ABSTRACT
Due to the COVID-19 pandemic, many robot competitions have been canceled in the past years. To address this problem, we proposed a cloud-based VR platform for the crowdsourcing of embodied human-robot interactions. However, this system only suggested the feasibility of the competition application, and actual competitions had not yet been held and implemented. Therefore, through demonstration experiments in the RoboCup Asia Pacific (RCAP) conducted in a hybrid format with on-site and remote participation, we evaluated the usefulness of using cloud computing on AWS from whether the latency time causes problems in human-robot interaction in a virtual reality environment. [ FROM AUTHOR] Copyright of Advanced Robotics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Due to the COVID-19 pandemic, many robot competitions have been canceled in the past years. To address this problem, we proposed a cloud-based VR platform for the crowdsourcing of embodied human-robot interactions. However, this system only suggested the feasibility of the competition application, and actual competitions had not yet been held and implemented. Therefore, through demonstration experiments in the RoboCup Asia Pacific (RCAP) conducted in a hybrid format with on-site and remote participation, we evaluated the usefulness of using cloud computing on AWS from whether the latency time causes problems in human-robot interaction in a virtual reality environment. [ FROM AUTHOR]
ABSTRACT
Background: The mortality rate due to COVID-19 in kidney transplant recipients (KTRs) is 16.8 to 32%. Vaccination against COVID-19 is expected to contribute to the prevention of infection, severe disease, and mortality; however, it has been reported that the humoral response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccine in KTRs is poor. Vaccination strategies against COVID-19 vary from country to country, and in Japan, the third dose is given 6 months after the second dose. Few studies have evaluated long-term humoral responses after the second dose of SARS-CoV-2 mRNA vaccine. In addition, the superiority of BNT162b2 vaccine and mRNA-1,273 vaccine in KTRs regarding humoral response is controversial. Methods: Ninety-four KTRs were administered a second dose of the BNT162b2 or mRNA-1,273 vaccines, and anti-spike (anti-S) and anti-nucleocapsid (anti-N) SARS-CoV-2 antibody levels were measured 5 months (149.2 ± 45.5 days) later. The cutoff value of anti-S antibodies was defined ≥50 AU/ml and 1.4 Index for anti-N antibodies. The primary outcome was the rate of seropositivity, and factors associated with an appropriate humoral response were assessed by univariate and multivariate analysis. Results: Of 94 KTRs, only 45 (47.9%) patients were positive for anti-S antibodies. The median anti-S SARS-CoV-2 IgG antibody titers was 35.3 (Interquartile range 3.8 to 159.7). Anti-N SARS-CoV-2 IgG antibodies in all patients were < 1.4 Index. Response to SARS-CoV-2 mRNA vaccines were 43.2 and 65% for BNT162b2 and mRNA-1,273, respectively (p = 0.152). In comparison with high-dose, low-dose of mycophenolic acid was a robust factor associated with an adequate humoral response. Conclusion: The long-term humoral response after a second dose of SARS-CoV-2 mRNA vaccine in Japanese KTRs was poor. In comparison with high-dose, low-dose mycophenolic acid was related to an appropriate humoral response. Five months is too long to wait for a 3rd dose after 2nd dose of SARS-CoV-2 vaccine in KTRs. In this cohort, there was no statistical difference in humoral response to the BNT162b2 and mRNA-1,273 vaccines. Additional large observational studies and meta-analyses are needed to clarify the factors related to an appropriate humoral immune response to COVID-19 vaccination.
ABSTRACT
Data-driven approaches in materials science demand the collection of large amounts of data on the target materials at synchrotron beamlines. To accurately gather suitable experimental data, it is essential to establish fully automated measurement systems to reduce the workload of the beamline staff. Moreover, the recent COVID-19 pandemic has further emphasized the necessity of automated and/or remote measurements at synchrotron beamlines. Here, the installation of a new sample changer combined with a high-temperature furnace and a fully automated alignment system on beamline BL04B2 at SPring-8 is reported. The system allows X-ray total scattering measurements of up to 21 samples at different temperatures (from room temperature to 1200°C) to be conducted without any human assistance.
Subject(s)
COVID-19 , Robotics , Humans , Pandemics , SARS-CoV-2 , Synchrotrons , Temperature , X-RaysABSTRACT
The COVID-19 pandemic has made it difficult to conduct research involving human-robot interactions (HRIs). As a result, many robot competitions have been canceled in the past year. To address this problem, we propose a cloud-based VR platform for the crowdsourcing of embodied cognition with multiple human users and a virtual robot. The feasibility of the platform is evaluated from the latency of the interactive events and the motions of avatars, based on the number of users logging in to the VR scene and the distance between the local and server environments. We also discuss the feasibility of our system when dealing with large-scale datasets in embodied HRI experiments. [ABSTRACT FROM AUTHOR] Copyright of Advanced Robotics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)