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

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

Experimental observation of chiral phonons in monolayer WSe2

Chirality characterizes an object that is not identical to its mirror image. In condensed matter physics, Fermions have been demonstrated to obtain chirality through structural and time-reversal symmetry breaking. These systems display unconventional electronic transport phenomena such as the quantum Hall effect and Weyl semimetals. However, for bosonic collective excitations in atomic lattices, chirality was only theoretically predicted and has never been observed. We experimentally show that phonons can exhibit intrinsic chirality in monolayer tungsten diselenide, whose lattice breaks the inversion symmetry and enables inequivalent electronic K and -K valley states. The time-reversal symmetry is also broken when we selectively excite the valley polarized holes by circularly polarized light. Brillouin-zone-boundary phonons are then optically created by the indirect infrared absorption through the hole-phonon interactions. The unidirectional intervalley transfer of holes ensures that only the phonon modes in one valley are excited. We found that such photons are chiral through the transient infrared circular dichroism, which proves the valley phonons responsible to the indirect absorption has non-zero pseudo-angular momentum. From the spectrum we further deduce the energy transferred to the phonons that agrees with both the first principle calculation and the double-resonance Raman spectroscopy. The chiral phonons have significant implications for electron-phonon coupling in solids, lattice-driven topological states, and energy efficient information processing

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

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 $R^2$ 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

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

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

A Surrogate-Assisted Extended Generative Adversarial Network for Parameter Optimization in Free-Form Metasurface Design

Metasurfaces have widespread applications in fifth-generation (5G) microwave communication. Among the metasurface family, free-form metasurfaces excel in achieving intricate spectral responses compared to regular-shape counterparts. However, conventional numerical methods for free-form metasurfaces are time-consuming and demand specialized expertise. Alternatively, recent studies demonstrate that deep learning has great potential to accelerate and refine metasurface designs. Here, we present XGAN, an extended generative adversarial network (GAN) with a surrogate for high-quality free-form metasurface designs. The proposed surrogate provides a physical constraint to XGAN so that XGAN can accurately generate metasurfaces monolithically from input spectral responses. In comparative experiments involving 20000 free-form metasurface designs, XGAN achieves 0.9734 average accuracy and is 500 times faster than the conventional methodology. This method facilitates the metasurface library building for specific spectral responses and can be extended to various inverse design problems, including optical metamaterials, nanophotonic devices, and drug discovery

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

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

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