ABSTRACT
In recent years, COVID-19 has impacted all aspects of human life. As a result, numerous publications relating to this disease have been issued. Due to the massive volume of publications, some retrieval systems have been developed to provide researchers with useful information. In these systems, lexical searching methods are widely used, which raises many issues related to acronyms, synonyms, and rare keywrds. In this paper, we present a hybrid relation retrieval system, CovRelex-SE, based on embeddings to provide high-quality search results. Our system can be accessed through the following URL: https://www.jaist.ac.jp/is/labs/nguyen-lab/systems/covrelex-se/. © 2023 Association for Computational Linguistics.
ABSTRACT
A method to find a probability that a given bias of mutations occur naturally is proposed to test whether a newly detected virus is a product of natural evolution or a product of non-natural process such as genetic manipulation. The probability is calculated based on the neutral theory of molecular evolution and binominal distribution of non-synonymous (N) and synonymous (S) mutations. Though most of the conventional analyses, including dN/dS analysis, assume that any kinds of point mutations from a nucleotide to another nucleotide occurs with the same probability, the proposed model takes into account the bias in mutations, where the equilibrium of mutations is considered to estimate the probability of each mutation. The proposed method is applied to evaluate whether the Omicron variant strain of SARS-CoV-2, whose spike protein includes 29 N mutations and only one S mutation, can emerge through natural evolution. The result of binomial test based on the proposed model shows that the bias of N/S mutations in the Omicron spike can occur with a probability of 2.0 × 10−3 or less. Even with the conventional model where the probabilities of any kinds of mutations are all equal, the strong N/S mutation bias in the Omicron spike can occur with a probability of 3.7 × 10−3, which means that the Omicron variant is highly likely a product of non-natural process including artifact. © 2022 Information Processing Society of Japan.
ABSTRACT
This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers. This work aims at building a system supporting users efficiently in acquiring knowledge across a huge number of COVID-19 scientific papers published rapidly. Our system can be accessed via https://www.jaist.ac.jp/is/labs/ nguyen-lab/systems/covrelex/.
ABSTRACT
Fukushima Daiichi Nuclear Power Station Accident in March 2011 caused a massive release of radionuclides, such as I-131, Cs-134 and Cs-137, to the atmosphere. To date, there are no documented health effects among Fukushima residents, which are directly attributable to radiation exposure from the accident. In addition, it is not likely that the incidence of solid cancer and leukemia increases to a discernible extent. Indeed a substantial increase of thyroid cancer is observed, but this is likely due to ultrasensitive screening procedures rather than radiation exposure. Nevertheless, there was increased public concern about the effects of radiation in human health since the accident. I have provided information and knowledge on radiation and its health effects to general public on request. I have been also engaged in scientific education in elementary schools or junior high schools. In 2020 and 2021 under COVID-19 situation, the classes in elementary schools or junior high schools were provided mainly online, where both demerits and merits of online classes were found. I would also briefly introduce recent research to analyze the effects of low dose/low dose-rate radiation on mutation frequency and spectrum in genome-wide.
ABSTRACT
Background: We previously reported the prevalence of frailty and relation of disease activity at patients with rheumatoid arthritis (RA)1. The behavioral restriction of COVID-19 pandemic influenced for the lifestyle of people included patients with RA. Objectives: The relationship between the behavioral restriction of COVID-19 pandemic and frailty was investigated. Methods: We used the date from prospective observational study (CHIKARA study: UMIN000023744). 70 from 100 patients with RA were followed-up and evaluated the frailty and subcategories (social, physical, mental, nutrition, and cognitive) by frailty checklist. The prevalence of frailty and the change of exercise and daily life activities by visual analog scale were investigated at pre-and post-behavioral restriction. The correlation of frailty and change of amount of exercise and daily life activity examined by univariate analysis. Results: Mean age was 69.7 years (women n=57, men n=13). The prevalence of frailty at post-behavioral restriction increased compared that at pre-behavio-ral restriction (post:35.8% vs pre:30.0%). Especially, cognitive and total score at post-behavioral restriction increased signifcantly. The rate of decrease of exercise by <25%, 26~50%, and 51%< were 70%, 21%, and 9%, respectively (mean:20% decrease). Whereas, the rate of decrease of daily life activities by <25%, 26~50%, and 51%< were 37%, 27%, and 36%, respectively (mean:44% decrease). The change of exercise was signifcantly negatively correlated with the change of nutrition (R=-0.245, P=0.041) at Table 1. There was no correlation between the change of daily life activities and subcategories. Conclusion: The exercise slightly decreased and the daily life activities decreased almost 50% by the behavioral restriction of COVID-19 pandemic. The prevalence of frailty increased 5.8%, and cognitive and total score were signif-cantly high at post-behavioral restriction of COVID-19 pandemic. The decrease of exercise correlated with the worse of nutrition.
ABSTRACT
Background: We previously reported the prevalence of sarcopenia and body compositions at patients with rheumatoid arthritis (RA)1. The behavioral restriction of COVID-19 pandemic influenced for the lifestyle of people included patients with RA. Objectives: The change of exercise and daily life activity of patients with RA were investigated and body composition and muscle function were compared pre-and post-behavioral restriction. Methods: We used the date from prospective observational study (CHIKARA study: UMIN000023744). 70 from 100 patients with RA were followed-up and evaluated the change of exercise and daily life activity by visual analog scale. They were measured the muscle mass, fat mass, basal metabolic rate by body composition analyzer and grip strength as muscle function. The relationship between the change of exercise and daily life activity and body composition was investigated by univariate analysis. Results: Mean age was 69.7 years (women n=57, men n=13). The rate of decrease of exercise by <25%, 26~50%, and 51%< were 70%, 21%, and 9%, respectively (mean:20% decrease). Whereas, the rate of decrease of daily life activities by <25%, 26~50%, and 51%< were 37%, 27%, and 36%, respectively (mean:44% decrease). Muscle mass at post-behavioral restriction decrease signifcantly compared that at pre-behavioral restriction activities (34.0kg vs 34.7kg, P<0.001). Fat mass at post-behavioral restriction increase signifcantly compared that at pre-behavioral restriction (16.2kg vs 15.5kg, P=0.014). Grip strength at post-behavioral restriction decrease signifcantly compared that at pre-behavioral restriction (16.2kg vs 17.2kg, P=0.026). The change of exercise was signifcantly positively correlated with the change of muscle mass and basal metabolic rate (R=0.273, P=0.021 and R=0.256, P=0.033, relatively) at Table 1. Whereas, the change of daily living activities was not signifcantly correlated with the change of muscle mass and muscle function. Conclusion: Muscle mass and grip strength decrease and fat mass increase in patients with RA by the behavioral restriction of COVID-19 pandemic. Muscle mass and basal metabolic rate decrease in patients without exercise habits. Maintenance of muscle mass might be important during the COVID-19 pandemic.
ABSTRACT
Discourse parsing has been studied for decades. However, it still remains challenging to utilize discourse parsing for real-world applications because the parsing accuracy degrades significantly on out-of-domain text. In this paper, we report and discuss the effectiveness and limitations of bootstrapping methods for adapting modern BERT-based discourse dependency parsers to out-of-domain text without relying on additional human supervision. Specifically, we investigate self-training, cotraining, tri-training, and asymmetric tritraining of graph-based and transition-based discourse dependency parsing models, as well as confidence measures and sample selection criteria in two adaptation scenarios: Monologue adaptation between scientific disciplines and dialogue genre adaptation. We also release COVID-19 Discourse Dependency Treebank (COVID19-DTB), a new manually annotated resource for discourse dependency parsing of biomedical paper s. The experimental results show that bootstrapping is significantly and consistently effective for unsupervised domain adaptation of discourse dependency parsing, but the low coverage of accurately predicted pseudo labels is a bottleneck for further improvement. We show that active learning can mitigate this limitation. © 2022 Association for Computational Linguistics.