Full Spectrum Analysis Research Articles

Ex vivo cortical porosity and thickness predictions at the tibia using full-spectrum ultrasonic guided-wave analysis

SummaryThe estimation of cortical thickness (Ct.Th) and porosity (Ct.Po) at the tibia using axial transmission ultrasound was successfully validated ex vivo against site-matched micro-computed tomography. The assessment of cortical parameters based on full-spectrum guided-wave analysis might improve the prediction of bone fractures in a cost-effective and radiation-free manner.PurposeCortical thickness (Ct.Th) and porosity (Ct.Po) are key parameters for the identification of patients with fragile bones. The main objective of this ex vivo study was to validate the measurement of Ct.Po and Ct.Th at the tibia using a non-ionizing, low-cost, and portable 500-kHz ultrasound axial transmission system. Additional ultrasonic velocities and site-matched reference parameters were included in the study to broaden the analysis.MethodsGuided waves were successfully measured ex vivo in 17 human tibiae using a novel 500-kHz bi-directional axial transmission probe. Theoretical dispersion curves of a transverse isotropic free plate model with invariant matrix stiffness were fitted to the experimental dispersion curves in order to estimate Ct.Th and Ct.Po. In addition, the velocities of the first arriving signal (υFAS) and A0 mode (υA0) were measured. Reference Ct.Po, Ct.Th, and vBMD were obtained from site-matched micro-computed tomography. Scanning acoustic microscopy (SAM) provided the acoustic impedance of the axial cortical bone matrix.ResultsThe best predictions of Ct.Po (R2 = 0.83, RMSE = 2.2%) and Ct.Th (R2 = 0.92, RMSE = 0.2 mm, one outlier excluded) were obtained from the plate model. The second best predictors of Ct.Po and Ct.Th were vBMD (R2 = 0.77, RMSE = 2.6%) and υA0 (R2 = 0.28, RMSE = 0.67 mm), respectively.ConclusionsCt.Th and Ct.Po were accurately predicted at the human tibia ex vivo using a transverse isotropic free plate model with invariant matrix stiffness. The model-based predictions were not further enhanced when we accounted for variations in axial tissue stiffness as reflected by the acoustic impedance from SAM.

Measured and simulated spectra for a 22Na source in a well counter

This paper presents a test of a methodology to describe the shape of true and accidental coincidence gamma-ray spectra. The effect of the coincidence summing was enhanced by using a 50 kBq 22Na source in a NaI well counter. The spectra were described by convoluting Monte Carlo simulated spectra in a spreadsheet for true, as well accidental coincidence summing. In this paper we show that applying convolution techniques to the MCNP simulated probability spectra, not only allows a reconstruction of the shape of the true coincidence spectrum, but the simulations also prove to be an invaluable tool to understand the continuum in the spectra made up of double and even triple random coincidences. Each of these summing processes was used to generate so-called standard spectra that may be used in a full-spectrum analysis of the measured spectra to quantitatively derive the contributions of each of the summing processes. For the case presented it is shown that the accidental coincidences can be accounted for to a 0.1% level, a considerable improvement to the precision in previous papers.

Full angular spectrum analysis of tensor current contribution to $A_{cp}(\tau \rightarrow K_{s} \pi \nu_{\tau})$.

Babar collaboration has reported an intriguing opposite sign in the integrated decay rate asymmetry \(A_{cp}(\tau \rightarrow K_{s} \pi \nu_{\tau})\) than that of SM prediction from the known \(K^{0} - \bar{K^{0}}\) mixing. Babar's result deviate from the SM prediction by about 2.7\(\sigma\). If the result stands with higher precision in the future experiments, the observed sign anomaly in the \(A_{cp}(\tau \rightarrow K_{s} \pi \nu_{\tau})\) can most likely come only from a NP. In this work we present a full angular spectrum analysis on the contribution to \(A_{cp}(\tau \rightarrow K_{s} \pi \nu_{\tau})\) coming from the tensorial term. Assuming the real part of the NP tensorial coupling is negligible compare to its imaginary part and with \(A_{cp}(\tau \rightarrow K_{s} \pi \nu_{\tau})\) and \(Br(\tau \rightarrow K_{s} \pi \nu_{\tau})\) as data points to fit the imaginary part of the NP coupling, we have been able to fit the result within 1\(\sigma\) of the experimental values.

Full Band Spectra Analysis of Gait Acceleration Signals for Peripheral Arterial Disease Patients.

Peripheral arterial disease (PAD) is an artherosclerotic occlusive disorder of distal arteries, which can give rise to the intermittent claudication (IC) phenomenon, i.e., limb pain and necessity to stop. PAD patients with IC have altered their gait, increasing the fall risk. Several gait analysis works have studied acceleration signals (from sensors) to characterize the gait. One common technique is spectral analysis. However, this approach mainly uses dominant frequency (fd) to characterize gait patterns, and in a narrow spectral band, disregarding the full spectra information. We propose to use a full band spectral analysis (up to 15 Hz) and the fundamental frequency (f0) in order to completely characterize gait for both control subjects and PAD patients. Acceleration gait signals were recorded using an acquisition equipment consisting of four wireless sensor nodes located at ankle and hip height on both sides. Subjects had to walk, free-fashion, up to 10 min. The analysis of the periodicity of the gait acceleration signals, showed that f0 is statistically higher (p < 0.05) in control subjects (0.9743 ± 0.0716) than in PAD patients (0.8748 ± 0.0438). Moreover, the spectral envelope showed that, in controls, the power spectral density distribution is higher than in PAD patients, and that the power concentration is hither around the fd. In conclusion, full spectra analysis allowed to better characterize gait in PAD patients than classical spectral analysis. It allowed to better discriminate PAD patients and control subjects, and it also showed promising results to assess severity of PAD.

Integrated measurement of ultrasonic parameters for polymeric materials via full spectrum analysis

Ultrasound velocity and attenuation coefficient are important parameters for characterizing polymeric materials. How to accurately and conveniently measure ultrasonic parameters is always a significant topic. This paper presents a novel method for integrally measuring ultrasonic parameters via full spectrum analysis (UFSA). Reflected signals from the upper and lower surfaces of the polymeric materials are connected by a frequency dependent transfer function. The logarithm of the transfer function can be linearly fitted, and the ultrasonic parameters, including the ultrasound velocity and attenuation coefficient, can be calculated from the vertical intercept and slope of the fitting line. Experiments with various polymeric materials of different stiffnesses and dimensions, as well as several influence factors, were carried out to verify the proposed UFSA method. Compared to the conventional method, the proposed method does not need to measure the thickness of the polymeric material and makes full use of data in measured waves. Experimental results showed that the proposed method has high accuracy in measuring ultrasonic parameters and characterizing flexible materials. The proposed method would have broad applications in polymer testing.

Metamaterial Window Glass

A computational study of a metamaterial (MTM)-on-glass composite is presented for the purpose of increasing the energy efficiency of buildings in seasonal or cold climates. A full-spectrum analysis yields the ability to predict optical and thermal transmission properties from ultraviolet through far-infrared frequencies. An opportunity to increase efficiency beyond that of commercial low-emissivity glass is identified through a MTM implementation of Ag and dielectric thin-film structures. Three-dimensional finite difference time-domain (FDTD) simulations predict selective nonlinear absorption of near-infrared energy, providing the means to capture a substantial portion of solar energy during cold periods, while retaining high visible transmission and high reflectivity in far-infrared frequencies. The effect of various configuration parameters is quantified, with prediction of the net sustainability advantage. MTM window glass technology can be realized as a modification to commercial low-emissivity windows through the application of nanomanufactured films, creating the opportunity for both new and after-market sustainable construction.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24h and 48h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms.

Reconstructing the deposition environment and long-term fate of Chernobyl 137Cs at the floodplain scale through mobile gamma spectrometry

Cs-137 is considered to be the most significant anthropogenic contributor to human dose and presents a particularly difficult remediation challenge after a dispersal following nuclear incident. The Chernobyl Nuclear Power Plant meltdown in April 1986 represents the largest nuclear accident in history and released over 80 PBq of 137Cs into the environment. As a result, much of the land in close proximity to Chernobyl, which includes the Polessie State Radioecology Reserve in Belarus, remains highly contaminated with 137Cs to such an extent they remain uninhabitable. Whilst there is a broad scale understanding of the depositional patterns within and beyond the exclusion zone, detailed mapping of the distribution is often limited. New developments in mobile gamma spectrometry provide the opportunity to map the fallout of 137Cs and begin to reconstruct the depositional environment and the long-term behaviour of 137Cs in the environment. Here, full gamma spectrum analysis using algorithms based on the peak-valley ratio derived from Monte Carlo simulations are used to estimate the total 137Cs deposition and its depth distribution in the soil. The results revealed a pattern of 137Cs distribution consistent with the deposition occurring at a time of flooding, which is validated by review of satellite imagery acquired at similar times of the year. The results were also consistent with systematic burial of the fallout 137Cs by annual flooding events. These results were validated by sediment cores collected along a transect across the flood plain. The true merit of the approach was confirmed by exposing new insights into the spatial distribution and long term fate of 137Cs across the floodplain. Such systematic patterns of behaviour are likely to be fundamental to the understanding of the radioecological behaviour of 137Cs whilst also providing a tracer for quantifying the ecological controls on sediment movement and deposition at a landscape scale.

Noise reduction of PGNAA spectrum using empirical mode decomposition technique

Prompt gamma neutron activation analysis (PGNAA) is frequently used in on–line analysis of raw materials in cement and coal industries which normally incorporates bismuth germanate (BGO) or sodium iodide (NaI(Tl)) scintillators. The quantitative results are basically undertaken through full–spectrum analysis method which requires an efficient noise reduction procedure to optimize PGNAA data. Here in this study, the empirical mode decomposition (EMD) technique has been used to reduce the noise level of PGNAA spectra of a neutron–irradiated NaCl·H2O solution and then the results have been compared with those of wavelet technique. The mean square errors (MSEs) comparisons confirm that both EMD and wavelet techniques can be efficiently used for noise reduction purposes, however, this study recommends the EMD technique for its independency of basic functions, simplicity and spectrum data-based operation.

Discrimination of wood and charcoal from six Caatinga species by near-infrared spectroscopy

Correct identification of species in wood and charcoal commerce is important, and rapid and nondestructive evaluation based on near-infrared techniques can be a good alternative. Four trees from Combretum leprosum, Croton argyrophylloides, Jatropha mutabilis, Luetzelburgia auriculata, Mimosa tenuiflora and Poincianella bracteosa, were cut in a natural forest in the municipality of Coremas, Paraiba state and stem discs with thickness of about 80 mm were taken at 0, 25, 50, 75 and 100% of commercial height. For charcoal production, each sample was wrapped in aluminum foil and carbonized in a muffle furnace, with a final temperature of 450 °C and a heating rate of 1.66 °C min-1. Spectra were collected directly from sample surface. The best pretreatment was second derivative, while the best classification method was PCA-LDA, and the analysis of full spectra (4000-10000 cm-1) was indicated. In classification, there was no difference between surfaces where spectra was collected, so in practice, in commercial control for example, the information can be obtained from any surface. For rapid analysis for purposes of control of forest practices or illegal commerce, spectra collected directly from wood and charcoal can be applied to distinguish these six Caatinga species.

PCA based model on chlorophyll content diagnosis of winter wheat

The spectroscopy is one of the efficient methods used in crop monitor. In order to break through the limit of sensitive waveband instability at different growth stages, a full spectrum analysis method was applied in this study. Firstly, the winter wheat canopy reflectance were collected in the range of 325nm ~1075nm by ASD at the setting stage, jointing stage, booting stage and flowering stage respectively. And the corresponding chlorophyll contents were measured by spectrophotometric method. Secondly, the spectral data were pre-processed by wavelet de-noising and multiple scattering correction (MSC). Then, the principal component analysis (PCA) algorithm was used to reduce the dimension of spectra and the correlation coefficient analysis method was used to select the best principal component combinations at different growth stages. Finally, multiple regression models of chlorophyll content were established based on the selected principal component combinations at each growth stage. As a result, the decision coefficients (Rc2) for all the models were above 0.6, of which the maximum reached 0.8385 at the booting stage. The minimum of validation decision coefficient (Rv2) was only 0.4887 at the setting stage, while the maximum reached 0.9063 at the jointing stage. It could provide a technical support for the diagnosis of chlorophyll content during the winter wheat growth process.

Exploring the Metaphor of Information under the Context of Information Science Research: A Co-words Analysis

Present study intends to explore the various definitions of information via co-words analysis procedure based on the Natural Language Process (NLP). 3593 academic papers from an academic database, LISTA, are covered. In short, present study proposes four types of information definitions based on co-words for full spectrum analysis on abstracts of scientific papers under the context of Information Science research as: information as records, information as individual experience, information as the update of data or as the foundation of knowledge and information as ability of individuals.

Applying Full Spectrum Analysis to a Raman Spectroscopic Assessment of Fracture Toughness of Human Cortical Bone.

A decline in the inherent quality of bone tissue is a † Equal contributors contributor to the age-related increase in fracture risk. Although this is well-known, the important biochemical factors of bone quality have yet to be identified using Raman spectroscopy (RS), a nondestructive, inelastic light-scattering technique. To identify potential RS predictors of fracture risk, we applied principal component analysis (PCA) to 558 Raman spectra (370-1720 cm-1) of human cortical bone acquired from 62 female and male donors (nine spectra each) spanning adulthood (age range = 21-101 years). Spectra were analyzed prior to R-curve, nonlinear fracture mechanics that delineate crack initiation (Kinit) from crack growth toughness (Kgrow). The traditional ν1phosphate peak per amide I peak (mineral-to-matrix ratio) weakly correlated with Kinit (r = 0.341, p = 0.0067) and overall crack growth toughness (J-int: r = 0.331, p = 0.0086). Sub-peak ratios of the amide I band that are related to the secondary structure of type 1 collagen did not correlate with the fracture toughness properties. In the full spectrum analysis, one principal component (PC5) correlated with all of the mechanical properties (Kinit: r = - 0.467, Kgrow: r = - 0.375, and J-int: r = - 0.428; p < 0.0067). More importantly, when known predictors of fracture toughness, namely age and/or volumetric bone mineral density (vBMD), were included in general linear models as covariates, several PCs helped explain 45.0% (PC5) to 48.5% (PC7), 31.4% (PC6), and 25.8% (PC7) of the variance in Kinit, Kgrow, and J-int, respectively. Deriving spectral features from full spectrum analysis may improve the ability of RS, a clinically viable technology, to assess fracture risk.

Co-Electrolysis, Quo Vadis?

Co-electrolysis, the electrochemical conversion of steam and carbon dioxide with the use of renewably generated electricity to produce syngas, can be regarded as the enabling step to the sustainable production of synfuels and high-value chemicals. This advantageous method of beneficial CO2-valorization is predetermined to couple energy-intense sectors such as “traffic and transportation” and “chemical industry”. The needed products for these markets presuppose different syngas compositions through their production routes and according to that determine the applied technology of syngas generation by its achievable H2:CO ratio. The concept of high-temperature co-electrolysis offers both an efficient electrochemical conversion and accessibility to H2:CO distributions from 1:1 to 3:1 by a given set of parameters (temperature, current density, material,…). Though, this is yet to be shown as research has been focused on electrochemical analysis of materials, cells and stacks rather than on product distribution depending on operating parameters and an all-embracing quantitative product analysis[1]. Herein, we examine the possibilities and variety on syngas production with focus on (electrochemical) performance and syngas yield and composition under different conditions, e.g. temperature, current density, substrate composition. The experiments were executed on a cathode supported cell (CeramTec) composed of an LSCF anode, a CGO barrier-layer, an 8YSZ electrolyte and a Ni/8YSZ cathode. The testing took place in the temperature range of 750 to 900 °C with preset cell voltages up to 1.4 V. The ratios of water vapor to carbon dioxide have been set to 3:1, 2:1 and 1:1. Furthermore, the cells have been tested with a 50% water – 50% hydrogen mixture for comparison. I/V-measurements and electrochemical impedance spectroscopy have been conducted under the combinations of mentioned conditions. In addition, a full spectrum analysis of the product gases has been performed, i. e. water was not condensed from the product stream prior to the mass spectrometer. Current densities of up to over 1.7 A·cm-2 with polarization resistances of 24 mΩ·cm-2 have been obtained at 900 °C and a cell voltage of 1.4 V with a 9 nl·h-1 flow of 40% water, 40% CO2 and 20% H2 used. I/V-curves decrease in slope and increase in current density with increasing temperature (figure 1). Further investigation is ongoing and the electrochemical performance and efficiency of syngas production will be presented and discussed in detail. [1] S. Foit, I. C. Vinke, L. G. J. de Haart, R.-A. Eichel, Angewandte Chemie International Edition 2016, DOI: 10.1002/anie.201607552 Figure 1: I/V characteristics of a Ni/YSZ//YSZ//CGO//LSCF single cell during co-electrolysis of different H2/CO2 mixtures in dependence of temperature Figure 1

Practical Techniques for Enhancing the High-Frequency MASW Method

For soil exploration in the vadose zone, a high-frequency multi-channel analysis of surface waves (HF-MASW) method has been developed. In the study, several practical techniques were applied to enhance the overtone image of the HF-MASW method. They included (1) the self-adaptive MASW method using a variable sensor spacing configuration, (2) the phase-only MASW method, and (3) a nonlinear acoustic technique. To demonstrate the capability of these techniques, a HF-MASW test was conducted, which consisted of a small shaker operated in chirp mode with three gapped frequency bands and a geophone array with a variable spacing configuration. The overtone images obtained from (1) full spreadlength, (2) self-adaptive spreadlength, (3) full-spectra analysis including magnitude and phase spectra, and (4) phase-only spectrum analysis MASWs, respectively, were compared in each frequency bands. The results revealed the enhanced dispersive images by the HF-MASW using the self-adaptive and phase-only with the variable spacing configuration technique. The study also demonstrated the nonlinear acoustic technique by means of harmonic generation to increase the measurable frequency range of dispersion curves. It is worthy to mention that these techniques can also be applied to the conventional MASW method using controlled seismic vibrators, such as vibroseis.

Development of full spectrum analysis (FSA) to analyze the gamma backscattering on concrete

Full spectrum analysis, FSA, has been being widely used for the identification in environmental radioactive. In this work, firstly, FSA is developed to analyze the gamma backscattering spectrum on concrete to determine the component densities. The concrete samples are mixed of Portland cement, sand, gravel and water in the different proportions. The experiments are carried out by the radioactive source Cs137 (0.5mCi) and the detector NaI(Tl) 2 inch x 2 inch. The obtained results show that FSA would be a good approach to analyze the gamma backscattering on concrete.

Reference-free spectroscopic determination of fat and protein in milk in the visible and near infrared region below 1000 nm using spatially resolved diffuse reflectance fiber probe

New technique of diffuse reflectance spectroscopic analysis of milk fat and total protein content in the visible (Vis) and adjacent near infrared (NIR) region (400–995nm) has been developed and tested. Sample analysis was performed through a probe having eight 200-µm fiber channels forming a linear array. One of the end fibers was used for the illumination and other seven – for the spectroscopic detection of diffusely reflected light. One of the detection channels was used as a reference to normalize the spectra and to convert them into absorbance-equivalent units. The method has been tested experimentally using a designed sample set prepared from industrial raw milk standards with widely varying fat and protein content. To increase the modelling robustness all milk samples were measured in three different homogenization degrees. Comprehensive data analysis has shown the advantage of combining both spectral and spatial resolution in the same measurement and revealed the most relevant channels and wavelength regions. The modelling accuracy was further improved using joint variable selection and preprocessing optimization method based on the genetic algorithm. The root mean-square errors of different validation methods were below 0.10% for fat and below 0.08% for total protein content. Based on the present experimental data, it was computationally shown that the full-spectrum analysis in this method can be replaced by a sensor measurement at several specific wavelengths, for instance, using light-emitting diodes (LEDs) for illumination. Two optimal sensor configurations have been suggested: with nine LEDs for the analysis of fat and seven – for protein content. Both simulated sensors exhibit nearly the same component determination accuracy as corresponding full-spectrum analysis.

Radioactivity concentrations and dose characteristics of granite stones

We obtained the radionuclide concentrations of 238U, 232Th, and 40K in various samples of the granite stones by measuring with a high efficiency NaI(Tl) (10.16 cm x 10.16 cm) scintillation detector. The activities of 238U, 232Th, and 40K were recorded and determined by a full-spectrum analysis. The concentrations of radionuclides were found to be in ranges of 32.3-92.6 Bqkg-1, 23.9-52.2 Bqkg-1, and 796.5-2018.4 Bqkg-1 for 238U, 232Th, and 40K, respectively. The radiological dose rates and the hazard indices were also calculated in this analysis.

Molecular dynamics and reverse Monte Carlo modeling of scheelite-type AWO4 (A = Ca, Sr, Ba) W L3-edge EXAFS spectra

Classical molecular dynamics (MD) and reverse Monte Carlo methods coupled with ab initio multiple-scattering extended x-ray absorption fine structure (EXAFS) calculations were used for modeling of scheelite-type AWO4 (A = Ca, Sr, Ba) W L3-edge EXAFS spectra. The two theoretical approaches are complementary and allowed us to perform analysis of full EXAFS spectra. Both methods reproduce well the structure and dynamics of tungstates in the outer coordination shells, however the classical MD simulations underestimate the W–O bond MSRD due to a neglect of quantum zero-point-motion. The thermal vibration amplitudes, correlation effects and anisotropy of the tungstate structure were also estimated.

Model-based fatigue crack identification in rotors integrated with active magnetic bearings

This paper investigates the behavior of a rotor-bearing system with a breathing crack, under the action of active magnetic bearings, implemented to suppress the vibration induced by the presence of the crack and the unbalance. In such a case, identification of the crack with help of vibration signals may be difficult; other observables such as the controller current may be utilized for the purpose. Linear system equations of motion together with the switching crack excitation function are used to develop the identification algorithm. The use of full spectrum analysis is made to determine the crack force coefficients of the harmonics exciting the rotor in the same and the reverse direction of the rotor spin. Usage of these coefficients in the identification algorithm estimates the viscous damping, disc unbalance and additive crack stiffness. The algorithm has been tested for measurement noise and bias errors in system parameters, for robustness. In practical terms, the situation analyzed in this paper relates to identification of crack and other parameters in a rotor integrated with an active magnetic bearing.