A Study on Self-Diagnosis Method to Prevent the Spread of COVID-19 Based on SVM

In this paper, a study was conducted to find a self-diagnosis method to prevent the spread of COVID-19 based on machine learning. COVID-19 is an infectious disease caused by a newly discovered coronavirus. According to WHO(World Health Organization)’s situation report published on May 18th, 2020, COVID-19 has already affected 4,600,000 cases and 310,000 deaths globally and still increasing. The most severe problem of COVID-19 virus is that it spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, which occurs in everyday life. And also, at this time, there are no specific vaccines or treatments for COVID-19.Because of the secure diffusion method and the absence of a vaccine, it is essential to self-diagnose or do a self-diagnosis questionnaire whenever possible. But self-diagnosing has too many questions, and ambiguous standards also take time. Therefore, in this study, using SVM(Support Vector Machine), Decision Tree and correlation analysis found two vital factors to predict the infection of the COVID-19 virus with an accuracy of 80%. Applying the result proposed in this paper, people can self-diagnose quickly to prevent COVID-19 and further prevent the spread of COVID-19

Prevalence of Enterobius vermicularis among Preschool Children in Gimhae-si, Gyeongsangnam-do, Korea

The present study was performed to determine the prevalence of Enterobius vermicularis among preschool children in Gimhae-si, Korea. A total of 6,921 preschool children in 76 kindergartens were examined using the cellotape perianal swab method. The overall egg positive rate (EPR) was 10.5%. The EPR in boys was higher than that in girls (adjusted odds ratio [AOR]: 1.5, P<0.001), and it was higher in rural than in urban children (AOR: 1.2, P=0.022). The present study confirmed that the prevalence of E. vermicularis infection is fairly high among preschool children in Gimhae-si. Therefore, systematic control and preventive measures should be adopted to reduce morbidity associated with this nematode infection

Room-temperature polariton lasing in quantum heterostructure nanocavities

Controlling light-matter interactions in solid-state systems has motivated intense research to produce bosonic quasi-particles known as exciton-polaritons, which requires strong coupling between excitons and cavity photons. Ultra-low threshold coherent light emitters can be achieved through lasing from exciton-polariton condensates, but this generally requires sophisticated device structures and cryogenic temperatures. Polaritonic nanolasers operating at room temperature lie on the crucial path of related research, not only for the exploration of polariton physics at the nanoscale but also for potential applications in quantum information systems, all-optical logic gates, and ultra-low threshold lasers. However, at present, progress toward room-temperature polariton nanolasers has been limited by the thermal instability of excitons and the inherently low quality factors of nanocavities. Here, we demonstrate room-temperature polaritonic nanolasers by designing wide-gap semiconductor heterostructure nanocavities to produce thermally stable excitons coupled with nanocavity photons. The resulting mixed states of exciton-polaritons with Rabi frequencies of approximately 370 meV enable persistent polariton lasing up to room temperature, facilitating the realization of miniaturized and integrated polariton systems

Genetic diversity and phylogeography of Seewis virus in the Eurasian common shrew in Finland and Hungary

Recent identification of a newfound hantavirus, designated Seewis virus (SWSV), in the Eurasian common shrew (Sorex araneus), captured in Switzerland, corroborates decades-old reports of hantaviral antigens in this shrew species from Russia. To ascertain the spatial or geographic variation of SWSV, archival liver tissues from 88 Eurasian common shrews, trapped in Finland in 1982 and in Hungary during 1997, 1999 and 2000, were analyzed for hantavirus RNAs by reverse transcription-polymerase chain reaction. SWSV RNAs were detected in 12 of 22 (54.5%) and 13 of 66 (19.7%) Eurasian common shrews from Finland and Hungary, respectively. Phylogenetic analyses of S- and L-segment sequences of SWSV strains, using maximum likelihood and Bayesian methods, revealed geographic-specific genetic variation, similar to the phylogeography of rodent-borne hantaviruses, suggesting long-standing hantavirus-host co-evolutionary adaptation

Multiple Functions of Nm23-H1 Are Regulated by Oxido-Reduction System

Nucleoside diphosphate kinase (NDPK, Nm23), a housekeeping enzyme, is known to be a multifunctional protein, acting as a metastasis suppressor, transactivation activity on c-myc, and regulating endocytosis. The cellular mechanisms regulating Nm23 functions are poorly understood. In this study, we identified the modifications and interacting proteins of Nm23-H1 in response to oxidative stress. We found that Cys109 in Nm23-H1 is oxidized to various oxidation states including intra- and inter-disulfide crosslinks, glutathionylation, and sulfonic acid formation in response to H2O2 treatment both in vivo and in vitro. The cross-linking sites and modifications of oxidized Nm23-H1 were identified by peptide sequencing using UPLC-ESI-q-TOF tandem MS. Glutathionylation and oxidation of Cys109 inhibited the NDPK enzymatic activity of Nm23-H1. We also found that thioredoxin reductase 1 (TrxR1) is an interacting protein of Nm23-H1, and it binds specifically to oxidized Nm23-H1. Oxidized Nm23 is a substrate of NADPH-TrxR1-thioredoxin shuttle system, and the disulfide crosslinking is reversibly reduced and the enzymatic activity is recovered by this system. Oxidation of Cys109 in Nm23-H1 inhibited its metastatic suppressor activity as well as the enzymatic activities. The mutant, Nm23-H1 C109A, retained both the enzymatic and metastasis suppressor activities under oxidative stress. This suggests that key enzymatic and metastasis suppressor functions of Nm23-H1 are regulated by oxido-reduction of its Cys109

Structural System Reliability: Overview of Theories and Applications to Optimization

This paper provides an overview of theories and applications of structural system reliability (SSR). The paper defines SSR problems and discusses the growing needs for SSR analysis and technical challenges. Detailed literature reviews are provided for three subtopics: SSR methods for Boolean system events, SSR methods for sequential failures, and SSR-based design/topology optimization. Discussions of each subtopic define the target problem using mathematical formulations and categorize existing SSR methods in terms of the characteristics of the problems and approaches. The paper summarizes SSR methods that are considered critical in the history and have introduced notable technological developments in recent years. In each subtopic or category, the reviewed methods are compared with each other in terms of accuracy, computational efficiency, and implementation issues to allow identifying apposite methods for SSR applications. The paper concludes with remarks on future research needs and opportunities