Local Spectrum Research Articles

Atomic-scale probing of heterointerface phonon bridges in nitride semiconductor

Interface phonon modes that are generated by several atomic layers at the heterointerface play a major role in the interface thermal conductance for nanoscale high-power devices such as nitride-based high-electron-mobility transistors and light-emitting diodes. Here we measure the local phonon spectra across AlN/Si and AlN/Al interfaces using atomically resolved vibrational electron energy-loss spectroscopy in a scanning transmission electron microscope. At the AlN/Si interface, we observe various interface phonon modes, of which the extended and localized modes act as bridges to connect the bulk AlN modes and bulk Si modes and are expected to boost the phonon transport, thus substantially contributing to interface thermal conductance. In comparison, no such phonon bridge is observed at the AlN/Al interface, for which partially extended modes dominate the interface thermal conductivity. This work provides valuable insights into understanding the interfacial thermal transport in nitride semiconductors and useful guidance for thermal management via interface engineering.

Ambidexterity in chromatic homotopy theory

We extend the theory of ambidexterity developed by M. J. Hopkins and J. Lurie and show that the infty -categories of T!left( nright) -local spectra are infty -semiadditive for all n, where T!left( nright) is the telescope on a v_{n}-self map of a type n spectrum. This generalizes and provides a new proof for the analogous result of Hopkins–Lurie on K!left( nright) -local spectra. Moreover, we show that K!left( nright) -local and T!left( nright) -local spectra are respectively, the minimal and maximal 1-semiadditive localizations of spectra with respect to a homotopy ring, and that all such localizations are in fact infty -semiadditive. As a consequence, we deduce that several different notions of “bounded chromatic height” for homotopy rings are equivalent, and in particular, that T!left( nright) -homology of pi -finite spaces depends only on the nth Postnikov truncation. A key ingredient in the proof of the main result is a construction of a certain power operation for commutative ring objects in stable 1-semiadditive infty -categories. This is closely related to some known constructions for Morava E-theory and is of independent interest. Using this power operation we also give a new proof, and a generalization, of a nilpotence conjecture of J. P. May, which was proved by A. Mathew, N. Naumann, and J. Noel.

The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication

Although many Soil Spectral Libraries (SSLs) have been created globally, these libraries still have not been operationalized for end-users. To address this limitation, this study created an online Brazilian Soil Spectral Service (BraSpecS). The system was based on the Brazilian Soil Spectral Library (BSSL) with samples collected in the Visible–Near–Short-wave infrared (vis–NIR–SWIR) and Mid-infrared (MIR) ranges. The interactive platform allows users to find spectra, act as custodians of the data, and estimate several soil properties and classification. The system was tested by 500 Brazilian and 65 international users. Users accessed the platform (besbbr.com.br), uploaded their spectra, and received soil organic carbon (SOC) and clay content prediction results via email. The BraSpecS prediction provided good results for Brazilian data, but performed variably for other countries. Prediction for countries outside of Brazil using local spectra (External Country Soil Spectral Libraries, ExCSSL) mostly showed greater performance than BraSpecS. Clay R2 ranged from 0.5 (BraSpecS) to 0.8 (ExCSSL) in vis–NIR–SWIR, but BraSpecS MIR models were more accurate in most situations. The development of external models based on the fusion of local samples with BSSL formed the Global Soil Spectral Library (GSSL). The GSSL models improved soil properties prediction for different countries. Nevertheless, the proposed system needs to be continually updated with new spectra so they can be applied broadly. Accordingly, the online system is dynamic, users can contribute their data and the models will adapt to local information. Our community-driven web platform allows users to predict soil attributes without learning soil spectral modeling, which will invite end-users to utilize this powerful technique.

A Hint of a Low-energy Excess in Cosmic-Ray Fluorine

Abstract Since its launch, the Alpha Magnetic Spectrometer–02 (AMS-02) has delivered outstanding quality measurements of the spectra of cosmic-ray (CR) species ( p ¯ , e ±) and nuclei (H–O, Ne, Mg, Si, Fe), which resulted in a number of breakthroughs. The most recent AMS-02 result is the measurement of the spectrum of CR fluorine up to ∼2 TV. Given its very low solar system abundance, fluorine in CRs is thought to be mostly secondary, produced in fragmentations of heavier species, predominantly Ne, Mg, and Si. Similar to the best-measured secondary-to-primary boron to carbon nuclei ratio that is widely used to study the origin and propagation of CR species, the precise fluorine data would allow the origin of Si-group nuclei to be studied independently. Meanwhile, the secondary origin of CR fluorine has never been tested in a wide energy range due to the lack of accurate CR data. In this paper, we use the first ever precise measurements of the fluorine spectrum by AMS-02 together with ACE-CRIS and Voyager 1 data to actually test this paradigm. Our detailed modeling shows an excess below 10 GV in the fluorine spectrum that may hint at a primary fluorine component. We also provide an updated local interstellar spectrum (LIS) of fluorine in the rigidity range from a few MV to ∼2 TV. Our calculations employ the self-consistent GalProp–HelMod framework that has proved to be a reliable tool in deriving the LIS of CR p ¯ and e −, and nuclei Z ≤ 28.

Expanding the range of the resolvable strain from distributed fiber optic sensors using a local adaptive reference approach.

Optical frequency domain reflectometry (OFDR) is a spectral measurement technique in which shifts in the local Rayleigh backscatter spectra can be used to perform distributed temperature or strain measurements relative to a reference measurement using ordinary single-mode optical fibers. This work demonstrates a data processing methodology for improving the resolvable range of temperature and strain by adaptively varying the reference measurement position by position, based on the time evolution of the local optical intensities and the correlation between the reference and active measurements. These methods nearly double the resolvable range of temperature and strain compared with that achieved using the traditional static reference approach.

On the Picard group graded homotopy groups of a finite type two $K(2)$-local spectrum at the prime three

On the Picard group graded homotopy groups of a finite type two $K(2)$-local spectrum at the prime three

M-CORE: A Novel Approach for Land Cover Fraction Mapping Using Multisite Spectral Libraries

The concept of a generic spectral library (GSL), i.e., a structured collection of image spectra sampled from various optical remote sensing images covering different sites and points in time, has been suggested in previous studies to facilitate the tedious process of producing training data for remote sensing-based land cover (LC) mapping. When using multisource libraries collected over different sites, library pruning approaches are needed to extract an apt set of labeled spectra to perform mapping on a specific area. Library pruning mainly aims to discard image-irrelevant and redundant spectra, while limiting spectral confusion during the mapping process. Most library pruning approaches focus only on one of these aspects, which has been shown to negatively affect mapping accuracies. This article emphasizes the need for a multistep approach to optimize a GSL for site-specific mapping. We propose a new library pruning method called M-CORE, specifically designed to facilitate LC fraction mapping. The method extends multiple signal classification (MUSIC) with a confusion reduction (CORE) component. Vegetation-impervious-soil (VIS) fraction mapping experiments on a Sentinel-2 image of Brussels, using a GSL with and without local spectra, show the added value of M-CORE over previously proposed library pruning methods and demonstrate the feasibility of GSL-based mapping in an urban context.

Cross-Attention Spectral–Spatial Network for Hyperspectral Image Classification

Hyperspectral image (HSI) classification aims to identify categories of hyperspectral pixels. Recently, many convolutional neural networks (CNNs) have been designed to explore the spectrums and spatial information of HSI for classification. In recent CNN-based methods, 2-D or 3-D convolutions are inevitably utilized as basic operations to extract the spatial or spectral–spatial features. However, 2-D and 3-D convolutions are sensitive to the image rotation, which may result in that recent CNN-based methods are not robust to the HSI rotation. In this article, a cross-attention spectral–spatial network (CASSN) is proposed to alleviate the problem of HSI rotation. First, a cross-spectral attention component is proposed to exploit the local and global spectrums of the pixel to generate band weight for suppressing redundant bands. Second, a spectral feature extraction component is utilized to capture spectral features. Then, a cross-spatial attention component is proposed to generate spectral–spatial features from the HSI patch under the guidance of the pixel to be classified. Finally, the spectral–spatial feature is fed to a softmax classifier to obtain the category. The effectiveness of CASSN is demonstrated on three public databases.

A Comprehensive Overview on Modified Versions of Stockwell Transform For Power Quality Monitoring

The increasing trends toward the accurate identification of power quality disturbances (PQD) via power quality (PQ) monitoring require an appropriate digital signal processing (DSP) technique and a robust classifier. To this end, Stockwell transform (ST), one of the most efficient feature extraction DSP tools, and its several variants play an utmost role in PQ assessment framework. Its time-varying spectral characteristics generally extract the local instantaneous frequency spectrum from the global temporary behavior of PQD signal. However, the Standard ST suffers from thepoor time-frequency resolution because of its frequency-dependent Gaussian window (GW). While the analysis of the statistically time-varying signals requires a suitable balance between time and frequency resolution. To this end, this paper provides a comprehensive literature review on several modified versions of Standard ST for the first time to reduce the computational complexity of the algorithm as well as maximize the energy concentration of the time-frequency plane. A comparative analysis of all the modified STs has been presented in tabular form to provide the key characteristics of each technique. Additionally, a case study has been presented to substantiate the highest accuracy of the proposed algorithm over the other ST variants. Apart from the PQD classification, miscellaneous applications of Standard ST and its modified variants have been indicated. This review paper may provide a valuable resource to the researchers for further improvement of the time-frequency resolution of ST not only in classifying PQD but also for its other wide applications.

Mean and Turbulent Characteristics of a Bottom Mixing‐Layer Forced by a Strong Surface Tide and Large Amplitude Internal Waves

AbstractWe present 15 days of both mean and turbulent field observations bottom mixing‐layer at a gently sloping 250 m deep continental shelf site, energized by tides and nonlinear internal waves (NLIWs). The tidal frequency forcing was due to the combined effects of the barotropic tide and a mode‐1 internal tide (IT), while the NLIWs were predominantly mode‐1 waves of depression. The bottom mixing‐layer thickness varied at both semidiurnal and sub‐tidal ∼O(10)d frequencies, with an average thickness of around 10 m. Compression and expansion of the mixing‐layer by both the IT and NLIWs affected the mean velocity profiles in the mixing‐layer, while the phasing between the barotropic and baroclinic flows led to an asymmetry in mean velocity profiles between periods of rising and falling isotherms. With the exception of periods of flow reversal, the turbulent kinetic energy balance and turbulent stress observations were consistent with the existence of an inertial‐sublayer with thickness of approximately 10%–15% of the mixing‐layer thickness ( ∼1 m), even beneath NLIWs. In the outer portion of the mixing‐layer—that is, above the inertial‐sublayer—NLIWs modulated the local turbulence spectra. We discuss the observations in the context of a predictive model for mixing‐layer thickness. The analysis suggests that the high‐frequency variability in mixing‐layer thickness was dominated by internal wave pumping, though strength of the ambient stratification and the frequency of the forcing were important controls on the time‐averaged (sub‐tidal) variation.

Influence of nonlinear effects on forward stimulated Brillouin scattering distributed sensing

The influences of nonlinear effects on sensing performance of forward stimulated Brillouin scattering (FSBS) are investigated using opto-mechanical time-domain analysis sensor, which is taken for example. The excitation of FSBS often requires high pulse power (at Watt level) because of the lower gain coefficient. Owing to the co-propagation of reading pulse and scattered light, high-power activation pulses will induce various nonlinear effects in an FSBS sensing system. Using the reported method based on activation-reading time-domain separation, the influences of nonlinear effects due to activation pulses can be effectively avoided. However, the nonlinear effects of reading pulses directly affect the sensing performance. Based on this consideration, we study the influences of nonlinear effects on FSBS sensing and their physical mechanisms under different values of peak power of reading pulses; the variation process of the 1st- and 2nd-order FSBS spectrums along ～4.7 km standard single-mode fiber are revealed in detail. Finally, the optimal region is found, in which a perfect FSBS local spectrum is obtained, and the sensing distance can be extended.

Bacterial etiology and antibiotic sensitivity patterns in late-onset neonatal blood infection: A 6-year retrospective study

Introduction: The incidence and etiology of neonatal bloodstream infections vary globally. Early appropriate antibiotic therapy is crucial. An empiric antibiotic choice should be driven by accurate knowledge of the local spectrum of pathogens and susceptibilities. Methodology: A retrospective observational study was conducted on neonates born at local tertiary center from January 1, 2013, to December 31, 2018, with late-onset bloodstream infection (LBSI). Trends of causative organisms and antibiotic susceptibilities were analyzed. Results: A total of 696 LBSI occurred in 469 neonates. Overall incidence over the 6 years was 122/1000 admissions. The median time to LBSI was 13 days of life. Majority of infections occurred in infants <32 weeks. About 75.9% were caused by Gram-positive and the rest by Gram-negative bacteria. The most common organism was coagulase-negative staphylococcus (CoNS) which showed an increase in resistance to amikacin over time, but with stable sensitivity patterns to teicoplanin. Klebsiella and Escherichia coli were the most common Gram-negative organisms. There was improving sensitivity to cephalosporin in Klebsiella species. Sixteen percent of Gram-negative isolates were extended spectrum beta-lactamase (ESBL) producing. Majority of the Gram-negative bacteria including ESBL-producing strains remained sensitive to amikacin. An empiric antibiotic combination of teicoplanin and amikacin was appropriate to cover the majority of LBSIs. Conclusions: The majority of late-onset neonatal bloodstream infections in this study cohort were caused by Gram-positive organisms of which CoNS was the most common. The empiric antibiotic choices for LBSI on our unit seem appropriate based on the data. In units where the organism and susceptibility patterns are similar, the same antibiotic choices may be justified.

Adaptive Scaling Demodulation Transform: Algorithm and Applications

Classic post-processing time-frequency analysis (TFA) methods calculated by the short-time Fourier transform (STFT) suffer from the problems of blurry cross points and unsatisfied time-frequency concentration under noise interference. For solving the problems, a novel TFA technique, termed adaptive scaling demodulation transform (ASDT) is developed in this paper. The ASDT aims to calculate ideal time-frequency representation (TFR) by adaptively estimating the instantaneous frequency (IF) curves, extracting the time-frequency amplitudes at the estimated IF curves, and reassigning these time-frequency amplitudes into a new TFR. The IF curves are adaptively estimated by constructing the scaling demodulation operator and maximum criterion of local spectrum amplitude. The time-frequency amplitudes at the calculated IF curves are selected from the SFTF result. In this way, the ASDT can eliminate smeared time-frequency amplitudes and background noise, and accurately characterize intersecting frequency ridges with high energy concentration. The effectiveness of the developed technique is verified through simulated signal and two different mechanical vibration signals. Comparison analysis with classic TFA techniques shows that the ASDT has much better ability for processing signal with intersecting frequency curves under noise interference.

Innovative Analytical Method for X-ray Imaging and Space-Resolved Spectroscopy of ECR Plasmas

At the Italian National Institute for Nuclear Physics-Southern National Laboratory (INFN-LNS), and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, interfero-polarimetry, X-ray detectors), and here we focus on high-resolution, spatially resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5–20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high-precision, X-ray, spectrally resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolutions were 0.5 mm and 300 eV at 8 keV, respectively. Here, we present the innovative analysis algorithm that we properly developed to obtain Single Photon-Counted (SPhC) images providing the local plasma-emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows for a quantitative characterization of warm electrons population in the plasma (and its 2D distribution), which are the most important for ionization, and to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise that is often observable at very low exposure times (msec). The setup is now being updated, including fast shutters and trigger systems to allow simultaneous space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

Survey on encode biometric data for transmission in wireless communication networks

The aim of this research survey is to review an enhanced model supported by artificial intelligence to encode biometric data for transmission in wireless communication networks can be tricky as performance decreases with increasing size due to interference, especially if channels and network topology are not selected carefully beforehand. Additionally, network dissociations may occur easily if crucial links fail as redundancy is neglected for signal transmission. Therefore, we present several algorithms and its implementation which addresses this problem by finding a network topology and channel assignment that minimizes interference and thus allows a deployment to increase its throughput performance by utilizing more bandwidth in the local spectrum by reducing coverage as well as connectivity issues in multiple AI-based techniques. Our evaluation survey shows an increase in throughput performance of up to multiple times or more compared to a baseline scenario where an optimization has not taken place and only one channel for the whole network is used with AI-based techniques. Furthermore, our solution also provides a robust signal transmission which tackles the issue of network partition for coverage and for single link failures by using airborne wireless network. The highest end-to-end connectivity stands at 10 Mbps data rate with a maximum propagation distance of several kilometers. The transmission in wireless network coverage depicted with several signal transmission data rate with 10 Mbps as it has lowest coverage issue with moderate range of propagation distance using enhanced model to encode biometric data for transmission in wireless communication.

AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series

We present the AdaptSPEC-X method for the joint analysis of a panel of possibly nonstationary time series. The approach is Bayesian and uses a covariate-dependent infinite mixture model to incorporate multiple time series, with mixture components parameterized by a time-varying mean and log spectrum. The mixture components are based on AdaptSPEC, a nonparametric model which adaptively divides the time series into an unknown number of segments and estimates the local log spectra by smoothing splines. AdaptSPEC-X extends AdaptSPEC in three ways. First, through the infinite mixture, it applies to multiple time series linked by covariates. Second, it can handle missing values, a common feature of time series which can cause difficulties for nonparametric spectral methods. Third, it allows for a time-varying mean. Through these extensions, AdaptSPEC-X can estimate time-varying means and spectra at observed and unobserved covariate values, allowing for predictive inference. Estimation is performed by Markov chain Monte Carlo (MCMC) methods, combining data augmentation, reversible jump, and Riemann manifold Hamiltonian Monte Carlo techniques. We evaluate the methodology using simulated data, and describe applications to Australian rainfall data and measles incidence in the United States. Software implementing the method proposed in this article is available in the R package BayesSpec. Supplementary files for this article are available online.

Impedance Spectroscopy Measurements of Ionomer Film Oxygen Transport Resistivity in Operating Low-Pt PEM Fuel Cell.

The work presents a model for local impedance of low-Pt proton exchange membrane fuel cells (PEMFCs), including cathode pore size distribution and O2 transport along pores and through a thin ionomer film covering Pt/C agglomerates. The model was applied to fit the local impedance spectra of low-Pt fuel cells operated at current densities from 100 to 800 mA cm−2 and recorded by a segmented cell system. Assuming an ionomer film thickness of 10 nm, the fitting returned the product of the dimensionless Henry’s constant of oxygen dissolution in ionomer KH by the oxygen diffusivity DN in the ionomer (KHDN). This parameter allowed us to determine the fundamental O2 transport resistivity through the ionomer film in the working electrode under conditions relevant to the realistic operation of PEMFCs. The results show that variation of the operating current density does not affect , which remains nearly constant at ≃0.4 s cm−1.

Levantine overkill: 1.5 million years of hunting down the body size distribution

Multiple large-bodied species went extinct during the Pleistocene. Changing climates and/or human hunting are the main hypotheses used to explain these extinctions. We studied the causes of Pleistocene extinctions in the Southern Levant, and their subsequent effect on local hominin food spectra, by examining faunal remains in archaeological sites across the last 1.5 million years. We examined whether climate and climate changes, and/or human cultures, are associated with these declines. We recorded animal abundances published in the literature from 133 stratigraphic layers, across 58 Pleistocene and Early Holocene archaeological sites, in the Southern Levant. We used linear regressions and mixed models to assess the weighted mean mass of faunal assemblages through time and whether it was associated with temperature, paleorainfall, or paleoenvironment (C3 vs. C4 vegetation). We found that weighted mean body mass declined log-linearly through time. Mean hunted animal masses 10,500 years ago, were only 1.7% of those 1.5 million years ago. Neither body size at any period, nor size change from one layer to the next, were related to global temperature or to temperature changes. Throughout the Pleistocene, new human lineages hunted significantly smaller prey than the preceding ones. This suggests that humans extirpated megafauna throughout the Pleistocene, and when the largest species were depleted the next-largest were targeted. Technological advancements likely enabled subsequent human lineages to effectively hunt smaller prey replacing larger species that were hunted to extinction or until they became exceedingly rare.

Using laser marking to engrave optimal patterns for in‐plane displacement and strain measurement

AbstractThe checkerboard constitutes the best pattern for in‐plane displacement and strain measurement because it maximizes image gradient. The use of laser marking to deposit such a pattern on flat surfaces is investigated in this paper. Optimal settings for the parameters influencing the quality of the pattern are given. This pattern being periodic, the images are processed with the localized spectrum analysis, which is one of the spectral techniques used to process such images. It is shown that the metrological performance in terms of measurement resolution is equivalent to the one obtained with transferred checkerboards. Compared to the classic transfer technique generally used to deposit such patterns, the benefit of using laser marking is its ease of use, a much higher print speed and the fact that a thin coat of white paint instead of a thicker layer of white adhesive is employed to ensure a good contrast in the images. Various examples of strain measurements are given, in particular the measurement of the strain field around a knot embedded in a wood specimen subjected to a tensile test.

A Perspective on the Solar Modulation of Cosmic Anti-Matter

Global modulation studies with comprehensive numerical models contribute meaningfully to the refinement of very local interstellar spectra (VLISs) for cosmic rays. Modulation of positrons and anti-protons are investigated to establish how the ratio of their intensity, and with respect to electrons and protons, are changing with solar activity. This includes the polarity reversal of the solar magnetic field which creates a 22-year modulation cycle. Modeling illustrates how they are modulated over time and the particle drift they experience which is significant at lower kinetic energy. The VLIS for anti-protons has a peculiar spectral shape in contrast to protons so that the total modulation of anti-protons is awkwardly different to that for protons. We find that the proton-to-anti-proton ratio between 1–2 GeV may change by a factor of 1.5 over a solar cycle and that the intensity for anti-protons may decrease by a factor of ~2 at 100 MeV during this cycle. A composition is presented of VLIS for protons, deuteron, helium isotopes, electrons, and particularly for positrons and anti-protons. Gaining knowledge of their respective 11 and 22 year modulation is useful to interpret observations of low-energy anti-nuclei at the Earth as tests of dark matter annihilation.