11,298 research outputs found

    Using Thermal Remote Sensing to Quantify Impact of Traffic on Urban Heat Islands during COVID

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    A three-month lockdown in the U.S. at the beginning of the COVID-19 outbreak in 2020 greatly reduced the traffic volume in many cities, especially large metropolitan areas such as the San Francisco Bay Area. This research explores the impact of transportation on climate change by using remote sensing technology and statistical analysis during the COVID-19 lockdown. Using thermal satellite data, this research measures the intensity of the urban heat island, the main driver for climate change during the urbanization process. The research team acquired morning and afternoon MODIS data in the same periods in 2019 before the pandemic and 2020 during the pandemic. MODIS imagery provides a wall-to-wall land surface temperature map to precisely measure the dynamics of the urban heat effect. In situ meteorological data were also acquired to build an urban surface energy budget and construct statistical models between solar radiation and the intensity of heat dynamics. The team implemented this urban heat budget in six counties in Northern California. This research quantifies the impact of lockdown policies on heat intensity in urban areas and human mobility in the context of COVID-19 and future pandemics. The quantitative results obtained in this study provide critical information for analyses of climate change impact on an urban scale

    Improving the mapping of condition-specific health-related quality of life onto SF-6D score

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    Background This study sought to improve the predictive performance and goodness-of-fit of mapping models, as part of indirect valuation, by introducing cubic spline smoothing to map a group of health-related quality of life (HRQOL) measures onto a preference-based measure. Methods This study was a secondary analysis of a cross-sectional health survey data assessing the HRQOL for patients with colorectal neoplasms. Mapping functions of condition-specific functional assessment of cancer therapy—colorectal (FACT-C) onto preference-based SF-6D measure were developed using a dataset of 553 Chinese subjects with different stages of colorectal neoplasm. The missing values of FACT-C were imputed using multiple imputation. Then three widely applicable models (ordinary least square (OLS), Tobit and two-part models) were employed for the mapping function after applying the cubic spline smoothing on the data. For the evaluation of the effectiveness of cubic spline smoothing and multiple imputation, the goodness-of-fit and prediction performance of each model were compared. Results Analyses showed that the models fitted with transformed data from cubic spline smoothing offered better performance in goodness-of-fit and prediction than the models fitted with the original data. The values of R2R^2 were improved by over 10 %, and the root mean square error and the mean absolute error were both reduced. The best goodness-of-fit and performance were achieved by OLS model using transformed data from cubic spline smoothing. Conclusions Cubic spline smoothing and multiple imputation were recommended for the mapping of HRQOL measures onto the preference-based measure. Among the three mapping models, the simple-to-use OLS model had the best performance.postprin

    Genetic diversity of ST5 Staphylococcus aureus isolated from swine veterinarians in the USA

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    The term livestock associated methicillin resistant Staphylococcus aureus (LA-MRSA) has been synonymous with sequence type ST398 since the identification of this lineage of MRSA in Holland. Subsequent research indicates borader genetic diversity of MRSA strains in swine, with MRSA variants belonging to MLST sequence type ST9, and ST5 also being reported in studies of swine in varioust countries

    Genomic characterization of Staphylococcus aureus at the swine-human interface

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    The epidemiology of S. aureus in swine held little interest until the ST398 lineage of MRSA was found to be prevalent in pigs and pig farmers in the Netherlands in 2004 (Voss et al. 2005). ST398 MRSA have since been detected in multiple livestock species and in many countries (EFSA, 2009; Smith and Pearson, 2011), while genetically distinct variants of ST398 S. aureus occur in some human populations independent of livestock reservoirs (Carrel et al., 2017). Furthermore, other genotypes of MRSA can occur in pigs, particularly ST9 MRSA in Asia, and ST5 MRSA in North America (Chuang and Huang, 2015; Frana et al. 2013). In the USA, methicillin susceptible variants of the ST398, ST9 and ST5 lineages are widespread in commercial swine, yet MRSA variants appear to occur at relatively low prevalence (Sun, et al., 2015). Despite common exposure to, and colonization of, swine workers by livestock associated S. aureus, significant clinical infections appear to be uncommon in occupationally exposed people. However, invasive and even fatal infections are reported at relatively low incidence in some countries, and medically compromised people appear to be at particular risk, even in the absence of animal contact (Larsen et al., 2017). There is evidence that ST398 MRSA of livestock origin are less transmissible among humans than MRSA of human origin. Also, genomic studies typically have indicated that livestock associated MRSA (both ST398 and ST5) lack most virulence factors that occur in human clinical isolates (Schijffelen et al. 2010; Price et al. 2012; Hau et al, 2015). However, to date there has been little genomic characterization of methicillin susceptible S. aureus (MSSA) that are prevalent in swine populations. The purpose of this study was to describe the occurrence of virulence factors and antibiotic resistance genes in S. aureus isolates from pigs and swine veterinarians in the USA

    Boosting the power conversion efficiency of organic solar cells using weakly luminescent gold(III) corrole with long-lived exciton state

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    Poster Session: P-69Transition metal complexes have been widely used as light-emitting and photon-absorbing materials in optoelectronic devices with diverse applications. While these complexes have been intensively studied in the field of organic light-emitting devices (OLEDs) due to their inherently high phosphorescence quantum yields …postprin

    NODIS: Neural Ordinary Differential Scene Understanding

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    Semantic image understanding is a challenging topic in computer vision. It requires to detect all objects in an image, but also to identify all the relations between them. Detected objects, their labels and the discovered relations can be used to construct a scene graph which provides an abstract semantic interpretation of an image. In previous works, relations were identified by solving an assignment problem formulated as Mixed-Integer Linear Programs. In this work, we interpret that formulation as Ordinary Differential Equation (ODE). The proposed architecture performs scene graph inference by solving a neural variant of an ODE by end-to-end learning. It achieves state-of-the-art results on all three benchmark tasks: scene graph generation (SGGen), classification (SGCls) and visual relationship detection (PredCls) on Visual Genome benchmark

    Operator entanglement of two-qubit joint unitary operations revisited: Schmidt number approach

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    Operator entanglement of two-qubit joint unitary operations is revisited. Schmidt number is an important attribute of a two-qubit unitary operation, and may have connection with the entanglement measure of the unitary operator. We found the entanglement measure of two-qubit unitary operators is classified by the Schmidt number of the unitary operators. The exact relation between the operator entanglement and the parameters of the unitary operator is clarified too.Comment: To appear in the Brazilian Journal of Physic
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