Examination of the affinity of anti-SARS-CoV-2 IgA, which is mucosal immunity, for SARS-CoV-2 BA.4 variant and BA.5 variant

Currently, the variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the mainstream of COVID-19 in the world, are the omicron type SARS-CoV-2 BA.4 variant and BA.5 variant derived from the omicron variant. In Japan, the Pfizer/BioNTech COVID-19 vaccine (BNT162b2) and the Moderna COVID-19 mRNA-1273 vaccine, which were created based on the viral gene of the Wuhan-type SARS-CoV-2 B.1.1.7 variant, have been inoculated. Previous clinical studies have reported that vaccination with these mRNA-based COVID-19 vaccines secretes a large amount of anti-SARSCoV- 2 IgA, which is mucosal immunity, into breast milk. However, recent clinical studies revealed that SARS-CoV-2 BA.4 and BA.5 variants have possessed the ability to successfully circumvent anti-SARS-CoV-2 immune mechanisms conferred by COVID-19 vaccination or prior SARS-CoV-2 infection. Therefore, we investigated the affinity of anti-SARS-CoV-2 IgA (PDB:CV2.1169 and PDB: CR3022) against SARS-CoV-2 B.1.1.7 variant (PDB: 7QEZ_A), SARS-CoV-2 BA.4 variant and BA.5 variant (PDB: 7XNS) by in silico analysis. As a result of the in silico analysis, the affinity of IgA CV2.1169 for each SARS-CoV-2 variant (B.1.1.7 variant, BA.4 variant, BA.5 variant) was -15.92 Kcal/mol, -9.26 Kcal/mol, -8.94 Kcal/ mol. The affinities of IgA CR3022 for each SARS-CoV-2 variant (B.1.1.7 variant, BA.4 variant, BA.5 variant) were -16.35 Kcal/ mol, -9.85 Kcal/mol, and -9.24 Kcal/mol. In addition, IgA derived from individuals vaccinated with the Pfizer/BioNTech COVID-19 vaccine (BNT162b2) or the Moderna COVID- 19 mRNA-1273 vaccine was found to have no high affinity to the omicron type SARS-CoV-2 BA.4 and BA.5 variants. In other words, the anti-SARS-CoV-2 IgA (PDB: CV2.1169 and PDB: CR3022), which has strong binding power to Wuhan type SARS-CoV-2 B.1.1.7 variant, was found not to have a strong affinity for omicron type SARS-CoV- 2 BA.4 variant and the BA.5 variant. In Japan, it has been reported that the COVID-19 vaccine for omicron type SARS-CoV-2 BA.4 variant and BA.5 variant may be approved in November 2022. We hope that the new COVID-19 vaccine will become widespread. Funding(s): This research was performed with research funding from the following: Japan Society for Promoting Science for TH (Grant No. 19K09840), and Japan Science and Technology Agency for TH (Grant No. STSC20001). Acknowledgments: We thank all medical staff for providing medical care to this patient at the National Hospital Organization Kyoto Medical Center.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Living Beyond Data with Feature Concepts

The inconsistencies between the requirement for, the collection of, and the use of data, and the inconsistencies among analysis models for dealing with different datasets have been solved via communication and thoughts using data jackets to solve problems in real life and solutions to problems using data. In these cases, essential information for the data-federative process has been externalized and used/reused. Feature concept, a model of the concept to be acquired from data that cannot be represented by a simple feature, such as a single variable but can be by a conceptual illustration, turned out to be a core essence here. Decision trees, clusters, and even deep neural networks can be regarded as examples of feature concepts. Useful feature concepts for satisfying the requirements of a data user have been elicited so far among data providers, data users, and other stakeholders in the market of data. In this chapter, the data-jacket-based design of creative communication is reviewed with some cases of application—marketing, detection of earthquake precursors, suppression of COVID-19, cases, and highlight the elicited feature concepts. © 2023, Springer Nature Switzerland AG.

Online Competition of Small Electric Vehicle as an Exercise in Design Education - pico-EV Eco Challenge

To develop sustainable societies, it is necessary to reduce the use of fossil fuels. Therefore, widespread use of electric vehicles (EVs) is the need. Many subjects such as mathematics-and physics-based-mechanics of machine taught at the universities are useful to meet this problem. However, to design EVs, the ability to unify such knowledge along with the fabrication cost, time management, and teamwork management is necessary. We think that EV competition is a useful exercise in design education that helps develop this ability. Considering the energy problem, we proposed an official competition for small EVs, named 'pico-EV Eco Challenge', as an exercise in engineering design education. In this competition, a small one-person EV using only small rechargeable batteries (7.2 V, 1000 mAh in total) is fabricated and the fabricated EVs run a 60 m circuit. The competition in the years 2021 and 2022 was held on online due to COVID19 pandemic. In this paper, the competition criteria, the flow and the analyses of EVs on 2021 competition are described. © 2022 ICROS.

Well-being Data Origination Using MROCs with Variable Quest: A Case Analysis of Gloom during COVID-19 Pandemic

Technologies using artificial intelligence (AI) have been implemented as services to solve various social problems. However, the contributions of AI to people's mentality and unknown/ unobserved events have not been extensively discussed. In this study, we focus on people's mental changes caused by the COVID-19 pandemic and discuss the origin of data sources for well-being using marketing research online communities (MROCs) and variable quest (VQ). In the experiment, we selected 15 females aged between 20 and 40 who were interested in exploring how daily life has changed since the emergence of COVID-19 using MROCs. The analysis results by VQ revealed that the variable sets of the events differed with the situations, mental states, and attitudes, while not being featured in any of the MROC topics as keywords. The result suggests that ing the features of unobserved events as variable sets, can help us acquire information potentially contributing to unexplored data discovery for human well-being from texts not containing any information related to the data. © 2022 for this paper by its authors.

Externalization of Unexplored Data with Data Origination: Case Analysis of Person-to-Object Contact Data During COVID-19 Pandemic

Various industries worldwide have been severely affected by the COVID-19 pandemic, highlighting the gaps between social systems and forcing major transformations of our lives. To understand and mitigate the phenomena related to the unprecedented danger of COVID-19, we have become acutely aware of the importance of data distribution, exchange, and sharing across fields;indeed, various data are published and used in decision-making processes. However, although many international organizations and companies have been publishing data and adopting relevant measures, data sharing regarding the question of what data are required for any purpose is insufficient;that is, data are principally provided by organizations who publish the data unilaterally;currently, data-related needs are not shared or leveraged. To address this issue, we introduce the concept of “data origination.” Data origination is the act of designing/acquiring/utilizing data that considers the subjective knowledge and diversity of perspectives of humans, and that aims to elucidate and support this process. We also discuss a case study of data needs and unexplored data externalization conducted during the COVID-19 pandemic, based on data origination. © 2023, Springer Nature Switzerland AG.

Living Beyond Data with Feature Concepts

The inconsistencies between the requirement for, the collection of, and the use of data, and the inconsistencies among analysis models for dealing with different datasets have been solved via communication and thoughts using data jackets to solve problems in real life and solutions to problems using data. In these cases, essential information for the data-federative process has been externalized and used/reused. Feature concept, a model of the concept to be acquired from data that cannot be represented by a simple feature, such as a single variable but can be by a conceptual illustration, turned out to be a core essence here. Decision trees, clusters, and even deep neural networks can be regarded as examples of feature concepts. Useful feature concepts for satisfying the requirements of a data user have been elicited so far among data providers, data users, and other stakeholders in the market of data. In this chapter, the data-jacket-based design of creative communication is reviewed with some cases of application—marketing, detection of earthquake precursors, suppression of COVID-19, cases, and highlight the elicited feature concepts. © 2023, Springer Nature Switzerland AG.

Growing Process of Communities on Data Platforms: Case Analysis of a COVID-19 Dataset

In recent years, there have been growing expectations for the creation of new businesses and the improvement of the value of existing services by exchanging data in different fields. Data stored in-house within organizations have become a new source of innovation. While there is a high need for the value creation of data, determining the data value is not an easy task, as there is a wide range of factors to be considered, such as data pricing, acquisition cost, usage value, and update frequency. In this study, we observe communication, such as the sharing of know-hows in data exchange and analysis, and discuss the growing process of a community on the data platform. For the experiment, we focused on the data community in the COVID-19 disaster and used a unique dataset from the data platform Kaggle, which is the data analysis competition service. The results suggest that user actions differ in the discussion of the dataset and analysis. Moreover, providing topics, user participation, and activating actions in the early stages after the dataset is released are essential for forming a data community. We argue that the actions on the data analysis, such as comments and votes, are also crucial for fostering a common understanding of the data value. © 2021 IEEE.

Development of Highly Reliable Crack Resistive Build-up Dielectric Material with Low Df Characteristic for Next-Gen 2.5D Packages

Due to the full-scale start-up of 5G communications as well as increase in use of online video sharing services and various teleworking services due to the impact of COVID-19, investments in data centers and high performance servers are accelerating leading to higher data transmission speed requirements in semiconductor device used in high performance computing (HPC). Technological breakthrough not only in silicon technologies but packaging technologies have become more crucial to enable these demands. One such technology, 2.5D packaging utilizing silicon interposers have emerged with increasing number of dies being placed in a single package, thereby making the size of silicon interposers larger. This has also led to advanced organic build-up laminated substrates, commonly used in these devices to connect the die/interposer to the PCBs, becoming ever complex and larger in size, requiring many features such as low insertion loss at high frequency even at elevated temperatures and high humidity conditions. Furthermore, maintaining reliability of these substrates are becoming more challenging as the size of the substrates continue to increase and greater stress is exerted on the substrates. In this paper, we present a newly developed dielectric build-up material;one of the main component of advanced organic build-up substrates, with designs to enable lower insertion loss even at elevated humidity and temperature. Furthermore, flexible segment was introduced into the resin to enable higher fracture toughness in an attempt to enable better reliability of larger substrates. The material design philosophy as well as the data showing the contribution of the flexible component to suppress substrate cracking and thus, enabling higher fracture toughness even at low temperatures, and the result of Thermal Shock Cycle Reliability Test will be presented. © 2021 IEEE

Association between Decreased Social Participation and Depressive Symptom Onset among Community-Dwelling Older Adults: A Longitudinal Study during the COVID-19 Pandemic.

OBJECTIVES: The coronavirus disease (COVID-19) pandemic has imposed restrictions on people's social behavior. However, there is limited evidence regarding the relationship between changes in social participation and depressive symptom onset among older adults during the pandemic. We examined the association between changes in social participation and the onset of depressive symptoms among community-dwelling older adults during the COVID-19 pandemic. DESIGN: This was a longitudinal study. SETTING: Communities in Minokamo City, a semi-urban area in Japan. PARTICIPANTS: We recruited community-dwelling older adults aged ≥ 65 years using random sampling. Participants completed a questionnaire survey at baseline (March 2020) and follow-up (October 2020). MEASUREMENTS: Depressive symptoms were assessed using the Two-Question Screen. Based on their social participation status in March and October 2020, participants were classified into four groups: "continued participation," "decreased participation," "increased participation," and "consistent non-participation." RESULTS: A total of 597 older adults without depressive symptoms at baseline were analyzed (mean age = 79.8 years; 50.4% females). Depressive symptoms occurred in 20.1% of the participants during the observation period. Multivariable Poisson regression analysis showed that decreased social participation was significantly associated with the onset of the depressive symptoms, compared to continued participation, after adjusting for all covariates (incidence rate ratio = 1.59, 95% confidence interval = 1.01-2.50, p = 0.045). CONCLUSION: Older adults with decreased social participation during the COVID-19 pandemic demonstrated a high risk of developing depressive symptoms. We recommend that resuming community activities and promoting the participation of older adults, with sufficient consideration for infection prevention, are needed to maintain mental health among older adults.

Data Requests and Scenarios for Data Design of Unobserved Events in Corona-related Confusion Using TEEDA

Due to the global violence of the novel coronavirus, various industries have been affected and the breakdown between systems has been apparent. To understand and overcome the phenomenon related to this unprecedented crisis caused by the coronavirus infectious disease (COVID-19), the importance of data exchange and sharing across fields has gained social attention. In this study, we use the interactive platform called treasuring every encounter of data affairs (TEEDA) to externalize data requests from data users, which is a tool to exchange not only the information on data that can be provided but also the call for data-what data users want and for what purpose. Further, we analyze the characteristics of missing data in the corona-related confusion stemming from both the data requests and the providable data obtained in the workshop. We also create three scenarios for the data design of unobserved events focusing on variables. © 2020 IEEE.

A new telestroke network system in northern area of Okayama prefecture

Background: Telestroke network can provide rapid access to specialized treatment and improves on-site management of acute stroke patients through the “hub-and-spoke” model. In the northern part of Okayama Prefecture, there has been a regional gap of stroke care due to the shortage of stroke specialists and facilities. In addition, due to the novel coronavirus disease 2019 (COVID-19), it is required to reduce the unnecessary contact with stroke patients from other hospitals. Aim: We organized a novel cost-free telestroke network with an image and video sharing for neurological diseases in the northern part of Okayama Prefecture to improve the stroke management in the area. Method: We prepared the tablet device on which Skype® application was installed for each hospital and recruited the patients who visited or hospitalized in the spoke hospitals and were suspected to have some neurological diseases from April 2019 to May 2020. The patient's clinical data were recorded and analyzed. Results: During the study period, 5 patients were recruited including the cases with the initial diagnosis of stroke or brain tumor. Among them, 2 cases were transferred to the hub hospital, 2 cases were transferred to other hospitals, and 1 case was treated on site under specialist's advice. Conclusion: The new telestroke network system may be beneficial for acute stroke management and reducing the unnecessary patient's transfer in the rural area, especially under coexistence with COVID-19.