The current study investigated the use of two-dimensional spatial distribution mapping representing the chlorophyll-a level in a river generated via an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV). A domestically developed UAV (Remo-M, Uconsystem Inc., Korea) and a USV developed by our research team were used to collect data from the Nae Seong stream in Korea. An adaptation of the “Data Cleaner” tool was developed and used for USV data processing and analysis. The operation of the autonomous USV was successful. Four previously described indices for quantifying algal blooms in rivers were utilized to create chlorophyll-a images, the normalized difference vegetation index (NDVI), the normalized green red difference index, the green normalized difference vegetation index (GNDVI), and the normalized difference red edge index. The suitability of the linear regression analysis of the correlation between the spectral indices obtained using the UAV and the in situ chlorophyll-a data obtained using the USV was evaluated with the coefficient of determination (R2) at a significance level of p &lt; 0.001. In field application and correlational analysis the NDVI was strongly correlated with chlorophyll-a (R2 = 0.88, p < 0.001), and the GNDVI was moderately correlated with chlorophyll-a (R2 = 0.74, p < 0.001). The map of chlorophyll-a was successfully quantified using the UAV and USV hybrid platforms.

Whole blood viscosity, a hemorheological factor, is currently used for diagnosis, as it is correlated with various vascular diseases that are difficult to diagnose early with a general blood test. It was determined that it was necessary to set reference intervals for further studies and utilization of whole blood viscosity in cats, a representative companion animal, and this study was conducted. 50 healthy cats were recruited for the study and whole blood viscosity, complete blood count, and serum chemistry tests were performed. The reference intervals of whole blood viscosity were 15.169 to 43.684 cP at a shear rate of 1 s-1 reflecting diastole, and 3.524 to 5.544 cP at a shear rate of 300 s-1 reflecting systole. Red blood cells, hematocrit, hemoglobin, white blood cells, and neutrophils in the complete blood count, and total protein, albumin, globulin, and cholesterol in the serum chemistry were significantly correlated with whole blood viscosity. The results of this study set reference intervals of whole blood viscosity for healthy cats in a wide shear rate range that has not yet been fully established and investigated its correlation with other blood indicators.

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China in December 2019, it has spread rapidly, and many coronavirus disease (COVID-19) cases have occurred in Gwangju, South Korea. Viral mutations following the COVID-19 epidemic have increased interest in the characteristics of epidemics in this region, and pathogen genetic analysis is required for infection control and prevention. In this study, SARS-CoV-2 whole-genome analysis was performed on samples from patients with COVID-19 in Gwangju from 2020 to 2022 to identify the trends in COVID-19 prevalence and to analyze the phylogenetic tree of dominant variants. B.41 and B.1.497 prevailed in 2020, the early stage of the COVID-19 outbreak; then, B.1.619.1 mainly occurred until June 2021. B.1.617.2, classified as sublineage AY.69 and AY.122, occurred continuously from July to December 2021. Since strict measures to strengthen national quarantine management had been implemented in South Korea until this time, mutations phylogenetic analysis was also able to infer the epidemiological relationship between infection transmission routes. Since the first identification of the Omicron variant in late December 2021, the spread of infection has been very rapid, and weekly whole-genome analysis of specimens has enabled us to monitor new Omicron sublineage occurring in Gwangju. Our study suggests that conducting reginal surveillance in addition to nation-level genomic surveillance will enable more rapid and detailed variant surveillance, which will be helpful in the overall prevention and management of infectious diseases.