Detection of small single-cycle signals by stochastic resonance using a bistable superconducting quantum interference device

We propose and experimentally demonstrate detecting small single-cycle and few-cycle signals by using the symmetric double-well potential of a radio frequency superconducting quantum interference device (rf-SQUID). We show that the response of this bistable system to single- and few-cycle signals has a non-monotonic dependence on the noise strength. The response, measured by the probability of transition from initial potential well to the opposite one, becomes maximum when the noise-induced transition rate between the two stable states of the rf-SQUID is comparable to the signal frequency. Comparison to numerical simulations shows that the phenomenon is a manifestation of stochastic resonance.Comment: 5 pages 3 figure

Solvothermal synthesis of ternary sulfides of Sb2_xBixS3 (x=0.4,1) with 3D flower-like architectures

Flower-like nanostructures of Sb2 − xBixS3(x = 0.4, 1.0) were successfully prepared using both antimony diethyldithiocarbamate [Sb(DDTC)3] and bismuth diethyldithiocarbamate [Bi(DDTC)3] as precursors under solvothermal conditions at 180 °C. The prepared Sb2 − xBixS3 with flower-like 3D architectures were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDS), high-resolution transmission electron microscopy (HRTEM), and selected area electron diffraction (SAED). The flower-like architectures, with an average diameter of ~4 μm, were composed of single-crystalline nanorods with orthorhombic structures. The optical absorption properties of the Sb2 − xBixS3 nanostructures were investigated by UV–Visible spectroscopy, and the results indicate that the Sb2 − xBixS3 compounds are semiconducting with direct band gaps of 1.32 and 1.30 eV for x = 0.4 and 1.0, respectively. On the basis of the experimental results, a possible growth mechanism for the flower-like Sb2 − xBixS3 nanostructures is suggested

Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model

We developed a water-centric monthly scale simulation model (WaSSI-C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI-C model was evaluated with basin-scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE) estimates by multiple independent methods across 2103 eight-digit Hydrologic Unit Code watersheds in the conterminous United States from 2001 to 2006. Our results indicate that WaSSI-C captured the spatial and temporal variability and the effects of large droughts on key ecosystem fluxes. Our modeled mean (±standard deviation in space) ET (556 ± 228 mm yr−1) compared well to Moderate Resolution Imaging Spectroradiometer (MODIS) based (527 ± 251 mm yr−1) and watershed water balance based ET (571 ± 242 mm yr−1). Our mean annual GEP estimates (1362 ± 688 g C m−2 yr−1) compared well (R2 = 0.83) to estimates (1194 ± 649 g C m−2 yr−1) by eddy flux-based EC-MOD model, but both methods led significantly higher (25–30%) values than the standard MODIS product (904 ± 467 g C m−2 yr−1). Among the 18 water resource regions, the southeast ranked the highest in terms of its water yield and carbon sequestration capacity. When all ecosystems were considered, the mean NEE (−353 ± 298 g C m−2 yr−1) predicted by this study was 60% higher than EC-MOD\u27s estimate (−220 ± 225 g C m−2 yr−1) in absolute magnitude, suggesting overall high uncertainty in quantifying NEE at a large scale. Our water-centric model offers a new tool for examining the trade-offs between regional water and carbon resources under a changing environment

Changes in temperature-moisture covariance could increase soil carbon loss

Soils store about 1.5x10^16 g of carbon (C), about as much as terrestrial vegetation and atmosphere combined 1. The complex interplay between factors that regulate C release from soil through respiration is not completely understood, but could potentially exert strong influence on global radiation balance and climate change2. Respiration exerts strong effect on the spatial heterogeneity of terrestrial C cycle 3 and its temporal variation remains more poorly understood compared to gross ecosystem production (GEP) 4. This variation can analytically be attributed to changes in environmental factors, but forecasting individual deviations remains a challenge 4. Here we propose that deviations of the typical covariance pattern of primary environmental drivers (temperature, T, and moisture, presented in this study as volumetric water content, VWC) may affect the deviations of respiratory C loss. Typically, T and VWC are inversely related, with warm periods being generally drier and vice versa, and therefore the stimulating effect of one factor is counterbalanced by unfavorable levels of the other 5. However, should the driving variables be positively related, respiratory carbon release can increase significantly (Supplementary Fig. 1a). This hypothesis is supported by two consecutive years of ecosystem-level and soil carbon exchange data that differed in rain fall periodicity and T-VWC-covariance. With changing climate patterns, including the intensity and frequency of rainfall events, there is the possibility that the covariance patterns of T and VWC may change, and more frequent periods of positive T-VWC covariance may lead to greater loss of soil carbon, and contribute to greater radiative forcing on Earth’s energy budget

A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children.

A quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to ∼95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations.IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification

A Novel Compressed Sensing Method for Magnetic Resonance Imaging: Exponential Wavelet Iterative Shrinkage-Thresholding Algorithm with Random Shift

Aim. It can help improve the hospital throughput to accelerate magnetic resonance imaging (MRI) scanning. Patients will benefit from less waiting time. Task. In the last decade, various rapid MRI techniques on the basis of compressed sensing (CS) were proposed. However, both computation time and reconstruction quality of traditional CS-MRI did not meet the requirement of clinical use. Method. In this study, a novel method was proposed with the name of exponential wavelet iterative shrinkagethresholding algorithm with random shift (abbreviated as EWISTARS). It is composed of three successful components: (i) exponential wavelet transform, (ii) iterative shrinkage-thresholding algorithm, and (iii) randomshift. Results. Experimental results validated that, compared to state-of-the-art approaches, EWISTARS obtained the leastmean absolute error, the leastmean-squared error, and the highest peak signal-to-noise ratio. Conclusion. EWISTARS is superior to state-of-the-art approaches

Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset

To compare the impact of surface–atmosphere exchanges from rural and urban areas, fully vegetated areas (e.g. deciduous trees, evergreen trees and grass) commonly found adjacent to cities need to be modelled. Here we provide a general workflow to derive parameters for SUEWS (Surface Urban Energy and Water Balance Scheme), including those associated with vegetation phenology (via leaf area index, LAI), heat storage and surface conductance. As expected, attribution analysis of bias in SUEWS-modelled QE finds that surface conductance (gs) plays the dominant role; hence there is a need for more estimates of surface conductance parameters. The workflow is applied at 38 FLUXNET sites. The derived parameters vary between sites with the same plant functional type (PFT), demonstrating the challenge of using a single set of parameters for a PFT. SUEWS skill at simulating monthly and hourly latent heat flux (QE) is examined using the site-specific derived parameters, with the default NOAH surface conductance parameters (Chen et al., 1996). Overall evaluation for 2 years has similar metrics for both configurations: median hit rate between 0.6 and 0.7, median mean absolute error less than 25Wm-2, and median mean bias error ~5Wm-2. Performance differences are more evident at monthly and hourly scales, with larger mean bias error (monthly: ~40Wm-2; hourly ~30Wm-2) results using the NOAH-surface conductance parameters, suggesting that they should be used with caution. Assessment of sites with contrasting QE performance demonstrates how critical capturing the LAI dynamics is to the SUEWS prediction skills of gs and QE. Generally gs is poorest in cooler periods (more pronounced at night, when underestimated by ~3mms-1). Given the global LAI data availability and the workflow provided in this study, any site to be simulated should benefit

Direct Femtosecond Laser Inscription of High-Order Bragg Gratings in Fluoroaluminate Glass Fiber

This letter reports the fabrication of fiber Bragg gratings (FBGs) within in-house fabricated fluoroaluminate (AlF3) glass fibers using femtosecond (fs) laser inscription at 800 nm. The grating strength of the FBGs was investigated for different pulse energies and different orders, and a 3rd-order FBG with Bragg wavelength at 1557 nm was found to have the highest reflectivity of 99.5%. In addition, the reflectivity of the mid-IR grating peaks for different orders was also studied, and a 2nd-order FBG with a reflectivity of 98.8% was obtained at 2864 nm. Finally, the temperature characteristics of a mid-IR FBG were studied between 30 °C and 150 °C, showing a linear wavelength dependence and an excellent stability for the refractive index modulation. Such highly reflectivity FBGs in AlF3 fiber have significant potential for applications in the development of compact all-fiber mid-IR fiber lasers