to extract a digital human model. The DT simulates assembly operations performed by humans aiming to generate self-labeled data. Thereby, a Human Action Recognition dataset named InHARD-DT was created to validate a real use case in which we use the acquired auto-labeled DT data of the virtual representation of the InHARD dataset to train a Spatial–Temporal Graph Convolutional Neural Network with skeletal data on one hand. On the other hand, the Physical Twin (PT) data of the InHARD dataset was used for testing. Obtained results show the effectiveness of the proposed method.
Human motion analysis plays a crucial role in industry 4.0 and, more recently, in industry 5.0 where human-centered applications are becoming increasingly important, demonstrating its potential for ...enhancing safety, ergonomics and productivity. Considering this opportunity, an increasing number of studies are proposing works on the analysis of human motion in an industrial context, taking advantage of the rise of artificial intelligence technologies and sensor technologies. The objective of this work is to provide a review of recent studies exploring these technologies in the analysis of human movement while specifically considering industrial context. First, a taxonomy of key human motion analysis applications is proposed, presenting statistical insights to reveal trends and highlighting lacks in current research. Furthermore, this work identifies benchmark datasets acquired in various industrial case studies and associated sensors. Many recommendations for selecting optimal sensors and valuable benchmarks are proposed. Then, the paper outlines the current trend of utilizing hybrid deep learning methodologies in human movement analysis while underscoring the performance and limitations of these proposed methods, considering industrial constraints such as real-time recognition and frugality. Finally, challenges and future works are highlighted, focusing on the opportunities to address problems related to the complex industrial environment in order to achieve reliable performances.
Internet of Things (IoT) is commonly adopted in Industry 4.0/5.0, but generates an excessive amount of data that affects quality of service (QoS). To address this challenge, Fog-based architectures ...have emerged to enable faster and more efficient data processing. However, their deployment can be challenging, particularly when dealing with mobile connected devices like robots. To optimize the deployment of Fog-based solution in the presence of mobile connected devices, this article proposes an Integer Linear Programming (ILP) model to find the optimal network structure of hardware devices that will ensure complete coverage of the working area, good QoS, and cost minimization. The proposed model is tested in real and benchmark cases. Results show that the model is effective and robust in optimizing Fog-based solutions deployment while considering the dynamic aspect of mobile devices. Overall, the model offers a valuable approach for managing the increased data volume generated by IoT in industrial environments.
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