GLOCOLブックレット15 Preface

Current issues in dementia and dementia care in East Asi

Elastic Scattering Time–Gated Multi–Static Lidar Scheme for Mapping and Identifying Contaminated Atmospheric Droplets

Numerical simulations are performed to determine the angular dependence of the MIe scattering cross-section intensities of pure water droplets and pollutants such as contaminated water droplets and black carbon as a function of the wavelength of the incident laser light, complex refractive index, and size of the scatterer. Our results show distinct scattering features when varying the various scattering parameters, thereby allowing the identification of the scattering particle with specific application to the identification of atmospheric pollutants including black carbon. Regardless of the type of scatterer, the scattering intensity is nearly uniform with a slight preference for forward scattering when the size of the particle is within 20% of the incident laser’s wavelength. The scattering patterns start to exhibit distinguishable features when the size parameter equals 1.77, corresponding to an incident laser wavelength of 0.355 μm and a particle radius of 0.1 μm. The patterns then become increasingly unique as the size parameter increases. Based on these calculations, we propose a time-gated lidar scheme consisting of multiple detectors that can rotate through a telescopic angle and be placed equidistantly around the scattering particles to collect the backscattered light and a commercially available Q-switched laser system emitting at tunable laser wavelengths. By using a pulsed laser with 10-ns pulse duration, our scheme could distinguish scattering centers that are at least 3 m apart. Our scheme called MIe Scattering Time-gated multi-Static LIDAR (MISTS–LIDAR) would be capable of identifying the type of atmospheric pollutant and mapping its location with a spatial resolution of a few meters.Mui L.V., Hung T.N., Shinohara K., et al. Elastic Scattering Time–Gated Multi–Static Lidar Scheme for Mapping and Identifying Contaminated Atmospheric Droplets. Applied Sciences (Switzerland) 13, 172 (2023); https://doi.org/10.3390/app13010172

Isolation and molecular characterization of extended-spectrum β-lactamase producing Escherichia coli from industrial food animals in Mekong Delta, Vietnam

The aim of this study was to investigate if extended-spectrum β-lactamase producing Escherichia coli (ESBL-EC) is present in intestinal tracts of apparently healthy broiler chickens at large-scale chicken farm and pigs, and their environments in Vietnam. ESBL-EC was isolated from 86.7% cloacal swabs of chickens (13 out of 15), 55.0% rectal swabs of pigs (11 out of 20) and 100% from their surroundings (2 beddings in a chicken farm and 2 drainages in pig farms). All the isolates from chicken and pig farms were multidrug-resistant. Interestingly, 94.7% (36/38) isolates from chicken were resistant to ciprofloxacin and mcr-1 gene-positive (related to colistin resistance), respectively, while ciprofloxacin resistance and mcr-1 gene was found in only 12.8% (5/39) and none (0/39) from pig, respectively. CTX-M type in most of the chicken isolates belonged to group-1 whereas that in the pig isolates belonged to group-9. Virulence gene profiling revealed that some of these isolates indeed carry eae or astA pathogenic genes. Plasmid profiling and PFGE analysis indicated that most of them showed various genotypes although some isolates showed nearly identical genotype, suggesting that a number of ESBL-EC with various genotypes were distributed in chickens and pigs in Mekong Delta. To the best of our knowledge, this is the first report regarding isolation of ESBL-EC from broiler chickens in large scale-farms and pigs in Vietnam. Taken together, these results suggest that chickens and pigs in Mekong Delta, Vietnam used for food industry could also serve as reservoirs of ESBL-EC isolates carrying virulence genes

Elastic Scattering Time–Gated Multi–Static Lidar Scheme for Mapping and Identifying Contaminated Atmospheric Droplets

Numerical simulations are performed to determine the angular dependence of the MIe scattering cross-section intensities of pure water droplets and pollutants such as contaminated water droplets and black carbon as a function of the wavelength of the incident laser light, complex refractive index, and size of the scatterer. Our results show distinct scattering features when varying the various scattering parameters, thereby allowing the identification of the scattering particle with specific application to the identification of atmospheric pollutants including black carbon. Regardless of the type of scatterer, the scattering intensity is nearly uniform with a slight preference for forward scattering when the size of the particle is within 20% of the incident laser’s wavelength. The scattering patterns start to exhibit distinguishable features when the size parameter equals 1.77, corresponding to an incident laser wavelength of 0.355 μm and a particle radius of 0.1 μm. The patterns then become increasingly unique as the size parameter increases. Based on these calculations, we propose a time-gated lidar scheme consisting of multiple detectors that can rotate through a telescopic angle and be placed equidistantly around the scattering particles to collect the backscattered light and a commercially available Q-switched laser system emitting at tunable laser wavelengths. By using a pulsed laser with 10-ns pulse duration, our scheme could distinguish scattering centers that are at least 3 m apart. Our scheme called MIe Scattering Time-gated multi-Static LIDAR (MISTS–LIDAR) would be capable of identifying the type of atmospheric pollutant and mapping its location with a spatial resolution of a few meters