Spectral Order Research Articles

Spectral and Higher Order Statistical Characteristics of Expiratory Tracheal Breathing Sounds During Wakefulness and Sleep in People with Different Levels of Obstructive Sleep Apnea

We investigated plausible changes in spectral and higher order statistical properties of tracheal respiratory sounds from wakefulness to sleep in relation to obstructive sleep apnea (OSA). Data consisted of expiratory sounds of 30 participants suspected of OSA during wakefulness and sleep, both recorded in supine position. Participants were divided into two groups of mild and severe OSA (15 in each group) based on their apnea/hypopnea index (AHI) per hour. Three different frequency-based features of their power spectra in addition to Kurtosis and Katz fractal dimension (KFD) were estimated from each normalized expiratory sound; they were compared within and between the groups. During wakefulness, the sounds average power at low-frequency components in severe group was lesser than that of the mild group. However, during sleep, the average power of high-frequency components in severe subjects was more than that of the mild group. The kurtosis value of both mild and severe OSA groups increased significantly from wakefulness to sleep using both mouth and nasal breathing sounds during wakefulness. The KFD increased significantly from wakefulness to sleep for both mild and severe OSA group using only nasal breathing sounds during wakefulness. These changes are indicative that the upper airway of severe OSA show more compliance and thickness compare to that of the mild OSA during both wakefulness and sleep and represent an increased stiffness during sleep. This implies a regional narrowing which cause both more compliance and stiffness simultaneously in different regions of the upper airway.

Alignment of UAV-hyperspectral bands using keypoint descriptors in a spectrally complex environment

ABSTRACTNear earth imaging spectroscopy has gained popularity in the recent past due to its increasing capabilities to acquire data with unprecedented abundance of spatial resolution and spectral purity. Unmanned Aerial Vehicle (UAV) based portable hyperspectral sensors employing snapshot based scanning mechanisms further advances these capabilities with improved spatial co-registration of pixels. However, unavoidable motion of UAV pose challenges in spectral co-registration which is pronounced in spectrally complex environments of heterogeneous ecosystems. In this study, the different feature descriptor techniques such as Harris-Stephens Features (HSF), Min Eigen Features (MEF), Scale Invariant Feature Transformation (SIFT), Speeded-Up Robust Features (SURF), Binary Robust Invariant Scalable Keypoints (BRISK), and Features from Accelerated Segment Test (FAST) were evaluated to align hyperspectral bands in a spectrally complex environment. A band alignment workflow was devised and operated in different band-wise arrangements (spectral order and temporal order) of the acquired hypercube. The co-registration accuracy between the adjacent band pairs (reference-transformed) upon registration was estimated using Root-Mean-Square Error (RMSE) and Pearson’s Correlation Coefficient (PCC) based approaches. Furthermore, a standard transformation workflow was used to evaluate the efficiency of the different feature descriptor based band-to-band registration approaches.

Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

Listening effort (LE) induced by speech degradation reduces performance on concurrent cognitive tasks. However, a converse effect of extrinsic cognitive load on recognition of spoken words in sentences has not been shown. The aims of the present study were to (a) examine the impact of extrinsic cognitive load on spoken word recognition in a sentence recognition task and (b) determine whether cognitive load and/or LE needed to understand spectrally degraded speech would differentially affect word recognition in high- and low-predictability sentences. Downstream effects of speech degradation and sentence predictability on the cognitive load task were also examined. One hundred twenty young adults identified sentence-final spoken words in high- and low-predictability Speech Perception in Noise sentences. Cognitive load consisted of a preload of short (low-load) or long (high-load) sequences of digits, presented visually before each spoken sentence and reported either before or after identification of the sentence-final word. LE was varied by spectrally degrading sentences with four-, six-, or eight-channel noise vocoding. Level of spectral degradation and order of report (digits first or words first) were between-participants variables. Effects of cognitive load, sentence predictability, and speech degradation on accuracy of sentence-final word identification as well as recall of preload digit sequences were examined. In addition to anticipated main effects of sentence predictability and spectral degradation on word recognition, we found an effect of cognitive load, such that words were identified more accurately under low load than high load. However, load differentially affected word identification in high- and low-predictability sentences depending on the level of sentence degradation. Under severe spectral degradation (four-channel vocoding), the effect of cognitive load on word identification was present for high-predictability sentences but not for low-predictability sentences. Under mild spectral degradation (eight-channel vocoding), the effect of load was present for low-predictability sentences but not for high-predictability sentences. There were also reliable downstream effects of speech degradation and sentence predictability on recall of the preload digit sequences. Long digit sequences were more easily recalled following spoken sentences that were less spectrally degraded. When digits were reported after identification of sentence-final words, short digit sequences were recalled more accurately when the spoken sentences were predictable. Extrinsic cognitive load can impair recognition of spectrally degraded spoken words in a sentence recognition task. Cognitive load affected word identification in both high- and low-predictability sentences, suggesting that load may impact both context use and lower-level perceptual processes. Consistent with prior work, LE also had downstream effects on memory for visual digit sequences. Results support the proposal that extrinsic cognitive load and LE induced by signal degradation both draw on a central, limited pool of cognitive resources that is used to recognize spoken words in sentences under adverse listening conditions.

Spectral Order on a Synaptic Algebra

We define and study an alternative partial order, called the spectral order, on a synaptic algebra—a generalization of the self-adjoint part of a von Neumann algebra. We prove that if the synaptic algebra A is norm complete (a Banach synaptic algebra), then under the spectral order, A is Dedekind σ-complete lattice, and the corresponding effect algebra E is a σ-complete lattice. Moreover, E can be organized into a Brouwer-Zadeh algebra in both the usual (synaptic) and spectral ordering; and if A is Banach, then E is a Brouwer-Zadeh lattice in the spectral ordering. If A is of finite type, then De Morgan laws hold on E in both the synaptic and spectral ordering.

Using local correlation tracking to recover solar spectral information from a slitless spectrograph

The Multi-Order Solar EUV Spectrograph (MOSES) is a sounding rocket instrument that utilizes a concave spherical diffraction grating to form simultaneous images in the diffraction orders m=0, +1, and −1. MOSES is designed to capture high-resolution cotemporal spectral and spatial information of solar features over a large two-dimensional field of view. Our goal is to estimate the Doppler shift as a function of position for every MOSES exposure. Since the instrument is designed to operate without an entrance slit, this requires disentangling overlapping spectral and spatial information in the m=±1 images. Dispersion in these images leads to a field-dependent displacement that is proportional to Doppler shift. We identify these Doppler shift-induced displacements for the single bright emission line in the instrument passband by comparing images from each spectral order. We demonstrate the use of local correlation tracking as a means to quantify these differences between a pair of cotemporal image orders. The resulting vector displacement field is interpreted as a measurement of the Doppler shift. Since three image orders are available, we generate three Doppler maps from each exposure. These may be compared to produce an error estimate.

Two-dimensional correlation analysis of spectra collected without knowing sampling order

Two-dimensional correlation spectroscopy (2DCOS) without a priori knowledge of meaningful spectral sampling order is considered. Construction of synchronous 2D correlation spectrum does not require the knowledge of sampling order, and disrelation spectrum derived from synchronous spectrum possesses useful features similar to those of asynchronous spectrum. Disrelation analysis may provide enhanced spectral resolution and distinction of bands arising from different sources but not the sequential order of intensity variations. Dataset sampled in an arbitrary or scrambled order may be reassembled into a more structured form by rank ordering the spectra with the intensity of a select band. If there is no meaningful data structure, asynchronous 2D correlation should not be attempted, although synchronous and disrelation spectra may still be useful. The intrinsic ambiguity in the direction of sampling order may sometimes be resolved using additional physical information known about the sample system.

Performance analysis of fully explicit and fully implicit solvers within a spectral element shallow-water atmosphere model

Explicit Runge–Kutta methods and implicit multistep methods utilizing a Newton–Krylov nonlinear solver are evaluated for a range of configurations of the shallow-water dynamical core of the spectral element community atmosphere model to evaluate their computational performance. These configurations are designed to explore the attributes of each method under different but relevant model usage scenarios including varied spectral order within an element, static regional refinement, and scaling to the largest problem sizes. This analysis is performed within the shallow-water dynamical core option of a full climate model code base to enable a wealth of simulations for study, with the aim of informing solver development within the more complete hydrostatic dynamical core used for climate research. The limitations and benefits to using explicit versus implicit methods, with different parameters and settings, are discussed in light of the trade-offs with Message Passing Interface (MPI) communication and memory and their inherent efficiency bottlenecks. Given the performance behavior across the configurations analyzed here, the recommendation for future work using the implicit solvers is conditional based on scale separation and the stiffness of the problem. For the regionally refined configurations, the implicit method has about the same efficiency as the explicit method, without considering efficiency gains from a preconditioner. The potential for improvement using a preconditioner is greatest for higher spectral order configurations, where more work is shifted to the linear solver. Initial simulations with OpenACC directives to utilize a Graphics Processing Unit (GPU) when performing function evaluations show improvements locally, and that overall gains are possible with adjustments to data exchanges.

Fast phase retrieval in slightly off-axis digital holography

In this study, three efficient algorithms are proposed for fast phase retrieval in slightly off-axis digital holography using spectrum cropping, spatial multiplexing, and complex encoding. In the first algorithm, the real spectral order of the subtracted hologram is filtered and cropped, and the number of pixels is decreased in the subsequent retrieval operations. In the second algorithm, two sequential subtracted holograms are digitally phase shifted and spatial multiplexed into one synthetic hologram, and thus only one inverse Fourier transformation is then required. In the third algorithm, two sequential subtracted holograms are encoded separately into the real part and the imaginary part of a complex hologram. Two cross-correlations can be used to reconstruct the phase, thereby improving the utilization of the spectrum. The three new algorithms speed up our previously proposed retrieval method with the assistance of specimen-free holograms. Our experiments demonstrated the validity and improved time requirements of the proposed methods.

Auditory spectral versus spatial temporal order judgment: Threshold distribution analysis.

Some researchers suggested that one central mechanism is responsible for temporal order judgments (TOJ), within and across sensory channels. This suggestion is supported by findings of similar TOJ thresholds in same modality and cross-modality TOJ tasks. In the present study, we challenge this idea by analyzing and comparing the threshold distributions of the spectral and spatial TOJ tasks. In spectral TOJ, the tones differ in their frequency ("high" and "low") and are delivered either binaurally or monaurally. In spatial (or dichotic) TOJ, the two tones are identical but are presented asynchronously to the two ears and thus differ with respect to which ear received the first tone and which ear received the second tone ("left"/"left"). Although both tasks are regarded as measures of auditory temporal processing, a review of data published in the literature suggests that they trigger different patterns of response. The aim of the current study was to systematically examine spectral and spatial TOJ threshold distributions across a large number of studies. Data are based on 388 participants in 13 spectral TOJ experiments, and 222 participants in 9 spatial TOJ experiments. None of the spatial TOJ distributions deviated significantly from the Gaussian; while all of the spectral TOJ threshold distributions were skewed to the right, with more than half of the participants accurately judging temporal order at very short interstimulus intervals (ISI). The data do not support the hypothesis that 1 central mechanism is responsible for all temporal order judgments. We suggest that different perceptual strategies are employed when performing spectral TOJ than when performing spatial TOJ. We posit that the spectral TOJ paradigm may provide the opportunity for two-tone masking or temporal integration, which is sensitive to the order of the tones and thus provides perceptual cues that may be used to judge temporal order. This possibility should be considered when interpreting spectral TOJ data, especially in the context of comparing different populations. (PsycINFO Database Record

A General Approach to Testing Volatility Models in Time Series

Volatility models have been playing important roles in economics and finance. Using a generalized spectral second order derivative approach, we propose a new class of generally applicable omnibus tests for the adequacy of linear and nonlinear volatility models. Our tests have a convenient asymptotic null N(0,1) distribution, and can detect a wide range of misspecifications for volatility dynamics, including both neglected linear and nonlinear volatility dynamics. Distinct from the existing diagnostic tests for volatility models, our tests are robust to time-varying higher order moments of unknown form (e.g., time-varying skewness and kurtosis). They check a large number of lags and are therefore expected to be powerful against neglected volatility dynamics that occurs at higher order lags or display long memory properties. Despite using a large number of lags, our tests do not suffer much from the loss of a large number of degrees of freedom, because our approach naturally discounts higher order lags, which is consistent with the stylized fact that economic or financial markets are affected more by the recent past events than by the remote past events. No specific estimation method is required, and parameter estimation uncertainty has no impact on the convenient limit N(0,1) distribution of the test statistics. Moreover, there is no need to formulate an alternative volatility model, and only estimated standardized residuals are needed to implement our tests. We do not have to calculate tedious and model-specific score functions or derivatives of volatility models with respect to estimated parameters, which are required in some existing popular diagnostic tests for volatility models. We examine the finite sample performance of the proposed tests. It is documented that the new tests are rather powerful in detecting neglected nonlinear volatility dynamics which the existing tests can easily miss. They are useful diagnostic tools for practitioners when modelling volatility dynamics.

Quantum Spectral Symmetries

Quantum symmetries of spectral lattices are studied. Basic properties of spectral order on A W ∗-algebras are summarized. Connection between projection and spectral automorphisms is clarified by showing that, under mild conditions, any spectral automorphism is a composition of function calculus and Jordan ∗-automorphism. Complete description of quantum spectral symmetries on Type I and Type II A W ∗-factors are completely described.

Conservative and nondispersive schemes for diffusion terms with strong property variations

ABSTRACTThe spatial discretization of diffusion terms leads to a theoretical order loss, specially in the presence of strong property and variable gradients. New conservative and nondispersive numerical schemes are proposed to circumvent this issue. Their spectral resolution, numerical order, and cost are evaluated and compared to traditional finite volume and difference schemes. Cost is measured through the computer time and memory it takes these schemes to reach a user-prescribed error tolerance. A manufactured test case is constructed to evaluate these characteristics. Its analysis shows that the new schemes are more cost-effective than traditional schemes under the conditions analyzed.

Some results of mesh convergence estimation for the spectral element method of different orders in FIDESYS industrial package

The article describes the Mesh convergence estimation for the method of spectral elements of different orders in FIDESYS industrial package. Estimation is done using the automated testing system developed for FIDESYS package. The tasks with known exact solutions were used for estimation. By changing the spectral element order the exponential decrease computational errors is shown against the degree of approximating polynomials.

Comparison of various methods of nonlinear signatures extraction

Nonlinear Acoustic NDE (NA NDE) methods are very sensitive to defect presence and currently number on publications on this matter exceed several thousand. Despite intensive research of NA NDE, these methods are still do not widely used in practice and the goal of this presentation is to give review of various methods of nonlinear signatures extraction and to show advantages on some of them in the comparison with the others. The major part of the NA NDE was applied for characterization the tested part as whole. These methods include: High Harmonic Generation, Nonlinear Resonant Ultrasound Spectroscopy (NRUS), Amplitude Dependent Internal Friction, Nonlinear Wave Modulation Spectroscopy (NWMS) or Vibro Acoustic Modulation (VAM), Slow Dynamics Diagnostics (SDD), Nonlinear Reverberation Spectroscopy (NRS) or Nonlinear Impact Resonance Acoustic Spectroscopy (NRAS), Nonlinear Coda Wave Interferometry, Bi Spectral and High Order Statistic Analysis, Subharmonic and Ultraharmonic Methods. The methods that can provide nonlinear imaging and damage localization include: Nonlinear Time Reversal Acoustics (NTRA) or TR NEWS, Nonlinear Harmonic Imaging, Nonlinear Acoustic Tomography, Pulse Modification of Vibro Acoustic Modulation (VAM), Nonlinear Guided Wave Imaging and Tomography, Subharmonic and Ultraharmonic imaging, Nonlinear Structural Intensity.

Olson Order of Quantum Observables

Using ideas of Olson \cite{Ols} who showed that the system of effect operators of a Hilbert space can be ordered by the so-called spectral order such that the system of effect operators is a complete lattice. Using his ideas, we introduce a partial order, called the Olson order, on the set of bounded observables of a complete lattice effect algebra. We show that the set of bounded observables is a Dedekind complete lattice.0

Spectral order on AW*-algebras and its preservers

We study the spectral order on the set of positive contractions in an AW*-algebra. We introduce the concept of lattice theoretic center of the resulting spectral lattice and show that it coincides with the algebraic center of the underlying AW*-algebra A if A is finite. By applying this result we generalize hitherto known characterizations of preserves of the spectral order by showing that any bijection φ acting on the spectral lattice of a finite AW*-algebra that preserves spectral order and orthogonality in both directions is a composition of function calculus and a Jordan *-isomorphism. We show that this result holds in a wide context of all AW*-algebras provided that φ preserves in addition the multiples of unity.

Two-dimensional analytical modeling of a linear variable filter for spectral order sorting.

A two-dimensional thin film thickness model based on the geometry of a commercial coater which can calculate more effectively the profiles of linear variable filters (LVFs) has been developed. This is done by isolating the substrate plane as an independent coordinate (local coordinate), while the rotation and translation matrices are used to establish the coordinate transformation and combine the characteristic vector with the step function to build a borderline which can conclude whether the local mask will block the deposition or not. The height of the local mask has been increased up to 40 mm in the proposed model, and two-dimensional simulations are developed to obtain a thin film profile deposition on the substrate inside the evaporation chamber to achieve the specific request of producing a LVF zone width in a more economical way than previously reported [Opt. Express23, 5102 (2015)OPEXFF1094-408710.1364/OE.23.005102].

Spectral and nonlinear optical studies of Propane-1, 3-diaminium nitrate

Propane-1, 3-diaminium nitrate [C3H12N2] (NO3)2 (PDAN), an hybrid organic–inorganic nonlinear optical material combining an acentric octupolar moiety (nitrate) with a centrosymmetric organic molecule (Propane-1, 3-diaminium) was prepared by slow evaporation technique at room temperature from its aqueous solution. Good quality and well-developed crystals of size 0.133mm×0.092mm×0.078mm were harvested from the mother solution. The grown single crystals were characterized for their spectral, thermal, linear and second order nonlinear optical properties. Solid-state 13C and 1H MAS-NMR spectroscopies are in agreement with the X-ray structure. The decomposition of the title compound is confirmed by the thermogravimetric analysis (TGA). The UV–visible absorption spectrum, show that PDAN is suitable for frequency doubling applications in a wide spectral range in the visible and near IR. The NLO response of the crystal was evaluated using a SHG powder technique, indicating an effective quadratic nonlinear coefficient two times higher than that of KDP in spite of the low hyperpolarizability of the nitrate ion and of the centrosymmetric character of the diaminium derivative.

Numerical investigations on mapping permeability heterogeneity in coal seam gas reservoirs using seismo-electric methods

Mapping the horizontal distribution of permeability is a key problem for the coal seam gas industry. Poststack seismic data with anisotropy attributes provide estimates for fracture density and orientation which are then interpreted in terms of permeability. This approach delivers an indirect measure of permeability and can fail if other sources of anisotropy (for instance stress) come into play. Seismo-electric methods, based on recording the electric signal from pore fluid movements stimulated through a seismic wave, measure permeability directly. In this paper we use numerical simulations to demonstrate that the seismo-electric method is potentially suitable to map the horizontal distribution of permeability changes across coal seams. We propose the use of an amplitude to offset (AVO) analysis of the electrical signal in combination with poststack seismic data collected during the exploration phase. Recording of electrical signals from a simple seismic source can be closer to production planning and operations. The numerical model is based on a sonic wave propagation model under the low frequency, saturated media assumption and uses a coupled high order spectral element and low order finite element solver. We investigate the impact of seam thickness, coal seam layering, layering in the overburden and horizontal heterogeneity of permeability.

Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil.