Local Spectrum Research Articles

Regulation of external electric field on sensitivity of ICM energetic materials.

[2,2'-Bi(1,3,4-oxadiazole)]-5,5'-dinitramide (ICM-101), 2,4,6-triamino-5-nitropyrimidine-1,3-dioxide (ICM-102), and 6-nitro-7-azido-pyrazol[3,4-d][1,2,3]triazine-2-oxide (ICM-103) are excellent China-made explosives, but their performance under external electric fields (EEF) has never been explored, especially sensitivity. To study the induction effect of EEF on it, the chemical reactivity, electron localization function (ELF), spectrum, and other parameters were calculated by density functional theory. The results show that the increasing EEF can weaken the △EHOMO-LUMO (△EHOMO-LUMO = EHOMO-ELUMO) materials, making the stability worse and the sensitivity higher. The proportion of the positive electrostatic surface potential area is also smaller under the increasing EEF, indicating that ICM molecules are becoming more and more unstable. The ELF and localized orbital locator (LOL) decrease with the increase of EEF strength, which suggests that the trigger bond length increases, the EBDE decreases, and the molecular sensitivity increases. When the intensity of EEF increases, the absorption peak of the molecular spectrum gradually redshifts, and even a weak new absorption peak appears, indicating that the color of the material may change. Finally, EEF strength affects electron density, nitro charge, and chemical reactivity parameters. Gaussian 16 software was used for calculation. The calculation levels are B3LYP/6-311G+ (d, p) and B3LYP/Def2-TZVPP. The optimized structure has a local true minimum energy on the potential energy surface and no imaginary frequency. Multiwfn 3.8 and VMD 1.9.3 were used in this work to analyze the ICM series of energetic material wave functions. The strength range of EEF is 0.000-0.016 a.u., and the increasing gradient is 0.002 a.u.

Time-resolved photoemission and resonant inelastic x-ray scattering study of a site-selective Mott insulator

Inspired by the physics of rare earth nickelates, we study the photoemission (PES) and resonant inelastic X-ray scattering (RIXS) spectra of a correlated electron system with two types of insulating sublattices. Sublattice A is characterized by a hybridization gap and a low-spin state, while sublattice B features a Mott gap and a local magnetic moment. We show how the coupling of these two qualitatively different insulating states affects the dynamics of photo-induced charge carriers and how the nonequilibrium states manifest themselves in the PES and RIXS signals. In particular, we find that charge carriers created on the B sublattice migrate to the A sublattice, where they contribute to the creation of in-gap states in the PES signal, and to characteristic peaks in the nonequilibrium RIXS spectrum. While the contributions from the two sublattices cannot be easily distinguished in the local photoemission spectrum, the weights of the RIXS signals in the two-dimensional $\omega_\text{in}$-$\omega_\text{out}$ space provide information on the local state evolution on both sublattices.

Time evolution of Majorana corner modes in a Floquet second-order topological superconductor

We propose a practically feasible time-periodic sinusoidal drive protocol in onsite mass term to generate the two-dimensional~(2D) Floquet second-order topological superconductor, hosting both the regular $0$- and anomalous $\pi$-Majorana corner modes~(MCMs) while starting from a static 2D topological insulator/$d$-wave superconductor heterostructure setup. We theoretically study the local density spectra and the time dynamics of MCMs in the presence of such drive. The dynamical MCMs are topologically characterized by employing the average quadrupolar motion. Furthermore, we employ the Floquet perturbation theory~(FPT) in the strong driving amplitude limit to provide analytical insight into the problem. We compare our exact (numerical), and the FPT results in terms of the eigenvalue spectra and the time dynamics of the MCMs. We emphasize that the agreement between the exact numerical and the FPT results are more prominent in the higher frequency regime for close to the $0$-quasi-energy mode.

Localized Surface Magnon Modes in Cubic Ferromagnetic Lattices

A theoretical formalism for calculating the bulk and surface spin modes in Heisenberg semi-infinite lattices is presented on a ferromagnetic cubic network of spins, coupled via nearest and next-nearest neighbors exchange interactions. The magnetic surface can be considered as semi-infinite slabs at the end of the bulk structures. The breakdown of translation symmetry, in the normal direction of the surface, gives rise to localized spin wave modes in its neighborhood. The localized magnon spectrum is derived as elements of a Landauer-type scattering matrix, in the three cubic lattices sc, bcc and fcc. The magnon properties are simulated and determined numerically for each cubic lattice by using the matching technique. The observed fluctuations in the numerical results demonstrate the interference magnon effects between scattered spinwaves and the localized magnon states, generated by the surface region with characteristic Fano resonances. In cubic leads, the localized surface spin states are sensitive to the local magnetic coupling and the incident direction in the surface boundary. In this contribution, the normalized energy of spinwaves arising from the absence of translation symmetry is analyzed for each cubic system as a function of the exchange integral parameters. This addresses the dependence of the surface magnon on the different possibilities of the of the exchange parameters variation from softening to hardening in the neighborhood of the surface region.

Effect of spectrum measurement position on detection of Klason lignin content of snow pears by a portable NIR spectrometer

AbstractSnow pears are an important and widespread agricultural product that can relieve respiratory symptoms, constipation, and alcoholism. Lignin content (LC) has a direct and negative role on the fruit texture and taste of snow pears. Here, we studied the effect on the near‐infrared (NIR) spectroscopy determination of the LC in snow pears due to the position at which spectral measurements were obtained. NIR diffuse reflection spectra were collected from nine measurement positions on each sample by a portable NIR spectrometer. Partial least squares regression (PLSR) was used to develop spectrum compensation models of the LC for three local spectrum models, an average spectrum model, and a global spectrum model. The results indicated that the prediction accuracy of the LC was affected by the spectral measurement position. Compared with the local spectrum models and the global spectrum model, the average spectrum model had good prediction results. Next, synergy interval partial least squares, bootstrapping soft shrinkage, competitive adaptive reweighted sampling, genetic algorithm, and an improved variable stability and frequency analysis algorithm (VSFAA) method were used to select the most effective variables to build the PLSR model. The average spectrum calibration model established using the 10 effective variables selected by VSFAA reduced the influence of the variation of the spectral measurement position for LC prediction and achieved more promising results, with the correlation coefficient of calibration and prediction of 0.842 and 0.824, respectively. The root mean square error of cross‐validation and prediction were 0.736 and 0.694, respectively. The overall results showed that the average spectrum model based on the nine spectral measurement positions reduced the sensitivity to the variation of spectral measurement position for predicting the LC and combined the VSFAA variable selection algorithm to improve the accuracy and provide a robust model for prediction of LC in snow pears. Compared with the local spectrum position models and the global spectrum position model, the average spectrum position model combining the nine measurement positions (three stem‐calyx longitudes intersected three latitudes (stem, equator, calyx)) produced good prediction results and reduced the sensitivity to the variation of the spectral measurement position. The effective wavelengths (SNV‐VSFAA‐PLSR)‐average spectrum position model achieved good results, reducing the influence of the variation of the spectral measurement position for LC prediction, and the effective wavelengths selected from the average spectrum position model were helpful for offsetting the influence of the variation of spectral measurement position on the PLSR models based on the spectrum from the equatorial positions alone.

RETRACTED ARTICLE: Maps preserving peripheral local spectrum of skew Jordan product of operators

RETRACTED ARTICLE: Maps preserving peripheral local spectrum of skew Jordan product of operators

Weighted Diffraction-Based Migration Velocity Analysis of Common-Offset GPR Reflection Data

Migration focusing analysis of diffractions is an increasingly important tool for estimating the large-scale subsurface velocity structure from surface-based common-offset ground-penetrating radar (GPR) reflection data. We present a weighting strategy, whose aim is to improve the reliability of estimations of the root-mean-square (rms) velocity obtained using a local semblance focusing measure. In this regard, we increase the resolution of the inferred semblance spectra through a weighting function that varies in accordance with the sensitivity of a diffraction curve to changes in velocity. The weighting function is derived from coherency and slope attributes of the diffracted wavefield components. To demonstrate the viability of our proposed method, we consider its application in two synthetic test cases and one field GPR dataset. Compared with conventional unweighted local semblance spectra, their weighted counterparts allow for a significantly increased resolution and correspondingly reduced picking uncertainty.

Association between brain N-acetylaspartate levels and sensory and motor dysfunction in patients who have spinal cord injury with spasticity: an observational case-control study.

Spinal cord injury is a severe and devastating disease, and spasticity is a common and severe complication that is notoriously refractory to treatment. However, the pathophysiological mechanisms underlying spasticity and its development remain largely unknown. The goal of the present study was to find differences, if any, in metabolites of the left precentral gyrus and basal ganglia of patients who have spinal cord injury with or without spasticity, and to explore the relationship between the brain metabolite concentrations and clinical status. Thirty-six participants were recruited for magnetic resonance spectroscopic examination: 23 with spinal cord injury (12 with spasticity and 11 without spasticity) and 13 healthy controls. We acquired localized proton spectra from the precentral gyrus and basal ganglia via 10 mm3 voxels. Notably, univariate linear regression analysis demonstrated that the lower that the N-acetylaspartate concentration (a marker for neuronal loss) was in the precentral gyrus of the patients, the lower their ASIA (American Spinal Injury Association) light-touch scores, pinprick scores, and motor scores. Additionally, longer durations of injury were associated with higher N-acetylaspartate levels in the precentral gyrus. Compared with the healthy participants and patients without spasticity, N-acetylaspartate levels in the patients with spasticity were significantly lower in both the precentral gyrus and basal ganglia. Lower N-acetylaspartate levels also correlated with greater sensory and motor dysfunction in the patients who had spinal cord injury with spasticity.

The transition from Galactic to extragalactic cosmic rays: The high–energy end of the Galactic spectrum

Understanding the transition from Galactic to extragalactic cosmic rays (CRs) is essential to make sense of the Local cosmic ray spectrum. Several models have been proposed to account for this transition in the 0.1 - 10 × 1018 eV range. For instance: ankle models, where the change from a steep Galactic component to a hard extragalactic spectrum occurs in the 4 − 10 × 1018 eV region, dip models, where the interactions of CR protons with the CMB producing electron-positron pairs shape the ankle, or mixed composition models, in which extragalactic CRs are composed of nuclei of various types. In all these scenarios, the low-energy part of the transition involves the high-energy part of the Galactic component. Therefore, any information on the Galactic component, such as maximum energy, chemical composition, and spectrum after propagation, is crucial to understanding the Galactic-extragalactic transition. We briefly review the high-energy part of the CR spectrum expected from the best potential sources of Galactic CRs.

On Velocity Spectra within the Wake behind a Circular Cylinder

The canonical case of a circular cylinder in crossflow is studied experimentally at Reynolds number 5k. The power-spectra of all velocity components in the turbulent wake are studied in detail. Special attention is paid to the appearance of peaks and spectra shape, i.e., to the slope of spectra parts. Signatures of presence forward energy cascade and inverse enstrophy cascade are detected. Three peaks corresponding to 1st, 2nd and 3rd harmonics of the Strouhal frequency are detected as well as local spectra slopes conforming to the Kolmogorov and Kraichnan theories.

Infections in Critically Ill Children.

Health care-associated infections (HAI) directly influence the survival of children in pediatric intensive care units (PICU), the most common being central line-associated bloodstream infection (CLABSI) 25-30%, followed by ventilator-associated pneumonia (VAP) 20-25%, and others such as catheter-associated urinary tract infection (CAUTI) 15%, surgical site infection (SSI)11%. HAIs complicate the course of the disease, especially the critical one, thereby increasing the mortality, morbidity, length of hospital stay, and cost. The incidence of HAI in Western countries is 6.1-15.1% and in India, it is 10.5 to 19.5%. The advances in healthcare practices have reduced the incidence of HAIs in the recent years which is possible due to strict asepsis, hand hygiene practices, surveillance of infections, antibiotic stewardship, and adherence to bundled care. The burden of drug resistance and emerging infections are increasing with limited antibiotics in hand, is still a dreadful threat. The most common manifestation of HAIs is fever in PICU, hence the appropriate targeted search to identify the cause of fever should be done. Proper isolation practices, judicious handling of devices, regular microbiologic audit, local spectrum of organisms, identification of barriers in compliance of hand hygiene practices, appropriate education and training, all put together in an efficient and sustained system improves patient outcome.

Experimental SDR implementation of cooperative spectrum sensing in cognitive radio networks

In this paper, a Software Defined Radio (SDR) implementation of Cooperative Spectrum Sensing (CSS) is investigated. More precisely, various local spectrum sensing algorithms have been implemented and validated on USRP B210 using the Qt framework. The realized test bed is based on a client-server architecture. In the client interface, different spectrum sensing techniques have been implemented and analyzed. The fusion center interface implements all hard decision combination schemes, namely OR, AND, and the MAJORITY rule. Finally, several realistic scenarios have been considered to validate our SDR implementation. Moreover, these implementations allowed us to assess the efficiency of different hard-decision combination schemes for cooperative detection in the context of cognitive radio. Besides, the performance improvement is analytically evaluated and corroborated by the experimental results. These results regarding real scenarios confirm that Goodness of Fit-based (GoF) sensing methods outperform conventional methods. Furthermore, theoretical and simulation results from CSS have been validated experimentally that OR-rule gives clearly better results than other hard decisions combinations schemes.

Multiscale spectral modelling for nonstationary time series within an ordered multiple-trial experiment

Within the neurosciences it is natural to observe variability across time in the dynamics of an underlying brain process. Wavelets are essential in analysing brain signals because, even within a single trial, brain signals exhibit nonstationary behaviour. However, neurological signals generated within an experiment may also potentially exhibit evolution across trials (replicates), even for identical stimuli. As neurologists consider localised spectra of brain signals to be most informative, we propose the MULtiple-Trials Locally Stationary Wavelet process (MULT-LSW) that fills the gap in the literature by directly giving a stochastic wavelet representation of the time series of ordered replicates itself. MULT-LSW yields a natural desired time- and trial-localisation of the process dynamics, capturing nonstationary behaviour both within and across trials. While current techniques are restricted by the assumption of uncorrelated replicates, here we account for between-trial correlation. We rigorously develop the associated wavelet spectral estimation framework along with its asymptotic properties. By means of thorough simulation studies, we demonstrate the theoretical estimator properties hold in practice. A real data investigation into the evolutionary dynamics of the hippocampus and nucleus accumbens, during an associative learning experiment, demonstrates the applicability of our proposed methodology as well as the new insights it provides. Our model is general and facilitates wider experimental data analysis than the current literature allows.

A parametric study of nose landing gear noise in a large-scale aeroacoustic wind tunnel

The nose landing gear (NLG) of an aircraft considerably contributes to the undercarriage noise. In this paper, a large-scale testing program was conducted within the FL-17 5.5 m×4 m aeroacoustic wind tunnel in CARDC to characterize the effects from various parameters on the acoustic performance of a generic NLG model. Those investigated parameters include incoming flow velocity, wheel size, height, angle of attack and yaw angles. The test was majorly comprised of noise source localization and free-field sound pressure level spectra analysis. Two categories of tonal noise were distinguished depending on variation between frequency and incoming flow speed. Effects of the sideline directivity were analyzed, and it was found that the side distribution of OASPL shows a saddle-like trend with the flow/flight direction and the tonal noise changes significantly with directivity angle. Regarding spectral scaling, U∞7 was found to be more appropriate for a large-scale NLG model, while for a compact small-scale NLG model, the traditional U∞6 is still recommended. As to transitional size, a combination of U∞7 and U∞6 showed to be more suitable for scaling within the high and low frequency ranges respectively. Contributions of different elements to NLG noise to different noise sources were discussed, which were found not to be dependent on their relative sizes. Analysis of the wheel diameter showed it does not cause obvious changes to the overall spectra trend but can induce variation of the amplitude and frequency tones. When the wheel is sufficiently small, the upper head of the sliding piston can be directly exposed to the incoming flow and thus generate sharp tonal noise. In terms of NLG height, the main effects on the acoustic performance was found to be associated not with the change in the height itself, but rather with the accompanying changes from other elements. Finally, the effects of angle of attack (α) and yaw angle (β) were analyzed with results showing that the angle of attack could potentially lead to substantial changes in the acoustic performance, while the yaw angle within 0°-8° has minimal effects.

Seismic multi-attribute approach using visual saliency for subtle fault visualization

This study improves a collection of attributes to detect subtle faults in three dimensional data obtained from the Krishna-Godavari (KG) basin, with results displayed on synthetic and real datasets. Seismic attributes, for instance, curvature and coherence, are often used to delineate discontinuities, such as faults and fractures where hydrocarbons may have been trapped. These attributes have their advantages subjective to the seismic data. In this paper, we propose a multi-attribute framework for identifying subtle faults inside seismic volumes. Curvature attribute is a powerful and popular technique to deal with these faults. The faulted horizon is fitted on the quadratic surface using the least-square method, and the most positive and most-negative curvature attributes are calculated, which are further used in saliency map calculations. Several signal processing techniques, such as Hough transform and ant tracking, have been used to delineate faults. Here, we have proposed a novel signal processing approach based on energy variations known as top-down saliency on the curvature attributes using 3D-FFT local spectra and multi-dimensional plane projections. To analyze the directional nature of seismic data, the directional center-surround technique is employed for visual attention. Furthermore, the log-Gabor filter and image erosion are applied to the saliency-rendered seismic volume to highlight the oriented amplitude discontinuities at faults. Most of the time, these discontinuities may not be very prominent to find the subtle faults and other trace-to-trace hidden geological features in three-dimensional seismic data. In our work, calculated attributes assist us in mapping these changes, because they are all differently sensitive to the faults and fractures in unique ways. Experimental results on real field seismic data from the Krishna-Godavari basin prove that the proposed algorithm is effective and efficient in tracking subtle and minor faults, better than previous works.

Diffuse supernova neutrino background as a probe of late-time neutrino mass generation

The relic neutrinos from old supernova explosions are among the most ancient neutrino fluxes within experimental reach. Thus, the diffuse supernova neutrino background (DSNB) could teach us if neutrino masses were different in the past (redshifts $z\ensuremath{\lesssim}5$). Oscillations inside the supernova depend strongly on the neutrino mass-squared differences and the values of the mixing angles, rendering the DSNB energy spectrum sensitive to variations of these parameters. Considering a purely phenomenological parametrization of the neutrino masses as a function of redshift, we compute the expected local DSNB spectrum here on Earth. Given the current knowledge of neutrino oscillation parameters, especially the fact that $|{U}_{e3}{|}^{2}$ is small, we find that the ${\ensuremath{\nu}}_{e}$ spectrum could be significantly different from standard expectations if neutrinos were effectively massless at $z\ensuremath{\gtrsim}1$ as long as the neutrino mass ordering is normal. On the other hand, the ${\overline{\ensuremath{\nu}}}_{e}$ flux is not expected to be significantly impacted. Hence, a measurement of both the neutrino and antineutrino components of the DSNB should allow one to test the possibility of recent neutrino mass generation.

Mm-DSF: A Method for Identifying Dangerous Driving Behaviors Based on the Lateral Fusion of Micro-Doppler Features Combined.

To address the dangerous driving behaviors prevalent among current car drivers, it is necessary to provide real-time, accurate warning and correction of driver's driving behaviors in a small, movable, and enclosed space. In this paper, we propose a method for detecting dangerous behaviors based on frequency-modulated continuous-wave radar (mm-DSF). The highly packaged millimeter-wave radar chip has good in-vehicle emotion recognition capability. The acquired millimeter-wave differential frequency signal is Fourier-transformed to obtain the intermediate frequency signal. The physiological decomposition of the local micro-Doppler feature spectrum of the target action is then used as the eigenvalue. Matrix signal intensity and clutter filtering are performed by analyzing the signal echo model of the input channel. The signal classification is based on the estimation and variety of the feature vectors of the target key actions using a modified and optimized level fusion method of the SlowFast dual-channel network. Nine typical risky driving behaviors were set up by the Dula Hazard Questionnaire and TEIQue-SF, and the accuracy of the classification results of the self-built dataset was analyzed to verify the high robustness of the method. The recognition accuracy of this method increased by 1.97% compared with the traditional method.

Probing Local Emission Properties in InGaN/GaN Quantum Wells by Scanning Tunneling Luminescence Microscopy

Scanning tunneling electroluminescence (STL) microscopy is performed on a 3 nm‐thick InGaN/GaN quantum well (QW) with [In] = 0.23 such that the main light emission occurs in the green. The technique is used to map the radiative recombination properties at a scale of a few nanometers and correlate the local electroluminescence map with the surface topography simultaneously imaged by scanning tunneling microscopy. While the expected green emission is observed all over the sample, measurements performed on a 500 nm × 500 nm area around a 150 nm‐large and 2.5 nm‐deep hexagonal defect reveal intense emission peaks at higher energies close to the defect edges, features which are not visible in the macrophotoluminescence spectrum of the sample. Via a fitting of the local tunneling electroluminescence spectra, quantitative information on the fluctuations of the intensity, peak energy, width, and phonon replica intensity of the different spectral contributions is obtained, which provides information on carrier localization in the QW. This procedure also indicates that the carrier diffusion length on the probed area of the QW is shorter than 50 nm.

Distributed pH sensing based on hydrogel coated single mode fibers and optical frequency domain reflectometry.

We propose a distributed pH sensor based on an optical frequency domain reflectometry using a PEGDA-based pH-sensitive hydrogel coated on a single mode fiber. The volume of hydrogel increased as pH value of the surrounding fluid decreased, which converts the pH value to the axial strain in the fiber. Taking capacity of distributed strain measurement with high spatial resolution in optical frequency domain reflectometry, the pH value of the external medium is distributed measured by the wavelength shifts of the local Rayleigh backscattering spectra. The basic hydrogel with different molecular weight was optimized to balance the sensitivity, the response time and also the stability. In the experiment, the range of the pH value from 2 to 6 was measured with a sampling resolution of 1.7 mm, a sensitivity of -199 pm/pH and a response time of 14 min when the hydrogel coating diameter is 2 mm. Such a distributed pH sensing system has a potential to detect and locate some chemical or biological substances in a large-scale environment.

Nonlinear simulation of wave group attenuation due to scattering in broken floe fields

Direct phase-resolved simulations are performed to investigate the propagation and scattering of nonlinear ocean waves in fragmented sea ice. The numerical model solves the full time-dependent equations for nonlinear potential flow coupled with a nonlinear thin-plate representation of the ice cover, and it neglects dissipative processes. The two-dimensional setting with incident wave groups on deep water is considered, in view of applications to wave attenuation along transects of the marginal ice zone. A spatially-varying weight is assigned to the surface pressure so that irregular distributions of ice floes can be directly specified in the physical domain. For various wave regimes and floe configurations, a local wave spectrum across the ice field is computed and then least-squares fitted to extract a spatial attenuation rate as a function of wave frequency. A general increase with frequency is found, consistent with typical predictions from linear theory. However, a non-monotonic behavior around a certain frequency is also observed, especially in cases with a highly fragmented ice cover. The key role played by nonlinear interactions in this phenomenon is highlighted.