Damage detection and identification of parameter matrices using residual force vector

Beginning with incomplete mode shape measurement data, this study presents analytical equations to predict the actual stiffness and mass matrices. The measured modal data, including the measurement, manufacturing and modeling errors, should be updated for subsequent analysis. In this study, the incomplete mode shape data are expanded to a full set of degrees-of-freedom (DOFs) based on the generalized inverse method and the concept of residual force vector. The corrected parameter matrices are straightforwardly derived using the estimated mode shape data and the pseudo inverse method. The validity of the proposed method is evaluated based on the number of measured modes in an application, and its limitations are investigated

Damage detection and identification of parameter matrices using residual force vector

Beginning with incomplete mode shape measurement data, this study presents analytical equations to predict the actual stiffness and mass matrices. The measured modal data, including the measurement, manufacturing and modeling errors, should be updated for subsequent analysis. In this study, the incomplete mode shape data are expanded to a full set of degrees-of-freedom (DOFs) based on the generalized inverse method and the concept of residual force vector. The corrected parameter matrices are straightforwardly derived using the estimated mode shape data and the pseudo inverse method. The validity of the proposed method is evaluated based on the number of measured modes in an application, and its limitations are investigated

Impact assessment in a non-government organisation

<p>Supplemental_figure for A Simple Scoring System Using the Red Blood Cell Distribution Width, Delta Neutrophil Index, and Platelet Count to Predict Mortality in Patients With Severe Sepsis and Septic Shock by Yong Chan Kim, Je Eun Song, Eun Jin Kim, Heun Choi, Woo Yong Jeong, In Young Jung, Su Jin Jeong, Nam Su Ku, Jun Yong Choi, Young Goo Song, and June Myung Kim in Journal of Intensive Care Medicine</p

Superparamagnetic Iron Oxide Nanoparticles Coated with Galactose-Carrying Polymer for Hepatocyte Targeting

Our goal is to develop the functionalized superparamagnetic iron oxide nanoparticles (SPIONs) demonstrating the capacities to be delivered in liver specifically and to be dispersed in physiological environment stably. For this purpose, SPIONs were coated with polyvinylbenzyl-O-β-D-galactopyranosyl-D-gluconamide (PVLA) having galactose moieties to be recognized by asialoglycoprotein receptors (ASGP-R) on hepatocytes. For use as a control, we also prepared SPIONs coordinated with 2-pyrrolidone. The sizes, size distribution, structure, and coating of the nanoparticles were characterized by transmission electron microscopy (TEM), electrophoretic light scattering spectrophotometer (ELS), X-ray diffractometer (XRD), and Fourier transform infrared (FT-IR), respectively. Intracellular uptake of the PVLA-coated SPIONs was visualized by confocal laser scanning microscopy, and their hepatocyte-specific delivery was also investigated through magnetic resonance (MR) images of rat liver. MRI experimental results indicated that the PVLA-coated SPIONs possess the more specific accumulation property in liver compared with control, which suggests their potential utility as liver-targeting MRI contrast agent

Genomic molecular epidemiology of carbapenemase-producing Escherichia coli ST410 isolates by complete genome analysis

The circulation of carbapenemase-producing Escherichia coli (CPEC) in our society is a serious concern for vulnerable patients in nosocomial environments. However, the genomic epidemiology of the circulation of CPEC bacteria among companion animals remains largely unknown. In this study, epidemiological analysis was conducted using complete genome identification of CPEC ST410 isolates obtained from companion animals. To estimate the genomic distance and relatedness of the isolates, a total of 37 whole-genome datasets of E. coli ST410 strains were downloaded and comparatively analysed. As a result of the analysis, the genomic structure of the chromosomes and plasmids was identified, revealing the genomic positions of multiple resistance and virulence genes. The isolates in this study were grouped into the subclade H24/RxC, with fimH24, and substituted quinolone resistance-determining regions (QRDRs) and multiple beta-lactamases, including extended-spectrum β-lactamase (ESBL) and carbapenemase. In addition, the in silico comparison of the whole-genome datasets revealed unidentified ST410 H24/Rx subgroups, including either high pathogenicity islands (HPIs) or H21 serotypes. Considering the genetic variations and resistance gene dissemination of the isolates carried by companion animals, future approaches for preventive measurement must include the One Health perspective for public health in our society.This work was supported by the National Research Foundation (NRF- 2020R1A2C200879414), BK21 FOUR Future Veterinary Medicine Leading Education and Research Center and Research Institute for Veterinary Science, Seoul National University, Seoul, Republic of Kore