Genomic Epidemiology: Whole-Genome-Sequencing–Powered Surveillance and Outbreak Investigation of Foodborne Bacterial Pathogens

As we are approaching the twentieth anniversary of PulseNet, a network of public health and regulatory laboratories that has changed the landscape of foodborne illness surveillance through molecular subtyping, public health microbiology is undergoing another transformation brought about by so-called next-generation sequencing (NGS) technologies that have made whole-genome sequencing (WGS) of foodborne bacterial pathogens a realistic and superior alternative to traditional subtyping methods. Routine, real-time, and widespread application of WGS in food safety and public health is on the horizon. Technological, operational, and policy challenges are still present and being addressed by an international and multidisciplinary community of researchers, public health practitioners, and other stakeholders. </jats:p

Channel Estimation with Dynamic Metasurface Antennas via Model-Based Learning

Dynamic Metasurface Antenna (DMA) is a cutting-edge antenna technology offering scalable and sustainable solutions for large antenna arrays. The effectiveness of DMAs stems from their inherent configurable analog signal processing capabilities, which facilitate cost-limited implementations. However, when DMAs are used in multiple input multiple output (MIMO) communication systems, they pose challenges in channel estimation due to their analog compression. In this paper, we propose two model-based learning methods to overcome this challenge. Our approach starts by casting channel estimation as a compressed sensing problem. Here, the sensing matrix is formed using a random DMA weighting matrix combined with a spatial gridding dictionary. We then employ the learned iterative shrinkage and thresholding algorithm (LISTA) to recover the sparse channel parameters. LISTA unfolds the iterative shrinkage and thresholding algorithm into a neural network and trains the neural network into a highly efficient channel estimator fitting with the previous channel. As the sensing matrix is crucial to the accuracy of LISTA recovery, we introduce another data-aided method, LISTA-sensing matrix optimization (LISTA-SMO), to jointly optimize the sensing matrix. LISTA-SMO takes LISTA as a backbone and embeds the sensing matrix optimization layers in LISTA's neural network, allowing for the optimization of the sensing matrix along with the training of LISTA. Furthermore, we propose a self-supervised learning technique to tackle the difficulty of acquiring noise-free data. Our numerical results demonstrate that LISTA outperforms traditional sparse recovery methods regarding channel estimation accuracy and efficiency. Besides, LISTA-SMO achieves better channel accuracy than LISTA, demonstrating the effectiveness in optimizing the sensing matrix

Optimum Tower Crane Selection and Supporting Design Management

To optimize tower crane selection and supporting design, lifting requirements (as well as stability) should be examined, followed by a review of economic feasibility. However, construction engineers establish plans based on data provided by equipment suppliers since there are no tools with which to thoroughly examine a support design’s suitability for various crane types, and such plans lack the necessary supporting data. In such cases it is impossible to optimize a tower crane selection to satisfy lifting requirements in terms of cost, and to perform lateral support and foundation design. Thus, this study is intended to develop an optimum tower crane selection and supporting design management method based on stability. All cases that are capable of generating an optimization of approximately 3,000 ~ 15,000 times are calculated to identify the candidate cranes with minimized cost, which are examined. The optimization method developed in the study is expected to support engineers in determining the optimum lifting equipment management

HLA class I allele promiscuity revisited

The peptide repertoire presented on human leukocyte antigen (HLA) class I molecules is largely determined by the structure of the peptide binding groove. It is expected that the molecules having similar grooves (i.e., belonging to the same supertype) might present similar/overlapping peptides. However, the extent of promiscuity among HLA class I ligands remains controversial: while in many studies T cell responses are detected against epitopes presented by alternative molecules across HLA class I supertypes and loci, peptide elution studies report minute overlaps between the peptide repertoires of even related HLA molecules. To get more insight into the promiscuous peptide binding by HLA molecules, we analyzed the HLA peptide binding data from the large epitope repository, Immune Epitope Database (IEDB), and further performed in silico analysis to estimate the promiscuity at the population level. Both analyses suggest that an unexpectedly large fraction of HLA ligands (>50%) bind two or more HLA molecules, often across supertype or even loci. These results suggest that different HLA class I molecules can nevertheless present largely overlapping peptide sets, and that “functional” HLA polymorphism on individual and population level is probably much lower than previously anticipated

Radiation fluxes in a business district of Shanghai, China

Radiative fluxes are key drivers of surface-atmosphere heat exchanges in cities. Here the first year-long (December 2012 – November 2013) measurements of the full radiation balance for a dense urban site in Shanghai are presented, collected with a net radiometer CNR4 mounted 80 m above ground. Clear sky incoming shortwave radiation (K↓) (median daytime maxima) ranges from 575 W m-2 in winter to 875 W m-2 in spring, with cloud cover reducing the daily maxima by about 160 W m-2. The median incoming longwave radiation daytime maxima is 305 and 468 W m-2 in winter and summer, respectively, with increases of 30 and 15 W m-2 for cloudy conditions. The effect of air quality is evident: ‘haze’ conditions decrease hourly median K↓ by 11.3%. The midday (11:00 -13:00 LST) clear sky surface albedo (α) is 0.128, 0.141, 0.143 and 0.129 for winter, spring, summer and autumn, respectively. α varies with solar elevation and azimuth angle due to heterogeneity of the urban surface. In winter, shadows play an important role in decreasing α in the late afternoon. For the site, the bulk α is 0.14. The NARP/SUEWS land surface model reproduces the radiation components at this site well, a promising result for applications elsewhere. These observations help to fill the gap of long-term radiation measurements in East Asian and low-latitude cities quantifying the effects of season, cloud cover and air quality

Extension of all-optical reconstruction method for isolated attosecond pulses using high-harmonic generation streaking spectra

An all-optical method for directly reconstructing the spectral phase of isolated attosecond pulse (IAP) has been proposed recently [New J. Phys. 25, 083003 (2023)]. This method is based on the high-harmonic generation (HHG) streaking spectra generated by an IAP and a time-delayed intense infrared (IR) laser, which can be accurately simulated by an extended quantitative rescattering model. Here we extend the retrieval algorithm in this method to successfully retrieve the spectral phase of an shaped IAP, which has a spectral minimum, a phase jump about $\pi$, and a "split" temporal profile. We then reconstruct the carrier-envelope phase of IR laser from HHG streaking spectra. And we finally discuss the retrieval of the phase of high harmonics by the intense IR laser alone using the Fourier transform of HHG streaking spectra

A new model to downscale urban and rural surface and air temperatures evaluated in Shanghai, China

A simple model, TsT2m (Surface Temperature and near surface air Temperature (at 2 m) model), is developed to downscale numerical model output (such as from ECMWF) to obtain higher temporal and spatial resolution surface and near surface air temperature. It is evaluated in Shanghai, China. Surface temperature (TS) and near surface air temperature (Ta) sub-models account for variations in land covers and their different thermal properties, resulting in spatial variations of surface and air temperature. The Net All Wave Radiation Parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature sub-model, the Objective Hysteresis Model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near surface air temperature sub-model considers the horizontal and vertical energy changes for a column of well mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land cover types values are more similar. Downscaled, higher temporal and spatial resolution air temperatures are compared to observations at 110 Automatic Weather Stations across Shanghai. After downscaling with the TsT2m model, the average forecast accuracy of near surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stres

Evaluation of the Surface Urban Energy and Water balance Scheme (SUEWS) at a dense urban site in Shanghai: sensitivity to anthropogenic heat and irrigation

The Surface Urban Energy and Water balance Scheme (SUEWS) is used to investigate the impact of anthropogenic heat flux (QF) and irrigation on surface energy balance partitioning in a central business district of Shanghai. Diurnal profiles of QF are carefully derived based on city-specific hourly electricity consumption data, hourly traffic data and dynamic population density. QF is estimated to be largest in summer (mean daily peak 236 W m-2). When QF is omitted, the SUEWS sensible heat flux (QH) reproduces the observed diurnal pattern generally well, but the magnitude is underestimated compared to observations for all seasons. When QF is included, the QH estimates are improved in spring, summer and autumn, but poorer in winter indicating winter QF is overestimated. Inclusion of QF has little influence on the simulated latent heat flux (QE), but improves the storage heat flux estimates except in winter. Irrigation, both amount and frequency, has a large impact on QE. When irrigation is not considered, the simulated QE is underestimated for all seasons. The mean summer daytime QE is largely overestimated compared to observations under continuous irrigation conditions. Model results are improved when irrigation occurs with a 3-day frequency, especially in summer. Results are consistent with observed monthly out-door water use. This study highlights the importance of appropriately including the QF and irrigation in urban land surface models - terms not generally considered in many previous studies

Exploiting macrophage autophagy-lysosomal biogenesis as a therapy for atherosclerosis

Macrophages specialize in removing lipids and debris present in the atherosclerotic plaque. However, plaque progression renders macrophages unable to degrade exogenous atherogenic material and endogenous cargo including dysfunctional proteins and organelles. Here we show that a decline in the autophagy-lysosome system contributes to this as evidenced by a derangement in key autophagy markers in both mouse and human atherosclerotic plaques. By augmenting macrophage TFEB, the master transcriptional regulator of autophagy-lysosomal biogenesis, we can reverse the autophagy dysfunction of plaques, enhance aggrephagy of p62-enriched protein aggregates and blunt macrophage apoptosis and pro-inflammatory IL-1β levels, leading to reduced atherosclerosis. In order to harness this degradative response therapeutically, we also describe a natural sugar called trehalose as an inducer of macrophage autophagy-lysosomal biogenesis and show trehalose's ability to recapitulate the atheroprotective properties of macrophage TFEB overexpression. Our data support this practical method of enhancing the degradative capacity of macrophages as a therapy for atherosclerotic vascular disease