Set Of Spectral Parameters Research Articles

Spectral Analysis of Mare Ingenii Basin (Lunar Farside)

AbstractMare Ingenii is a site of great interest for lunar geology as it is one of the few basaltic plains on the farside of the Moon. It is located within the outer edge of the South Pole‐Aitken basin, the largest and oldest impact basin in our Solar System. Mare Ingenii includes two large craters, Thomson and Thomson M, and a prominent swirl, a high‐albedo sinuous feature whose origin is still debated. We conducted spectral analysis on 28 selected regions of interest within Mare Ingenii, with the aim of inferring its mineralogy. We considered reflectance data acquired in the visible to near‐infrared spectral range by the Moon Mineralogy Mapper (M3) imaging spectrometer onboard the Chandrayaan‐1 mission, to derive a set of spectral parameters. Our results show wide compositional variability, with the dark material of the mare basaltic floor showing the centers of the Fe2+ absorption bands of the pyroxenes shifted toward long wavelengths (0.96–0.99 and 2.03–2.12 μm, respectively), consistent with the spectral characteristics of high‐Ca pyroxenes (as well as swirl material and intermediate albedo regions). In contrast, the bright material of the small surrounding craters shows Fe2+ absorption bands shifted toward short wavelengths (0.91–0.94 and 1.91–2.04 μm, respectively), more consistent with low‐Ca or Ca‐free pyroxenes. The obtained results suggest a mafic signature throughout the surface of Mare Ingenii, probably representative of the composition of the lower lunar crust.

Prediction of the distribution of soil properties in deep Colluvisols in different pedogeographic regions (Czech Republic) using diffuse reflectance infrared spectroscopy

Colluvisols form a significant part of the erosion–deposition soil catena mainly in undulating, agriculturally managed landscapes. Due to their sedimentary origin, they are soils with highly variable properties. For such diverse and often extremely deep soils, it is essential to capture the vertical distribution of properties in as much detail as possible. This study demonstrates the potential of the diffuse reflectance infrared spectroscopy (DRIFT) to derive accurate information on the stratigraphy and selected soil properties (soil organic carbon and calcium carbonate contents and aluminium and iron concentrations) of deep colluvial profiles in three regions in the Czech Republic with different dominant soil types (Chernozem, Luvisol, and Cambisol). The normalization of the spectrum using the quartz spectral band was found to be suitable for assessing the carbonate content in Chernozems and Luvisols (coefficients of determination (R2) were 0.89 and 0.88, respectively). The amount of organic carbon can be predicted from such normalized spectra with less confidence (R2 = 0.64). Organic matter quality as an indicator of their stability and maturity was computed from aliphatic compounds spectral bands (2930 cm–1) and aromatics and CO groups band around 1640 cm–1. The highest values of this indicator were found in Colluvisols in the Chernozem region (> 6, while, e.g., in the Cambisol region it is < 1), especially in the layers corresponding to the oldest sediments or buried in-situ horizons. In the Cambisol region, the buried B horizon was identified based on normalized (i) clays and Fe oxides bands and (ii) wider band of OH groups, which in this case is related to the content of iron oxyhydroxides. The study proved that the applied set of spectral parameters is an effective tool for the description of diverse soil parameters and for identification of the boundaries of individual soil layers. It is equally suitable for carbonate-free soils as well as for soils with higher carbonate contents, which usually cause difficulties in the interpretation of soil organic matter spectral parameters. It provides a comprehensive view of the soil and its mineral and organic components and can provide information that is difficult to measure by other methods.

Construction of determinants for the six-vertex model with domain wall boundary conditions

We consider the problem of construction of determinant formulas for the partition function of the six-vertex model with domain wall boundary conditions that depend on two sets of spectral parameters. In the pioneering works of Korepin and Izergin a determinant formula was proposed and proved using a recursion relation. In later works, equivalent determinant formulas were given by Kostov for the rational case and by Foda and Wheeler for the trigonometric case. Here, we develop an approach in which the recursion relation is replaced by a system of algebraic equations with respect to one of the two sets of spectral parameters. We prove that this system has a unique solution. The result can be easily given as a determinant parametrized by an arbitrary basis of polynomials. In particular, the choice of the basis of Lagrange polynomials with respect to the remaining set of spectral parameters leads to the Izergin–Korepin representation, and the choice of the monomial basis leads to the Kostov and Foda–Wheeler representations.

On Features of the Solution of a Boundary-Value Problem for the Multidimensional Integro-Differential Benney–Luke Equation with Spectral Parameters

In this paper, we consider the problems on the solvability and constructing solutions of one nonlocal boundary-value problem for the multidimensional, fourth-order, integro-differential Benney–Luke equation with degenerate kernel and spectral parameters. For various values of spectral parameters, necessary and sufficient conditions of the existence of a solution are obtained. The Fourier series for solutions of the problem corresponding to various sets of spectral parameters are obtained. For regular values of spectral parameters, the absolute and uniform convergence of the series and the possibility of their termwise differentiation with respect to all variables are proved. The problem is also examined studied for cases of irregular values of spectral parameters.

Recognition of arable soils from photographs obtained as part of crowdsourcing technologies

The study focuses on the possibilities of using photographs obtained using crowdsourcing technologies for the operational inventory of arable soils. The object of the study is the spectral reflectance of the open surface of arable soils of the test plots, measured using a HandHeld-2 spectroradiometer operating in the range of 325–1 075 nm, and their image in photographs taken with conventional cameras. Test sites are located in the Tula, Moscow and Tver regions. The soils of the test plots are sod-podzolic, gray forest, and leached chernozems. Based on the analysis of photographs of the surface and information obtained using a spectroradiometer, a set of spectral parameters in the RGB, YMC and HSI color systems, as well as their ratios (45 parameters), was calculated. These parameters were used to separate the analyzed soil types using classification trees. The accuracy of classification based on the results of validation varies from 63–100%. At the same time, the parameters of the HSI and YMC color systems turned out to be more informative than the parameters of the RGB color system. The established classification rules can later be used to determine the classification position of soils from images collected using crowdsourcing technologies.

Testing emission models on the extreme blazar 2WHSP J073326.7+515354 detected at very high energies with the MAGIC telescopes

ABSTRACT Extreme high-energy-peaked BL Lac objects (EHBLs) are an emerging class of blazars. Their typical two-hump-structured spectral energy distribution (SED) peaks at higher energies with respect to conventional blazars. Multiwavelength (MWL) observations constrain their synchrotron peak in the medium to hard X-ray band. Their gamma-ray SED peaks above the GeV band, and in some objects it extends up to several TeV. Up to now, only a few EHBLs have been detected in the TeV gamma-ray range. In this paper, we report the detection of the EHBL 2WHSP J073326.7+515354, observed and detected during 2018 in TeV gamma rays with the MAGIC telescopes. The broad-band SED is studied within an MWL context, including an analysis of the Fermi-LAT data over 10 yr of observation and with simultaneous Swift-XRT, Swift-UVOT, and KVA data. Our analysis results in a set of spectral parameters that confirms the classification of the source as an EHBL. In order to investigate the physical nature of this extreme emission, different theoretical frameworks were tested to model the broad-band SED. The hard TeV spectrum of 2WHSP J073326.7+515354 sets the SED far from the energy equipartition regime in the standard one-zone leptonic scenario of blazar emission. Conversely, more complex models of the jet, represented by either a two-zone spine-layer model or a hadronic emission model, better represent the broad-band SED.

Renormalization of Lagrangian bias via spectral parameters

We extend the definition of Lagrangian local bias proposed by Matsubara (2008) to include curvature and higher-derivative bias operators. Evolution of initially biased tracers using perturbation theory (PT) generates multivariate bias parameters as soon as nonlinear fluctuations become important. We present a procedure that reparametrize a set of spectral parameters, the arguments of the Fourier transformed Lagrangian bias function, from which multivariate renormalized biases can be derived at any order in bias expansion and PT. We find our method simpler than previous renormalization schemes because it only relies on the definition of bias, fixed from the beginning, and in one equation relating renormalized and unrenormalized spectral parameters. We also show that our multivariate biases can be obtained within the peak background split framework, in that sense this work extends that of Schmidt, Jeong and Desjacques (2013); however, we restrict our method to Gaussian initial conditions. Non-linear evolution also leads to the appearance of products of correlators evaluated at the same point, commonly named contact terms, yielding divergent contributions to the power spectrum, in this work we present an explicit method to remove these divergences by introducing stochastic fields.

Spectral Characteristics of the Unitary Critical Almost-Mathieu Operator

We discuss spectral characteristics of a one-dimensional quantum walk whose coins are distributed quasi-periodically. The unitary update rule of this quantum walk shares many spectral characteristics with the critical Almost-Mathieu Operator; however, it possesses a feature not present in the Almost-Mathieu Operator, namely singularity of the associated cocycles (this feature is, however, present in the so-called Extended Harper's Model). We show that this operator has empty absolutely continuous spectrum and that the Lyapunov exponent vanishes on the spectrum; hence, this model exhibits Cantor spectrum of zero Lebesgue measure for all irrational frequencies and arbitrary phase, which in physics is known as Hofstadter's butterfly. In fact, we will show something stronger, namely, that all spectral parameters in the spectrum are of critical type, in the language of Avila's global theory of analytic quasiperiodic cocycles. We further prove that it has empty point spectrum for each irrational frequency and away from a frequency-dependent set of phases having Lebesgue measure zero. The key ingredients in our proofs are an adaptation of Avila's Global Theory to the present setting, self-duality via the Fourier transform, and a Johnson-type theorem for singular dynamically defined CMV matrices which characterizes their spectra as the set of spectral parameters at which the associated cocycles fail to admit a dominated splitting.

A Monte Carlo estimate for the fraction of thermal Comptonized photons that impinge back on the soft source in neutron star LMXBs

In earlier works, it was shown that the energy dependent soft time lags observed in kHz QPOs of neutron star low mass X-ray binaries (LMXBs) can be explained as being due to Comptonization lags provided a significant fraction ($\eta \sim 0.2$ - $0.8$) of the Comptonized photons impinge back into the soft photon source. Here we use a Monte Carlo scheme to verify if such a fraction is viable or not. In particular we consider three different Comptonizing medium geometries: (i) a spherical shell, (ii) a boundary layer like torus and (iii) a corona on top of an accretion disk. Two set of spectral parameters corresponding to the 'hot' and 'cold' seed photon models were explored. The general result of the study is that for a wide range of sizes, the fraction lies within $\eta \sim 0.3$ - $0.7$, and hence compatible with the range required to explain the soft time lags. Since there is a large uncertainty in the range, we cannot concretely rule out any of the geometries or spectral models, but the analysis suggests that a boundary layer type geometry with a 'cold' seed spectral model is favoured over an accretion corona model. Better quality data will allow one to constrain the geometry more rigorously. Our results emphasise that there is significant heating of the soft photon source by the Comptonized photons and hence this effect needs to be taken into account for any detailed study of these sources.

Spectral parameters for Dawn FC color data: Carbonaceous chondrites and aqueous alteration products as potential cerean analog materials

We identified a set of spectral parameters based on Dawn Framing Camera (FC) bandpasses, covering the wavelength range 0.4–1.0μm, for mineralogical mapping of potential chondritic material and aqueous alteration products on dwarf planet Ceres. Our parameters are inferred from laboratory spectra of well-described and clearly classified carbonaceous chondrites representative for a dark component. We additionally investigated the FC signatures of candidate bright materials including carbonates, sulfates and hydroxide (brucite), which can possibly be exposed on the cerean surface by impact craters or plume activity. Several materials mineralogically related to carbonaceous chondrites, including pure ferromagnesian phyllosilicates, and serpentinites were also investigated. We tested the potential of the derived FC parameters for distinguishing between different carbonaceous chondritic materials, and between other plausible cerean surface materials. We found that the major carbonaceous chondrite groups (CM, CO, CV, CK, and CR) are distinguishable using the FC filter ratios 0.56/0.44μm and 0.83/0.97μm. The absorption bands of Fe-bearing phyllosilicates at 0.7 and 0.9μm in terrestrial samples and CM carbonaceous chondrites can be detected by a combination of FC band parameters using the filters at 0.65, 0.75, 0.83, 0.92 and 0.97μm. This set of parameters serves as a basis to identify and distinguish different lithologies on the cerean surface by FC multispectral data.

The NMR and X-ray study of l-arginine derived Schiff bases and its cadmium complexes

The structure study of five Schiff bases derived from l-arginine (l-Arg) and 2-hydroxy carbonyl compounds were performed in both solution and solid state using NMR and X-ray methods. Both analytical methods applied to the solid state sample of two Schiff bases showed a significant difference in molecular structures of unsubstituted and 7-CH3 substituted compounds. This effect was explained as a steric interaction of methyl group. Additionally the structure of two Cd2+ complexes with some Schiff bases were determined by NMR methods in DMSO solution and in the solid state. On the base of heteronuclear NMR measurement (13C, 15N and 113Cd) it was possible to define the complexation site on nitrogen atom. The large set of spectral parameters: chemical shifts, homo- and heteronuclear coupling constants, were used in structure study.

Bright N-Soliton Solutions to the Vector Hirota Equation from Nonlinear Optics with Symbolic Computation

Under investigation in this paper is the vector Hirota (VH) equation which governs the simultaneous propagation of multiple interacting femtosecond pulses in a certain type of coupled optical waveguides. By the Nth iterated Darboux transformation starting from the zero potential, the VH equation is found to admit the bright N-soliton solutions in terms of the multi-component Wronskian. Asymptotic formulae of the bright N-soliton solutions are derived for any given set of spectral parameters, which allows us to directly analyze the collision dynamics of VH solitons. Via symbolic computation, some collision properties possessed by the two- and three-soliton solutions are revealed from four aspects: the asymptotic patterns of the colliding solitons, parametric conditions for the amplitude-preserving collisions, phase shifts induced by the vector-soliton collisions, and soliton state changes described by the generalized linear fractional transformations.

Use of Variable Time-Delay Sum-Frequency Generation for Improved Spectroscopic Analysis

The interpretation of vibrationally resonant sum-frequency generation (VR-SFG) spectra is often complicated by two factors: spectral congestion and the presence of a nonresonant signal. With broadband VR-SFG systems, the spectra are further distorted because of incomplete sampling, or apodization, of the resonant free induction decay (FID) in the time domain. An experimental method is presented that takes advantage of these time-domain effects to obtain more accurate parameters than can be achieved by fitting a single VR-SFG spectrum. VR-SFG spectra are acquired at multiple delay times of the visible pulse with full suppression of the nonresonant signal and then simultaneously fit to determine a single set of spectral parameters. The multiple, independent spectra serve to constrain the results of the fitting. This variable time-delay approach allows for improved determination of the parameters of the resonant spectrum, including the proper number of peaks in the spectrum, and is demonstrated for thin films of polystyrene and surface-bound octadecylsilane. An additional advantage of the technique is that it can be implemented with minimal modification to an operational broadband VR-SFG system.

Characterising spectral sea wave conditions with statistical clustering of actual spectra

The Clustering LARge Applications (CLARA) statistical sampling and clustering algorithm is used to classify sea wave spectra into groups with different spectral properties. The actual spectrum is used in the classification, not proxy sets of spectral parameters. The clustering needs no a priori information on spectral properties, statistical distributions, or number of modes in the spectra. Cluster membership can be viewed as being essentially determined by the geometrical or shape properties of spectra, and is uninfluenced by the numerical dominance of particular shapes if a sufficient number of clusters is requested. The CLARA algorithm also enables outlier detection. CLARA provides a spectrum from each grouping or cluster as a central tendency measure or medoid. This allows a collection of spectra to be reduced to a set of basis or representative spectra according to the different spectral shapes present. However, other statistical measures constructed from the clusters form more suitable basis spectra than medoids. The methods are illustrated with a one-year long waverider data set from a shallow water coastal site off northwest Australia. The site experiences spectral peaks in three frequency bands, seasonally changing conditions, and daily sea breezes.

New opportunities in acquisition and analysis of natural abundance complex solid-state 33S MAS NMR spectra: (CH3NH3)2WS4

Population transfer from the satellite transitions to the central transition in solid-state (33)S MAS NMR, employing WURST inversion pulses, has led to detection of the most complex (33)S MAS NMR spectrum observed so far. The spectrum is that of (CH(3)NH(3))(2)WS(4) and consists of three sets of overlapping resonances for the three non-equivalent S atoms, in accord with its crystal structure. It has been fully analyzed in terms of three sets of (33)S quadrupole coupling and anisotropic/isotropic chemical shift parameters along with their corresponding set of three Euler angles describing the relative orientation of the tensors for these two interactions. The three sets of spectral parameters have been assigned to the three different sulfur sites in (CH(3)NH(3))(2)WS(4) by relating the changes observed for the spectral parameters to the changes in crystal structures in a comparison with the corresponding data for the isostructural (NH(4))(2)WS(4) analog.

Efficient spectral measures for automatic speech recognition

It is well known that automatic speech recognition (ASR) requires good spectral analysis in order to have successful ASR accuracy. A wideband spectrogram seems to contain all the needed acoustic information to map any given speech signal into its corresponding sequence of phonemes. (For ASR, language models are often used to augment acoustics, but here we will limit ourselves to acoustic analysis.) Various methods beyond the basic Fourier transform have found success in ASR, e.g., linear predictive analysis, wavelets, and mel-frequency cepstra (MFCC). These have all been focussed on extracting an efficient set of spectral parameters to facilitate phonetic discrimination. Part of the difficulty is separating spectral envelope information from excitation parameters, as variations in pitch are largely viewed as orthogonal to phoneme recognition. Another complicating factor is that amplitude and frequency scales in speech production and perception are better modeled as nonlinear (unlike the linear, fixed-bandwidth approach of Fourier transforms). Modern ASR techniques are far from optimal, as the front-end data compression yielding MFCCs, for a basic 80-ms phoneme, typically has more than 100 parameters, to distinguish among approximately 32 phonemes (a 5-bit choice). We will investigate various ways to render ASR analysis more efficient. [Work supported by NSERC-Canada.]

Intrinsic Information Content of NMR Dipolar Couplings: A Conformational Investigation of 1,3‐Butadiene in a Nematic Phase

The conformational equilibrium of 1,3-butadiene in a condensed fluid phase is investigated by liquid-crystal NMR spectroscopy. The full set of D(HH) and D(CH) dipolar couplings is determined from the analysis of the (1)H spectra of the three 1,3-butadiene most-abundant isotopomers (i.e. the all (12)C and the two single-labeled (13)C isotopomers) for a total of 21 independent dipolar couplings. A very good starting set of spectral parameters for the analysis of the (1)H spectrum is determined in a semiautomated way by the analysis of the (N-1) (specifically, N=6, the number of 1/2 spin nuclei in the spin system) quantum refocused (5QR), and not (5Q), spectra. As an alternative approach, a Monte Carlo (MC) numerical simulation, capable of predicting the solute ordering, is tested to simulate the 5QR spectrum. The set of D(ij) couplings is very good, proving that the MC method can represent a novel, valid alternative to the existing spectral simplification procedures. The experimentally determined dipolar-coupling data set is fully compatible with the 1,3-butadiene conformational distribution reported in the literature for isolated molecules, indicating the presence of about 99 % of s-trans conformer. With regards to the remaining 1 %, in spite of the direct and very strong dependence of the observables on the molecular structure, it was not possible to discriminate between the planar s-cis and s-gauche forms, both of which produce a very good fit of the dipolar couplings. Vibrational corrections, up to the anharmonic term, were applied; the calculated geometrical parameters are in good- although not exact-agreement with those reported in the literature from experimental and theoretical investigations. This result can be considered as supporting the methodology used for obtaining the structure and conformational distribution of a flexible molecule in a liquid phase.

The performance of pixel window algorithms in the classification of habitats using VHSR imagery

This study investigates the potential of three advanced pixel window classification methods for habitat mapping, namely Kernel based spatial Re-Classification (KRC), Radial Basis Function (RBF) neural networks (NN) and Support Vector Machines (SVM). KRC classifier takes into account the spatial arrangement and frequency of spectral classes present within a predefined square kernel. On the other hand, RBF-NN and SVM classifiers use a set of spectral parameters (digital numbers of training pixels, mean values and standard deviations within a specified window kernel) as input information. The fuzzy means clustering algorithm is utilized for training the RBF networks. This method is based on a fuzzy partition of the input space and requires only a short amount of time to determine both the structure and the parameters of the RBF-NN classifier. The radial basis function is also adopted as the kernel function in the implementation of the SVM methodology. The test area of the present study is Lake Kerkini, a wetland ecosystem located in Macedonia (Northern Greece). The methods are applied to a very high spatial resolution multispectral satellite image acquired by IKONOS-2. The nomenclature used is EUNIS, a detailed hierarchical habitat classification scheme. Several classification experiments are carried out using the same training samples in order to study the behaviour of the three classifiers and perform meaningful comparisons. Overall, all three classifiers performed satisfactorily; however the SVM and RBF-NN classifiers consistently outperformed KRC, reaching overall accuracies of 72% and 69%, respectively.

Automated voice pattern filter

An automated voice pattern filtering method implemented in a system having a client side and a server side is disclosed. At the client side, a speech signal is transformed into a first set of spectral parameters which are encoded into a set of spectral shapes that are compared to a second set of spectral parameters corresponding to one or more keywords. From the comparison, the client side determines if the speech signal is acceptable. If so, spectral information indicating a difference in a voice pattern between the speech signal and the keyword(s) is encoded and utilized as a basis to generate a voice pattern filter.

Speech processing apparatus and method measuring signal to noise ratio and scaling speech and noise

A speech processing apparatus and method are provided for processing an input speech signal to compensate for the effects of noise in the input speech signal. The method and apparatus divide the input speech signal into a plurality of sequential time frames and a set of spectral parameters are extracted for each time frame, which parameters are representative of the input signal during the time frame. The system then processes the input speech by scaling the parameters for each frame in dependence upon a measure of the signal to noise ratio for the input frame. In this way, the effects of additive noise on the input signal can be reduced.