Blast investigation by fast multispectral radiometric analysis

NASA Astrophysics Data System (ADS)

Devir, A. D.; Bushlin, Y.; Mendelewicz, I.; Lessin, A. B.; Engel, M.

2011-06-01

Knowledge regarding the processes involved in blasts and detonations is required in various applications, e.g. missile interception, blasts of high-explosive materials, final ballistics and IED identification. Blasts release large amount of energy in short time duration. Some part of this energy is released as intense radiation in the optical spectral bands. This paper proposes to measure the blast radiation by a fast multispectral radiometer. The measurement is made, simultaneously, in appropriately chosen spectral bands. These spectral bands provide extensive information on the physical and chemical processes that govern the blast through the time-dependence of the molecular and aerosol contributions to the detonation products. Multi-spectral blast measurements are performed in the visible, SWIR and MWIR spectral bands. Analysis of the cross-correlation between the measured multi-spectral signals gives the time dependence of the temperature, aerosol and gas composition of the blast. Farther analysis of the development of these quantities in time may indicate on the order of the detonation and amount and type of explosive materials. Examples of analysis of measured explosions are presented to demonstrate the power of the suggested fast multispectral radiometric analysis approach.

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Compact characterization of liquid absorption and emission spectra using linear variable filters integrated with a CMOS imaging camera.

PubMed

Wan, Yuhang; Carlson, John A; Kesler, Benjamin A; Peng, Wang; Su, Patrick; Al-Mulla, Saoud A; Lim, Sung Jun; Smith, Andrew M; Dallesasse, John M; Cunningham, Brian T

2016-07-08

A compact analysis platform for detecting liquid absorption and emission spectra using a set of optical linear variable filters atop a CMOS image sensor is presented. The working spectral range of the analysis platform can be extended without a reduction in spectral resolution by utilizing multiple linear variable filters with different wavelength ranges on the same CMOS sensor. With optical setup reconfiguration, its capability to measure both absorption and fluorescence emission is demonstrated. Quantitative detection of fluorescence emission down to 0.28 nM for quantum dot dispersions and 32 ng/mL for near-infrared dyes has been demonstrated on a single platform over a wide spectral range, as well as an absorption-based water quality test, showing the versatility of the system across liquid solutions for different emission and absorption bands. Comparison with a commercially available portable spectrometer and an optical spectrum analyzer shows our system has an improved signal-to-noise ratio and acceptable spectral resolution for discrimination of emission spectra, and characterization of colored liquid's absorption characteristics generated by common biomolecular assays. This simple, compact, and versatile analysis platform demonstrates a path towards an integrated optical device that can be utilized for a wide variety of applications in point-of-use testing and point-of-care diagnostics.

Flow Injection Mass Spectral Fingerprints Demonstrate Chemical Differences in Rio Red Grapefruit with Respect to Year, Harvest Time, and Conventional versus Organic Farming

PubMed Central

Chen, Pei; Harnly, James M.; Lester, Gene E.

2013-01-01

Spectral fingerprints were acquired for Rio Red grapefruit using flow injection electrospray ionization with ion trap and time-of-flight mass spectrometry (FI-ESI-IT-MS and FI-ESI-TOF-MS). Rio Red grapefruits were harvested 3 times a year (early, mid, and late harvests) in 2005 and 2006 from conventionally and organically grown trees. Data analysis using analysis of variance principal component analysis (ANOVA-PCA) demonstrated that, for both MS systems, the chemical patterns were different as a function of farming mode (conventional vs organic), as well as growing year and time of harvest. This was visually obvious with PCA and was shown to be statistically significant using ANOVA. The spectral fingerprints provided a more inclusive view of the chemical composition of the grapefruit and extended previous conclusions regarding the chemical differences between conventionally and organically grown Rio Red grapefruit. PMID:20337420

Real-time new satellite product demonstration from microwave sensors and GOES-16 at NRL TC web

NASA Astrophysics Data System (ADS)

Cossuth, J.; Richardson, K.; Surratt, M. L.; Bankert, R.

2017-12-01

The Naval Research Laboratory (NRL) Tropical Cyclone (TC) satellite webpage (https://www.nrlmry.navy.mil/TC.html) provides demonstration analyses of storm imagery to benefit operational TC forecast centers around the world. With the availability of new spectral information provided by GOES-16 satellite data and recent research into improved visualization methods of microwave data, experimental imagery was operationally tested to visualize the structural changes of TCs during the 2017 hurricane season. This presentation provides an introduction into these innovative satellite analysis methods, NRL's next generation satellite analysis system (the Geolocated Information Processing System, GeoIPSTM), and demonstration the added value of additional spectral frequencies when monitoring storms in near-realtime.

Direct measurement of group delay with joint time-frequency analysis of a white-light spectral interferogram.

PubMed

Deng, Yuqiang; Yang, Weijian; Zhou, Chun; Wang, Xi; Tao, Jun; Kong, Weipeng; Zhang, Zhigang

2008-12-01

We propose and demonstrate an analysis method to directly extract the group delay rather than the phase from the white-light spectral interferogram. By the joint time-frequency analysis technique, group delay is directly read from the ridge of wavelet transform, and group-delay dispersion is easily obtained by additional differentiation. The technique shows reasonable potential for the characterization of ultra-broadband chirped mirrors.

Spectral reconstruction analysis for enhancing signal-to-noise in time-resolved spectroscopies

NASA Astrophysics Data System (ADS)

Wilhelm, Michael J.; Smith, Jonathan M.; Dai, Hai-Lung

2015-09-01

We demonstrate a new spectral analysis for the enhancement of the signal-to-noise ratio (SNR) in time-resolved spectroscopies. Unlike the simple linear average which produces a single representative spectrum with enhanced SNR, this Spectral Reconstruction analysis (SRa) improves the SNR (by a factor of ca. 0 . 6 √{ n } ) for all n experimentally recorded time-resolved spectra. SRa operates by eliminating noise in the temporal domain, thereby attenuating noise in the spectral domain, as follows: Temporal profiles at each measured frequency are fit to a generic mathematical function that best represents the temporal evolution; spectra at each time are then reconstructed with data points from the fitted profiles. The SRa method is validated with simulated control spectral data sets. Finally, we apply SRa to two distinct experimentally measured sets of time-resolved IR emission spectra: (1) UV photolysis of carbonyl cyanide and (2) UV photolysis of vinyl cyanide.

Examination of Spectral Transformations on Spectral Mixture Analysis

NASA Astrophysics Data System (ADS)

Deng, Y.; Wu, C.

2018-04-01

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

Quantitative Doppler Analysis Using Conventional Color Flow Imaging Acquisitions.

PubMed

Karabiyik, Yucel; Ekroll, Ingvild Kinn; Eik-Nes, Sturla H; Lovstakken, Lasse

2018-05-01

Interleaved acquisitions used in conventional triplex mode result in a tradeoff between the frame rate and the quality of velocity estimates. On the other hand, workflow becomes inefficient when the user has to switch between different modes, and measurement variability is increased. This paper investigates the use of power spectral Capon estimator in quantitative Doppler analysis using data acquired with conventional color flow imaging (CFI) schemes. To preserve the number of samples used for velocity estimation, only spatial averaging was utilized, and clutter rejection was performed after spectral estimation. The resulting velocity spectra were evaluated in terms of spectral width using a recently proposed spectral envelope estimator. The spectral envelopes were also used for Doppler index calculations using in vivo and string phantom acquisitions. In vivo results demonstrated that the Capon estimator can provide spectral estimates with sufficient quality for quantitative analysis using packet-based CFI acquisitions. The calculated Doppler indices were similar to the values calculated using spectrograms estimated on a commercial ultrasound scanner.

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

Low Cost Solar Array Project: Composition Measurements by Analytical Photon Catalysis

NASA Technical Reports Server (NTRS)

Sutton, D. G.; Galvan, L.; Melzer, J.; Heidner, R. F., III

1979-01-01

The applicability of the photon catalysis technique for effecting composition analysis of silicon samples was assessed. Third quarter activities were devoted to the study of impurities in silicon matrices. The evaporation process was shown to be congruent; thus, the spectral analysis of the vapor yields the composition of the bulk sample. Qualitative analysis of metal impurities in silicon was demonstrated e part per million level. Only one atomic spectral interference was noted; however, it is imperative to maintain a leak tight system due to chemical and spectral interferences caused by the presence of even minute amounts of oxygen in the active nitrogen afterglow.

Hilbert-Huang Transform: A Spectral Analysis Tool Applied to Sunspot Number and Total Solar Irradiance Variations, as well as Near-Surface Atmospheric Variables

NASA Astrophysics Data System (ADS)

Barnhart, B. L.; Eichinger, W. E.; Prueger, J. H.

2010-12-01

Hilbert-Huang transform (HHT) is a relatively new data analysis tool which is used to analyze nonstationary and nonlinear time series data. It consists of an algorithm, called empirical mode decomposition (EMD), which extracts the cyclic components embedded within time series data, as well as Hilbert spectral analysis (HSA) which displays the time and frequency dependent energy contributions from each component in the form of a spectrogram. The method can be considered a generalized form of Fourier analysis which can describe the intrinsic cycles of data with basis functions whose amplitudes and phases may vary with time. The HHT will be introduced and compared to current spectral analysis tools such as Fourier analysis, short-time Fourier analysis, wavelet analysis and Wigner-Ville distributions. A number of applications are also presented which demonstrate the strengths and limitations of the tool, including analyzing sunspot number variability and total solar irradiance proxies as well as global averaged temperature and carbon dioxide concentration. Also, near-surface atmospheric quantities such as temperature and wind velocity are analyzed to demonstrate the nonstationarity of the atmosphere.

Spectral stratigraphy

NASA Technical Reports Server (NTRS)

Lang, Harold R.

1991-01-01

A new approach to stratigraphic analysis is described which uses photogeologic and spectral interpretation of multispectral remote sensing data combined with topographic information to determine the attitude, thickness, and lithology of strata exposed at the surface. The new stratigraphic procedure is illustrated by examples in the literature. The published results demonstrate the potential of spectral stratigraphy for mapping strata, determining dip and strike, measuring and correlating stratigraphic sequences, defining lithofacies, mapping biofacies, and interpreting geological structures.

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

Compact characterization of liquid absorption and emission spectra using linear variable filters integrated with a CMOS imaging camera

PubMed Central

Wan, Yuhang; Carlson, John A.; Kesler, Benjamin A.; Peng, Wang; Su, Patrick; Al-Mulla, Saoud A.; Lim, Sung Jun; Smith, Andrew M.; Dallesasse, John M.; Cunningham, Brian T.

2016-01-01

A compact analysis platform for detecting liquid absorption and emission spectra using a set of optical linear variable filters atop a CMOS image sensor is presented. The working spectral range of the analysis platform can be extended without a reduction in spectral resolution by utilizing multiple linear variable filters with different wavelength ranges on the same CMOS sensor. With optical setup reconfiguration, its capability to measure both absorption and fluorescence emission is demonstrated. Quantitative detection of fluorescence emission down to 0.28 nM for quantum dot dispersions and 32 ng/mL for near-infrared dyes has been demonstrated on a single platform over a wide spectral range, as well as an absorption-based water quality test, showing the versatility of the system across liquid solutions for different emission and absorption bands. Comparison with a commercially available portable spectrometer and an optical spectrum analyzer shows our system has an improved signal-to-noise ratio and acceptable spectral resolution for discrimination of emission spectra, and characterization of colored liquid’s absorption characteristics generated by common biomolecular assays. This simple, compact, and versatile analysis platform demonstrates a path towards an integrated optical device that can be utilized for a wide variety of applications in point-of-use testing and point-of-care diagnostics. PMID:27389070

Compact characterization of liquid absorption and emission spectra using linear variable filters integrated with a CMOS imaging camera

NASA Astrophysics Data System (ADS)

Wan, Yuhang; Carlson, John A.; Kesler, Benjamin A.; Peng, Wang; Su, Patrick; Al-Mulla, Saoud A.; Lim, Sung Jun; Smith, Andrew M.; Dallesasse, John M.; Cunningham, Brian T.

2016-07-01

A compact analysis platform for detecting liquid absorption and emission spectra using a set of optical linear variable filters atop a CMOS image sensor is presented. The working spectral range of the analysis platform can be extended without a reduction in spectral resolution by utilizing multiple linear variable filters with different wavelength ranges on the same CMOS sensor. With optical setup reconfiguration, its capability to measure both absorption and fluorescence emission is demonstrated. Quantitative detection of fluorescence emission down to 0.28 nM for quantum dot dispersions and 32 ng/mL for near-infrared dyes has been demonstrated on a single platform over a wide spectral range, as well as an absorption-based water quality test, showing the versatility of the system across liquid solutions for different emission and absorption bands. Comparison with a commercially available portable spectrometer and an optical spectrum analyzer shows our system has an improved signal-to-noise ratio and acceptable spectral resolution for discrimination of emission spectra, and characterization of colored liquid’s absorption characteristics generated by common biomolecular assays. This simple, compact, and versatile analysis platform demonstrates a path towards an integrated optical device that can be utilized for a wide variety of applications in point-of-use testing and point-of-care diagnostics.

DoE Phase II SBIR: Spectrally-Assisted Vehicle Tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Villeneuve, Pierre V.

2013-02-28

The goal of this Phase II SBIR is to develop a prototype software package to demonstrate spectrally-aided vehicle tracking performance. The primary application is to demonstrate improved target vehicle tracking performance in complex environments where traditional spatial tracker systems may show reduced performance. Example scenarios in Figure 1 include a) the target vehicle obscured by a large structure for an extended period of time, or b), the target engaging in extreme maneuvers amongst other civilian vehicles. The target information derived from spatial processing is unable to differentiate between the green versus the red vehicle. Spectral signature exploitation enables comparison ofmore » new candidate targets with existing track signatures. The ambiguity in this confusing scenario is resolved by folding spectral analysis results into each target nomination and association processes. Figure 3 shows a number of example spectral signatures from a variety of natural and man-made materials. The work performed over the two-year effort was divided into three general areas: algorithm refinement, software prototype development, and prototype performance demonstration. The tasks performed under this Phase II to accomplish the program goals were as follows: 1. Acquire relevant vehicle target datasets to support prototype. 2. Refine algorithms for target spectral feature exploitation. 3. Implement a prototype multi-hypothesis target tracking software package. 4. Demonstrate and quantify tracking performance using relevant data.« less

Multichannel spectral mode of the ALOHA up-conversion interferometer

NASA Astrophysics Data System (ADS)

Lehmann, L.; Darré, P.; Boulogne, H.; Delage, L.; Grossard, L.; Reynaud, F.

2018-06-01

In this paper, we propose a multichannel spectral configuration of the Astronomical Light Optical Hybrid Analysis (ALOHA) instrument dedicated to high-resolution imaging. A frequency conversion process is implemented in each arm of an interferometer to transfer the astronomical light to a shorter wavelength domain. Exploiting the spectral selectivity of this non-linear optical process, we propose to use a set of independent pump lasers in order to simultaneously study multiple spectral channels. This principle is experimentally demonstrated with a dual-channel configuration as a proof-of-principle.

A far-infrared spatial/spectral Fourier interferometry laboratory-based testbed instrument

NASA Astrophysics Data System (ADS)

Spencer, Locke D.; Naylor, David A.; Scott, Jeremy P.; Weiler, Vince F.; MacCrimmon, Roderick K.; Sitwell, Geoffrey R. H.; Ade, Peter A. R.

2016-07-01

We describe the current status, including preliminary design, characterization efforts, and recent progress, in the development of a spatial/spectral double Fourier laboratory-based interferometer testbed instrument within the Astronomical Instrumentation Group (AIG) laboratories at the University of Lethbridge, Canada (UL). Supported by CRC, CFI, and NSERC grants, this instrument development will provide laboratory demonstration of spatial-spectral interferometry with a concentration of furthering progress in areas including the development of spatial/spectral interferometry observation, data processing, characterization, and analysis techniques in the Far-Infrared (FIR) region of the electromagnetic spectrum.

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

NASA Technical Reports Server (NTRS)

Sree, Dave; Kjelgaard, Scott O.; Sellers, William L., III

1994-01-01

Spectral analysis of laser velocimetry (LV) data plays an important role in characterizing a turbulent flow and in estimating the associated turbulence scales, which can be helpful in validating theoretical and numerical turbulence models. The determination of turbulence scales is critically dependent on the accuracy of the spectral estimates. Spectral estimations from 'individual realization' laser velocimetry data are typically based on the assumption of a Poisson sampling process. What this Note has demonstrated is that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

Single-chip source-free terahertz spectroscope across 0.04-0.99 THz: combining sub-wavelength near-field sensing and regression analysis.

PubMed

Wu, Xue; Sengupta, Kaushik

2018-03-19

This paper demonstrates a methodology to miniaturize THz spectroscopes into a single silicon chip by eliminating traditional solid-state architectural components such as complex tunable THz and optical sources, nonlinear mixing and amplifiers. The proposed method achieves this by extracting incident THz spectral signatures from the surface of an on-chip antenna itself. The information is sensed through the spectrally-sensitive 2D distribution of the impressed current surface under the THz incident field. By converting the antenna from a single-port to a massively multi-port architecture with integrated electronics and deep subwavelength sensing, THz spectral estimation is converted into a linear estimation problem. We employ rigorous regression techniques and analysis to demonstrate a single silicon chip system operating at room temperature across 0.04-0.99 THz with 10 MHz accuracy in spectrum estimation of THz tones across the entire spectrum.

Stark broadening of resonant Cr II 3d5-3d44p spectral lines in hot stellar atmospheres

NASA Astrophysics Data System (ADS)

Simić, Z.; Dimitrijević, M. S.; Sahal-Bréchot, S.

2013-07-01

New Stark broadening parameters of interest for the astrophysical, laboratory and technological plasma modelling, investigations and analysis for nine resonant Cr II multiplets have been determined within the semiclassical perturbation approach. In order to demonstrate one possibility for their usage in astrophysical plasma research, obtained results have been applied to the analysis of the Stark broadening influence on stellar spectral line shapes.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Combined spectral-domain optical coherence tomography and hyperspectral imaging applied for tissue analysis: Preliminary results

NASA Astrophysics Data System (ADS)

Dontu, S.; Miclos, S.; Savastru, D.; Tautan, M.

2017-09-01

In recent years many optoelectronic techniques have been developed for improvement and the development of devices for tissue analysis. Spectral-Domain Optical Coherence Tomography (SD-OCT) is a new medical interferometric imaging modality that provides depth resolved tissue structure information with resolution in the μm range. However, SD-OCT has its own limitations and cannot offer the biochemical information of the tissue. These data can be obtained with hyperspectral imaging, a non-invasive, sensitive and real time technique. In the present study we have combined Spectral-Domain Optical Coherence Tomography (SD-OCT) with Hyperspectral imaging (HSI) for tissue analysis. The Spectral-Domain Optical Coherence Tomography (SD-OCT) and Hyperspectral imaging (HSI) are two methods that have demonstrated significant potential in this context. Preliminary results using different tissue have highlighted the capabilities of this technique of combinations.

Practical Approach for Hyperspectral Image Processing in Python

NASA Astrophysics Data System (ADS)

Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.

2018-04-01

Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

Three-stage Fabry-Perot liquid crystal tunable filter with extended spectral range.

PubMed

Zheng, Zhenrong; Yang, Guowei; Li, Haifeng; Liu, Xu

2011-01-31

A method to extend spectral range of tunable optical filter is proposed in this paper. Two same tunable Fabry-Perot filters and an additional tunable filter with different free spectral range are cascaded to extend spectral range and reduce sidelobes. Over 400 nm of free spectral range and 4 nm of full width at half maximum of the filter were achieved. Design procedure and simulation are described in detail. An experimental 3-stage tunable Fabry-Perot filter with visible and infrared spectra is demonstrated. The experimental results and the theoretical analysis are presented in detail to verify this method. The results revealed that a compact and extended tunable spectral range of Fabry-Perot filter can be easily attainable by this method.

Covariance propagation in spectral indices

DOE PAGES

Griffin, P. J.

2015-01-09

In this study, the dosimetry community has a history of using spectral indices to support neutron spectrum characterization and cross section validation efforts. An important aspect to this type of analysis is the proper consideration of the contribution of the spectrum uncertainty to the total uncertainty in calculated spectral indices (SIs). This study identifies deficiencies in the traditional treatment of the SI uncertainty, provides simple bounds to the spectral component in the SI uncertainty estimates, verifies that these estimates are reflected in actual applications, details a methodology that rigorously captures the spectral contribution to the uncertainty in the SI, andmore » provides quantified examples that demonstrate the importance of the proper treatment the spectral contribution to the uncertainty in the SI.« less

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

PubMed Central

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J.; Li, Ming

2013-01-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables. PMID:22552787

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines.

PubMed

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J; Li, Ming; Tabb, David L

2012-09-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

Implemented Lomb-Scargle periodogram: a valuable tool for improving cyclostratigraphic research on unevenly sampled deep-sea stratigraphic sequences

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2011-12-01

One important handicap when working with stratigraphic sequences is the discontinuous character of the sedimentary record, especially relevant in cyclostratigraphic analysis. Uneven palaeoclimatic/palaeoceanographic time series are common, their cyclostratigraphic analysis being comparatively difficult because most spectral methodologies are appropriate only when working with even sampling. As a means to solve this problem, a program for calculating the smoothed Lomb-Scargle periodogram and cross-periodogram, which additionally evaluates the statistical confidence of the estimated power spectrum through a Monte Carlo procedure (the permutation test), has been developed. The spectral analysis of a short uneven time series calls for assessment of the statistical significance of the spectral peaks, since a periodogram can always be calculated but the main challenge resides in identifying true spectral features. To demonstrate the effectiveness of this program, two case studies are presented: the one deals with synthetic data and the other with paleoceanographic/palaeoclimatic proxies. On a simulated time series of 500 data, two uneven time series (with 100 and 25 data) were generated by selecting data at random. Comparative analysis between the power spectra from the simulated series and from the two uneven time series demonstrates the usefulness of the smoothed Lomb-Scargle periodogram for uneven sequences, making it possible to distinguish between statistically significant and spurious spectral peaks. Fragmentary time series of Cd/Ca ratios and δ18O from core AII107-131 of SPECMAP were analysed as a real case study. The efficiency of the direct and cross Lomb-Scargle periodogram in recognizing Milankovitch and sub-Milankovitch signals related to palaeoclimatic/palaeoceanographic changes is demonstrated. As implemented, the Lomb-Scargle periodogram may be applied to any palaeoclimatic/palaeoceanographic proxies, including those usually recovered from contourites, and it holds special interest in the context of centennial- to millennial-scale climatic changes affecting contouritic currents.

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Compact full-motion video hyperspectral cameras: development, image processing, and applications

NASA Astrophysics Data System (ADS)

Kanaev, A. V.

2015-10-01

Emergence of spectral pixel-level color filters has enabled development of hyper-spectral Full Motion Video (FMV) sensors operating in visible (EO) and infrared (IR) wavelengths. The new class of hyper-spectral cameras opens broad possibilities of its utilization for military and industry purposes. Indeed, such cameras are able to classify materials as well as detect and track spectral signatures continuously in real time while simultaneously providing an operator the benefit of enhanced-discrimination-color video. Supporting these extensive capabilities requires significant computational processing of the collected spectral data. In general, two processing streams are envisioned for mosaic array cameras. The first is spectral computation that provides essential spectral content analysis e.g. detection or classification. The second is presentation of the video to an operator that can offer the best display of the content depending on the performed task e.g. providing spatial resolution enhancement or color coding of the spectral analysis. These processing streams can be executed in parallel or they can utilize each other's results. The spectral analysis algorithms have been developed extensively, however demosaicking of more than three equally-sampled spectral bands has been explored scarcely. We present unique approach to demosaicking based on multi-band super-resolution and show the trade-off between spatial resolution and spectral content. Using imagery collected with developed 9-band SWIR camera we demonstrate several of its concepts of operation including detection and tracking. We also compare the demosaicking results to the results of multi-frame super-resolution as well as to the combined multi-frame and multiband processing.

Toward a hyperspectral optical signature of extra virgin olive oil

NASA Astrophysics Data System (ADS)

Mignani, A. G.; Ciaccheri, L.; Thienpont, H.; Ottevaere, H.; Attilio, C.; Cimato, A.

2007-05-01

Italian extra virgin olive oils bearing labels of certified area of origin were considered. Their multispectral digital signature was measured by means of absorption spectroscopy in the 200-1700 nm spectral range. The instrumentation was a fiber optic-based, cheap, and compact device. The spectral data were processed by means of multivariate analysis and plotted on a 2D classification map. The map showed sharp clusters according to the geographical origin of the oils, thus demonstrating the potentials of UV-VIS-NIR spectroscopy for optical fingerprinting. Then, the spectral data were correlated to the content of the most important fatty acids. The good fitting achieved demonstrated that the optical fingerprinting can be used also for predicting nutritional and chemical parameters.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

PubMed Central

Prerau, Michael J.; Brown, Ritchie E.; Bianchi, Matt T.; Ellenbogen, Jeffrey M.; Purdon, Patrick L.

2016-01-01

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible—elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications. PMID:27927806

Data analysis of multi-laser standoff spectral identification of chemical and biological compounds

NASA Astrophysics Data System (ADS)

Farahi, R.; Zaharov, V.; Tetard, L.; Thundat, T.; Passian, A.

2013-06-01

With the availability of tunable broadband coherent sources that emit mid-infrared radiation with well-defined beam characteristics, spectroscopies that were traditionally not practical for standoff detection1 or for development of miniaturized infrared detectors2, 3 have renewed interest. While obtaining compositional information for objects from a distance remains a major challenge in chemical and biological sensing, recently we demonstrated that capitalizing on mid-infrared excitation of target molecules by using quantum cascade lasers and invoking a pump probe scheme can provide spectral fingerprints of substances from a variable standoff distance.3 However, the standoff data is typically associated with random fluctuations that can corrupt the fine spectral features and useful data. To process the data from standoff experiments toward better recognition we consider and apply two types of denoising techniques, namely, spectral analysis and Karhunen-Loeve Transform (KLT). Using these techniques, infrared spectral data have been effectively improved. The result of the analysis illustrates that KLT can be adapted as a powerful data denoising tool for the presented pump-probe infrared standoff spectroscopy.

Spectral analysis software improves confidence in plant and soil water stable isotope analyses performed by isotope ratio infrared spectroscopy (IRIS).

PubMed

West, A G; Goldsmith, G R; Matimati, I; Dawson, T E

2011-08-30

Previous studies have demonstrated the potential for large errors to occur when analyzing waters containing organic contaminants using isotope ratio infrared spectroscopy (IRIS). In an attempt to address this problem, IRIS manufacturers now provide post-processing spectral analysis software capable of identifying samples with the types of spectral interference that compromises their stable isotope analysis. Here we report two independent tests of this post-processing spectral analysis software on two IRIS systems, OA-ICOS (Los Gatos Research Inc.) and WS-CRDS (Picarro Inc.). Following a similar methodology to a previous study, we cryogenically extracted plant leaf water and soil water and measured the δ(2)H and δ(18)O values of identical samples by isotope ratio mass spectrometry (IRMS) and IRIS. As an additional test, we analyzed plant stem waters and tap waters by IRMS and IRIS in an independent laboratory. For all tests we assumed that the IRMS value represented the "true" value against which we could compare the stable isotope results from the IRIS methods. Samples showing significant deviations from the IRMS value (>2σ) were considered to be contaminated and representative of spectral interference in the IRIS measurement. Over the two studies, 83% of plant species were considered contaminated on OA-ICOS and 58% on WS-CRDS. Post-analysis, spectra were analyzed using the manufacturer's spectral analysis software, in order to see if the software correctly identified contaminated samples. In our tests the software performed well, identifying all the samples with major errors. However, some false negatives indicate that user evaluation and testing of the software are necessary. Repeat sampling of plants showed considerable variation in the discrepancies between IRIS and IRMS. As such, we recommend that spectral analysis of IRIS data must be incorporated into standard post-processing routines. Furthermore, we suggest that the results from spectral analysis be included when reporting stable isotope data from IRIS. Copyright © 2011 John Wiley & Sons, Ltd.

Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

PubMed

Awan, Ruqayya; Al-Maadeed, Somaya; Al-Saady, Rafif

2018-01-01

The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images.

Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

PubMed Central

Al-Maadeed, Somaya; Al-Saady, Rafif

2018-01-01

The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images. PMID:29874262

The analysis of forest policy using Landsat multi-spectral scanner data and geographic information systems

NASA Technical Reports Server (NTRS)

Peterson, D. L.; Brass, J. A.; Norman, S. D.; Tosta-Miller, N.

1984-01-01

The role of Landsat multi-spectral scanner (MSS) data for forest policy analysis in the state of California has been investigated. The combined requirements for physical, socio-economic, and institutional data in policy analysis were studied to explain potential data needs. A statewide MSS data and general land cover classification was created from which country-wide data sets could be extracted for detailed analyses. The potential to combine point sample data with MSS data was examined as a means to improve specificity in estimations. MSS data was incorporated into geographic information systems to demonstrate modeling techniques using abiotic, biotic, and socio-economic data layers. The review of system configurations to help the California Department of Forestry (CDF) acquire the capability demonstrated resulted in a sequence of options for implementation.

Quality assurance of temporal variability of natural decay chain and neutron induced background for low-level NORM analysis

DOE PAGES

Yoho, Michael; Porterfield, Donivan R.; Landsberger, Sheldon

2015-09-22

In this study, twenty-one high purity germanium (HPGe) background spectra were collected over 2 years at Los Alamos National Laboratory. A quality assurance methodology was developed to monitor spectral background levels from thermal and fast neutron flux levels and naturally occurring radioactive material decay series radionuclides. 238U decay products above 222Rn demonstrated minimal temporal variability beyond that expected from counting statistics. 238U and 232Th progeny below Rn gas displayed at most twice the expected variability. Further, an analysis of the 139 keV 74Ge(n, γ) and 691 keV 72Ge(n, n') spectral features demonstrated temporal stability for both thermal and fastmore » neutron fluxes.« less

New Methods of Spectral-Density Based Graph Construction and Their Application to Hyperspectral Image Analysis

NASA Astrophysics Data System (ADS)

Stevens, Jeffrey

The past decade has seen the emergence of many hyperspectral image (HSI) analysis algorithms based on graph theory and derived manifold-coordinates. Yet, despite the growing number of algorithms, there has been limited study of the graphs constructed from spectral data themselves. Which graphs are appropriate for various HSI analyses--and why? This research aims to begin addressing these questions as the performance of graph-based techniques is inextricably tied to the graphical model constructed from the spectral data. We begin with a literature review providing a survey of spectral graph construction techniques currently used by the hyperspectral community, starting with simple constructs demonstrating basic concepts and then incrementally adding components to derive more complex approaches. Throughout this development, we discuss algorithm advantages and disadvantages for different types of hyperspectral analysis. A focus is provided on techniques influenced by spectral density through which the concept of community structure arises. Through the use of simulated and real HSI data, we demonstrate density-based edge allocation produces more uniform nearest neighbor lists than non-density based techniques through increasing the number of intracluster edges, facilitating higher k-nearest neighbor (k-NN) classification performance. Imposing the common mutuality constraint to symmetrify adjacency matrices is demonstrated to be beneficial in most circumstances, especially in rural (less cluttered) scenes. Many complex adaptive edge-reweighting techniques are shown to slightly degrade nearest-neighbor list characteristics. Analysis suggests this condition is possibly attributable to the validity of characterizing spectral density by a single variable representing data scale for each pixel. Additionally, it is shown that imposing mutuality hurts the performance of adaptive edge-allocation techniques or any technique that aims to assign a low number of edges (<10) to any pixel. A simple k bias addresses this problem. Many of the adaptive edge-reweighting techniques are based on the concept of codensity, so we explore codensity properties as they relate to density-based edge reweighting. We find that codensity may not be the best estimator of local scale due to variations in cluster density, so we introduce and compare two inherently density-weighted graph construction techniques from the data mining literature: shared nearest neighbors (SNN) and mutual proximity (MP). MP and SNN are not reliant upon a codensity measure, hence are not susceptible to its shortcomings. Neither has been used for hyperspectral analyses, so this presents the first study of these techniques on HSI data. We demonstrate MP and SNN can offer better performance, but in general none of the reweighting techniques improve the quality of these spectral graphs in our neighborhood structure tests. As such, these complex adaptive edge-reweighting techniques may need to be modified to increase their effectiveness. During this investigation, we probe deeper into properties of high-dimensional data and introduce the concept of concentration of measure (CoM)--the degradation in the efficacy of many common distance measures with increasing dimensionality--as it relates to spectral graph construction. CoM exists in pairwise distances between HSI pixels, but not to the degree experienced in random data of the same extrinsic dimension; a characteristic we demonstrate is due to the rich correlation and cluster structure present in HSI data. CoM can lead to hubness--a condition wherein some nodes have short distances (high similarities) to an exceptionally large number of nodes. We study hub presence in 49 HSI datasets of varying resolutions, altitudes, and spectral bands to demonstrate hubness effects are negligible in a k-NN classification example (generalized counting scenarios), but we note its impact on methods that use edge weights to derive manifold coordinates or splitting clusters based on spectral graph theory requires more investigation. Many of these new graph-related quantities can be exploited to demonstrate new techniques for HSI classification and anomaly detection. We present an initial exploration into this relatively new and exciting field based on an enhanced Schroedinger Eigenmap classification example and compare results to the current state-of-the-art approach. We produce equivalent results, but demonstrate different types of misclassifications, opening the door to combine the best of both approaches to achieve truly superior performance. A separate less mature hubness-assisted anomaly detector (HAAD) is also presented.

A Comparison of Raman Spectral Features of Frozen and Deparaffinized Tissues in Neuroblastoma and Ganglioneuroma

NASA Astrophysics Data System (ADS)

Devpura, Suneetha; Thakur, Jagdish S.; Poulik, Janet M.; Rabah, Raja; Naik, Vaman M.; Naik, Ratna

2012-02-01

We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of normal adrenal gland. Thin sections from both frozen and deparaffinized tissues, obtained from the same tissue specimen, were studied in conjunction with the pathological examination of the tissues. We found a significant difference in the spectral features of frozen sections of normal adrenal gland, neuroblastoma, and ganglioneuroma when compared to deparaffinized tissues. The quantitative analysis of the Raman data using chemometric methods of principal component analysis and discriminant function analysis obtained from the frozen tissues show a sensitivity and specificity of 100% each. The biochemical identification based on the spectral differences shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared to the neuroblastoma and ganglioneuroma frozen tissues. However, deparaffinized tissues show complete removal of these biochemicals in adrenal tissues. This study demonstrates that Raman spectroscopy combined with chemometric methods can successfully distinguish neuroblastoma and ganglioneuroma at cellular level.

A multimodal spectral approach to characterize rhythm in natural speech.

PubMed

Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta

2016-01-01

Human utterances demonstrate temporal patterning, also referred to as rhythm. While simple oromotor behaviors (e.g., chewing) feature a salient periodical structure, conversational speech displays a time-varying quasi-rhythmic pattern. Quantification of periodicity in speech is challenging. Unimodal spectral approaches have highlighted rhythmic aspects of speech. However, speech is a complex multimodal phenomenon that arises from the interplay of articulatory, respiratory, and vocal systems. The present study addressed the question of whether a multimodal spectral approach, in the form of coherence analysis between electromyographic (EMG) and acoustic signals, would allow one to characterize rhythm in natural speech more efficiently than a unimodal analysis. The main experimental task consisted of speech production at three speaking rates; a simple oromotor task served as control. The EMG-acoustic coherence emerged as a sensitive means of tracking speech rhythm, whereas spectral analysis of either EMG or acoustic amplitude envelope alone was less informative. Coherence metrics seem to distinguish and highlight rhythmic structure in natural speech.

Carbon charge exchange analysis in the ITER-like wall environment.

PubMed

Menmuir, S; Giroud, C; Biewer, T M; Coffey, I H; Delabie, E; Hawkes, N C; Sertoli, M

2014-11-01

Charge exchange spectroscopy has long been a key diagnostic tool for fusion plasmas and is well developed in devices with Carbon Plasma-Facing Components. Operation with the ITER-like wall at JET has resulted in changes to the spectrum in the region of the Carbon charge exchange line at 529.06 nm and demonstrates the need to revise the core charge exchange analysis for this line. An investigation has been made of this spectral region in different plasma conditions and the revised description of the spectral lines to be included in the analysis is presented.

Spectral Monitoring of Surfactant Clearance during Alveolar Epithelial Type II Cell Differentiation

PubMed Central

Swain, Robin J.; Kemp, Sarah J.; Goldstraw, Peter; Tetley, Teresa D.; Stevens, Molly M.

2008-01-01

In this study, we report on the noninvasive identification of spectral markers of alveolar type II (ATII) cell differentiation in vitro using Raman microspectroscopy. ATII cells are progenitor cells for alveolar type I (ATI) cells in vivo, and spontaneously differentiate toward an ATI-like phenotype in culture. We analyzed undifferentiated and differentiated primary human ATII cells, and correlated Raman spectral changes to cellular changes in morphology and marker protein synthesis (surfactant protein C, alkaline phosphatase, caveolin-1). Undifferentiated ATII cells demonstrated spectra with strong phospholipid vibrations, arising from alveolar surfactant stored within cytoplasmic lamellar bodies (Lbs). Differentiated ATI-like cells yielded spectra with significantly less lipid content. Factor analysis revealed a phospholipid-dominated spectral component as the main discriminator between the ATII and ATI-like phenotypes. Spectral modeling of the data revealed a significant decrease in the spectral contribution of cellular lipids—specifically phosphatidyl choline, the main constituent of surfactant, as ATII cells differentiate. These observations were consistent with the clearance of surfactant from Lbs as ATII cells differentiate, and were further supported by cytochemical staining for Lbs. These results demonstrate the first spectral characterization of primary human ATII cells, and provide insight into the biochemical properties of alveolar surfactant in its unperturbed cellular environment. PMID:18820234

Spectral interferometry for morphological imaging in in vitro fertilization (IVF) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhu, Yizheng; Li, Chengshuai

2016-03-01

Morphological assessment of spermatozoa is of critical importance for in vitro fertilization (IVF), especially intracytoplasmic sperm injection (ICSI)-based IVF. In ICSI, a single sperm cell is selected and injected into an egg to achieve fertilization. The quality of the sperm cell is found to be highly correlated to IVF success. Sperm morphology, such as shape, head birefringence and motility, among others, are typically evaluated under a microscope. Current observation relies on conventional techniques such as differential interference contrast microscopy and polarized light microscopy. Their qualitative nature, however, limits the ability to provide accurate quantitative analysis. Here, we demonstrate quantitative morphological measurement of sperm cells using two types of spectral interferometric techniques, namely spectral modulation interferometry and spectral multiplexing interferometry. Both are based on spectral-domain low coherence interferometry, which is known for its exquisite phase determination ability. While spectral modulation interferometry encodes sample phase in a single spectrum, spectral multiplexing interferometry does so for sample birefringence. Therefore they are capable of highly sensitive phase and birefringence imaging. These features suit well in the imaging of live sperm cells, which are small, dynamic objects with only low to moderate levels of phase and birefringence contrast. We will introduce the operation of both techniques and demonstrate their application to measuring the phase and birefringence morphology of sperm cells.

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

Computerized EEG analysis for studying the effect of drugs on the central nervous system.

PubMed

Rosadini, G; Cavazza, B; Rodriguez, G; Sannita, W G; Siccardi, A

1977-11-01

Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.

Planck 2013 results. IX. HFI spectral response

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chen, X.; Chiang, H. C.; Chiang, L.-Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; North, C.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rusholme, B.; Santos, D.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J.-L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-11-01

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (includingthe level of out-of-band signal rejection) of all HFI detectors to a known source of electromagnetic radiation individually. This was determined by measuring the interferometric output of a continuously scanned Fourier transform spectrometer with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. Knowledge of the relative variations in the spectral response between HFI detectors allows for a more thorough analysis of the HFI data. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. While previous papers describe the pre-flight experiments conducted on the Planck HFI, this paper focusses on the analysis of the pre-flight spectral response measurements and the derivation of data products, e.g. band-average spectra, unit conversion coefficients, and colour correction coefficients, all with related uncertainties. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 108. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.

Performance enhancement of optical code-division multiple-access systems using transposed modified Walsh code

NASA Astrophysics Data System (ADS)

Sikder, Somali; Ghosh, Shila

2018-02-01

This paper presents the construction of unipolar transposed modified Walsh code (TMWC) and analysis of its performance in optical code-division multiple-access (OCDMA) systems. Specifically, the signal-to-noise ratio, bit error rate (BER), cardinality, and spectral efficiency were investigated. The theoretical analysis demonstrated that the wavelength-hopping time-spreading system using TMWC was robust against multiple-access interference and more spectrally efficient than systems using other existing OCDMA codes. In particular, the spectral efficiency was calculated to be 1.0370 when TMWC of weight 3 was employed. The BER and eye pattern for the designed TMWC were also successfully obtained using OptiSystem simulation software. The results indicate that the proposed code design is promising for enhancing network capacity.

Application of Artificial Neural Networks and Singular-Spectral Analysis in Forecasting the Daily Traffic in the Moscow Metro

NASA Astrophysics Data System (ADS)

Ivanov, Victor; Osetrov, Evgenii

2018-02-01

In this paper, we investigate the possibility of applying various approaches to solving the problem of medium-term forecasting of daily passenger traffic volumes in the Moscow metro (MM): 1) on the basis of artificial neural networks (ANN); 2) using the singular-spectral analysis implemented in the package "Caterpillar"-SSA; 3) sharing the ANN and the "Caterpillar"-SSA approach. We demonstrate that the developed methods and algorithms allow us to conduct medium-term forecasting of passenger traffic in the MM with reasonable accuracy.

Sensitive Multi-Species Emissions Monitoring: Infrared Laser-Based Detection of Trace-Level Contaminants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steill, Jeffrey D.; Huang, Haifeng; Hoops, Alexandra A.

This report summarizes our development of spectroscopic chemical analysis techniques and spectral modeling for trace-gas measurements of highly-regulated low-concentration species present in flue gas emissions from utility coal boilers such as HCl under conditions of high humidity. Detailed spectral modeling of the spectroscopy of HCl and other important combustion and atmospheric species such as H 2 O, CO 2 , N 2 O, NO 2 , SO 2 , and CH 4 demonstrates that IR-laser spectroscopy is a sensitive multi-component analysis strategy. Experimental measurements from techniques based on IR laser spectroscopy are presented that demonstrate sub-ppm sensitivity levels to thesemore » species. Photoacoustic infrared spectroscopy is used to detect and quantify HCl at ppm levels with extremely high signal-to-noise even under conditions of high relative humidity. Additionally, cavity ring-down IR spectroscopy is used to achieve an extremely high sensitivity to combustion trace gases in this spectral region; ppm level CH 4 is one demonstrated example. The importance of spectral resolution in the sensitivity of a trace-gas measurement is examined by spectral modeling in the mid- and near-IR, and efforts to improve measurement resolution through novel instrument development are described. While previous project reports focused on benefits and complexities of the dual-etalon cavity ring-down infrared spectrometer, here details on steps taken to implement this unique and potentially revolutionary instrument are described. This report also illustrates and critiques the general strategy of IR- laser photodetection of trace gases leading to the conclusion that mid-IR laser spectroscopy techniques provide a promising basis for further instrument development and implementation that will enable cost-effective sensitive detection of multiple key contaminant species simultaneously.« less

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Peer-to-Peer Instruction with Interactive Demonstrations in Upper Level Astronomy Courses

NASA Astrophysics Data System (ADS)

Gelderman, Richard

2013-06-01

Spectral and polarization properties of light are topics that most intro physics courses barely touch. Students therefore rarely have any useful experience to draw on when those topics come up in an upper level astronomy class. This means that they approach problems dealing with spectra or polarization as plug-and-chug mathematics applications, devoid of physical context. We have been addressing such dilemmas by using interactive demonstrations in the lecture meeting to give students direct experience with polarization filters, diffraction gratings, spectral sources, and situations requiring them to analyze sources based on the observed polarization of spectral properties. Each student individually predicts the outcomes for a demonstration. Students then collaborate within in a group of three to discuss their prediction, reporting the group’s consensus prediction. After observing the demonstration, students in the group compare their predictions to the results, and attempt to explain the phenomena. Based on curricular reforms in physics education, these methods have provided our students with the ability to much more than just manipulate equations related to spectroscopic and polarization analysis.

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

PubMed

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Linearized spectrum correlation analysis for line emission measurements

NASA Astrophysics Data System (ADS)

Nishizawa, T.; Nornberg, M. D.; Den Hartog, D. J.; Sarff, J. S.

2017-08-01

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

Can unaided non-linguistic measures predict cochlear implant candidacy?

PubMed Central

Shim, Hyun Joon; Won, Jong Ho; Moon, Il Joon; Anderson, Elizabeth S.; Drennan, Ward R.; McIntosh, Nancy E.; Weaver, Edward M.; Rubinstein, Jay T.

2014-01-01

Objective To determine if unaided, non-linguistic psychoacoustic measures can be effective in evaluating cochlear implant (CI) candidacy. Study Design Prospective split-cohort study including predictor development subgroup and independent predictor validation subgroup. Setting Tertiary referral center. Subjects Fifteen subjects (28 ears) with hearing loss were recruited from patients visiting the University of Washington Medical Center for CI evaluation. Methods Spectral-ripple discrimination (using a 13-dB modulation depth) and temporal modulation detection using 10- and 100-Hz modulation frequencies were assessed with stimuli presented through insert earphones. Correlations between performance for psychoacoustic tasks and speech perception tasks were assessed. Receiver operating characteristic (ROC) curve analysis was performed to estimate the optimal psychoacoustic score for CI candidacy evaluation in the development subgroup and then tested in an independent sample. Results Strong correlations were observed between spectral-ripple thresholds and both aided sentence recognition and unaided word recognition. Weaker relationships were found between temporal modulation detection and speech tests. ROC curve analysis demonstrated that the unaided spectral ripple discrimination shows a good sensitivity, specificity, positive predictive value, and negative predictive value compared to the current gold standard, aided sentence recognition. Conclusions Results demonstrated that the unaided spectral-ripple discrimination test could be a promising tool for evaluating CI candidacy. PMID:24901669

Least Squares Moving-Window Spectral Analysis.

PubMed

Lee, Young Jong

2017-08-01

Least squares regression is proposed as a moving-windows method for analysis of a series of spectra acquired as a function of external perturbation. The least squares moving-window (LSMW) method can be considered an extended form of the Savitzky-Golay differentiation for nonuniform perturbation spacing. LSMW is characterized in terms of moving-window size, perturbation spacing type, and intensity noise. Simulation results from LSMW are compared with results from other numerical differentiation methods, such as single-interval differentiation, autocorrelation moving-window, and perturbation correlation moving-window methods. It is demonstrated that this simple LSMW method can be useful for quantitative analysis of nonuniformly spaced spectral data with high frequency noise.

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Model-free methods to study membrane environmental probes: a comparison of the spectral phasor and generalized polarization approaches

PubMed Central

Malacrida, Leonel; Gratton, Enrico; Jameson, David M

2016-01-01

In this note, we present a discussion of the advantages and scope of model-free analysis methods applied to the popular solvatochromic probe LAURDAN, which is widely used as an environmental probe to study dynamics and structure in membranes. In particular, we compare and contrast the generalized polarization approach with the spectral phasor approach. To illustrate our points we utilize several model membrane systems containing pure lipid phases and, in some cases, cholesterol or surfactants. We demonstrate that the spectral phasor method offers definitive advantages in the case of complex systems. PMID:27182438

Spectrally resolved digital holography using a white light LED

NASA Astrophysics Data System (ADS)

Claus, D.; Pedrini, G.; Buchta, D.; Osten, W.

2017-06-01

This paper introduces the concept of spectrally resolved digital holography. The measurement principle and the analysis of the data will be discussed in detail. The usefulness of spectrally resolved digital holography is demonstrated for colour imaging and optical metrology with regards to the recovery of modulus information and phase information, respectively. The phase information will be used to measure the shape of an object via the application of the dual wavelength method. Based on the large degree of data available, multiple speckle de-correlated dual wavelength phase maps can be obtained, which when averaged result in a signal to noise ratio improvement.

Quantitative polarized light microscopy using spectral multiplexing interferometry.

PubMed

Li, Chengshuai; Zhu, Yizheng

2015-06-01

We propose an interferometric spectral multiplexing method for measuring birefringent specimens with simple configuration and high sensitivity. The retardation and orientation of sample birefringence are simultaneously encoded onto two spectral carrier waves, generated interferometrically by a birefringent crystal through polarization mixing. A single interference spectrum hence contains sufficient information for birefringence determination, eliminating the need for mechanical rotation or electrical modulation. The technique is analyzed theoretically and validated experimentally on cellulose film. System simplicity permits the possibility of mitigating system birefringence background. Further analysis demonstrates the technique's exquisite sensitivity as high as ∼20  pm for retardation measurement.

Development and application of the maximum entropy method and other spectral estimation techniques

NASA Astrophysics Data System (ADS)

King, W. R.

1980-09-01

This summary report is a collection of four separate progress reports prepared under three contracts, which are all sponsored by the Office of Naval Research in Arlington, Virginia. This report contains the results of investigations into the application of the maximum entropy method (MEM), a high resolution, frequency and wavenumber estimation technique. The report also contains a description of two, new, stable, high resolution spectral estimation techniques that is provided in the final report section. Many examples of wavenumber spectral patterns for all investigated techniques are included throughout the report. The maximum entropy method is also known as the maximum entropy spectral analysis (MESA) technique, and both names are used in the report. Many MEM wavenumber spectral patterns are demonstrated using both simulated and measured radar signal and noise data. Methods for obtaining stable MEM wavenumber spectra are discussed, broadband signal detection using the MEM prediction error transform (PET) is discussed, and Doppler radar narrowband signal detection is demonstrated using the MEM technique. It is also shown that MEM cannot be applied to randomly sampled data. The two new, stable, high resolution, spectral estimation techniques discussed in the final report section, are named the Wiener-King and the Fourier spectral estimation techniques. The two new techniques have a similar derivation based upon the Wiener prediction filter, but the two techniques are otherwise quite different. Further development of the techniques and measurement of the technique spectral characteristics is recommended for subsequent investigation.

EDDIE Seismology: Introductory spectral analysis for undergraduates

NASA Astrophysics Data System (ADS)

Soule, D. C.; Gougis, R.; O'Reilly, C.

2016-12-01

We present a spectral seismology lesson in which students use spectral analysis to describe the frequency of seismic arrivals based on a conceptual presentation of waveforms and filters. The goal is for students to surpass basic waveform terminology and relate a time domain signals to their conjugates in the frequency domain. Although seismology instruction commonly engages students in analysis of authentic seismological data, this is less true for lower-level undergraduate seismology instruction due to coding barriers to many seismological analysis tasks. To address this, our module uses Seismic Canvas (Kroeger, 2015; https://seiscode.iris.washington.edu/projects/seismiccanvas), a graphically interactive application for accessing, viewing and analyzing waveform data, which we use to plot earthquake data in the time domain. Once students are familiarized with the general components of the waveform (i.e. frequency, wavelength, amplitude and period), they use Seismic Canvas to transform the data into the frequency domain. Bypassing the mathematics of Fourier Series allows focus on conceptual understanding by plotting and manipulating seismic data in both time and frequency domains. Pre/post-tests showed significant improvements in students' use of seismograms and spectrograms to estimate the frequency content of the primary wave, which demonstrated students' understanding of frequency and how data on the spectrogram and seismogram are related. Students were also able to identify the time and frequency of the largest amplitude arrival, indicating understanding of amplitude and use of a spectrogram as an analysis tool. Students were also asked to compare plots of raw data and the same data filtered with a high-pass filter, and identify the filter used to create the second plot. Students demonstrated an improved understanding of how frequency content can be removed from a signal in the spectral domain.

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

NASA Astrophysics Data System (ADS)

Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

2012-11-01

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

NASA Technical Reports Server (NTRS)

Srivastava, Askok N.; Matthews, Bryan; Das, Santanu

2008-01-01

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Targeting Inaccurate Atomic Data in the Eta Car Ejecta Absorption

NASA Technical Reports Server (NTRS)

Nielsen, K. E.; Kober, G. Vieira; Gull, T. R.; Blackwell-Whitehead, R.; Nilsson, H.

2006-01-01

The input from the laboratory spectroscopist community has on many occasions helped the analysis of the eta Car spectrum. Our analysis has targeted spectra where improved wavelengths and oscillator strengths are needed. We will demonstrate how experimentally derived atomic data have improved our spectral analysis, and illuminate where more work still is needed.

A wavelet transform algorithm for peak detection and application to powder x-ray diffraction data.

PubMed

Gregoire, John M; Dale, Darren; van Dover, R Bruce

2011-01-01

Peak detection is ubiquitous in the analysis of spectral data. While many noise-filtering algorithms and peak identification algorithms have been developed, recent work [P. Du, W. Kibbe, and S. Lin, Bioinformatics 22, 2059 (2006); A. Wee, D. Grayden, Y. Zhu, K. Petkovic-Duran, and D. Smith, Electrophoresis 29, 4215 (2008)] has demonstrated that both of these tasks are efficiently performed through analysis of the wavelet transform of the data. In this paper, we present a wavelet-based peak detection algorithm with user-defined parameters that can be readily applied to the application of any spectral data. Particular attention is given to the algorithm's resolution of overlapping peaks. The algorithm is implemented for the analysis of powder diffraction data, and successful detection of Bragg peaks is demonstrated for both low signal-to-noise data from theta-theta diffraction of nanoparticles and combinatorial x-ray diffraction data from a composition spread thin film. These datasets have different types of background signals which are effectively removed in the wavelet-based method, and the results demonstrate that the algorithm provides a robust method for automated peak detection.

Assessment of Infrared Sounder Radiometric Noise from Analysis of Spectral Residuals

NASA Astrophysics Data System (ADS)

Dufour, E.; Klonecki, A.; Standfuss, C.; Tournier, B.; Serio, C.; Masiello, G.; Tjemkes, S.; Stuhlmann, R.

2016-08-01

For the preparation and performance monitoring of the future generation of hyperspectral InfraRed sounders dedicated to the precise vertical profiling of the atmospheric state, such as the Meteosat Third Generation hyperspectral InfraRed Sounder, a reliable assessment of the instrument radiometric error covariance matrix is needed.Ideally, an inflight estimation of the radiometrric noise is recommended as certain sources of noise can be driven by the spectral signature of the observed Earth/ atmosphere radiance. Also, unknown correlated noise sources, generally related to incomplete knowledge of the instrument state, can be present, so a caracterisation of the noise spectral correlation is also neeed.A methodology, relying on the analysis of post-retreival spectral residuals, is designed and implemented to derive in-flight the covariance matrix on the basis of Earth scenes measurements. This methodology is successfully demonstrated using IASI observations as MTG-IRS proxy data and made it possible to highlight anticipated correlation structures explained by apodization and micro-vibration effects (ghost). This analysis is corroborated by a parallel estimation based on an IASI black body measurement dataset and the results of an independent micro-vibration model.

Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis

NASA Astrophysics Data System (ADS)

Li, D.; Xu, L.; Peng, J.; Ma, J.

2018-04-01

Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.

An evaluation of random analysis methods for the determination of panel damping

NASA Technical Reports Server (NTRS)

Bhat, W. V.; Wilby, J. F.

1972-01-01

An analysis is made of steady-state and non-steady-state methods for the measurement of panel damping. Particular emphasis is placed on the use of random process techniques in conjunction with digital data reduction methods. The steady-state methods considered use the response power spectral density, response autocorrelation, excitation-response crosspower spectral density, or single-sided Fourier transform (SSFT) of the response autocorrelation function. Non-steady-state methods are associated mainly with the use of rapid frequency sweep excitation. Problems associated with the practical application of each method are evaluated with specific reference to the case of a panel exposed to a turbulent airflow, and two methods, the power spectral density and the single-sided Fourier transform methods, are selected as being the most suitable. These two methods are demonstrated experimentally, and it is shown that the power spectral density method is satisfactory under most conditions, provided that appropriate corrections are applied to account for filter bandwidth and background noise errors. Thus, the response power spectral density method is recommended for the measurement of the damping of panels exposed to a moving airflow.

Karhunen-Loève treatment to remove noise and facilitate data analysis in sensing, spectroscopy and other applications.

PubMed

Zaharov, V V; Farahi, R H; Snyder, P J; Davison, B H; Passian, A

2014-11-21

Resolving weak spectral variations in the dynamic response of materials that are either dominated or excited by stochastic processes remains a challenge. Responses that are thermal in origin are particularly relevant examples due to the delocalized nature of heat. Despite its inherent properties in dealing with stochastic processes, the Karhunen-Loève expansion has not been fully exploited in measurement of systems that are driven solely by random forces or can exhibit large thermally driven random fluctuations. Here, we present experimental results and analysis of the archetypes (a) the resonant excitation and transient response of an atomic force microscope probe by the ambient random fluctuations and nanoscale photothermal sample response, and (b) the photothermally scattered photons in pump-probe spectroscopy. In each case, the dynamic process is represented as an infinite series with random coefficients to obtain pertinent frequency shifts and spectral peaks and demonstrate spectral enhancement for a set of compounds including the spectrally complex biomass. The considered cases find important applications in nanoscale material characterization, biosensing, and spectral identification of biological and chemical agents.

Parametric mapping using spectral analysis for 11C-PBR28 PET reveals neuroinflammation in mild cognitive impairment subjects.

PubMed

Fan, Zhen; Dani, Melanie; Femminella, Grazia D; Wood, Melanie; Calsolaro, Valeria; Veronese, Mattia; Turkheimer, Federico; Gentleman, Steve; Brooks, David J; Hinz, Rainer; Edison, Paul

2018-07-01

Neuroinflammation and microglial activation play an important role in amnestic mild cognitive impairment (MCI) and Alzheimer's disease. In this study, we investigated the spatial distribution of neuroinflammation in MCI subjects, using spectral analysis (SA) to generate parametric maps and quantify 11 C-PBR28 PET, and compared these with compartmental and other kinetic models of quantification. Thirteen MCI and nine healthy controls were enrolled in this study. Subjects underwent 11 C-PBR28 PET scans with arterial cannulation. Spectral analysis with an arterial plasma input function was used to generate 11 C-PBR28 parametric maps. These maps were then compared with regional 11 C-PBR28 V T (volume of distribution) using a two-tissue compartment model and Logan graphic analysis. Amyloid load was also assessed with 18 F-Flutemetamol PET. With SA, three component peaks were identified in addition to blood volume. The 11 C-PBR28 impulse response function (IRF) at 90 min produced the lowest coefficient of variation. Single-subject analysis using this IRF demonstrated microglial activation in five out of seven amyloid-positive MCI subjects. IRF parametric maps of 11 C-PBR28 uptake revealed a group-wise significant increase in neuroinflammation in amyloid-positive MCI subjects versus HC in multiple cortical association areas, and particularly in the temporal lobe. Interestingly, compartmental analysis detected group-wise increase in 11 C-PBR28 binding in the thalamus of amyloid-positive MCI subjects, while Logan parametric maps did not perform well. This study demonstrates for the first time that spectral analysis can be used to generate parametric maps of 11 C-PBR28 uptake, and is able to detect microglial activation in amyloid-positive MCI subjects. IRF parametric maps of 11 C-PBR28 uptake allow voxel-wise single-subject analysis and could be used to evaluate microglial activation in individual subjects.

A two-step along-track spectral analysis for estimating the magnetic signals of magnetospheric ring current from Swarm data

NASA Astrophysics Data System (ADS)

Martinec, Zdeněk; Velímský, Jakub; Haagmans, Roger; Šachl, Libor

2018-02-01

This study deals with the analysis of Swarm vector magnetic field measurements in order to estimate the magnetic field of magnetospheric ring current. For a single Swarm satellite, the magnetic measurements are processed by along-track spectral analysis on a track-by-track basis. The main and lithospheric magnetic fields are modelled by the CHAOS-6 field model and subtracted from the along-track Swarm magnetic data. The mid-latitude residual signal is then spectrally analysed and extrapolated to the polar regions. The resulting model of the magnetosphere (model MME) is compared to the existing Swarm Level 2 magnetospheric field model (MMA_SHA_2C). The differences of up to 10 nT are found on the nightsides Swarm data from 2014 April 8 to May 10, which are due to different processing schemes used to construct the two magnetospheric magnetic field models. The forward-simulated magnetospheric magnetic field generated by the external part of model MME then demonstrates the consistency of the separation of the Swarm along-track signal into the external and internal parts by the two-step along-track spectral analysis.

On modelling three-dimensional piezoelectric smart structures with boundary spectral element method

NASA Astrophysics Data System (ADS)

Zou, Fangxin; Aliabadi, M. H.

2017-05-01

The computational efficiency of the boundary element method in elastodynamic analysis can be significantly improved by employing high-order spectral elements for boundary discretisation. In this work, for the first time, the so-called boundary spectral element method is utilised to formulate the piezoelectric smart structures that are widely used in structural health monitoring (SHM) applications. The resultant boundary spectral element formulation has been validated by the finite element method (FEM) and physical experiments. The new formulation has demonstrated a lower demand on computational resources and a higher numerical stability than commercial FEM packages. Comparing to the conventional boundary element formulation, a significant reduction in computational expenses has been achieved. In summary, the boundary spectral element formulation presented in this paper provides a highly efficient and stable mathematical tool for the development of SHM applications.

Stability analysis of spectral methods for hyperbolic initial-boundary value systems

NASA Technical Reports Server (NTRS)

Gottlieb, D.; Lustman, L.; Tadmor, E.

1986-01-01

A constant coefficient hyperbolic system in one space variable, with zero initial data is discussed. Dissipative boundary conditions are imposed at the two points x = + or - 1. This problem is discretized by a spectral approximation in space. Sufficient conditions under which the spectral numerical solution is stable are demonstrated - moreover, these conditions have to be checked only for scalar equations. The stability theorems take the form of explicit bounds for the norm of the solution in terms of the boundary data. The dependence of these bounds on N, the number of points in the domain (or equivalently the degree of the polynomials involved), is investigated for a class of standard spectral methods, including Chebyshev and Legendre collocations.

Remote Stratigraphic Analysis: Combined TM and AIS Results in the Wind River/bighorn Basin Area, Wyoming

NASA Technical Reports Server (NTRS)

Lang, H. R.; Paylor, E. D.; Adams, S.

1985-01-01

An in-progress study demonstrates the utility of airborne imaging spectrometer (AIS) data for unraveling the stratigraphic evolution of a North American, western interior foreland basin. AIS data are used to determine the stratigraphic distribution of mineralogical facies that are diagnostic of specific depositional environments. After wavelength and amplitude calibration using natural ground targets with known spectral characteristics, AIS data identify calcite, dolomite, gypsum and montmorillonite-bearing strata in the Permian-Cretaceous sequence. Combined AIS and TM results illustrate the feasibility of spectral stratigraphy, remote analysis of stratigraphic sequences.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

NASA Astrophysics Data System (ADS)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

Pretreatment and integrated analysis of spectral data reveal seaweed similarities based on chemical diversity.

PubMed

Wei, Feifei; Ito, Kengo; Sakata, Kenji; Date, Yasuhiro; Kikuchi, Jun

2015-03-03

Extracting useful information from high dimensionality and large data sets is a major challenge for data-driven approaches. The present study was aimed at developing novel integrated analytical strategies for comprehensively characterizing seaweed similarities based on chemical diversity. The chemical compositions of 107 seaweed and 2 seagrass samples were analyzed using multiple techniques, including Fourier transform infrared (FT-IR) and solid- and solution-state nuclear magnetic resonance (NMR) spectroscopy, thermogravimetry-differential thermal analysis (TG-DTA), inductively coupled plasma-optical emission spectrometry (ICP-OES), CHNS/O total elemental analysis, and isotope ratio mass spectrometry (IR-MS). The spectral data were preprocessed using non-negative matrix factorization (NMF) and NMF combined with multivariate curve resolution-alternating least-squares (MCR-ALS) methods in order to separate individual component information from the overlapping and/or broad spectral peaks. Integrated analysis of the preprocessed chemical data demonstrated distinct discrimination of differential seaweed species. Further network analysis revealed a close correlation between the heavy metal elements and characteristic components of brown algae, such as cellulose, alginic acid, and sulfated mucopolysaccharides, providing a componential basis for its metal-sorbing potential. These results suggest that this integrated analytical strategy is useful for extracting and identifying the chemical characteristics of diverse seaweeds based on large chemical data sets, particularly complicated overlapping spectral data.

The Raman spectrum character of skin tumor induced by UVB

NASA Astrophysics Data System (ADS)

Wu, Shulian; Hu, Liangjun; Wang, Yunxia; Li, Yongzeng

2016-03-01

In our study, the skin canceration processes induced by UVB were analyzed from the perspective of tissue spectrum. A home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for monitoring the skin changed irradiated by UVB was studied and the discrimination were evaluated. Raman scattering signals of the SCC and normal skin were acquired. Spectral differences in Raman spectra were revealed. Linear discriminant analysis (LDA) based on principal component analysis (PCA) were employed to generate diagnostic algorithms for the classification of skin SCC and normal. The results indicated that Raman spectroscopy combined with PCA-LDA demonstrated good potential for improving the diagnosis of skin cancers.

Binary Population and Spectral Synthesis Version 2.1: Construction, Observational Verification, and New Results

NASA Astrophysics Data System (ADS)

Eldridge, J. J.; Stanway, E. R.; Xiao, L.; McClelland, L. A. S.; Taylor, G.; Ng, M.; Greis, S. M. L.; Bray, J. C.

2017-11-01

The Binary Population and Spectral Synthesis suite of binary stellar evolution models and synthetic stellar populations provides a framework for the physically motivated analysis of both the integrated light from distant stellar populations and the detailed properties of those nearby. We present a new version 2.1 data release of these models, detailing the methodology by which Binary Population and Spectral Synthesis incorporates binary mass transfer and its effect on stellar evolution pathways, as well as the construction of simple stellar populations. We demonstrate key tests of the latest Binary Population and Spectral Synthesis model suite demonstrating its ability to reproduce the colours and derived properties of resolved stellar populations, including well-constrained eclipsing binaries. We consider observational constraints on the ratio of massive star types and the distribution of stellar remnant masses. We describe the identification of supernova progenitors in our models, and demonstrate a good agreement to the properties of observed progenitors. We also test our models against photometric and spectroscopic observations of unresolved stellar populations, both in the local and distant Universe, finding that binary models provide a self-consistent explanation for observed galaxy properties across a broad redshift range. Finally, we carefully describe the limitations of our models, and areas where we expect to see significant improvement in future versions.

The original method for imaging of biological tissues in optical coherence tomography with usage of hyperchromatic lens

NASA Astrophysics Data System (ADS)

Egorov, D. I.

2017-06-01

Our study focuses on an analysis of the original method of investigation biological tissues in the spectral OCT (optical coherence tomography) with usage hyperchromatic lenses. Using hyperchromatic lens, i.e. the lens with uncorrected longitudinal color allows scanning in the depth of the object by changing the wavelength of the emitter. In this case, the depth of the scan will be determined not by the microlens depth of field, but the value of axial color. In our study, we demonstrated the advantages of this method of research on biological tissues existing. Spectral OCT schemes with the hyperchromatic lens could increase the depth of spectral scanning, eliminate the use of multi-channel systems with a set of microscope objectives, reduce the time of measurement. In our paper, we show the developed method of calculation of hyperchromatic lenses and hybrid hyperchromatic lens consisting of a diffractive and refractive component in spectral OCT systems. We also demonstrate the results of aberration calculation designed microscope lenses. We show examples of developed hyperchromatic lenses with the diffractive element and without it.

Monitoring Urban Greenness Dynamics Using Multiple Endmember Spectral Mixture Analysis

PubMed Central

Gan, Muye; Deng, Jinsong; Zheng, Xinyu; Hong, Yang; Wang, Ke

2014-01-01

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development. PMID:25375176

Improvements in Virtual Sensors: Using Spatial Information to Estimate Remote Sensing Spectra

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Srivastava, Ashok N.; Stroeve, Julienne

2005-01-01

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. Sometimes these instruments are built in a phased approach, with additional measurement capabilities added in later phases. In other cases, technology may mature to the point that the instrument offers new measurement capabilities that were not planned in the original design of the instrument. In still other cases, high resolution spectral measurements may be too costly to perform on a large sample and therefore lower resolution spectral instruments are used to take the majority of measurements. Many applied science questions that are relevant to the earth science remote sensing community require analysis of enormous amounts of data that were generated by instruments with disparate measurement capabilities. In past work [1], we addressed this problem using Virtual Sensors: a method that uses models trained on spectrally rich (high spectral resolution) data to "fill in" unmeasured spectral channels in spectrally poor (low spectral resolution) data. We demonstrated this method by using models trained on the high spectral resolution Terra MODIS instrument to estimate what the equivalent of the MODIS 1.6 micron channel would be for the NOAA AVHRR2 instrument. The scientific motivation for the simulation of the 1.6 micron channel is to improve the ability of the AVHRR2 sensor to detect clouds over snow and ice. This work contains preliminary experiments demonstrating that the use of spatial information can improve our ability to estimate these spectra.

Snapshot hyperspectral imaging probe with principal component analysis and confidence ellipse for classification

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-06-01

Hyperspectral imaging combines imaging and spectroscopy to provide detailed spectral information for each spatial point in the image. This gives a three-dimensional spatial-spatial-spectral datacube with hundreds of spectral images. Probe-based hyperspectral imaging systems have been developed so that they can be used in regions where conventional table-top platforms would find it difficult to access. A fiber bundle, which is made up of specially-arranged optical fibers, has recently been developed and integrated with a spectrograph-based hyperspectral imager. This forms a snapshot hyperspectral imaging probe, which is able to form a datacube using the information from each scan. Compared to the other configurations, which require sequential scanning to form a datacube, the snapshot configuration is preferred in real-time applications where motion artifacts and pixel misregistration can be minimized. Principal component analysis is a dimension-reducing technique that can be applied in hyperspectral imaging to convert the spectral information into uncorrelated variables known as principal components. A confidence ellipse can be used to define the region of each class in the principal component feature space and for classification. This paper demonstrates the use of the snapshot hyperspectral imaging probe to acquire data from samples of different colors. The spectral library of each sample was acquired and then analyzed using principal component analysis. Confidence ellipse was then applied to the principal components of each sample and used as the classification criteria. The results show that the applied analysis can be used to perform classification of the spectral data acquired using the snapshot hyperspectral imaging probe.

Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.

PubMed

Valm, Alex M; Mark Welch, Jessica L; Rieken, Christopher W; Hasegawa, Yuko; Sogin, Mitchell L; Oldenbourg, Rudolf; Dewhirst, Floyd E; Borisy, Gary G

2011-03-08

Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escherichia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight fluorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus- and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter- and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares.

PubMed

Fadel, Maya Abou; de Juan, Anna; Vezin, Hervé; Duponchel, Ludovic

2016-12-01

Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra. Copyright © 2016 Elsevier B.V. All rights reserved.

Trade-off studies of a hyperspectral infrared sounder on a geostationary satellite.

PubMed

Wang, Fang; Li, Jun; Schmit, Timothy J; Ackerman, Steven A

2007-01-10

Trade-off studies on spectral coverage, signal-to-noise ratio (SNR), and spectral resolution for a hyperspectral infrared (IR) sounder on a geostationary satellite are summarized. The data density method is applied for the vertical resolution analysis, and the rms error between true and retrieved profiles is used to represent the retrieval accuracy. The effects of spectral coverage, SNR, and spectral resolution on vertical resolution and retrieval accuracy are investigated. The advantages of IR and microwave sounder synergy are also demonstrated. When focusing on instrument performance and data processing, the results from this study show that the preferred spectral coverage combines long-wave infrared (LWIR) with the shorter middle-wave IR (SMidW). Using the appropriate spectral coverage, a hyperspectral IR sounder with appropriate SNR can achieve the required science performance (1 km vertical resolution, 1 K temperature, and 10% relative humidity retrieval accuracy). The synergy of microwave and IR sounders can improve the vertical resolution and retrieval accuracy compared to either instrument alone.

Spectral analysis of the turbulent mixing of two fluids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steinkamp, M.J.

1996-02-01

The authors describe a spectral approach to the investigation of fluid instability, generalized turbulence, and the interpenetration of fluids across an interface. The technique also applies to a single fluid with large variations in density. Departures of fluctuating velocity components from the local mean are far subsonic, but the mean Mach number can be large. Validity of the description is demonstrated by comparisons with experiments on turbulent mixing due to the late stages of Rayleigh-Taylor instability, when the dynamics become approximately self-similar in response to a constant body force. Generic forms for anisotropic spectral structure are described and used asmore » a basis for deriving spectrally integrated moment equations that can be incorporated into computer codes for scientific and engineering analyses.« less

Short-Term EEG Spectral Pattern as a Single Event in EEG Phenomenology

PubMed Central

Fingelkurts, Al. A; Fingelkurts, An. A

2010-01-01

Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a “static” picture which cannot reflect adequately the underlying neurodynamic. A relatively new promising area in the study of EEG is based on reducing the signal to elementary short-term spectra of various types in accordance with the number of types of EEG stationary segments instead of using averaged power spectrum for the whole EEG. It is suggested that the various perceptual and cognitive operations associated with a mental or behavioural condition constitute a single distinguishable neurophysiological state with a distinct and reliable spectral pattern. In this case, one type of short-term spectral pattern may be considered as a single event in EEG phenomenology. To support this assumption the following issues are considered in detail: (a) the relations between local EEG short-term spectral pattern of particular type and the actual state of the neurons in underlying network and a volume conduction; (b) relationship between morphology of EEG short-term spectral pattern and the state of the underlying neurodynamical system i.e. neuronal assembly; (c) relation of different spectral pattern components to a distinct physiological mechanism; (d) relation of different spectral pattern components to different functional significance; (e) developmental changes of spectral pattern components; (f) heredity of the variance in the individual spectral pattern and its components; (g) intra-individual stability of the sets of EEG short-term spectral patterns and their percent ratio; (h) discrete dynamics of EEG short-term spectral patterns. Functional relevance (consistency) of EEG short-term spectral patterns in accordance with the changes of brain functional state, cognitive task and with different neuropsychopathologies is demonstrated. PMID:21379390

Label-free observation of tissues by high-speed stimulated Raman spectral microscopy and independent component analysis

NASA Astrophysics Data System (ADS)

Ozeki, Yasuyuki; Otsuka, Yoichi; Sato, Shuya; Hashimoto, Hiroyuki; Umemura, Wataru; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi

2013-02-01

We have developed a video-rate stimulated Raman scattering (SRS) microscope with frame-by-frame wavenumber tunability. The system uses a 76-MHz picosecond Ti:sapphire laser and a subharmonically synchronized, 38-MHz Yb fiber laser. The Yb fiber laser pulses are spectrally sliced by a fast wavelength-tunable filter, which consists of a galvanometer scanner, a 4-f optical system and a reflective grating. The spectral resolution of the filter is ~ 3 cm-1. The wavenumber was scanned from 2800 to 3100 cm-1 with an arbitrary waveform synchronized to the frame trigger. For imaging, we introduced a 8-kHz resonant scanner and a galvanometer scanner. We were able to acquire SRS images of 500 x 480 pixels at a frame rate of 30.8 frames/s. Then these images were processed by principal component analysis followed by a modified algorithm of independent component analysis. This algorithm allows blind separation of constituents with overlapping Raman bands from SRS spectral images. The independent component (IC) spectra give spectroscopic information, and IC images can be used to produce pseudo-color images. We demonstrate various label-free imaging modalities such as 2D spectral imaging of the rat liver, two-color 3D imaging of a vessel in the rat liver, and spectral imaging of several sections of intestinal villi in the mouse. Various structures in the tissues such as lipid droplets, cytoplasm, fibrous texture, nucleus, and water-rich region were successfully visualized.

Intelligent Unmanned Monitoring of Remediated Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emile Fiesler, Ph.D.

During this Phase I project, IOS demonstrated the feasibility of combining digital signal processing and neural network analysis to analyze spectral signals from pure samples of several typical contaminants. We fabricated and tested a prototype system by automatically analyzing Raman spectral data taken in the Vadose zone at the 321 M site in the M area of DOE's Savannah River Site in South Carolina. This test demonstration proved the ability of IOS's technology to detect the target contaminants, tetrachloroethylene (PCE) and trichloroethylene (TCE), in isolation, and to detect the spectra of these contaminants in real-world noisy samples taken from amore » mixture of materials obtained from this typical remediation target site.« less

Multivariable passive RFID vapor sensors: roll-to-roll fabrication on a flexible substrate.

PubMed

Potyrailo, Radislav A; Burns, Andrew; Surman, Cheryl; Lee, D J; McGinniss, Edward

2012-06-21

We demonstrate roll-to-roll (R2R) fabrication of highly selective, battery-free radio frequency identification (RFID) sensors on a flexible polyethylene terephthalate (PET) polymeric substrate. Selectivity of our developed RFID sensors is provided by measurements of their resonance impedance spectra, followed by the multivariate analysis of spectral features, and correlation of these spectral features to the concentrations of vapors of interest. The multivariate analysis of spectral features also provides the ability for the rejection of ambient interferences. As a demonstration of our R2R fabrication process, we employed polyetherurethane (PEUT) as a "classic" sensing material, extruded this sensing material as 25, 75, and 125-μm thick films, and thermally laminated the films onto RFID inlays, rapidly producing approximately 5000 vapor sensors. We further tested these RFID vapor sensors for their response selectivity toward several model vapors such as toluene, acetone, and ethanol as well as water vapor as an abundant interferent. Our RFID sensing concept features 16-bit resolution provided by the sensor reader, granting a highly desired independence from costly proprietary RFID memory chips with a low-resolution analog input. Future steps are being planned for field-testing of these sensors in numerous conditions.

Numerical solution of the unsteady diffusion-convection-reaction equation based on improved spectral Galerkin method

NASA Astrophysics Data System (ADS)

Zhong, Jiaqi; Zeng, Cheng; Yuan, Yupeng; Zhang, Yuzhe; Zhang, Ye

2018-04-01

The aim of this paper is to present an explicit numerical algorithm based on improved spectral Galerkin method for solving the unsteady diffusion-convection-reaction equation. The principal characteristics of this approach give the explicit eigenvalues and eigenvectors based on the time-space separation method and boundary condition analysis. With the help of Fourier series and Galerkin truncation, we can obtain the finite-dimensional ordinary differential equations which facilitate the system analysis and controller design. By comparing with the finite element method, the numerical solutions are demonstrated via two examples. It is shown that the proposed method is effective.

RIBAVIRIN: The analysis of a polymorphic substance by LC-MS and FTIR spectroscopy

NASA Astrophysics Data System (ADS)

Machal, A. C.; Flurer, R. A.; Brueggemeyer, T. W.; Ellis, L. E.; Satzger, R. D.; Stewart, K. R.

1998-06-01

The FTIR laboratory often has the task of identifying unknown pharmaceuticals. This case involves unknown capsules received at the Forensic Chemistry Center. Through extensive searching of pharmaceutical data bases, it was concluded that the capsules might contain ribavirin, which is classified as an anti-viral agent. Mass spectral analysis (LC-MS) concluded that the capsules contained ribavirin; however, the FTIR results did not agree with the mass spectral results. Additional experiments were performed and the results demonstrate the capabilities of FTIR to discern differences between polymorphic forms of a substance, such as ribavirin, when other techniques are unable to provide this information.

From ultraviolet to Prussian blue: a spectral response for the cyanotype process and a safe educational activity to explain UV exposure for all ages.

PubMed

Turner, J; Parisi, A V; Downs, N; Lynch, M

2014-12-01

Engaging students and the public in understanding UV radiation and its effects is achievable using the real time experiment that incorporates blueprint paper, an "educational toy" that is a safe and easy demonstration of the cyanotype chemical process. The cyanotype process works through the presence of UV radiation. The blueprint paper was investigated to be used as not only engagement in discussion for public outreach about UV radiation, but also as a practical way to introduce the exploration of measurement of UV radiation exposure and as a consequence, digital image analysis. Tests of print methods and experiments, dose response, spectral response and dark response were investigated. Two methods of image analysis for dose response calculation are provided using easy to access software and two methods of pixel count analysis were used to determine spectral response characteristics. Variation in manufacture of the blueprint paper product indicates some variance between measurements. Most importantly, as a result of this investigation, a preliminary spectral response range for the radiation required to produce the cyanotype reaction is presented here, which has until now been unknown.

Robust Multipoint Water-Fat Separation Using Fat Likelihood Analysis

PubMed Central

Yu, Huanzhou; Reeder, Scott B.; Shimakawa, Ann; McKenzie, Charles A.; Brittain, Jean H.

2016-01-01

Fat suppression is an essential part of routine MRI scanning. Multiecho chemical-shift based water-fat separation methods estimate and correct for Bo field inhomogeneity. However, they must contend with the intrinsic challenge of water-fat ambiguity that can result in water-fat swapping. This problem arises because the signals from two chemical species, when both are modeled as a single discrete spectral peak, may appear indistinguishable in the presence of Bo off-resonance. In conventional methods, the water-fat ambiguity is typically removed by enforcing field map smoothness using region growing based algorithms. In reality, the fat spectrum has multiple spectral peaks. Using this spectral complexity, we introduce a novel concept that identifies water and fat for multiecho acquisitions by exploiting the spectral differences between water and fat. A fat likelihood map is produced to indicate if a pixel is likely to be water-dominant or fat-dominant by comparing the fitting residuals of two different signal models. The fat likelihood analysis and field map smoothness provide complementary information, and we designed an algorithm (Fat Likelihood Analysis for Multiecho Signals) to exploit both mechanisms. It is demonstrated in a wide variety of data that the Fat Likelihood Analysis for Multiecho Signals algorithm offers highly robust water-fat separation for 6-echo acquisitions, particularly in some previously challenging applications. PMID:21842498

Groupwise shape analysis of the hippocampus using spectral matching

NASA Astrophysics Data System (ADS)

Shakeri, Mahsa; Lombaert, Hervé; Lippé, Sarah; Kadoury, Samuel

2014-03-01

The hippocampus is a prominent subcortical feature of interest in many neuroscience studies. Its subtle morphological changes often predicate illnesses, including Alzheimer's, schizophrenia or epilepsy. The precise location of structural differences requires a reliable correspondence between shapes across a population. In this paper, we propose an automated method for groupwise hippocampal shape analysis based on a spectral decomposition of a group of shapes to solve the correspondence problem between sets of meshes. The framework generates diffeomorphic correspondence maps across a population, which enables us to create a mean shape. Morphological changes are then located between two groups of subjects. The performance of the proposed method was evaluated on a dataset of 42 hippocampus shapes and compared with a state-of-the-art structural shape analysis approach, using spherical harmonics. Difference maps between mean shapes of two test groups demonstrates that the two approaches showed results with insignificant differences, while Gaussian curvature measures calculated between matched vertices showed a better fit and reduced variability with spectral matching.

[Local Regression Algorithm Based on Net Analyte Signal and Its Application in Near Infrared Spectral Analysis].

PubMed

Zhang, Hong-guang; Lu, Jian-gang

2016-02-01

Abstract To overcome the problems of significant difference among samples and nonlinearity between the property and spectra of samples in spectral quantitative analysis, a local regression algorithm is proposed in this paper. In this algorithm, net signal analysis method(NAS) was firstly used to obtain the net analyte signal of the calibration samples and unknown samples, then the Euclidean distance between net analyte signal of the sample and net analyte signal of calibration samples was calculated and utilized as similarity index. According to the defined similarity index, the local calibration sets were individually selected for each unknown sample. Finally, a local PLS regression model was built on each local calibration sets for each unknown sample. The proposed method was applied to a set of near infrared spectra of meat samples. The results demonstrate that the prediction precision and model complexity of the proposed method are superior to global PLS regression method and conventional local regression algorithm based on spectral Euclidean distance.

[Rapid assessment of critical quality attributes of Chinese materia medica (II): strategy of NIR assignment].

PubMed

Pei, Yan-Ling; Wu, Zhi-Sheng; Shi, Xin-Yuan; Zhou, Lu-Wei; Qiao, Yan-Jiang

2014-09-01

The present paper firstly reviewed the research progress and main methods of NIR spectral assignment coupled with our research results. Principal component analysis was focused on characteristic signal extraction to reflect spectral differences. Partial least squares method was concerned with variable selection to discover characteristic absorption band. Two-dimensional correlation spectroscopy was mainly adopted for spectral assignment. Autocorrelation peaks were obtained from spectral changes, which were disturbed by external factors, such as concentration, temperature and pressure. Density functional theory was used to calculate energy from substance structure to establish the relationship between molecular energy and spectra change. Based on the above reviewed method, taking a NIR spectral assignment of chlorogenic acid as example, a reliable spectral assignment for critical quality attributes of Chinese materia medica (CMM) was established using deuterium technology and spectral variable selection. The result demonstrated the assignment consistency according to spectral features of different concentrations of chlorogenic acid and variable selection region of online NIR model in extract process. Although spectral assignment was initial using an active pharmaceutical ingredient, it is meaningful to look forward to the futurity of the complex components in CMM. Therefore, it provided methodology for NIR spectral assignment of critical quality attributes in CMM.

Polychromatic spectral pattern analysis of ultra-weak photon emissions from a human body.

PubMed

Kobayashi, Masaki; Iwasa, Torai; Tada, Mika

2016-06-01

Ultra-weak photon emission (UPE), often designated as biophoton emission, is generally observed in a wide range of living organisms, including human beings. This phenomenon is closely associated with reactive oxygen species (ROS) generated during normal metabolic processes and pathological states induced by oxidative stress. Application of UPE extracting the pathophysiological information has long been anticipated because of its potential non-invasiveness, facilitating its diagnostic use. Nevertheless, its weak intensity and UPE mechanism complexity hinder its use for practical applications. Spectroscopy is crucially important for UPE analysis. However, filter-type spectroscopy technique, used as a conventional method for UPE analysis, intrinsically limits its performance because of its monochromatic scheme. To overcome the shortcomings of conventional methods, the authors developed a polychromatic spectroscopy system for UPE spectral pattern analysis. It is based on a highly efficient lens systems and a transmission-type diffraction grating with a highly sensitive, cooled, charge-coupled-device (CCD) camera. Spectral pattern analysis of the human body was done for a fingertip using the developed system. The UPE spectrum covers the spectral range of 450-750nm, with a dominant emission region of 570-670nm. The primary peak is located in the 600-650nm region. Furthermore, application of UPE source exploration was demonstrated with the chemiluminescence spectrum of melanin and coexistence with oxidized linoleic acid. Copyright © 2016 Elsevier B.V. All rights reserved.

Spectral-domain optical coherence tomography of roth spots.

PubMed

Giovinazzo, Jerome; Mrejen, Sarah; Freund, K Bailey

2013-01-01

To describe the retinal findings of subacute bacterial endocarditis, their evolution after treatment, and analysis with spectral-domain optical coherence tomography. Retrospective chart review. A 21-year-old man presented with the sudden onset of a central scotoma in his left eye because of a sub-internal limiting membrane hemorrhage overlying the left fovea. When examined 2 weeks later, Roth spots were noted in his right eye. The patient was immediately referred to his internist and diagnosed with subacute bacterial endocarditis with cultures positive for Streptococcus viridans. He subsequently underwent aortic valve replacement surgery after 4 weeks of intravenous antibiotic therapy. When examined 4 weeks after valve replacement surgery, there was regression of the Roth spots. The present case demonstrates the importance of a funduscopic examination in the early diagnosis and management of subacute bacterial endocarditis. The analysis of Roth spots with spectral-domain optical coherence tomography suggested that they were septic emboli.

Modeling Electronic-Nuclear Interactions for Excitation Energy Transfer Processes in Light-Harvesting Complexes.

PubMed

Lee, Mi Kyung; Coker, David F

2016-08-18

An accurate approach for computing intermolecular and intrachromophore contributions to spectral densities to describe the electronic-nuclear interactions relevant for modeling excitation energy transfer processes in light harvesting systems is presented. The approach is based on molecular dynamics (MD) calculations of classical correlation functions of long-range contributions to excitation energy fluctuations and a separate harmonic analysis and single-point gradient quantum calculations for electron-intrachromophore vibrational couplings. A simple model is also presented that enables detailed analysis of the shortcomings of standard MD-based excitation energy fluctuation correlation function approaches. The method introduced here avoids these problems, and its reliability is demonstrated in accurate predictions for bacteriochlorophyll molecules in the Fenna-Matthews-Olson pigment-protein complex, where excellent agreement with experimental spectral densities is found. This efficient approach can provide instantaneous spectral densities for treating the influence of fluctuations in environmental dissipation on fast electronic relaxation.

Automated measurement of birefringence - Development and experimental evaluation of the techniques

NASA Technical Reports Server (NTRS)

Voloshin, A. S.; Redner, A. S.

1989-01-01

Traditional photoelasticity has started to lose its appeal since it requires a well-trained specialist to acquire and interpret results. A spectral-contents-analysis approach may help to revive this old, but still useful technique. Light intensity of the beam passed through the stressed specimen contains all the information necessary to automatically extract the value of retardation. This is done by using a photodiode array to investigate the spectral contents of the light beam. Three different techniques to extract the value of retardation from the spectral contents of the light are discussed and evaluated. An experimental system was built which demonstrates the ability to evaluate retardation values in real time.

Analysis of multispectral and hyperspectral longwave infrared (LWIR) data for geologic mapping

NASA Astrophysics Data System (ADS)

Kruse, Fred A.; McDowell, Meryl

2015-05-01

Multispectral MODIS/ASTER Airborne Simulator (MASTER) data and Hyperspectral Thermal Emission Spectrometer (HyTES) data covering the 8 - 12 μm spectral range (longwave infrared or LWIR) were analyzed for an area near Mountain Pass, California. Decorrelation stretched images were initially used to highlight spectral differences between geologic materials. Both datasets were atmospherically corrected using the ISAC method, and the Normalized Emissivity approach was used to separate temperature and emissivity. The MASTER data had 10 LWIR spectral bands and approximately 35-meter spatial resolution and covered a larger area than the HyTES data, which were collected with 256 narrow (approximately 17nm-wide) spectral bands at approximately 2.3-meter spatial resolution. Spectra for key spatially-coherent, spectrally-determined geologic units for overlap areas were overlain and visually compared to determine similarities and differences. Endmember spectra were extracted from both datasets using n-dimensional scatterplotting and compared to emissivity spectral libraries for identification. Endmember distributions and abundances were then mapped using Mixture-Tuned Matched Filtering (MTMF), a partial unmixing approach. Multispectral results demonstrate separation of silica-rich vs non-silicate materials, with distinct mapping of carbonate areas and general correspondence to the regional geology. Hyperspectral results illustrate refined mapping of silicates with distinction between similar units based on the position, character, and shape of high resolution emission minima near 9 μm. Calcite and dolomite were separated, identified, and mapped using HyTES based on a shift of the main carbonate emissivity minimum from approximately 11.3 to 11.2 μm respectively. Both datasets demonstrate the utility of LWIR spectral remote sensing for geologic mapping.

Non-invasive, Contrast-enhanced Spectral Imaging of Breast Cancer Signatures in Preclinical Animal Models In vivo

PubMed Central

Ramanujan, V Krishnan; Ren, Songyang; Park, Sangyong; Farkas, Daniel L

2011-01-01

We report here a non-invasive multispectral imaging platform for monitoring spectral reflectance and fluorescence images from primary breast carcinoma and metastatic lymph nodes in preclinical rat model in vivo. The system is built around a monochromator light source and an acousto-optic tunable filter (AOTF) for spectral selection. Quantitative analysis of the measured reflectance profiles in the presence of a widely-used lymphazurin dye clearly demonstrates the capability of the proposed imaging platform to detect tumor-associated spectral signatures in the primary tumors as well as metastatic lymphatics. Tumor-associated changes in vascular oxygenation and interstitial fluid pressure are reasoned to be the physiological sources of the measured reflectance profiles. We also discuss the translational potential of our imaging platform in intra-operative clinical setting. PMID:21572915

Arc-welding quality assurance by means of embedded fiber sensor and spectral processing combining feature selection and neural networks

NASA Astrophysics Data System (ADS)

Mirapeix, J.; García-Allende, P. B.; Cobo, A.; Conde, O.; López-Higuera, J. M.

2007-07-01

A new spectral processing technique designed for its application in the on-line detection and classification of arc-welding defects is presented in this paper. A non-invasive fiber sensor embedded within a TIG torch collects the plasma radiation originated during the welding process. The spectral information is then processed by means of two consecutive stages. A compression algorithm is first applied to the data allowing real-time analysis. The selected spectral bands are then used to feed a classification algorithm, which will be demonstrated to provide an efficient weld defect detection and classification. The results obtained with the proposed technique are compared to a similar processing scheme presented in a previous paper, giving rise to an improvement in the performance of the monitoring system.

A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

NASA Astrophysics Data System (ADS)

Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

2016-11-01

The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

Panchromatic Calibration of Astronomical Observations with State-of-the-Art White Dwarf Model Atmospheres

NASA Astrophysics Data System (ADS)

Rauch, T.

2016-05-01

Theoretical spectral energy distributions (SEDs) of white dwarfs provide a powerful tool for cross-calibration and sensitivity control of instruments from the far infrared to the X-ray energy range. Such SEDs can be calculated from fully metal-line blanketed NLTE model-atmospheres that are e.g. computed by the Tübingen NLTE Model-Atmosphere Package (TMAP) that has arrived at a high level of sophistication. TMAP was successfully employed for the reliable spectral analysis of many hot, compact post-AGB stars. High-quality stellar spectra obtained over a wide energy range establish a data base with a large number of spectral lines of many successive ions of different species. Their analysis allows to determine effective temperatures, surface gravities, and element abundances of individual (pre-)white dwarfs with very small error ranges. We present applications of TMAP SEDs for spectral analyses of hot, compact stars in the parameter range from (pre-) white dwarfs to neutron stars and demonstrate the improvement of flux calibration using white-dwarf SEDs that are e.g. available via registered services in the Virtual Observatory.

Multiwavelength FLIM: new applications and algorithms

NASA Astrophysics Data System (ADS)

Rück, A.; Strat, D.; Dolp, F.; von Einem, B.; von Arnim, C. A. F.

2011-03-01

The combination of time-resolved and spectral resolved techniques as achieved by SLIM (spectrally resolved fluorescence lifetime imaging) improves the analysis of complex situations, when different fluorophores have to be distinguished. This could be the case when endogenous fluorophores of living cells and tissues are observed to identify the redox state and oxidative metabolic changes of the mitochondria. Other examples are FRET (resonant energy transfer) measurements, when different donor/acceptor pairs are observed simultaneously. SLIM is working in the time domain employing excitation with short light pulses and detection of the fluorescence intensity decay in many cases with time-correlated single photon counting (TCSPC). Spectral resolved detection is achieved by a polychromator in the detection path and a 16-channel multianode photomultiplier tube with the appropriate routing electronics. Within this paper special attention will be focused on FRET measurements with respect to protein interactions in Alzheimers disease. Using global analysis as the phasor plot approach or integration of the kinetic equations taking into account the multidimensional datasets in every spectral channel we could demonstrate considerable improvement of our calculations.

Quantile regression applied to spectral distance decay

USGS Publications Warehouse

Rocchini, D.; Cade, B.S.

2008-01-01

Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.01), considering both OLS and quantile regressions. Nonetheless, the OLS regression estimate of the mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when the spectral distance approaches zero, was very low compared with the intercepts of the upper quantiles, which detected high species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.

Spectral distance decay: Assessing species beta-diversity by quantile regression

USGS Publications Warehouse

Rocchinl, D.; Nagendra, H.; Ghate, R.; Cade, B.S.

2009-01-01

Remotely sensed data represents key information for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (ols) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.05) considering both ols and quantile regression. Nonetheless, ols regression estimate of mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Toward Improved Hyperspectral Analysis in Semiarid Systems

NASA Astrophysics Data System (ADS)

Glenn, N. F.; Mitchell, J.

2012-12-01

Idaho State University's Boise Center Aerospace Laboratory (BCAL) has processed and applied hyperspectral data for a variety of biophysical sciences in semiarid systems over the past 10 years. HyMap hyperspectral data have been used in most of these studies, along with AVIRIS, CASI, and PIKA-II data. Our studies began with the detection of individual weed species, such as leafy spurge, corroborated with extensive field analysis, including spectrometer data. Early contributions to the field of hyperspectral analysis included the use of: time-series datasets and classification threshold methods for target detection, and subpixel analysis for characterizing weed invasions and post-fire vegetation and soil conditions. Subsequent studies optimized subpixel unmixing performance using spectral subsetting and vegetation abundance investigations. More recent studies have extended the application of hyperspectral data from individual plant species detection to identification of biochemical constituents. We demonstrated field and airborne hyperspectral Nitrogen absorption in sagebrush using combinations of data reduction and spectral transformation techniques (i.e., continuum removal, derivative analysis, partial least squares regression). In spite of these and many other successful demonstrations, gaps still exist in effective species level discrimination due to the high complexity of soil and nonlinear mixing in semiarid shrubland. BCAL studies are currently focusing on complimenting narrowband vegetation indices with LiDAR (light detection and ranging, both airborne and ground-based) derivatives to improve vegetation cover predictions. Future combinations of LiDAR and hyperspectral data will involve exploring the full range spectral information and serve as an integral step in scaling shrub biomass estimates from plot to landscape and regional scales.

A Living Periodic Table.

ERIC Educational Resources Information Center

Marshall, James L.

2000-01-01

Introduces a portable and permanent set of the elemental collection including 87 samples of elements which are, minimum, one gram or more. Demonstrates radioactivity, magnetism, fluorescence, melting solids, spectral analysis, and conduction of heat. Includes a display of minerals associated with the elements. (YDS)

Spectral analysis techniques for characterizing cadmium zinc telluride polarization modulators

NASA Astrophysics Data System (ADS)

FitzGerald, William R.; Taherion, Saeid; Kumar, F. Joseph; Giles, David; Hore, Dennis K.

2018-04-01

The low frequency electro-optic characteristics of cadmium zinc telluride are demonstrated in the mid-infrared, in the spectral range 2.5-11 μm. Conventional methods for characterizing the dynamic response by monitoring the amplitude of the time-varying light intensity do not account for spatial variation in material properties. In such cases, a more revealing method involves monitoring two distinct frequency components in order to characterize the dynamic and static contributions to the optical retardation. We demonstrate that, while this method works well for a ZnSe photo-elastic modulator, it does not fully capture the response of a cadmium zinc telluride electro-optic modulator. Ultimately, we show that acquiring the full waveform of the optical response enables a model to be created that accounts for inhomogeneity in the material that results in an asymmetric response with respect to the polarity of the driving voltage. This technique is applicable to broadband and fixed-wavelength applications in a variety of spectral ranges.

Dual-comb spectroscopy of laser-induced plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergevin, Jenna; Wu, Tsung-Han; Yeak, Jeremy

Dual-comb spectroscopy has become a powerful spectroscopic technique in applications that rely on its broad spectral coverage combined with high frequency resolution capabilities. Experiments to date have primarily focused on detection and analysis of multiple gas species under semi-static conditions, with applications ranging from environmental monitoring of greenhouse gases to high resolution molecular spectroscopy. Here, we utilize dual-comb spectroscopy to demonstrate broadband, high-resolution, and time-resolved measurements in a laser induced plasma for the first time. As a first demonstration, we simultaneously detect trace amounts of Rb and K in solid samples with a single laser ablation shot, with transitions separatedmore » by over 6 THz (13 nm) and spectral resolution sufficient to resolve isotopic and ground state hyperfine splittings of the Rb D2 line. This new spectroscopic approach offers the broad spectral coverage found in the powerful techniques of laser-induced breakdown spectroscopy (LIBS) while providing the high-resolution and accuracy of cw laser-based spectroscopies.« less

Sculpting narrowband Fano resonances inherent in the large-area mid-infrared photonic crystal microresonators for spectroscopic imaging

PubMed Central

Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.

2014-01-01

Fourier transform infrared (FT-IR) imaging spectrometers are almost universally used to record microspectroscopic imaging data in the mid-infrared (mid-IR) spectral region. While the commercial standard, interferometry necessitates collection of large spectral regions, requires a large data handling overhead for microscopic imaging and is slow. Here we demonstrate an approach for mid-IR spectroscopic imaging at selected discrete wavelengths using narrowband resonant filtering of a broadband thermal source, enabled by high-performance guided-mode Fano resonances in one-layer, large-area mid-IR photonic crystals on a glass substrate. The microresonant devices enable discrete frequency IR (DF-IR), in which a limited number of wavelengths that are of interest are recorded using a mechanically robust instrument. This considerably simplifies instrumentation as well as overhead of data acquisition, storage and analysis for large format imaging with array detectors. To demonstrate the approach, we perform DF-IR spectral imaging of a polymer USAF resolution target and human tissue in the C−H stretching region (2600−3300 cm−1). DF-IR spectroscopy and imaging can be generalized to other IR spectral regions and can serve as an analytical tool for environmental and biomedical applications. PMID:25089433

Discrimination of common Mediterranean plant species using field spectroradiometry

NASA Astrophysics Data System (ADS)

Manevski, Kiril; Manakos, Ioannis; Petropoulos, George P.; Kalaitzidis, Chariton

2011-12-01

Field spectroradiometry of land surface objects supports remote sensing analysis, facilitates the discrimination of vegetation species, and enhances the mapping efficiency. Especially in the Mediterranean, spectral discrimination of common vegetation types, such as phrygana and maquis species, remains a challenge. Both phrygana and maquis may be used as a direct indicator for grazing management, fire history and severity, and the state of the wider ecosystem equilibrium. This study aims to investigate the capability of field spectroradiometry supporting remote sensing analysis of the land cover of a characteristic Mediterranean area. Five common Mediterranean maquis and phrygana species were examined. Spectra acquisition was performed during an intensive field campaign deployed in spring 2010, supported by a novel platform MUFSPEM@MED (Mobile Unit for Field SPEctral Measurements at the MEDiterranean) for high canopy measurements. Parametric and non-parametric statistical tests have been applied to the continuum-removed reflectance of the species in the visible to shortwave infrared spectral range. Interpretation of the results indicated distinct discrimination between the studied species at specific spectral regions. Statistically significant wavelengths were principally found in both the visible and the near infrared regions of the electromagnetic spectrum. Spectral bands in the shortwave infrared demonstrated significant discrimination features for the examined species adapted to Mediterranean drought. All in all, results confirmed the prospect for a more accurate mapping of the species spatial distribution using remote sensing imagery coupled with in situ spectral information.

Onboard spectral imager data processor

NASA Astrophysics Data System (ADS)

Otten, Leonard J.; Meigs, Andrew D.; Franklin, Abraham J.; Sears, Robert D.; Robison, Mark W.; Rafert, J. Bruce; Fronterhouse, Donald C.; Grotbeck, Ronald L.

1999-10-01

Previous papers have described the concept behind the MightySat II.1 program, the satellite's Fourier Transform imaging spectrometer's optical design, the design for the spectral imaging payload, and its initial qualification testing. This paper discusses the on board data processing designed to reduce the amount of downloaded data by an order of magnitude and provide a demonstration of a smart spaceborne spectral imaging sensor. Two custom components, a spectral imager interface 6U VME card that moves data at over 30 MByte/sec, and four TI C-40 processors mounted to a second 6U VME and daughter card, are used to adapt the sensor to the spacecraft and provide the necessary high speed processing. A system architecture that offers both on board real time image processing and high-speed post data collection analysis of the spectral data has been developed. In addition to the on board processing of the raw data into a usable spectral data volume, one feature extraction technique has been incorporated. This algorithm operates on the basic interferometric data. The algorithm is integrated within the data compression process to search for uploadable feature descriptions.

Spectral line polarimetry with a channeled polarimeter.

PubMed

van Harten, Gerard; Snik, Frans; Rietjens, Jeroen H H; Martijn Smit, J; Keller, Christoph U

2014-07-01

Channeled spectropolarimetry or spectral polarization modulation is an accurate technique for measuring the continuum polarization in one shot with no moving parts. We show how a dual-beam implementation also enables spectral line polarimetry at the intrinsic resolution, as in a classic beam-splitting polarimeter. Recording redundant polarization information in the two spectrally modulated beams of a polarizing beam-splitter even provides the possibility to perform a postfacto differential transmission correction that improves the accuracy of the spectral line polarimetry. We perform an error analysis to compare the accuracy of spectral line polarimetry to continuum polarimetry, degraded by a residual dark signal and differential transmission, as well as to quantify the impact of the transmission correction. We demonstrate the new techniques with a blue sky polarization measurement around the oxygen A absorption band using the groundSPEX instrument, yielding a polarization in the deepest part of the band of 0.160±0.010, significantly different from the polarization in the continuum of 0.2284±0.0004. The presented methods are applicable to any dual-beam channeled polarimeter, including implementations for snapshot imaging polarimetry.

Snapshot hyperspectral retinal imaging using compact spectral resolving detector array.

PubMed

Li, Hao; Liu, Wenzhong; Dong, Biqin; Kaluzny, Joel V; Fawzi, Amani A; Zhang, Hao F

2017-06-01

Hyperspectral retinal imaging captures the light spectrum from each imaging pixel. It provides spectrally encoded retinal physiological and morphological information, which could potentially benefit diagnosis and therapeutic monitoring of retinal diseases. The key challenges in hyperspectral retinal imaging are how to achieve snapshot imaging to avoid motions between the images from multiple spectral bands, and how to design a compact snapshot imager suitable for clinical use. Here, we developed a compact, snapshot hyperspectral fundus camera for rodents using a novel spectral resolving detector array (SRDA), on which a thin-film Fabry-Perot cavity filter was monolithically fabricated on each imaging pixel. We achieved hyperspectral retinal imaging with 16 wavelength bands (460 to 630 nm) at 20 fps. We also demonstrated false-color vessel contrast enhancement and retinal oxygen saturation (sO 2 ) measurement through spectral analysis. This work could potentially bring hyperspectral retinal imaging from bench to bedside. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bandwidth scalable, coherent transmitter based on the parallel synthesis of multiple spectral slices using optical arbitrary waveform generation.

PubMed

Geisler, David J; Fontaine, Nicolas K; Scott, Ryan P; He, Tingting; Paraschis, Loukas; Gerstel, Ori; Heritage, Jonathan P; Yoo, S J B

2011-04-25

We demonstrate an optical transmitter based on dynamic optical arbitrary waveform generation (OAWG) which is capable of creating high-bandwidth (THz) data waveforms in any modulation format using the parallel synthesis of multiple coherent spectral slices. As an initial demonstration, the transmitter uses only 5.5 GHz of electrical bandwidth and two 10-GHz-wide spectral slices to create 100-ns duration, 20-GHz optical waveforms in various modulation formats including differential phase-shift keying (DPSK), quaternary phase-shift keying (QPSK), and eight phase-shift keying (8PSK) with only changes in software. The experimentally generated waveforms showed clear eye openings and separated constellation points when measured using a real-time digital coherent receiver. Bit-error-rate (BER) performance analysis resulted in a BER < 9.8 × 10(-6) for DPSK and QPSK waveforms. Additionally, we experimentally demonstrate three-slice, 4-ns long waveforms that highlight the bandwidth scalable nature of the optical transmitter. The various generated waveforms show that the key transmitter properties (i.e., packet length, modulation format, data rate, and modulation filter shape) are software definable, and that the optical transmitter is capable of acting as a flexible bandwidth transmitter.

Evaluation of FTIR spectroscopy as diagnostic tool for colorectal cancer using spectral analysis

NASA Astrophysics Data System (ADS)

Dong, Liu; Sun, Xuejun; Chao, Zhang; Zhang, Shiyun; Zheng, Jianbao; Gurung, Rajendra; Du, Junkai; Shi, Jingsen; Xu, Yizhuang; Zhang, Yuanfu; Wu, Jinguang

2014-03-01

The aim of this study is to confirm FTIR spectroscopy as a diagnostic tool for colorectal cancer. 180 freshly removed colorectal samples were collected from 90 patients for spectrum analysis. The ratios of spectral intensity and relative intensity (/I1460) were calculated. Principal component analysis (PCA) and Fisher's discriminant analysis (FDA) were applied to distinguish the malignant from normal. The FTIR parameters of colorectal cancer and normal tissues were distinguished due to the contents or configurations of nucleic acids, proteins, lipids and carbohydrates. Related to nitrogen containing, water, protein and nucleic acid were increased significantly in the malignant group. Six parameters were selected as independent factors to perform discriminant functions. The sensitivity for FTIR in diagnosing colorectal cancer was 96.6% by discriminant analysis. Our study demonstrates that FTIR can be a useful technique for detection of colorectal cancer and may be applied in clinical colorectal cancer diagnosis.

Thermal energy harvesting near-infrared radiation and accessing low temperatures with plasmonic sensors

NASA Astrophysics Data System (ADS)

Karker, Nicholas A.; Dharmalingam, Gnanaprakash; Carpenter, Michael A.

2015-10-01

Near-infrared (NIR) thermal energy harvesting has been demonstrated for gold nanorods (AuNRs), allowing concentration dependent, ppm-level, gas detection of H2, CO, and NO2 at 500 °C without using a white light source. Part-per-million detection capabilities of the gold nanorods are demonstrated with a factor of 11 reduction in collection times in the NIR as compared to measurements made in the visible light region. Decreased collection times are enabled by an increase in S : N ratio, which allowed a demonstration of selectivity through the use of both full spectral and a reduced spectral-based principal component analysis. Furthermore, low temperature thermal imaging spectra have been obtained at sample temperatures ranging from 275-500 °C, showing the possibility of energy harvested gas sensing at lower temperatures. These findings are promising in the area of miniaturizing plasmonic gas sensing technology and integration in areas such as gas turbines.

Smith-Purcell radiation from concave dotted gratings

NASA Astrophysics Data System (ADS)

Sergeeva, D. Yu.; Tishchenko, A. A.; Aryshev, A. S.; Strikhanov, M. N.

2018-02-01

We present the first-principles theory of Smith-Purcell effect from the concave dotted grating consisting of bent chains of separated micro- or nanoparticles. The numerical analysis demonstrates that the obtained spectral-angular distributions change significantly depending on the structure of the grating.

Spectral characteristics of wake vortex sound during roll-up

DOT National Transportation Integrated Search

2003-12-01

This report presents an analysis of the sound spectra generated by a trailing aircraft vortex during its rolling-up process. The : study demonstrates that a rolling-up vortex could produce low frequency (less than 100 Hz) sound with very high intensi...

Effect of toxicity of Ag nanoparticles on SERS spectral variance of bacteria

NASA Astrophysics Data System (ADS)

Cui, Li; Chen, Shaode; Zhang, Kaisong

2015-02-01

Ag nanoparticles (NPs) have been extensively utilized in surface-enhanced Raman scattering (SERS) spectroscopy for bacterial identification. However, Ag NPs are toxic to bacteria. Whether such toxicity can affect SERS features of bacteria and interfere with bacterial identification is still unknown and needed to explore. Here, by carrying out a comparative study on non-toxic Au NPs with that on toxic Ag NPs, we investigated the influence of nanoparticle concentration and incubation time on bacterial SERS spectral variance, both of which were demonstrated to be closely related to the toxicity of Ag NPs. Sensitive spectral alterations were observed on Ag NPs with increase of NPs concentration or incubation time, accompanied with an obvious decrease in number of viable bacteria. In contrast, SERS spectra and viable bacterial number on Au NPs were rather constant under the same conditions. A further analysis on spectral changes demonstrated that it was cell response (i.e. metabolic activity or death) to the toxicity of Ag NPs causing spectral variance. However, biochemical responses to the toxicity of Ag were very different in different bacteria, indicating the complex toxic mechanism of Ag NPs. Ag NPs are toxic to a great variety of organisms, including bacteria, fungi, algae, protozoa etc., therefore, this work will be helpful in guiding the future application of SERS technique in various complex biological systems.

Hyperspectral imaging of polymer banknotes for building and analysis of spectral library

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-11-01

The use of counterfeit banknotes increases crime rates and cripples the economy. New countermeasures are required to stop counterfeiters who use advancing technologies with criminal intent. Many countries started adopting polymer banknotes to replace paper notes, as polymer notes are more durable and have better quality. The research on authenticating such banknotes is of much interest to the forensic investigators. Hyperspectral imaging can be employed to build a spectral library of polymer notes, which can then be used for classification to authenticate these notes. This is however not widely reported and has become a research interest in forensic identification. This paper focuses on the use of hyperspectral imaging on polymer notes to build spectral libraries, using a pushbroom hyperspectral imager which has been previously reported. As an initial study, a spectral library will be built from three arbitrarily chosen regions of interest of five circulated genuine polymer notes. Principal component analysis is used for dimension reduction and to convert the information in the spectral library to principal components. A 99% confidence ellipse is formed around the cluster of principal component scores of each class and then used as classification criteria. The potential of the adopted methodology is demonstrated by the classification of the imaged regions as training samples.

Terahertz Josephson spectral analysis and its applications

NASA Astrophysics Data System (ADS)

Snezhko, A. V.; Gundareva, I. I.; Lyatti, M. V.; Volkov, O. Y.; Pavlovskiy, V. V.; Poppe, U.; Divin, Y. Y.

2017-04-01

Principles of Hilbert-transform spectral analysis (HTSA) are presented and advantages of the technique in the terahertz (THz) frequency range are discussed. THz HTSA requires Josephson junctions with high values of characteristic voltages I c R n and dynamics described by a simple resistively shunted junction (RSJ) model. To meet these requirements, [001]- and [100]-tilt YBa2Cu3O7-x bicrystal junctions with deviations from the RSJ model less than 1% have been developed. Demonstrators of Hilbert-transform spectrum analyzers with various cryogenic environments, including integration into Stirling coolers, are described. Spectrum analyzers have been characterized in the spectral range from 50 GHz to 3 THz. Inside a power dynamic range of five orders, an instrumental function of the analyzers has been found to have a Lorentz form around a single frequency of 1.48 THz with a spectral resolution as low as 0.9 GHz. Spectra of THz radiation from optically pumped gas lasers and semiconductor frequency multipliers have been studied with these spectrum analyzers and the regimes of these radiation sources were optimized for a single-frequency operation. Future applications of HTSA will be related with quick and precise spectral characterization of new radiation sources and identification of substances in the THz frequency range.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

VizieR Online Data Catalog: NLTE spectral analysis of white dwarf G191-B2B (Rauch+, 2013)

NASA Astrophysics Data System (ADS)

Rauch, T.; Werner, K.; Bohlin, R.; Kruk, J. W.

2013-08-01

In the framework of the Virtual Observatory, the German Astrophysical Virtual Observatory developed the registered service TheoSSA. It provides easy access to stellar spectral energy distributions (SEDs) and is intended to ingest SEDs calculated by any model-atmosphere code. In case of the DA white dwarf G191-B2B, we demonstrate that the model reproduces not only its overall continuum shape but also the numerous metal lines exhibited in its ultraviolet spectrum. (3 data files).

Spectroscopic diagnostics of solar flares

NASA Astrophysics Data System (ADS)

Bely-Dubau, F.; Dubau, J.; Faucher, P.; Loulergue, M.; Steenman-Clarke, L.

Observations made with the X-ray polychromator (XRP) on board the Solar Maximum Mission satellite were analyzed. Data from the bent crystal spectrometer portion of the XRP experiment, in the spectral domain 1 to 3 A, with high spectral and temporal resolution, were used. Results for the spectrum analysis of iron are given. The possibility of polarization effects is considered. Although it is demonstrated that hyperfine analyses of a given spectrum are obtainable, provided calculations include large quantities of high precision atomic data, the interpretation is limited by the hypothesis of homogeneity of the emitting plasma.

Mass Spectral Library Quality Assurance by Inter-Library Comparison

NASA Astrophysics Data System (ADS)

Wallace, William E.; Ji, Weihua; Tchekhovskoi, Dmitrii V.; Phinney, Karen W.; Stein, Stephen E.

2017-04-01

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared, the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided.

Multiple-channel guided mode resonance Brewster filter with controllable spectral separation.

PubMed

Ma, Jianyong; Cao, Hongchao; Zhou, Changhe

2014-05-01

In this work, a single-layer, multiple-channel guided mode resonance (GMR) Brewster filter with controllable spectral separation is proposed using the plane waveguide method and rigorous coupled-wave analysis. Based on the normalized eigenvalue equation, the controllability of the spectral separation is analyzed when the fill ratio of the grating layer is changed while its effective index is identical to that of the substrate. The location and the separation between resonances can be specifically controlled by modifying the fill ratio of the grating layer. In contrast to the ordinary GMR filter, where the location of the resonances is material dependent, it is demonstrated that the spectral separation for the first and second resonances can be linearly controlled by altering the fill ratio of the grating layer. In addition, the maximal shift of the second resonance is up to 5% of the first resonant wavelength using the single-layer Brewster filter.

Mass Spectral Library Quality Assurance by Inter-Library Comparison

PubMed Central

Wallace, W.E.; Ji, W.; Tchekhovskoi, D.V.; Phinney, K.W.; Stein, S.E.

2017-01-01

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided. PMID:28127680

Silicon oxide nanoparticles doped PQ-PMMA for volume holographic imaging filters.

PubMed

Luo, Yuan; Russo, Juan M; Kostuk, Raymond K; Barbastathis, George

2010-04-15

Holographic imaging filters are required to have high Bragg selectivity, namely, narrow angular and spectral bandwidth, to obtain spatial-spectral information within a three-dimensional object. In this Letter, we present the design of holographic imaging filters formed using silicon oxide nanoparticles (nano-SiO(2)) in phenanthrenquinone-poly(methyl methacrylate) (PQ-PMMA) polymer recording material. This combination offers greater Bragg selectivity and increases the diffraction efficiency of holographic filters. The holographic filters with optimized ratio of nano-SiO(2) in PQ-PMMA can significantly improve the performance of Bragg selectivity and diffraction efficiency by 53% and 16%, respectively. We present experimental results and data analysis demonstrating this technique in use for holographic spatial-spectral imaging filters.

Cellular imaging using temporally flickering nanoparticles.

PubMed

Ilovitsh, Tali; Danan, Yossef; Meir, Rinat; Meiri, Amihai; Zalevsky, Zeev

2015-02-04

Utilizing the surface plasmon resonance effect in gold nanoparticles enables their use as contrast agents in a variety of applications for compound cellular imaging. However, most techniques suffer from poor signal to noise ratio (SNR) statistics due to high shot noise that is associated with low photon count in addition to high background noise. We demonstrate an effective way to improve the SNR, in particular when the inspected signal is indistinguishable in the given noisy environment. We excite the temporal flickering of the scattered light from gold nanoparticle that labels a biological sample. By preforming temporal spectral analysis of the received spatial image and by inspecting the proper spectral component corresponding to the modulation frequency, we separate the signal from the wide spread spectral noise (lock-in amplification).

Arc-Welding Spectroscopic Monitoring based on Feature Selection and Neural Networks.

PubMed

Garcia-Allende, P Beatriz; Mirapeix, Jesus; Conde, Olga M; Cobo, Adolfo; Lopez-Higuera, Jose M

2008-10-21

A new spectral processing technique designed for application in the on-line detection and classification of arc-welding defects is presented in this paper. A noninvasive fiber sensor embedded within a TIG torch collects the plasma radiation originated during the welding process. The spectral information is then processed in two consecutive stages. A compression algorithm is first applied to the data, allowing real-time analysis. The selected spectral bands are then used to feed a classification algorithm, which will be demonstrated to provide an efficient weld defect detection and classification. The results obtained with the proposed technique are compared to a similar processing scheme presented in previous works, giving rise to an improvement in the performance of the monitoring system.

Spectral analysis of point-vortex dynamics: first application to vortex polygons in a circular domain

NASA Astrophysics Data System (ADS)

Speetjens, M. F. M.; Meleshko, V. V.; van Heijst, G. J. F.

2014-06-01

The present study addresses the classical problem of the dynamics and stability of a cluster of N-point vortices of equal strength arranged in a polygonal configuration (‘N-vortex polygons’). In unbounded domains, such N-vortex polygons are unconditionally stable for N\\leqslant 7. Confinement in a circular domain tightens the stability conditions to N\\leqslant 6 and a maximum polygon size relative to the domain radius. This work expands on existing studies on stability and integrability by a first giving an exploratory spectral analysis of the dynamics of N vortex polygons in circular domains. Key to this is that the spectral signature of the time evolution of vortex positions reflects their qualitative behaviour. Expressing vortex motion by a generic evolution operator (the so-called Koopman operator) provides a rigorous framework for such spectral analyses. This paves the way to further differentiation and classification of point-vortex behaviour beyond stability and integrability. The concept of Koopman-based spectral analysis is demonstrated for N-vortex polygons. This reveals that conditional stability can be seen as a local form of integrability and confirms an important generic link between spectrum and dynamics: discrete spectra imply regular (quasi-periodic) motion; continuous (sub-)spectra imply chaotic motion. Moreover, this exposes rich nonlinear dynamics as intermittency between regular and chaotic motion and quasi-coherent structures formed by chaotic vortices. Dedicated to the memory of Slava Meleshko, a dear friend and inspiring colleague.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.

PubMed

Duffy, Frank H; Als, Heidelise

2012-06-26

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

Autoregressive modeling for the spectral analysis of oceanographic data

NASA Technical Reports Server (NTRS)

Gangopadhyay, Avijit; Cornillon, Peter; Jackson, Leland B.

1989-01-01

Over the last decade there has been a dramatic increase in the number and volume of data sets useful for oceanographic studies. Many of these data sets consist of long temporal or spatial series derived from satellites and large-scale oceanographic experiments. These data sets are, however, often 'gappy' in space, irregular in time, and always of finite length. The conventional Fourier transform (FT) approach to the spectral analysis is thus often inapplicable, or where applicable, it provides questionable results. Here, through comparative analysis with the FT for different oceanographic data sets, the possibilities offered by autoregressive (AR) modeling to perform spectral analysis of gappy, finite-length series, are discussed. The applications demonstrate that as the length of the time series becomes shorter, the resolving power of the AR approach as compared with that of the FT improves. For the longest data sets examined here, 98 points, the AR method performed only slightly better than the FT, but for the very short ones, 17 points, the AR method showed a dramatic improvement over the FT. The application of the AR method to a gappy time series, although a secondary concern of this manuscript, further underlines the value of this approach.

Understanding cancer complexome using networks, spectral graph theory and multilayer framework

NASA Astrophysics Data System (ADS)

Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

2017-02-01

Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

Understanding cancer complexome using networks, spectral graph theory and multilayer framework.

PubMed

Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K; Chowdhury, Rajdeep; Jalan, Sarika

2017-02-03

Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

Toward optimal spatial and spectral quality in widefield infrared spectromicroscopy of IR labelled single cells.

PubMed

Mattson, Eric C; Unger, Miriam; Clède, Sylvain; Lambert, François; Policar, Clotilde; Imtiaz, Asher; D'Souza, Roshan; Hirschmugl, Carol J

2013-10-07

Advancements in widefield infrared spectromicroscopy have recently been demonstrated following the commissioning of IRENI (InfraRed ENvironmental Imaging), a Fourier Transform infrared (FTIR) chemical imaging beamline at the Synchrotron Radiation Center. The present study demonstrates the effects of magnification, spatial oversampling, spectral pre-processing and deconvolution, focusing on the intracellular detection and distribution of an exogenous metal tris-carbonyl derivative 1 in a single MDA-MB-231 breast cancer cell. We demonstrate here that spatial oversampling for synchrotron-based infrared imaging is critical to obtain accurate diffraction-limited images at all wavelengths simultaneously. Resolution criteria and results from raw and deconvoluted images for two Schwarzschild objectives (36×, NA 0.5 and 74×, NA 0.65) are compared to each other and to prior reports for raster-scanned, confocal microscopes. The resolution of the imaging data can be improved by deconvolving the instrumental broadening that is determined with the measured PSFs, which is implemented with GPU programming architecture for fast hyperspectral processing. High definition, rapidly acquired, FTIR chemical images of respective spectral signatures of the cell 1 and shows that 1 is localized next to the phosphate- and Amide-rich regions, in agreement with previous infrared and luminescence studies. The infrared image contrast, localization and definition are improved after applying proven spectral pre-processing (principal component analysis based noise reduction and RMie scattering correction algorithms) to individual pixel spectra in the hyperspectral cube.

Computational analyses of spectral trees from electrospray multi-stage mass spectrometry to aid metabolite identification.

PubMed

Cao, Mingshu; Fraser, Karl; Rasmussen, Susanne

2013-10-31

Mass spectrometry coupled with chromatography has become the major technical platform in metabolomics. Aided by peak detection algorithms, the detected signals are characterized by mass-over-charge ratio (m/z) and retention time. Chemical identities often remain elusive for the majority of the signals. Multi-stage mass spectrometry based on electrospray ionization (ESI) allows collision-induced dissociation (CID) fragmentation of selected precursor ions. These fragment ions can assist in structural inference for metabolites of low molecular weight. Computational investigations of fragmentation spectra have increasingly received attention in metabolomics and various public databases house such data. We have developed an R package "iontree" that can capture, store and analyze MS2 and MS3 mass spectral data from high throughput metabolomics experiments. The package includes functions for ion tree construction, an algorithm (distMS2) for MS2 spectral comparison, and tools for building platform-independent ion tree (MS2/MS3) libraries. We have demonstrated the utilization of the package for the systematic analysis and annotation of fragmentation spectra collected in various metabolomics platforms, including direct infusion mass spectrometry, and liquid chromatography coupled with either low resolution or high resolution mass spectrometry. Assisted by the developed computational tools, we have demonstrated that spectral trees can provide informative evidence complementary to retention time and accurate mass to aid with annotating unknown peaks. These experimental spectral trees once subjected to a quality control process, can be used for querying public MS2 databases or de novo interpretation. The putatively annotated spectral trees can be readily incorporated into reference libraries for routine identification of metabolites.

Laser Doppler velocimeter system simulation for sensing aircraft wake vortices. Part 2: Processing and analysis of LDV data (for runs 1023 and 2023)

NASA Technical Reports Server (NTRS)

Meng, J. C. S.; Thomson, J. A. L.

1975-01-01

A data analysis program constructed to assess LDV system performance, to validate the simulation model, and to test various vortex location algorithms is presented. Real or simulated Doppler spectra versus range and elevation is used and the spatial distributions of various spectral moments or other spectral characteristics are calculated and displayed. Each of the real or simulated scans can be processed by one of three different procedures: simple frequency or wavenumber filtering, matched filtering, and deconvolution filtering. The final output is displayed as contour plots in an x-y coordinate system, as well as in the form of vortex tracks deduced from the maxima of the processed data. A detailed analysis of run number 1023 and run number 2023 is presented to demonstrate the data analysis procedure. Vortex tracks and system range resolutions are compared with theoretical predictions.

Analysis of thematic mapper simulator data collected over eastern North Dakota

NASA Technical Reports Server (NTRS)

Anderson, J. E. (Principal Investigator)

1982-01-01

The results of the analysis of aircraft-acquired thematic mapper simulator (TMS) data, collected to investigate the utility of thematic mapper data in crop area and land cover estimates, are discussed. Results of the analysis indicate that the seven-channel TMS data are capable of delineating the 13 crop types included in the study to an overall pixel classification accuracy of 80.97% correct, with relative efficiencies for four crop types examined between 1.62 and 26.61. Both supervised and unsupervised spectral signature development techniques were evaluated. The unsupervised methods proved to be inferior (based on analysis of variance) for the majority of crop types considered. Given the ground truth data set used for spectral signature development as well as evaluation of performance, it is possible to demonstrate which signature development technique would produce the highest percent correct classification for each crop type.

Spectral-Timing Analysis of Kilohetrz Quasi-Periodic Osciallations in Neutron Star Low-Mass X-ray Binaries

NASA Astrophysics Data System (ADS)

Cackett, Edward; Troyer, Jon; Peille, Philippe; Barret, Didier

2018-01-01

Kilohertz quasi-periodic oscillations or kHz QPOs are intensity variations that occur in the X-ray band observed in neutron star low-mass X-ray binary (LMXB) systems. In such systems, matter is transferred from a secondary low-mass star to a neutron star via the process of accretion. kHz QPOs occur on the timescale of the inner accretion flow and may carry signatures of the physics of strong gravity (c2 ~ GM/R) and possibly clues to constraining the neutron star equation of state (EOS). Both the timing behavior of kHz QPOs and the time-averaged spectra of these systems have been studied extensively. No model derived from these techniques has been able to illuminate the origin of kHz QPOs. Spectral-timing is an analysis technique that can be used to derive information about the nature of physical processes occurring within the accretion flow on the timescale of the kHz QPO. To date, kHz QPOs of (4) neutron star LMXB systems have been studied with spectral-timing techniques. We present a comprehensive study of spectral-timing products of kHz QPOs from systems where data is available in the RXTE archive to demonstrate the promise of this technique to gain insights regarding the origin of kHz QPOs. Using data averaged over the entire RXTE archive, we show correlated time-lags as a function of QPO frequency and energy, as well as energy-dependent covariance spectra for the various LMXB systems where spectral-timing analysis is possible. We find similar trends in all average spectral-timing products for the objects studied. This suggests a common origin of kHz QPOs.

Accounting for tissue heterogeneity in infrared spectroscopic imaging for accurate diagnosis of thyroid carcinoma subtypes.

PubMed

Martinez-Marin, David; Sreedhar, Hari; Varma, Vishal K; Eloy, Catarina; Sobrinho-Simões, Manuel; Kajdacsy-Balla, André; Walsh, Michael J

2017-07-01

Fourier transform infrared (FT-IR) microscopy was used to image tissue samples from twenty patients diagnosed with thyroid carcinoma. The spectral data were then used to differentiate between follicular thyroid carcinoma and follicular variant of papillary thyroid carcinoma using principle component analysis coupled with linear discriminant analysis and a Naïve Bayesian classifier operating on a set of computed spectral metrics. Classification of patients' disease type was accomplished by using average spectra from a wide region containing follicular cells, colloid, and fibrosis; however, classification of disease state at the pixel level was only possible when the extracted spectra were limited to follicular epithelial cells in the samples, excluding the relatively uninformative areas of fibrosis. The results demonstrate the potential of FT-IR microscopy as a tool to assist in the difficult diagnosis of these subtypes of thyroid cancer, and also highlights the importance of selectively and separately analyzing spectral information from different features of a tissue of interest.

Raman spectroscopy identifies radiation response in human non-small cell lung cancer xenografts

NASA Astrophysics Data System (ADS)

Harder, Samantha J.; Isabelle, Martin; Devorkin, Lindsay; Smazynski, Julian; Beckham, Wayne; Brolo, Alexandre G.; Lum, Julian J.; Jirasek, Andrew

2016-02-01

External beam radiation therapy is a standard form of treatment for numerous cancers. Despite this, there are no approved methods to account for patient specific radiation sensitivity. In this report, Raman spectroscopy (RS) was used to identify radiation-induced biochemical changes in human non-small cell lung cancer xenografts. Chemometric analysis revealed unique radiation-related Raman signatures that were specific to nucleic acid, lipid, protein and carbohydrate spectral features. Among these changes was a dramatic shift in the accumulation of glycogen spectral bands for doses of 5 or 15 Gy when compared to unirradiated tumours. When spatial mapping was applied in this analysis there was considerable variability as we found substantial intra- and inter-tumour heterogeneity in the distribution of glycogen and other RS spectral features. Collectively, these data provide unique insight into the biochemical response of tumours, irradiated in vivo, and demonstrate the utility of RS for detecting distinct radiobiological responses in human tumour xenografts.

Color analysis and image rendering of woodblock prints with oil-based ink

NASA Astrophysics Data System (ADS)

Horiuchi, Takahiko; Tanimoto, Tetsushi; Tominaga, Shoji

2012-01-01

This paper proposes a method for analyzing the color characteristics of woodblock prints having oil-based ink and rendering realistic images based on camera data. The analysis results of woodblock prints show some characteristic features in comparison with oil paintings: 1) A woodblock print can be divided into several cluster areas, each with similar surface spectral reflectance; and 2) strong specular reflection from the influence of overlapping paints arises only in specific cluster areas. By considering these properties, we develop an effective rendering algorithm by modifying our previous algorithm for oil paintings. A set of surface spectral reflectances of a woodblock print is represented by using only a small number of average surface spectral reflectances and the registered scaling coefficients, whereas the previous algorithm for oil paintings required surface spectral reflectances of high dimension at all pixels. In the rendering process, in order to reproduce the strong specular reflection in specific cluster areas, we use two sets of parameters in the Torrance-Sparrow model for cluster areas with or without strong specular reflection. An experiment on a woodblock printing with oil-based ink was performed to demonstrate the feasibility of the proposed method.

Development of space-stable thermal control coatings for use on large space vehicles

NASA Technical Reports Server (NTRS)

Gilligan, J. E.; Harada, Y.

1976-01-01

The potential of zinc orthotitanate as a pigment for spacecraft thermal control was demonstrated. The properties and performance of pigments prepared by solid state, coprecipitation, and mixed oxalate methods were compared. Environmental tests and subsequent spectral analysis were given primary emphasis.

Application of a Terahertz Multi-Frequency Radiation Source Based on Quantum-Cascade Lasers for Identification of Substances Basing on the Amplitude-Spectral Analysis of the Scattered Field

NASA Astrophysics Data System (ADS)

Aksenov, V. N.; Angeluts, A. A.; Balakin, A. V.; Maksimov, E. M.; Ozheredov, I. A.; Shkurinov, A. P.

2018-05-01

We demonstrate the possibility of using a multi-frequency terahertz source to identify substances basing on the analysis of relative amplitudes of the terahertz waves scattered by the object. The results of studying experimentally the scattering of quasi-monochromatic radiation generated by a two-frequency terahertz quantum-cascade laser by the surface of the samples containing inclusions of absorbing substances are presented. It is shown that the spectral features of absorption of these substances within the terahertz frequency range manifest themselves in variations of the amplitudes of the waves at frequencies of 3.0 and 3.7 THz, which are scattered by the samples under consideration.

[HRV-Spectral analysis of Pain, by 3D Evaluation and by Balance Index in the Pain Rehabilitation Field].

PubMed

Goto, Yukio

2015-07-01

Pain signaling is achieved by electrical impulses in the body; however, some electrical abnormalities can cause pain in the body without generating any visible symptoms. This phenomenon is sensed by the brain and a signal that may affect cardiac rhythms is immediately transmitted to the heart. To evaluate heart rate variability (HRV), the balance correction between an increase and decrease of heart rate was recorded in real time. Using a special method for spectral-analysis of the HRV, techniques for analyzing the essence of pain were developed, namely, the 'Balance index' and the '3D spectrum evaluation method'. Using these techniques, an alpha wave-like factor or a beta wave-like reaction can be obtained, and the nature and strength of pain can be displayed as spectral zones, as in a rainbow. The balance reaction can be shown by analyzing data in the frequency band using a 1/f-like spectral-analysis method. Additionally, emotional reactions can be detected using a 'Balance index' that can demonstrate imbalance responding to the pain. The mental state of the subject can also be inferred because this technique is adapted from the 1/f fluctuation theory related to the best balanced 1/f-sound wave in nature that comforts the human mind, similar to music (artificial sound wave). In this study, the variety and intensity of pain were determined from the frequency band resulting from the 1/f-spectral analysis of HRV fluctuation. These techniques could explain several situations related to medication or anesthesia and can be helpful in preventative treatment and/or explaining the differences in the effectiveness of various techniques for the rehabilitation of chronic pain.

Glimpses of Kolmogorov's spectral energy dynamics in nonlinear acoustic waves

NASA Astrophysics Data System (ADS)

Gupta, Prateek; Scalo, Carlo

2017-11-01

Gupta, Lodato, and Scalo (AIAA 2017) have demonstrated the existence of an equilibrium spectral energy cascade in shock waves formed as a result of continued modal thermoacoustic amplification consistent with Kolmogorov's theory for high-Reynolds-number hydrodynamic turbulence. In this talk we discuss the derivation of a perturbation energy density norm that guarantees energy conservation during the nonlinear wave steepening process, analogous to inertial subrange turbulent energy cascade dynamics. The energy cascade is investigated via a bi-spectral analysis limited to wave-numbers and frequencies lower than the ones associated with the shock, analogous to the viscous dissipation length scale in turbulence. The proposed norm is derived by recombining second-order nonlinear acoustic equations and is positive definite; moreover, it decays to zero in the presence of viscous dissipation and is hence classifiable as a Lyapunov function of acoustic perturbation variables. The cumulative energy spectrum wavenumber distribution demonstrates a -3/2 decay law in the inertial range. The governing equation for the thus-derived energy norm highlights terms responsible for energy cascade towards higher harmonics, analogous to vortex stretching terms in hydrodynamic turbulence.

Carotenoid Distribution in Living Cells of Haematococcus pluvialis (Chlorophyceae)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, Aaron M.; Jones, Howland D. T.; Han, Danxiang

Haematococcus pluvialis is a freshwater unicellular green microalga belonging to the class Chlorophyceae and is of commercial interest for its ability to accumulate massive amounts of the red ketocarotenoid astaxanthin (3,3'-dihydroxy-β,β-carotene-4,4'-dione). Using confocal Raman microscopy and multivariate analysis, we demonstrate the ability to spectrally resolve resonance–enhanced Raman signatures associated with astaxanthin and β-carotene along with chlorophyll fluorescence. By mathematically isolating these spectral signatures, in turn, it is possible to locate these species independent of each other in living cells of H. pluvialis in various stages of the life cycle. Chlorophyll emission was found only in the chloroplast whereas astaxanthin wasmore » identified within globular and punctate regions of the cytoplasmic space. Moreover, we found evidence for β-carotene to be co-located with both the chloroplast and astaxanthin in the cytosol. These observations imply that β-carotene is a precursor for astaxanthin and the synthesis of astaxanthin occurs outside the chloroplast. Finally, our work demonstrates the broad utility of confocal Raman microscopy to resolve spectral signatures of highly similar chromophores in living cells.« less

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Spectral degree of polarization uniformity for polarization-sensitive OCT

NASA Astrophysics Data System (ADS)

Baumann, Bernhard; Zotter, Stefan; Pircher, Michael; Götzinger, Erich; Rauscher, Sabine; Glösmann, Martin; Lammer, Jan; Schmidt-Erfurth, Ursula; Gröger, Marion; Hitzenberger, Christoph K.

2015-12-01

Depolarization of light can be measured by polarization-sensitive optical coherence tomography (PS-OCT) and has been used to improve tissue discrimination as well as segmentation of pigmented structures. Most approaches to depolarization assessment for PS-OCT - such as the degree of polarization uniformity (DOPU) - rely on measuring the uniformity of polarization states using spatial evaluation kernels. In this article, we present a different approach which exploits the spectral dimension. We introduce the spectral DOPU for the pixelwise analysis of polarization state variations between sub-bands of the broadband light source spectrum. Alongside a comparison with conventional spatial and temporal DOPU algorithms, we demonstrate imaging in the healthy human retina, and apply the technique for contrasting hard exudates in diabetic retinopathy and investigating the pigment epithelium of the rat iris.

Spectro-temporal modulation masking patterns reveal frequency selectivity.

PubMed

Oetjen, Arne; Verhey, Jesko L

2015-02-01

The present study investigated the possibility that the human auditory system demonstrates frequency selectivity to spectro-temporal amplitude modulations. Threshold modulation depth for detecting sinusoidal spectro-temporal modulations was measured using a generalized masked threshold pattern paradigm with narrowband masker modulations. Four target spectro-temporal modulations were examined, differing in their temporal and spectral modulation frequencies: a temporal modulation of -8, 8, or 16 Hz combined with a spectral modulation of 1 cycle/octave and a temporal modulation of 4 Hz combined with a spectral modulation of 0.5 cycles/octave. The temporal center frequencies of the masker modulation ranged from 0.25 to 4 times the target temporal modulation. The spectral masker-modulation center-frequencies were 0, 0.5, 1, 1.5, and 2 times the target spectral modulation. For all target modulations, the pattern of average thresholds for the eight normal-hearing listeners was consistent with the hypothesis of a spectro-temporal modulation filter. Such a pattern of modulation-frequency sensitivity was predicted on the basis of psychoacoustical data for purely temporal amplitude modulations and purely spectral amplitude modulations. An analysis of separability indicates that, for the present data set, selectivity in the spectro-temporal modulation domain can be described by a combination of a purely spectral and a purely temporal modulation filter function.

High-throughput spectral and lifetime-based FRET screening in living cells to identify small-molecule effectors of SERCA

PubMed Central

Schaaf, Tory M.; Peterson, Kurt C.; Grant, Benjamin D.; Bawaskar, Prachi; Yuen, Samantha; Li, Ji; Muretta, Joseph M.; Gillispie, Gregory D.; Thomas, David D.

2017-01-01

A robust high-throughput screening (HTS) strategy has been developed to discover small-molecule effectors targeting the sarco/endoplasmic reticulum calcium ATPase (SERCA), based on a fluorescence microplate reader that records both the nanosecond decay waveform (lifetime mode) and the complete emission spectrum (spectral mode), with high precision and speed. This spectral unmixing plate reader (SUPR) was used to screen libraries of small molecules with a fluorescence resonance energy transfer (FRET) biosensor expressed in living cells. Ligand binding was detected by FRET associated with structural rearrangements of green (GFP, donor) and red (RFP, acceptor) fluorescent proteins fused to the cardiac-specific SERCA2a isoform. The results demonstrate accurate quantitation of FRET along with high precision of hit identification. Fluorescence lifetime analysis resolved SERCA’s distinct structural states, providing a method to classify small-molecule chemotypes on the basis of their structural effect on the target. The spectral analysis was also applied to flag interference by fluorescent compounds. FRET hits were further evaluated for functional effects on SERCA’s ATPase activity via both a coupled-enzyme assay and a FRET-based calcium sensor. Concentration-response curves indicated excellent correlation between FRET and function. These complementary spectral and lifetime FRET detection methods offer an attractive combination of precision, speed, and resolution for HTS. PMID:27899691

Effective numerical method of spectral analysis of quantum graphs

NASA Astrophysics Data System (ADS)

Barrera-Figueroa, Víctor; Rabinovich, Vladimir S.

2017-05-01

We present in the paper an effective numerical method for the determination of the spectra of periodic metric graphs equipped by Schrödinger operators with real-valued periodic electric potentials as Hamiltonians and with Kirchhoff and Neumann conditions at the vertices. Our method is based on the spectral parameter power series method, which leads to a series representation of the dispersion equation, which is suitable for both analytical and numerical calculations. Several important examples demonstrate the effectiveness of our method for some periodic graphs of interest that possess potentials usually found in quantum mechanics.

Spatial resolution of a hard x-ray CCD detector.

PubMed

Seely, John F; Pereira, Nino R; Weber, Bruce V; Schumer, Joseph W; Apruzese, John P; Hudson, Lawrence T; Szabo, Csilla I; Boyer, Craig N; Skirlo, Scott

2010-08-10

The spatial resolution of an x-ray CCD detector was determined from the widths of the tungsten x-ray lines in the spectrum formed by a crystal spectrometer in the 58 to 70 keV energy range. The detector had 20 microm pixel, 1700 by 1200 pixel format, and a CsI x-ray conversion scintillator. The spectral lines from a megavolt x-ray generator were focused on the spectrometer's Rowland circle by a curved transmission crystal. The line shapes were Lorentzian with an average width after removal of the natural and instrumental line widths of 95 microm (4.75 pixels). A high spatial frequency background, primarily resulting from scattered gamma rays, was removed from the spectral image by Fourier analysis. The spectral lines, having low spatial frequency in the direction perpendicular to the dispersion, were enhanced by partially removing the Lorentzian line shape and by fitting Lorentzian curves to broad unresolved spectral features. This demonstrates the ability to improve the spectral resolution of hard x-ray spectra that are recorded by a CCD detector with well-characterized intrinsic spatial resolution.

Underresolved absorption spectroscopy of OH radicals in flames using broadband UV LEDs

NASA Astrophysics Data System (ADS)

White, Logan; Gamba, Mirko

2018-04-01

A broadband absorption spectroscopy diagnostic based on underresolution of the spectral absorption lines is evaluated for the inference of species mole fraction and temperature in combustion systems from spectral fitting. The approach uses spectrally broadband UV light emitting diodes and leverages low resolution, small form factor spectrometers. Through this combination, the method can be used to develop high precision measurement sensors. The challenges of underresolved spectroscopy are explored and addressed using spectral derivative fitting, which is found to generate measurements with high precision and accuracy. The diagnostic is demonstrated with experimental measurements of gas temperature and OH mole fraction in atmospheric air/methane premixed laminar flat flames. Measurements exhibit high precision, good agreement with 1-D flame simulations, and high repeatability. A newly developed model of uncertainty in underresolved spectroscopy is applied to estimate two-dimensional confidence regions for the measurements. The results of the uncertainty analysis indicate that the errors in the outputs of the spectral fitting procedure are correlated. The implications of the correlation between uncertainties for measurement interpretation are discussed.

Spectral Cauchy Characteristic Extraction: Gravitational Waves and Gauge Free News

NASA Astrophysics Data System (ADS)

Handmer, Casey; Szilagyi, Bela; Winicour, Jeff

2015-04-01

We present a fast, accurate spectral algorithm for the characteristic evolution of the full non-linear vacuum Einstein field equations in the Bondi framework. Developed within the Spectral Einstein Code (SpEC), we demonstrate how spectral Cauchy characteristic extraction produces gravitational News without confounding gauge effects. We explain several numerical innovations and demonstrate speed, stability, accuracy, exponential convergence, and consistency with existing methods. We highlight its capability to deliver physical insights in the study of black hole binaries.

Multimodal optical analysis discriminates freshly extracted human sample of gliomas, metastases and meningiomas from their appropriate controls

NASA Astrophysics Data System (ADS)

Zanello, Marc; Poulon, Fanny; Pallud, Johan; Varlet, Pascale; Hamzeh, H.; Abi Lahoud, Georges; Andreiuolo, Felipe; Ibrahim, Ali; Pages, Mélanie; Chretien, Fabrice; di Rocco, Federico; Dezamis, Edouard; Nataf, François; Turak, Baris; Devaux, Bertrand; Abi Haidar, Darine

2017-02-01

Delineating tumor margins as accurately as possible is of primordial importance in surgical oncology: extent of resection is associated with survival but respect of healthy surrounding tissue is necessary for preserved quality of life. The real-time analysis of the endogeneous fluorescence signal of brain tissues is a promising tool for defining margins of brain tumors. The present study aims to demonstrate the feasibility of multimodal optical analysis to discriminate fresh samples of gliomas, metastases and meningiomas from their appropriate controls. Tumor samples were studied on an optical fibered endoscope using spectral and fluorescence lifetime analysis and then on a multimodal set-up for acquiring spectral, one and two-photon fluorescence images, second harmonic generation signals and two-photon fluorescence lifetime datasets. The obtained data allowed us to differentiate healthy samples from tumor samples. These results confirmed the possible clinical relevance of this real-time multimodal optical analysis. This technique can be easily applied to neurosurgical procedures for a better delineation of surgical margins.

Co-registered Topographical, Band Excitation Nanomechanical, and Mass Spectral Imaging Using a Combined Atomic Force Microscopy/Mass Spectrometry Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ovchinnikova, Olga S.; Tai, Tamin; Bocharova, Vera

The advancement of a hybrid atomic force microscopy/mass spectrometry imaging platform demonstrating for the first time co-registered topographical, band excitation nanomechanical, and mass spectral imaging of a surface using a single instrument is reported. The mass spectrometry-based chemical imaging component of the system utilized nanothermal analysis probes for pyrolytic surface sampling followed by atmospheric pressure chemical ionization of the gas phase species produced with subsequent mass analysis. We discuss the basic instrumental setup and operation and the multimodal imaging capability and utility are demonstrated using a phase separated polystyrene/poly(2-vinylpyridine) polymer blend thin film. The topography and band excitation images showedmore » that the valley and plateau regions of the thin film surface were comprised primarily of one of the two polymers in the blend with the mass spectral chemical image used to definitively identify the polymers at the different locations. Data point pixel size for the topography (390 nm x 390 nm), band excitation (781 nm x 781 nm), mass spectrometry (690 nm x 500 nm) images was comparable and submicrometer in all three cases, but the data voxel size for each of the three images was dramatically different. The topography image was uniquely a surface measurement, whereas the band excitation image included information from an estimated 10 nm deep into the sample and the mass spectral image from 110-140 nm in depth. Moreover, because of this dramatic sampling depth variance, some differences in the band excitation and mass spectrometry chemical images were observed and were interpreted to indicate the presence of a buried interface in the sample. The spatial resolution of the mass spectral image was estimated to be between 1.5 m 2.6 m, based on the ability to distinguish surface features in that image that were also observed in the other images.« less

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

NASA Astrophysics Data System (ADS)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions.

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [(18)F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [(11)C]SCH23390 data, showing promising results.

Co-registered Topographical, Band Excitation Nanomechanical, and Mass Spectral Imaging Using a Combined Atomic Force Microscopy/Mass Spectrometry Platform

DOE PAGES

Ovchinnikova, Olga S.; Tai, Tamin; Bocharova, Vera; ...

2015-03-18

The advancement of a hybrid atomic force microscopy/mass spectrometry imaging platform demonstrating for the first time co-registered topographical, band excitation nanomechanical, and mass spectral imaging of a surface using a single instrument is reported. The mass spectrometry-based chemical imaging component of the system utilized nanothermal analysis probes for pyrolytic surface sampling followed by atmospheric pressure chemical ionization of the gas phase species produced with subsequent mass analysis. We discuss the basic instrumental setup and operation and the multimodal imaging capability and utility are demonstrated using a phase separated polystyrene/poly(2-vinylpyridine) polymer blend thin film. The topography and band excitation images showedmore » that the valley and plateau regions of the thin film surface were comprised primarily of one of the two polymers in the blend with the mass spectral chemical image used to definitively identify the polymers at the different locations. Data point pixel size for the topography (390 nm x 390 nm), band excitation (781 nm x 781 nm), mass spectrometry (690 nm x 500 nm) images was comparable and submicrometer in all three cases, but the data voxel size for each of the three images was dramatically different. The topography image was uniquely a surface measurement, whereas the band excitation image included information from an estimated 10 nm deep into the sample and the mass spectral image from 110-140 nm in depth. Moreover, because of this dramatic sampling depth variance, some differences in the band excitation and mass spectrometry chemical images were observed and were interpreted to indicate the presence of a buried interface in the sample. The spatial resolution of the mass spectral image was estimated to be between 1.5 m 2.6 m, based on the ability to distinguish surface features in that image that were also observed in the other images.« less

Rapid analysis of protein backbone resonance assignments using cryogenic probes, a distributed Linux-based computing architecture, and an integrated set of spectral analysis tools.

PubMed

Monleón, Daniel; Colson, Kimberly; Moseley, Hunter N B; Anklin, Clemens; Oswald, Robert; Szyperski, Thomas; Montelione, Gaetano T

2002-01-01

Rapid data collection, spectral referencing, processing by time domain deconvolution, peak picking and editing, and assignment of NMR spectra are necessary components of any efficient integrated system for protein NMR structure analysis. We have developed a set of software tools designated AutoProc, AutoPeak, and AutoAssign, which function together with the data processing and peak-picking programs NMRPipe and Sparky, to provide an integrated software system for rapid analysis of protein backbone resonance assignments. In this paper we demonstrate that these tools, together with high-sensitivity triple resonance NMR cryoprobes for data collection and a Linux-based computer cluster architecture, can be combined to provide nearly complete backbone resonance assignments and secondary structures (based on chemical shift data) for a 59-residue protein in less than 30 hours of data collection and processing time. In this optimum case of a small protein providing excellent spectra, extensive backbone resonance assignments could also be obtained using less than 6 hours of data collection and processing time. These results demonstrate the feasibility of high throughput triple resonance NMR for determining resonance assignments and secondary structures of small proteins, and the potential for applying NMR in large scale structural proteomics projects.

Raman spectral analysis for rapid screening of dengue infection

NASA Astrophysics Data System (ADS)

Mahmood, T.; Nawaz, H.; Ditta, A.; Majeed, M. I.; Hanif, M. A.; Rashid, N.; Bhatti, H. N.; Nargis, H. F.; Saleem, M.; Bonnier, F.; Byrne, H. J.

2018-07-01

Infection with the dengue virus is currently clinically detected according to different biomarkers in human blood plasma, commonly measured by enzyme linked immunosorbent assays, including non-structural proteins (Ns1), immunoglobulin M (IgM) and immunoglobulin G (IgG). However, there is little or no mutual correlation between the biomarkers, as demonstrated in this study by a comparison of their levels in samples from 17 patients. As an alternative, the label free, rapid screening technique, Raman spectroscopy has been used for the characterisation/diagnosis of healthy and dengue infected human blood plasma samples. In dengue positive samples, changes in specific Raman spectral bands associated with lipidic and amino acid/protein content are observed and assigned based on literature and these features can be considered as markers associated with dengue development. Based on the spectroscopic analysis of the current, albeit limited, cohort of samples, Principal Components Analysis (PCA) coupled Factorial Discriminant Analysis, yielded values of 97.95% sensitivity and 95.40% specificity for identification of dengue infection. Furthermore, in a comparison of the normal samples to the patient samples which scored low for only one of the biomarker tests, but high or medium for either or both of the other two, PCA-FDA demonstrated a sensitivity of 97.38% and specificity of 86.18%, thus providing an unambiguous screening technology.

Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications.

PubMed

Veronese, Mattia; Rizzo, Gaia; Bertoldo, Alessandra; Turkheimer, Federico E

2016-01-01

In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.

Planetary Hyperspectral Imager (PHI)

NASA Technical Reports Server (NTRS)

Silvergate, Peter

1996-01-01

A hyperspectral imaging spectrometer was breadboarded. Key innovations were use of a sapphire prism and single InSb focal plane to cover the entire spectral range, and a novel slit optic and relay optics to reduce thermal background. Operation over a spectral range of 450 - 4950 nm (approximately 3.5 spectral octaves) was demonstrated. Thermal background reduction by a factor of 8 - 10 was also demonstrated.

High-resolution single-shot spectral monitoring of hard x-ray free-electron laser radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makita, M.; Karvinen, P.; Zhu, D.

We have developed an on-line spectrometer for hard x-ray free-electron laser (XFEL) radiation based on a nanostructured diamond diffraction grating and a bent crystal analyzer. Our method provides high spectral resolution, interferes negligibly with the XFEL beam, and can withstand the intense hard x-ray pulses at high repetition rates of >100 Hz. The spectrometer is capable of providing shot-to-shot spectral information for the normalization of data obtained in scientific experiments and optimization of the accelerator operation parameters. We have demonstrated these capabilities of the setup at the Linac Coherent Light Source, in self-amplified spontaneous emission mode at full energy ofmore » >1 mJ with a 120 Hz repetition rate, obtaining a resolving power of Ε/δΕ > 3 × 10 4. In conclusion, the device was also used to monitor the effects of pulse duration down to 8 fs by analysis of the spectral spike width.« less

High-resolution single-shot spectral monitoring of hard x-ray free-electron laser radiation

DOE PAGES

Makita, M.; Karvinen, P.; Zhu, D.; ...

2015-10-16

We have developed an on-line spectrometer for hard x-ray free-electron laser (XFEL) radiation based on a nanostructured diamond diffraction grating and a bent crystal analyzer. Our method provides high spectral resolution, interferes negligibly with the XFEL beam, and can withstand the intense hard x-ray pulses at high repetition rates of >100 Hz. The spectrometer is capable of providing shot-to-shot spectral information for the normalization of data obtained in scientific experiments and optimization of the accelerator operation parameters. We have demonstrated these capabilities of the setup at the Linac Coherent Light Source, in self-amplified spontaneous emission mode at full energy ofmore » >1 mJ with a 120 Hz repetition rate, obtaining a resolving power of Ε/δΕ > 3 × 10 4. In conclusion, the device was also used to monitor the effects of pulse duration down to 8 fs by analysis of the spectral spike width.« less

Fast and Accurate Radiative Transfer Calculations Using Principal Component Analysis for (Exo-)Planetary Retrieval Models

NASA Astrophysics Data System (ADS)

Kopparla, P.; Natraj, V.; Shia, R. L.; Spurr, R. J. D.; Crisp, D.; Yung, Y. L.

2015-12-01

Radiative transfer (RT) computations form the engine of atmospheric retrieval codes. However, full treatment of RT processes is computationally expensive, prompting usage of two-stream approximations in current exoplanetary atmospheric retrieval codes [Line et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT computations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those few optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Kopparla et al. [2015, in preparation] extended the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Here, we apply the PCA method to a some typical (exo-)planetary retrieval problems. Comparisons between the new model, called Universal Principal Component Analysis Radiative Transfer (UPCART) model, two-stream models and line-by-line RT models are performed, for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the top of the atmosphere for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and stellar and viewing geometries. We demonstrate that very accurate radiance and flux estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases, as compared to a numerically exact line-by-line RT model. The accuracy is enhanced when the results are convolved to typical instrument resolutions. The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work on which is under way.

Hanny and the Mystery of the Voorwerp: Citizen Science in the Classroom

NASA Astrophysics Data System (ADS)

Costello, K.; Reilly, E.; Bracey, G.; Gay, P.

2012-08-01

The highly engaging graphic comic Hanny and the Mystery of the Voorwerp is the focus of an eight-day educational unit geared to middle level students. Activities in the unit link national astronomy standards to the citizen science Zooniverse website through tutorials that lead to analysis of real data online. NASA resources are also included in the unit. The content of the session focused on the terminology and concepts - galaxy formation, types and characteristics of galaxies, use of spectral analysis - needed to classify galaxies. Use of citizen science projects as tools to teach inquiry in the classroom was the primary focus of the workshop. The session included a hands-on experiment taken from the unit, including a NASA spectral analysis activity called "What's the Frequency, Roy G Biv?" In addition, presenters demonstrated the galaxy classification tools found in the "Galaxy Zoo" project at the Zooniverse citizen science website.

Moments distributions of single dye molecule spectra in a low-temperature polymer: Analysis of system ergodicity

NASA Astrophysics Data System (ADS)

Anikushina, T. A.; Naumov, A. V.

2013-12-01

This article demonstrates the principal advantages of the technique for analysis of the long-term spectral evolution of single molecules (SM) in the study of the microscopic nature of the dynamic processes in low-temperature polymers. We performed the detailed analysis of the spectral trail of single tetra-tert-butylterrylene (TBT) molecule in an amorphous polyisobutylene matrix, measured over 5 hours at T = 7K. It has been shown that the slow temporal dynamics is in qualitative agreement with the standard model of two-level systems and stochastic sudden-jump model. At the same time the distributions of the first four moments (cumulants) of the spectra of the selected SM measured at different time points were found not consistent with the standard theory prediction. It was considered as evidence that in a given time interval the system is not ergodic

Bayesian statistics as a new tool for spectral analysis - I. Application for the determination of basic parameters of massive stars

NASA Astrophysics Data System (ADS)

Mugnes, J.-M.; Robert, C.

2015-11-01

Spectral analysis is a powerful tool to investigate stellar properties and it has been widely used for decades now. However, the methods considered to perform this kind of analysis are mostly based on iteration among a few diagnostic lines to determine the stellar parameters. While these methods are often simple and fast, they can lead to errors and large uncertainties due to the required assumptions. Here, we present a method based on Bayesian statistics to find simultaneously the best combination of effective temperature, surface gravity, projected rotational velocity, and microturbulence velocity, using all the available spectral lines. Different tests are discussed to demonstrate the strength of our method, which we apply to 54 mid-resolution spectra of field and cluster B stars obtained at the Observatoire du Mont-Mégantic. We compare our results with those found in the literature. Differences are seen which are well explained by the different methods used. We conclude that the B-star microturbulence velocities are often underestimated. We also confirm the trend that B stars in clusters are on average faster rotators than field B stars.

Spectral iterative method and convergence analysis for solving nonlinear fractional differential equation

NASA Astrophysics Data System (ADS)

Yarmohammadi, M.; Javadi, S.; Babolian, E.

2018-04-01

In this study a new spectral iterative method (SIM) based on fractional interpolation is presented for solving nonlinear fractional differential equations (FDEs) involving Caputo derivative. This method is equipped with a pre-algorithm to find the singularity index of solution of the problem. This pre-algorithm gives us a real parameter as the index of the fractional interpolation basis, for which the SIM achieves the highest order of convergence. In comparison with some recent results about the error estimates for fractional approximations, a more accurate convergence rate has been attained. We have also proposed the order of convergence for fractional interpolation error under the L2-norm. Finally, general error analysis of SIM has been considered. The numerical results clearly demonstrate the capability of the proposed method.

EEG spectral coherence data distinguish chronic fatigue syndrome patients from healthy controls and depressed patients--a case control study.

PubMed

Duffy, Frank H; McAnulty, Gloria B; McCreary, Michelle C; Cuchural, George J; Komaroff, Anthony L

2011-07-01

Previous studies suggest central nervous system involvement in chronic fatigue syndrome (CFS), yet there are no established diagnostic criteria. CFS may be difficult to differentiate from clinical depression. The study's objective was to determine if spectral coherence, a computational derivative of spectral analysis of the electroencephalogram (EEG), could distinguish patients with CFS from healthy control subjects and not erroneously classify depressed patients as having CFS. This is a study, conducted in an academic medical center electroencephalography laboratory, of 632 subjects: 390 healthy normal controls, 70 patients with carefully defined CFS, 24 with major depression, and 148 with general fatigue. Aside from fatigue, all patients were medically healthy by history and examination. EEGs were obtained and spectral coherences calculated after extensive artifact removal. Principal Components Analysis identified coherence factors and corresponding factor loading patterns. Discriminant analysis determined whether spectral coherence factors could reliably discriminate CFS patients from healthy control subjects without misclassifying depression as CFS. Analysis of EEG coherence data from a large sample (n = 632) of patients and healthy controls identified 40 factors explaining 55.6% total variance. Factors showed highly significant group differentiation (p < .0004) identifying 89.5% of unmedicated female CFS patients and 92.4% of healthy female controls. Recursive jackknifing showed predictions were stable. A conservative 10-factor discriminant function model was subsequently applied, and also showed highly significant group discrimination (p < .001), accurately classifying 88.9% unmedicated males with CFS, and 82.4% unmedicated male healthy controls. No patient with depression was classified as having CFS. The model was less accurate (73.9%) in identifying CFS patients taking psychoactive medications. Factors involving the temporal lobes were of primary importance. EEG spectral coherence analysis identified unmedicated patients with CFS and healthy control subjects without misclassifying depressed patients as CFS, providing evidence that CFS patients demonstrate brain physiology that is not observed in healthy normals or patients with major depression. Studies of new CFS patients and comparison groups are required to determine the possible clinical utility of this test. The results concur with other studies finding neurological abnormalities in CFS, and implicate temporal lobe involvement in CFS pathophysiology.

Spectral fractionation detection of gold nanorod contrast agents using optical coherence tomography

PubMed Central

Jia, Yali; Liu, Gangjun; Gordon, Andrew Y.; Gao, Simon S.; Pechauer, Alex D.; Stoddard, Jonathan; McGill, Trevor J.; Jayagopal, Ashwath; Huang, David

2015-01-01

We demonstrate the proof of concept of a novel Fourier-domain optical coherence tomography contrast mechanism using gold nanorod contrast agents and a spectral fractionation processing technique. The methodology detects the spectral shift of the backscattered light from the nanorods by comparing the ratio between the short and long wavelength halves of the optical coherence tomography signal intensity. Spectral fractionation further divides the halves into sub-bands to improve spectral contrast and suppress speckle noise. Herein, we show that this technique can detect gold nanorods in intralipid tissue phantoms. Furthermore, cellular labeling by gold nanorods was demonstrated using retinal pigment epithelial cells in vitro. PMID:25836459

Automated classification and visualization of healthy and pathological dental tissues based on near-infrared hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Usenik, Peter; Bürmen, Miran; Vrtovec, Tomaž; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

2011-03-01

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots which are difficult to diagnose. If detected early enough, such demineralization can be arrested and reversed by non-surgical means through well established dental treatments (fluoride therapy, anti-bacterial therapy, low intensity laser irradiation). Near-infrared (NIR) hyper-spectral imaging is a new promising technique for early detection of demineralization based on distinct spectral features of healthy and pathological dental tissues. In this study, we apply NIR hyper-spectral imaging to classify and visualize healthy and pathological dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized areas. For this purpose, a standardized teeth database was constructed consisting of 12 extracted human teeth with different degrees of natural dental lesions imaged by NIR hyper-spectral system, X-ray and digital color camera. The color and X-ray images of teeth were presented to a clinical expert for localization and classification of the dental tissues, thereby obtaining the gold standard. Principal component analysis was used for multivariate local modeling of healthy and pathological dental tissues. Finally, the dental tissues were classified by employing multiple discriminant analysis. High agreement was observed between the resulting classification and the gold standard with the classification sensitivity and specificity exceeding 85 % and 97 %, respectively. This study demonstrates that NIR hyper-spectral imaging has considerable diagnostic potential for imaging hard dental tissues.

Development and Evaluation of a Spectral Analysis Method to Eliminate Organic Interference with Cavity Ring-Down Measurements of Water Isotope Ratios.

NASA Astrophysics Data System (ADS)

Lin, Z.; Kim-Hak, D.; Popp, B. N.; Wallsgrove, N.; Kagawa-Viviani, A.; Johnson, J.

2017-12-01

Cavity ring-down spectroscopy (CRDS) is a technology based on the spectral absorption of gas molecules of interest at specific spectral regions. The CRDS technique enables the analysis of hydrogen and oxygen stable isotope ratios of water by directly measuring individual isotopologue absorption peaks such as H16OH, H18OH, and D16OH. Early work demonstrated that the accuracy of isotope analysis by CRDS and other laser-based absorption techniques could be compromised by spectral interference from organic compounds, in particular methanol and ethanol, which can be prevalent in ecologically-derived waters. There have been several methods developed by various research groups including Picarro to address the organic interference challenge. Here, we describe an organic fitter and a post-processing algorithm designed to improve the accuracy of the isotopic analysis of the "organic contaminated" water specifically for Picarro models L2130-i and L2140-i. To create the organic fitter, the absorption features of methanol around 7200 cm-1 were characterized and incorporated into spectral analysis. Since there was residual interference remaining after applying the organic fitter, a statistical model was also developed for post-processing correction. To evaluate the performance of the organic fitter and the postprocessing correction, we conducted controlled experiments on the L2130-i for two water samples with different isotope ratios blended with varying amounts of methanol (0-0.5%) and ethanol (0-5%). When the original fitter was not used for spectral analysis, the addition of 0.5% methanol changed the apparent isotopic composition of the water samples by +62‰ for δ18O values and +97‰ for δ2H values, and the addition of 5% ethanol changed the apparent isotopic composition by -0.5‰ for δ18O values and -3‰ for δ2H values. When the organic fitter was used for spectral analysis, the maximum methanol-induced errors were reduced to +4‰ for δ18O values and +5‰ for δ2H values, and the maximum ethanol-induced errors were unchanged. When the organic fitter was combined with the post-processing correction, up to 99.8% of the total methanol-induced errors and 96% of the total ethanol-induced errors could be corrected. The applicability of the algorithm to natural samples such as plant and soil waters will be investigated.

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples.

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples. PMID:20586475

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

PubMed Central

2012-01-01

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Conclusions Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks. PMID:22730909

The EEG Split Alpha Peak: Phenomenological Origins and Methodological Aspects of Detection and Evaluation.

PubMed

Olejarczyk, Elzbieta; Bogucki, Piotr; Sobieszek, Aleksander

2017-01-01

Electroencephalographic (EEG) patterns were analyzed in a group of ambulatory patients who ranged in age and sex using spectral analysis as well as Directed Transfer Function, a method used to evaluate functional brain connectivity. We tested the impact of window size and choice of reference electrode on the identification of two or more peaks with close frequencies in the spectral power distribution, so called "split alpha." Together with the connectivity analysis, examination of spatiotemporal maps showing the distribution of amplitudes of EEG patterns allowed for better explanation of the mechanisms underlying the generation of split alpha peaks. It was demonstrated that the split alpha spectrum can be generated by two or more independent and interconnected alpha wave generators located in different regions of the cerebral cortex, but not necessarily in the occipital cortex. We also demonstrated the importance of appropriate reference electrode choice during signal recording. In addition, results obtained using the original data were compared with results obtained using re-referenced data, using average reference electrode and reference electrode standardization techniques.

Design and construction of an Offner spectrometer based on geometrical analysis of ring fields.

PubMed

Kim, Seo Hyun; Kong, Hong Jin; Lee, Jong Ung; Lee, Jun Ho; Lee, Jai Hoon

2014-08-01

A method to obtain an aberration-corrected Offner spectrometer without ray obstruction is proposed. A new, more efficient spectrometer optics design is suggested in order to increase its spectral resolution. The derivation of a new ring equation to eliminate ray obstruction is based on geometrical analysis of the ring fields for various numerical apertures. The analytical design applying this equation was demonstrated using the optical design software Code V in order to manufacture a spectrometer working in wavelengths of 900-1700 nm. The simulation results show that the new concept offers an analytical initial design taking the least time of calculation. The simulated spectrometer exhibited a modulation transfer function over 80% at Nyquist frequency, root-mean-square spot diameters under 8.6 μm, and a spectral resolution of 3.2 nm. The final design and its realization of a high resolution Offner spectrometer was demonstrated based on the simulation result. The equation and analytical design procedure shown here can be applied to most Offner systems regardless of the wavelength range.

High brightness diode lasers controlled by volume Bragg gratings

NASA Astrophysics Data System (ADS)

Glebov, Leonid

2017-02-01

Volume Bragg gratings (VBGs) recorded in photo-thermo-refractive (PTR) glass are holographic optical elements that are effective spectral and angular filters withstanding high power laser radiation. Reflecting VBGs are narrow-band spectral filters while transmitting VBGs are narrow-band angular filters. The use of these optical elements in external resonators of semiconductor lasers enables extremely resonant feedback that provides dramatic spectral and angular narrowing of laser diodes radiation without significant power and efficiency penalty. Spectral narrowing of laser diodes by reflecting VBGs demonstrated in wide spectral region from near UV to 3 μm. Commercially available VBGs have spectral width ranged from few nanometers to few tens of picometers. Efficient spectral locking was demonstrated for edge emitters (single diodes, bars, modules, and stacks), vertical cavity surface emitting lasers (VCSELs), grating coupled surface emitting lasers (GCSELs), and interband cascade lasers (ICLs). The use of multiplexed VBGs provides multiwavelength emission from a single emitter. Spectrally locked semiconductor lasers demonstrated CW power from milliwatts to a kilowatt. Angular narrowing by transmitting VBGs enables single transverse mode emission from wide aperture diode lasers having resonators with great Fresnel numbers. This feature provides close to diffraction limit divergence along a slow axis of wide stripe edge emitters. Radiation exchange between lasers by means of spatially profiled or multiplexed VBGs enables coherent combining of diode lasers. Sequence of VBGs or multiplexed VBGs enable spectral combining of spectrally narrowed diode lasers or laser modules. Thus the use of VBGs for diode lasers beam control provides dramatic increase of brightness.

High Energy Emission of V404 Cygni during 2015 outburst with INTEGRAL/SPI: Spectral analysis results, issues and solutions

NASA Astrophysics Data System (ADS)

Jourdain, Elisabeth; Roques, Jean-Pierre

2016-04-01

A strong outburst of the X-ray transient V404 Cygni (= GS2023-338) was observed in 2015 June/July up to a level of 50 Crab in the hard X-ray domain.We have used the INTEGRAL/SPI data to investigate the spectral behavior of the source between 20 and 1000 keV during its maximum of activity. We have found striking variability patterns at all timescales. For the 20-200 keV energy band, the huge signal to noise ratio allows us to scrutinize the source evolution on a never reached timescale (30 s). At higher energy, the spectral shape can be determined on a timescale < 1 h.However, we note that at this level of photon flux, instrument's behavior may be severely tested and that some instrumental artifacts could affect the data analysis. We have performed thorough checks to ensure a correct handling of the SPI data and present how to obtain reliable spectral results on the emission of V404 Cyg. We demonstrate that, with the correct configuration, the hard X-ray emission, up to the MeV region, is well described by a two component model (Comptonisation law + cutoff power law) as observed in Cyg X-1 and for V404 Cygni itself at lower flux levels.

Temporal measurement and analysis of high-resolution spectral signatures of plants and relationships to biophysical characteristics

NASA Astrophysics Data System (ADS)

Bostater, Charles R., Jr.; Rebbman, Jan; Hall, Carlton; Provancha, Mark; Vieglais, David

1995-11-01

Measurements of temporal reflectance signatures as a function of growing season for sand live oak (Quercus geminata), myrtle oak (Q. myrtifolia, and saw palmetto (Serenoa repens) were collected during a two year study period. Canopy level spectral reflectance signatures, as a function of 252 channels between 368 and 1115 nm, were collected using near nadir viewing geometry and a consistent sun illumination angle. Leaf level reflectance measurements were made in the laboratory using a halogen light source and an environmental optics chamber with a barium sulfate reflectance coating. Spectral measurements were related to several biophysical measurements utilizing optimal passive ambient correlation spectroscopy (OPACS) technique. Biophysical parameters included percent moisture, water potential (MPa), total chlorophyll, and total Kjeldahl nitrogen. Quantitative data processing techniques were used to determine optimal bands based on the utilization of a second order derivative or inflection estimator. An optical cleanup procedure was then employed that computes the double inflection ratio (DIR) spectra for all possible three band combinations normalized to the previously computed optimal bands. These results demonstrate a unique approach to the analysis of high spectral resolution reflectance signatures for estimation of several biophysical measures of plants at the leaf and canopy level from optimally selected bands or bandwidths.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation.

PubMed

Salinet, João L; Masca, Nicholas; Stafford, Peter J; Ng, G André; Schlindwein, Fernando S

2016-03-08

Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation. Autoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach. 3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz). We have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum

NASA Astrophysics Data System (ADS)

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum.

PubMed

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Spectral integration in primary auditory cortex attributable to temporally precise convergence of thalamocortical and intracortical input.

PubMed

Happel, Max F K; Jeschke, Marcus; Ohl, Frank W

2010-08-18

Primary sensory cortex integrates sensory information from afferent feedforward thalamocortical projection systems and convergent intracortical microcircuits. Both input systems have been demonstrated to provide different aspects of sensory information. Here we have used high-density recordings of laminar current source density (CSD) distributions in primary auditory cortex of Mongolian gerbils in combination with pharmacological silencing of cortical activity and analysis of the residual CSD, to dissociate the feedforward thalamocortical contribution and the intracortical contribution to spectral integration. We found a temporally highly precise integration of both types of inputs when the stimulation frequency was in close spectral neighborhood of the best frequency of the measurement site, in which the overlap between both inputs is maximal. Local intracortical connections provide both directly feedforward excitatory and modulatory input from adjacent cortical sites, which determine how concurrent afferent inputs are integrated. Through separate excitatory horizontal projections, terminating in cortical layers II/III, information about stimulus energy in greater spectral distance is provided even over long cortical distances. These projections effectively broaden spectral tuning width. Based on these data, we suggest a mechanism of spectral integration in primary auditory cortex that is based on temporally precise interactions of afferent thalamocortical inputs and different short- and long-range intracortical networks. The proposed conceptual framework allows integration of different and partly controversial anatomical and physiological models of spectral integration in the literature.

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints.

PubMed

Keitel, Anne; Gross, Joachim

2016-06-01

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles ("fingerprints"), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease.

Analysis of Solar Spectral Irradiance Measurements from the SBUV/2-Series and the SSBUV Instruments

NASA Technical Reports Server (NTRS)

Cebula, Richard P.; DeLand, Matthew T.; Hilsenrath, Ernest

1997-01-01

During this period of performance, 1 March 1997 - 31 August 1997, the NOAA-11 SBUV/2 solar spectral irradiance data set was validated using both internal and external assessments. Initial quality checking revealed minor problems with the data (e.g. residual goniometric errors, that were manifest as differences between the two scans acquired each day). The sources of these errors were determined and the errors were corrected. Time series were constructed for selected wavelengths and the solar irradiance changes measured by the instrument were compared to a Mg II proxy-based model of short- and long-term solar irradiance variations. This analysis suggested that errors due to residual, uncorrected long-term instrument drift have been reduced to less than 1-2% over the entire 5.5 year NOAA-11 data record. Detailed statistical analysis was performed. This analysis, which will be documented in a manuscript now in preparation, conclusively demonstrates the evolution of solar rotation periodicity and strength during solar cycle 22.

The fundamental parameter method applied to X-ray fluorescence analysis with synchrotron radiation

NASA Astrophysics Data System (ADS)

Pantenburg, F. J.; Beier, T.; Hennrich, F.; Mommsen, H.

1992-05-01

Quantitative X-ray fluorescence analysis applying the fundamental parameter method is usually restricted to monochromatic excitation sources. It is shown here, that such analyses can be performed as well with a white synchrotron radiation spectrum. To determine absolute elemental concentration values it is necessary to know the spectral distribution of this spectrum. A newly designed and tested experimental setup, which uses the synchrotron radiation emitted from electrons in a bending magnet of ELSA (electron stretcher accelerator of the university of Bonn) is presented. The determination of the exciting spectrum, described by the given electron beam parameters, is limited due to uncertainties in the vertical electron beam size and divergence. We describe a method which allows us to determine the relative and absolute spectral distributions needed for accurate analysis. First test measurements of different alloys and standards of known composition demonstrate that it is possible to determine exact concentration values in bulk and trace element analysis.

Frequency domain modeling and dynamic characteristics evaluation of existing wind turbine systems

NASA Astrophysics Data System (ADS)

Chiang, Chih-Hung; Yu, Chih-Peng

2016-04-01

It is quite well accepted that frequency domain procedures are suitable for the design and dynamic analysis of wind turbine structures, especially for floating offshore wind turbines, since random wind loads and wave induced motions are most likely simulated in the frequency domain. This paper presents specific applications of an effective frequency domain scheme to the linear analysis of wind turbine structures in which a 1-D spectral element was developed based on the axially-loaded member. The solution schemes are summarized for the spectral analyses of the tower, the blades, and the combined system with selected frequency-dependent coupling effect from foundation-structure interactions. Numerical examples demonstrate that the modal frequencies obtained using spectral-element models are in good agreement with those found in the literature. A 5-element mono-pile model results in less than 0.3% deviation from an existing 160-element model. It is preliminarily concluded that the proposed scheme is relatively efficient in performing quick verification for test data obtained from the on-site vibration measurement using the microwave interferometer.

Sentence intelligibility during segmental interruption and masking by speech-modulated noise: Effects of age and hearing loss

PubMed Central

Fogerty, Daniel; Ahlstrom, Jayne B.; Bologna, William J.; Dubno, Judy R.

2015-01-01

This study investigated how single-talker modulated noise impacts consonant and vowel cues to sentence intelligibility. Younger normal-hearing, older normal-hearing, and older hearing-impaired listeners completed speech recognition tests. All listeners received spectrally shaped speech matched to their individual audiometric thresholds to ensure sufficient audibility with the exception of a second younger listener group who received spectral shaping that matched the mean audiogram of the hearing-impaired listeners. Results demonstrated minimal declines in intelligibility for older listeners with normal hearing and more evident declines for older hearing-impaired listeners, possibly related to impaired temporal processing. A correlational analysis suggests a common underlying ability to process information during vowels that is predictive of speech-in-modulated noise abilities. Whereas, the ability to use consonant cues appears specific to the particular characteristics of the noise and interruption. Performance declines for older listeners were mostly confined to consonant conditions. Spectral shaping accounted for the primary contributions of audibility. However, comparison with the young spectral controls who received identical spectral shaping suggests that this procedure may reduce wideband temporal modulation cues due to frequency-specific amplification that affected high-frequency consonants more than low-frequency vowels. These spectral changes may impact speech intelligibility in certain modulation masking conditions. PMID:26093436

Detecting Weak Spectral Lines in Interferometric Data through Matched Filtering

NASA Astrophysics Data System (ADS)

Loomis, Ryan A.; Öberg, Karin I.; Andrews, Sean M.; Walsh, Catherine; Czekala, Ian; Huang, Jane; Rosenfeld, Katherine A.

2018-04-01

Modern radio interferometers enable observations of spectral lines with unprecedented spatial resolution and sensitivity. In spite of these technical advances, many lines of interest are still at best weakly detected and therefore necessitate detection and analysis techniques specialized for the low signal-to-noise ratio (S/N) regime. Matched filters can leverage knowledge of the source structure and kinematics to increase sensitivity of spectral line observations. Application of the filter in the native Fourier domain improves S/N while simultaneously avoiding the computational cost and ambiguities associated with imaging, making matched filtering a fast and robust method for weak spectral line detection. We demonstrate how an approximate matched filter can be constructed from a previously observed line or from a model of the source, and we show how this filter can be used to robustly infer a detection significance for weak spectral lines. When applied to ALMA Cycle 2 observations of CH3OH in the protoplanetary disk around TW Hya, the technique yields a ≈53% S/N boost over aperture-based spectral extraction methods, and we show that an even higher boost will be achieved for observations at higher spatial resolution. A Python-based open-source implementation of this technique is available under the MIT license at http://github.com/AstroChem/VISIBLE.

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

Spectral karyotyping reveals a comprehensive karyotype in an adult acute lymphoblastic leukemia

PubMed Central

Guo, Bo; Zhu, Hong Li; Li, Su Xia; Lu, Xue Chun; Fan, Hui; Da, Wan Ming

2012-01-01

Cytogenetic abnormalities are frequently detected in patients with acute lymphoblastic leukemia (ALL). Comprehensive karyotype was related to poor prognosis frequently in ALL. We present a comprehensive karyotype in an adult ALL by spectral karyotyping (SKY) and R-banding. SKY not only confirmed the abnormalities previously seen by R-banding but also improved comprehensive karyotype analysis with the following result 47,XY,+9, ins(1;5)(q23;q23q34) t(6;7)(q23;p13). Our report demonstrated that SKY is able to provide more information accurately for prediction of disease prognosis in adult ALL with comprehensive karyotype. PMID:27298606

Spectral interferences in the determination of rhenium in molybdenum and copper concentrates by inductively coupled plasma optical emission spectrometry (ICP-OES)

NASA Astrophysics Data System (ADS)

Karadjov, Metody; Velitchkova, Nikolaya; Veleva, Olga; Velichkov, Serafim; Markov, Pavel; Daskalova, Nonka

2016-05-01

This paper deals with spectral interferences of complex matrix containing Mo, Al, Ti, Fe, Mg, Ca and Cu in the determination of rhenium in molybdenum and copper concentrates by inductively coupled plasma optical emission spectrometry (ICP-OES). By radial viewing 40.68 MHz ICP equipped with a high resolution spectrometer (spectral bandwidth = 5 pm) the hyperfine structure (HFS) of the most prominent lines of rhenium (Re II 197.248 nm, Re II 221.426 nm and Re II 227.525 nm) was registered. The HFS components under high resolution conditions were used as separate prominent line in order to circumvent spectral interferences. The Q-concept was applied for quantification of spectral interferences. The quantitative databases for the type and the magnitude of the spectral interferences in the presence of above mentioned matrix constituents were obtained by using a radial viewing 40.68 MHz ICP with high resolution and an axial viewing 27.12 MHz ICP with middle resolution. The data for the both ICP-OES systems were collected chiefly with a view to spectrochemical analysis for comparing the magnitude of line and wing (background) spectral interference and the true detection limits with spectroscopic apparatus with different spectral resolution. The sample pretreatment methods by sintering with magnesium oxide and oxidizing agents as well as a microwave acid digestion were applied. The feasibility, accuracy and precision of the analytical results were experimentally demonstrated by certified reference materials.

Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information

NASA Astrophysics Data System (ADS)

Lau, C. L.; Halim, S.; Zulkepli, M.; Azwan, A. M.; Tang, W. L.; Chong, A. K.

2015-10-01

The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.

Essential Parameters for Structural Analysis and Dereplication by 1H NMR Spectroscopy

PubMed Central

2015-01-01

The present study demonstrates the importance of adequate precision when reporting the δ and J parameters of frequency domain 1H NMR (HNMR) data. Using a variety of structural classes (terpenoids, phenolics, alkaloids) from different taxa (plants, cyanobacteria), this study develops rationales that explain the importance of enhanced precision in NMR spectroscopic analysis and rationalizes the need for reporting Δδ and ΔJ values at the 0.1–1 ppb and 10 mHz level, respectively. Spectral simulations paired with iteration are shown to be essential tools for complete spectral interpretation, adequate precision, and unambiguous HNMR-driven dereplication and metabolomic analysis. The broader applicability of the recommendation relates to the physicochemical properties of hydrogen (1H) and its ubiquity in organic molecules, making HNMR spectra an integral component of structure elucidation and verification. Regardless of origin or molecular weight, the HNMR spectrum of a compound can be very complex and encode a wealth of structural information that is often obscured by limited spectral dispersion and the occurrence of higher order effects. This altogether limits spectral interpretation, confines decoding of the underlying spin parameters, and explains the major challenge associated with the translation of HNMR spectra into tabulated information. On the other hand, the reproducibility of the spectral data set of any (new) chemical entity is essential for its structure elucidation and subsequent dereplication. Handling and documenting HNMR data with adequate precision is critical for establishing unequivocal links between chemical structure, analytical data, metabolomes, and biological activity. Using the full potential of HNMR spectra will facilitate the general reproducibility for future studies of bioactive chemicals, especially of compounds obtained from the diversity of terrestrial and marine organisms. PMID:24895010

Bifocal Fresnel Lens Based on the Polarization-Sensitive Metasurface

NASA Astrophysics Data System (ADS)

Markovich, Hen; Filonov, Dmitrii; Shishkin, Ivan; Ginzburg, Pavel

2018-05-01

Thin structured surfaces allow flexible control over propagation of electromagnetic waves. Focusing and polarization state analysis are among functions, required for effective manipulation of radiation. Here a polarization sensitive Fresnel zone plate lens is proposed and experimentally demonstrated for GHz spectral range. Two spatially separated focal spots for orthogonal polarizations are obtained by designing metasurface pattern, made of overlapping tightly packed cross and rod shaped antennas with a strong polarization selectivity. Optimized subwavelength pattern allows multiplexing two different lenses with low polarization crosstalk on the same substrate and provides a control over focal spots of the lens only by changing of the polarization state of the incident wave. More than a wavelength separation between the focal spots was demonstrated for a broad spectral range, covering half a decade in frequency. The proposed concept could be straightforwardly extended for THz and visible spectra, where polarization-sensitive elements utilize localized plasmon resonance phenomenon.

Monolithically integrated broad-band Mach-Zehnder interferometers for highly sensitive label-free detection of biomolecules through dual polarization optics.

PubMed

Psarouli, A; Salapatas, A; Botsialas, A; Petrou, P S; Raptis, I; Makarona, E; Jobst, G; Tukkiniemi, K; Sopanen, M; Stoffer, R; Kakabakos, S E; Misiakos, K

2015-12-02

Protein detection and characterization based on Broad-band Mach-Zehnder Interferometry is analytically outlined and demonstrated through a monolithic silicon microphotonic transducer. Arrays of silicon light emitting diodes and monomodal silicon nitride waveguides forming Mach-Zehnder interferometers were integrated on a silicon chip. Broad-band light enters the interferometers and exits sinusoidally modulated with two distinct spectral frequencies characteristic of the two polarizations. Deconvolution in the Fourier transform domain makes possible the separation of the two polarizations and the simultaneous monitoring of the TE and the TM signals. The dual polarization analysis over a broad spectral band makes possible the refractive index calculation of the binding adlayers as well as the distinction of effective medium changes into cover medium or adlayer ones. At the same time, multi-analyte detection at concentrations in the pM range is demonstrated.

Photonic Jets for Strained-Layer Superlattice Infrared Photodetector Enhancement

DTIC Science & Technology

2014-06-25

top of a 40 µm photodetector fixed into position using a silicone rubber . As illustrated in Fig. 2, the spectral response was characterized before and...midwave-infrared spectral band (3-5 ?m). We optimized the design of these structures and experimentally demonstrated the increased sensitivity compared to...midwave-infrared spectral band (3-5 ?m). We optimized the design of these structures and experimentally demonstrated the increased sensitivity

Granger causality revisited

PubMed Central

Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

2014-01-01

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

PubMed Central

Liu, Wenfen

2017-01-01

Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically; compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted k-means clustering and thus gives the theoretical guarantee to this special kind of k-means clustering where each point has its corresponding weight. PMID:29312447

X-Ray Spectral Variability Signatures of Flares in BL Lac Objects

NASA Technical Reports Server (NTRS)

Boettcher, Markus; Chiang, James; White, Nicholas E. (Technical Monitor)

2002-01-01

We are presenting a detailed parameter study of the time-dependent electron injection and kinematics and the self-consistent radiation transport in jets of intermediate and low-frequency peaked BL Lac objects. Using a time-dependent, combined synchrotron-self-Compton and external-Compton jet model, we study the influence of variations of several essential model parameters, such as the electron injection compactness, the relative contribution of synchrotron to external soft photons to the soft photon compactness, the electron- injection spectral index, and the details of the time profiles of the electron injection episodes giving rise to flaring activity. In the analysis of our results, we focus on the expected X-ray spectral variability signatures in a region of parameter space particularly well suited to reproduce the broadband spectral energy distributions of intermediate and low-frequency peaked BL Lac objects. We demonstrate that SSC- and external-Compton dominated models for the gamma-ray emission from blazars are producing significantly different signatures in the X-ray variability, in particular in the soft X-ray light curves and the spectral hysteresis at soft X-ray energies, which can be used as a powerful diagnostic to unveil the nature of the high-energy emission from BL Lac objects.

Experimental demonstration of passive coherent combining of fiber lasers by phase contrast filtering.

PubMed

Jeux, François; Desfarges-Berthelemot, Agnès; Kermène, Vincent; Barthelemy, Alain

2012-12-17

We report experiments on a new laser architecture involving phase contrast filtering to coherently combine an array of fiber lasers. We demonstrate that the new technique yields a more stable phase-locking than standard methods using only amplitude filtering. A spectral analysis of the output beams shows that the new scheme generates more resonant frequencies common to the coupled lasers. This property can enhance the combining efficiency when the number of lasers to be coupled is large.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

X-ray spectroscopy of SNR E0102-72 with the ASCA satellite

NASA Technical Reports Server (NTRS)

Hayashi, Ichizo; Koyama, Katsuji; Ozaki, Masanobu; Miyata, Emi; Tsumeni, Hiroshi; Hughes, John P.; Petre, Robert

1994-01-01

The Advanced Satellite for Cosmology and Astrophysics (ASCA) satellite has obtained a moderate-resolution energy spectrum of E0102-72, the brightest Supernova Remnant (SNR) in the Small Magellanic Cloud (SMC). This paper reports on the first results of the analysis of the high quality spectrum of E0102-72. The spectrum shows resolved emission lines of He-like K alpha, H-like K alpha and K beta from oxygen, neon, and magnesium. The intensity ratios of these lines cannot be explained by a multi-component plasma model with uniform abundances, but requires abundance inhomogeneity in the plasma. We demonstrate how the spectral capabilities of the ASCA SIS make available new diagnostics of X-ray plasmas in a state of non-equilibrium ionization. Some interpretation based on the spectral analysis is also given.

On-chip wavelength multiplexed detection of cancer DNA biomarkers in blood

PubMed Central

Cai, H.; Stott, M. A.; Ozcelik, D.; Parks, J. W.; Hawkins, A. R.; Schmidt, H.

2016-01-01

We have developed an optofluidic analysis system that processes biomolecular samples starting from whole blood and then analyzes and identifies multiple targets on a silicon-based molecular detection platform. We demonstrate blood filtration, sample extraction, target enrichment, and fluorescent labeling using programmable microfluidic circuits. We detect and identify multiple targets using a spectral multiplexing technique based on wavelength-dependent multi-spot excitation on an antiresonant reflecting optical waveguide chip. Specifically, we extract two types of melanoma biomarkers, mutated cell-free nucleic acids —BRAFV600E and NRAS, from whole blood. We detect and identify these two targets simultaneously using the spectral multiplexing approach with up to a 96% success rate. These results point the way toward a full front-to-back chip-based optofluidic compact system for high-performance analysis of complex biological samples. PMID:28058082

Solution to the indexing problem of frequency domain simulation experiments

NASA Technical Reports Server (NTRS)

Mitra, Mousumi; Park, Stephen K.

1991-01-01

A frequency domain simulation experiment is one in which selected system parameters are oscillated sinusoidally to induce oscillations in one or more system statistics of interest. A spectral (Fourier) analysis of these induced oscillations is then performed. To perform this spectral analysis, all oscillation frequencies must be referenced to a common, independent variable - an oscillation index. In a discrete-event simulation, the global simulation clock is the most natural choice for the oscillation index. However, past efforts to reference all frequencies to the simulation clock generally yielded unsatisfactory results. The reason for these unsatisfactory results is explained in this paper and a new methodology which uses the simulation clock as the oscillation index is presented. Techniques for implementing this new methodology are demonstrated by performing a frequency domain simulation experiment for a network of queues.

Optical properties of metamorphic GaAs/InAlGaAs/InGaAs heterostructures with InAs/InGaAs quantum wells, emitting light in the 1250–1400-nm spectral range

DOE Office of Scientific and Technical Information (OSTI.GOV)

Egorov, A. Yu., E-mail: anton@beam.ioffe.ru; Karachinsky, L. Ya.; Novikov, I. I.

It is demonstrated that metamorphic GaAs/InAlGaAs/InGaAs heterostructures with InAs/InGaAs quantum wells, which emit light in the 1250–1400 nm spectral range, can be fabricated by molecular-beam epitaxy. The structural and optical properties of the heterostructures are studied by X-ray diffraction analysis, transmission electron microscopy, and the photoluminescence method. Comparative analysis of the integrated photoluminescence intensity of the heterostructures and a reference sample confirm the high efficiency of radiative recombination in the heterostructures. It is confirmed by transmission electron microscopy that dislocations do not penetrate into the active region of the metamorphic heterostructures, where the radiative recombination of carriers occurs.

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

PubMed Central

Tian, Yin; Zhang, Huiling; Xu, Wei; Zhang, Haiyong; Yang, Li; Zheng, Shuxing; Shi, Yupan

2017-01-01

Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces. PMID:28912701

Spectrum slicer for snapshot spectral imaging

NASA Astrophysics Data System (ADS)

Tamamitsu, Miu; Kitagawa, Yutaro; Nakagawa, Keiichi; Horisaki, Ryoichi; Oishi, Yu; Morita, Shin-ya; Yamagata, Yutaka; Motohara, Kentaro; Goda, Keisuke

2015-12-01

We propose and demonstrate an optical component that overcomes critical limitations in our previously demonstrated high-speed multispectral videography-a method in which an array of periscopes placed in a prism-based spectral shaper is used to achieve snapshot multispectral imaging with the frame rate only limited by that of an image-recording sensor. The demonstrated optical component consists of a slicing mirror incorporated into a 4f-relaying lens system that we refer to as a spectrum slicer (SS). With its simple design, we can easily increase the number of spectral channels without adding fabrication complexity while preserving the capability of high-speed multispectral videography. We present a theoretical framework for the SS and its experimental utility to spectral imaging by showing real-time monitoring of a dynamic colorful event through five different visible windows.

Joint Estimation of the Epoch of Reionization Power Spectrum and Foregrounds

NASA Astrophysics Data System (ADS)

Sims, Peter; Pober, Jonathan

2018-01-01

Bright astrophysical foregrounds present a significant impediment to the detection of redshifted 21-cm emission from the Epoch of Reionization on large spatial scales. In this talk I present a framework for the joint modeling of the power spectral contamination by astrophysical foregrounds and the power spectrum of the Epoch of Reionization. I show how informative priors on the power spectral contamination by astrophysical foregrounds at high redshifts, where emission from both the Epoch of Reionization and its foregrounds is present in the data, can be obtained through analysis of foreground-only emission at lower redshifts. Finally, I demonstrate how, by using such informative foreground priors, joint modeling can be employed to mitigate bias in estimates of the power spectrum of the Epoch of Reionization signal and, in particular, to enable recovery of more robust power spectral estimates on large spatial scales.

IV INTERNATIONAL CONFERENCE ON ATOM AND MOLECULAR PULSED LASERS (AMPL'99): Spectral properties of optical anisotropy induced by laser radiation in dye solutions

NASA Astrophysics Data System (ADS)

Pikulik, L. G.; Chernyavskii, V. A.; Grib, A. F.

2000-06-01

Spectral studies of induced quasi-crystal properties (which can be quantitatively characterised by the difference in the refractive indices of ordinary and extraordinary waves, Δn=no—ne) in Rhodamine 6G and Rhodamine 4C solutions in glycerine excited in the visible and UV ranges of the absorption spectrum are presented. It is demonstrated that the observed spectral dependences of Δn of these dye solutions excited in the visible (long-wavelength) and UV (short-wavelength) ranges of the absorption spectrum can be interpreted in terms of an oscillator model of a molecule. The proposed method for the analysis of induced optical anisotropy in solutions of organic compounds allows the relative orientation of oscillators in a molecule and, thus, the relative orientation of electronic transitions in a molecule to be determined in a reliable way.

Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures.

PubMed

Grözinger, M; Fell, J; Röschke, J

2001-11-01

In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of the new measures. The accuracy of the classification was significantly worse, however, when supplied with these variables alone. In view of results demonstrating the efficiency of nonconventional measures in EEG analysis, the benefit appears to depend on the nature of the problem.

Development and evaluation of a Hadamard transform imaging spectrometer and a Hadamard transform thermal imager

NASA Technical Reports Server (NTRS)

Harwit, M.; Swift, R.; Wattson, R.; Decker, J.; Paganetti, R.

1976-01-01

A spectrometric imager and a thermal imager, which achieve multiplexing by the use of binary optical encoding masks, were developed. The masks are based on orthogonal, pseudorandom digital codes derived from Hadamard matrices. Spatial and/or spectral data is obtained in the form of a Hadamard transform of the spatial and/or spectral scene; computer algorithms are then used to decode the data and reconstruct images of the original scene. The hardware, algorithms and processing/display facility are described. A number of spatial and spatial/spectral images are presented. The achievement of a signal-to-noise improvement due to the signal multiplexing was also demonstrated. An analysis of the results indicates both the situations for which the multiplex advantage may be gained, and the limitations of the technique. A number of potential applications of the spectrometric imager are discussed.

Shape from sound: toward new tools for quantum gravity.

PubMed

Aasen, David; Bhamre, Tejal; Kempf, Achim

2013-03-22

To unify general relativity and quantum theory is hard in part because they are formulated in two very different mathematical languages, differential geometry and functional analysis. A natural candidate for bridging this language gap, at least in the case of the Euclidean signature, is the discipline of spectral geometry. It aims at describing curved manifolds in terms of the spectra of their canonical differential operators. As an immediate benefit, this would offer a clean gauge-independent identification of the metric's degrees of freedom in terms of invariants that should be ready to quantize. However, spectral geometry is itself hard and has been plagued by ambiguities. Here, we regularize and break up spectral geometry into small, finite-dimensional and therefore manageable steps. We constructively demonstrate that this strategy works at least in two dimensions. We can now calculate the shapes of two-dimensional objects from their vibrational spectra.

Rate equation modeling of the frequency noise and the intrinsic spectral linewidth in quantum cascade lasers.

PubMed

Wang, Xing-Guang; Grillot, Frédéric; Wang, Cheng

2018-02-05

This work theoretically investigates the frequency noise (FN) characteristics of quantum cascade lasers (QCLs) through a three-level rate equation model, which takes into account both the carrier noise and the spontaneous emission noise through the Langevin approach. It is found that the power spectral density of the FN exhibits a broad peak due to the carrier noise induced carrier variation in the upper laser level, which is enhanced by the stimulated emission process. The peak amplitude is strongly dependent on the gain stage number and the linewidth broadening factor. In addition, an analytical formula of the intrinsic spectral linewidth of QCLs is derived based on the FN analysis. It is demonstrated that the laser linewidth can be narrowed by reducing the gain coefficient and/or accelerating the carrier scattering rates of the upper and the lower laser levels.

Using digital images to measure and discriminate small particles in cotton

NASA Astrophysics Data System (ADS)

Taylor, Robert A.; Godbey, Luther C.

1991-02-01

Inages from conventional video systems are being digitized in coraputers for the analysis of small trash particles in cotton. The method has been developed to automate particle counting and area measurements for bales of cotton prepared for market. Because the video output is linearly proportional to the amount of light reflected the best spectral band for optimum particle discrimination should be centered at the wavelength of maximum difference between particles and their surroundings. However due to the spectral distribution of the illumination energy and the detector sensitivity peak image performance bands were altered. Reflectance from seven mechanically cleaned cotton lint samples and trash removed were examined for spectral contrast in the wavelength range of camera sensitivity. Pixel intensity histograms from the video systent are reported for simulated trashmeter area reference samples (painted dots on panels) and for cotton containing trash to demonstrate the particle discrimination mechanism. 2.

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

Chandra Interactive Analysis of Observations (CIAO)

NASA Technical Reports Server (NTRS)

Dobrzycki, Adam

2000-01-01

The Chandra (formerly AXAF) telescope, launched on July 23, 1999, provides X-rays data with unprecedented spatial and spectral resolution. As part of the Chandra scientific support, the Chandra X-ray Observatory Center provides a new data analysis system, CIAO ("Chandra Interactive Analysis of Observations"). We will present the main components of the system: "First Look" analysis; SHERPA: a multi-dimensional, multi-mission modeling and fitting application; Chandra Imaging and Plotting System; Detect package-source detection algorithms; and DM package generic data manipulation tools, We will set up a demonstration of the portable version of the system and show examples of Chandra Data Analysis.

Exploring the potential of hyper-spectral imaging for the biogeochemical analysis of varved lake sediments

NASA Astrophysics Data System (ADS)

Butz, Christoph; Grosjean, Martin; Enters, Dirk; Tylmann, Wojciech

2014-05-01

Varved lake sediments have successfully been used to make inferences about past environmental and climate conditions from annual to multi-millennial scales. Among other proxies, concentrations of sedimentary photopigments have been used for temperature reconstructions. However, obtaining well calibrated annually resolved records from sediments still remains challenging. Most laboratory methods used to analyse lake sediments require physical subsampling and are destructive in the process. Hence, temporal resolution and number of data are limited by the amount of material available in the core. Furthermore, for very low sediment accumulation rates annual subsampling is often very difficult or even impossible. To address these problems we explore hyper-spectral imaging as a new method to analyse lake sediments based on their reflectance spectra in the visible and near infrared spectrum. In contrast to other fast and non-destructive methods like X-ray fluorescence, VIS/NIR reflectance spectrometry distinguishes between biogeochemical substances rather than single elements. Rein (2003) has shown that VIS-RS can be used to detect relative concentrations of sedimentary photopigments (e.g. chlorins, carotenoids) and clay minerals. This study presents an advanced approach using a hyper-spectral camera and remote sensing techniques to infer climate proxy data from reflectance spectra of varved lake sediments. Hyper-spectral imaging allows analysing an entire sediment core in a single measurement, producing a spectral dataset with very high spatial (30x30µm/pixel) and spectral resolutions (~1nm) and a higher spectral range (400-1000nm) compared to previously used spectrophotometers. This allows the analysis of data time series at sub-varve scales or spatial mapping of sedimentary substances (e.g. chlorophyll-a and diagenetic products) at very high resolution. The method is demonstrated on varved lake sediments from northern Poland showing the change of the relative concentrations of chlorin pigments within individual varve years. In a next step absolute concentrations of chlorins derived from HPLC measurements have been calibrated to the spectral data using a linear regression model. This results in a very high-resolution dataset of absolute sedimentary pigment concentrations. In a second example µXRF measurements are used to validate a spectral index for clay mineral detection.

Quantifying mineral abundances of complex mixtures by coupling spectral deconvolution of SWIR spectra (2.1-2.4 μm) and regression tree analysis

USGS Publications Warehouse

Mulder, V.L.; Plotze, Michael; de Bruin, Sytze; Schaepman, Michael E.; Mavris, C.; Kokaly, Raymond F.; Egli, Markus

2013-01-01

This paper presents a methodology for assessing mineral abundances of mixtures having more than two constituents using absorption features in the 2.1-2.4 μm wavelength region. In the first step, the absorption behaviour of mineral mixtures is parameterised by exponential Gaussian optimisation. Next, mineral abundances are predicted by regression tree analysis using these parameters as inputs. The approach is demonstrated on a range of prepared samples with known abundances of kaolinite, dioctahedral mica, smectite, calcite and quartz and on a set of field samples from Morocco. The latter contained varying quantities of other minerals, some of which did not have diagnostic absorption features in the 2.1-2.4 μm region. Cross validation showed that the prepared samples of kaolinite, dioctahedral mica, smectite and calcite were predicted with a root mean square error (RMSE) less than 9 wt.%. For the field samples, the RMSE was less than 8 wt.% for calcite, dioctahedral mica and kaolinite abundances. Smectite could not be well predicted, which was attributed to spectral variation of the cations within the dioctahedral layered smectites. Substitution of part of the quartz by chlorite at the prediction phase hardly affected the accuracy of the predicted mineral content; this suggests that the method is robust in handling the omission of minerals during the training phase. The degree of expression of absorption components was different between the field sample and the laboratory mixtures. This demonstrates that the method should be calibrated and trained on local samples. Our method allows the simultaneous quantification of more than two minerals within a complex mixture and thereby enhances the perspectives of spectral analysis for mineral abundances.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

NASA Astrophysics Data System (ADS)

Deshmukh, Atul; Singh, S. P.; Chaturvedi, Pankaj; Krishna, C. Murali

2011-12-01

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Identification of Pulmonary Edema in Forensic Autopsy Cases of Sudden Cardiac Death Using Fourier Transform Infrared Microspectroscopy: A Pilot Study.

PubMed

Lin, Hancheng; Luo, Yiwen; Sun, Qiran; Zhang, Ji; Tuo, Ya; Zhang, Zhong; Wang, Lei; Deng, Kaifei; Chen, Yijiu; Huang, Ping; Wang, Zhenyuan

2018-02-20

Many studies have proven the usefulness of biofluid-based infrared spectroscopy in the clinical domain for diagnosis and monitoring the progression of diseases. Here we present a state-of-the-art study in the forensic field that employed Fourier transform infrared microspectroscopy for postmortem diagnosis of sudden cardiac death (SCD) by in situ biochemical investigation of alveolar edema fluid in lung tissue sections. The results of amide-related spectral absorbance analysis demonstrated that the pulmonary edema fluid of the SCD group was richer in protein components than that of the neurologic catastrophe (NC) and lethal multiple injuries (LMI) groups. The complementary results of unsupervised principle component analysis (PCA) and genetic algorithm-guided partial least-squares discriminant analysis (GA-PLS-DA) further indicated different global spectral band patterns of pulmonary edema fluids between these three groups. Ultimately, a random forest (RF) classification model for postmortem diagnosis of SCD was built and achieved good sensitivity and specificity scores of 97.3% and 95.5%, respectively. Classification predictions of unknown pulmonary edema fluid collected from 16 cases were also performed by the model, resulting in 100% correct discrimination. This pilot study demonstrates that FTIR microspectroscopy in combination with chemometrics has the potential to be an effective aid for postmortem diagnosis of SCD.

A comparison of spectral magnitude and phase-locking value analyses of the frequency-following response to complex tones

PubMed Central

Zhu, Li; Bharadwaj, Hari; Xia, Jing; Shinn-Cunningham, Barbara

2013-01-01

Two experiments, both presenting diotic, harmonic tone complexes (100 Hz fundamental), were conducted to explore the envelope-related component of the frequency-following response (FFRENV), a measure of synchronous, subcortical neural activity evoked by a periodic acoustic input. Experiment 1 directly compared two common analysis methods, computing the magnitude spectrum and the phase-locking value (PLV). Bootstrapping identified which FFRENV frequency components were statistically above the noise floor for each metric and quantified the statistical power of the approaches. Across listeners and conditions, the two methods produced highly correlated results. However, PLV analysis required fewer processing stages to produce readily interpretable results. Moreover, at the fundamental frequency of the input, PLVs were farther above the metric's noise floor than spectral magnitudes. Having established the advantages of PLV analysis, the efficacy of the approach was further demonstrated by investigating how different acoustic frequencies contribute to FFRENV, analyzing responses to complex tones composed of different acoustic harmonics of 100 Hz (Experiment 2). Results show that the FFRENV response is dominated by peripheral auditory channels responding to unresolved harmonics, although low-frequency channels driven by resolved harmonics also contribute. These results demonstrate the utility of the PLV for quantifying the strength of FFRENV across conditions. PMID:23862815

Feasibility and demonstration of a cloud-based RIID analysis system

NASA Astrophysics Data System (ADS)

Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

2015-06-01

A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed.

Extension of the Time-Spectral Approach to Overset Solvers for Arbitrary Motion

NASA Technical Reports Server (NTRS)

Leffell, Joshua Isaac; Murman, Scott M.; Pulliam, Thomas H.

2012-01-01

Forced periodic flows arise in a broad range of aerodynamic applications such as rotorcraft, turbomachinery, and flapping wing configurations. Standard practice involves solving the unsteady flow equations forward in time until the initial transient exits the domain and a statistically stationary flow is achieved. It is often required to simulate through several periods to remove the initial transient making unsteady design optimization prohibitively expensive for most realistic problems. An effort to reduce the computational cost of these calculations led to the development of the Harmonic Balance method [1, 2] which capitalizes on the periodic nature of the solution. The approach exploits the fact that forced temporally periodic flow, while varying in the time domain, is invariant in the frequency domain. Expanding the temporal variation at each spatial node into a Fourier series transforms the unsteady governing equations into a steady set of equations in integer harmonics that can be tackled with the acceleration techniques afforded to steady-state flow solvers. Other similar approaches, such as the Nonlinear Frequency Domain [3,4,5], Reduced Frequency [6] and Time-Spectral [7, 8, 9] methods, were developed shortly thereafter. Additionally, adjoint-based optimization techniques can be applied [10, 11] as well as frequency-adaptive methods [12, 13, 14] to provide even more flexibility to the method. The Fourier temporal basis functions imply spectral convergence as the number of harmonic modes, and correspondingly number of time samples, N, is increased. Some elect to solve the equations in the frequency domain directly, while others choose to transform the equations back into the time domain to simplify the process of adding this capability to existing solvers, but each harnesses the underlying steady solution in the frequency domain. These temporal projection methods will herein be collectively referred to as Time-Spectral methods. Time-Spectral methods have demonstrated marked success in reducing the computational costs associated with simulating periodic forced flows, but have yet to be fully applied to overset or Cartesian solvers for arbitrary motion with dynamic hole-cutting. Overset and Cartesian grid methodologies are versatile techniques capable of handling complex geometry configurations in practical engineering applications, and the combination of the Time-Spectral approach with this general capability potentially provides an enabling new design and analysis tool. In an arbitrary moving-body scenario for these approaches, a Lagrangian body moves through a fixed Eulerian mesh and mesh points in the Eulerian mesh interior to the solid body are removed (cut or blanked), leaving a hole in the Eulerian mesh. During the dynamic motion some gridpoints in the domain are blanked and do not have a complete set of time-samples preventing a direct implementation of the Time-Spectral method. Murman[6] demonstrated the Time-Spectral approach for a Cartesian solver with a rigid domain motion, wherein the hole cutting remains constant. Similarly, Custer et al. [15, 16] used the NASA overset OVERFLOW solver and limited the amount of relative motion to ensure static hole-cutting and interpolation. Recently, Mavriplis and Mundis[17] demonstrated a qualitative method for applying the Time-Spectral approach to an unstructured overset solver for arbitrary motion. The goal of the current work is to develop a robust and general method for handling arbitrary motion with the Time-Spectral approach within an overset or Cartesian mesh method, while still approaching the spectral convergence rate of the original Time-Spectral approach. The viscous OVERFLOW solver will be augmented with the new Time-Spectral algorithm and the capability of the method for benchmark problems in rotorcraft and turbomachinery will be demonstrated. This abstract begins with a brief synopsis of the Time-Spectral approach for overset grids and provides details of e current approach to allow for arbitrary motion. Model problem results in one and two dimensions are included to demonstrate the viability of the method and the convergence properties. Section IV briefly outlines the implementation into the OVERFLOW solver, and the abstract closes with a description of the benchmark test cases which will be included in the final paper.

Detailed Spectral Analysis of the 260 ks XMM-Newton Data of 1E 1207.4-5209 and Significance of a 2.1 keV Absorption Feature

NASA Astrophysics Data System (ADS)

Mori, Kaya; Chonko, James C.; Hailey, Charles J.

2005-10-01

We have reanalyzed the 260 ks XMM-Newton observation of 1E 1207.4-5209. There are several significant improvements over previous work. First, a much broader range of physically plausible spectral models was used. Second, we have used a more rigorous statistical analysis. The standard F-distribution was not employed, but rather the exact finite statistics F-distribution was determined by Monte Carlo simulations. This approach was motivated by the recent work of Protassov and coworkers and Freeman and coworkers. They demonstrated that the standard F-distribution is not even asymptotically correct when applied to assess the significance of additional absorption features in a spectrum. With our improved analysis we do not find a third and fourth spectral feature in 1E 1207.4-5209 but only the two broad absorption features previously reported. Two additional statistical tests, one line model dependent and the other line model independent, confirmed our modified F-test analysis. For all physically plausible continuum models in which the weak residuals are strong enough to fit, the residuals occur at the instrument Au M edge. As a sanity check we confirmed that the residuals are consistent in strength and position with the instrument Au M residuals observed in 3C 273.

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

PubMed Central

Keitel, Anne; Gross, Joachim

2016-01-01

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease. PMID:27355236

Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization.

PubMed

Yuan, Yuan; Lin, Jianzhe; Wang, Qi

2016-12-01

Hyperspectral image (HSI) classification is a crucial issue in remote sensing. Accurate classification benefits a large number of applications such as land use analysis and marine resource utilization. But high data correlation brings difficulty to reliable classification, especially for HSI with abundant spectral information. Furthermore, the traditional methods often fail to well consider the spatial coherency of HSI that also limits the classification performance. To address these inherent obstacles, a novel spectral-spatial classification scheme is proposed in this paper. The proposed method mainly focuses on multitask joint sparse representation (MJSR) and a stepwise Markov random filed framework, which are claimed to be two main contributions in this procedure. First, the MJSR not only reduces the spectral redundancy, but also retains necessary correlation in spectral field during classification. Second, the stepwise optimization further explores the spatial correlation that significantly enhances the classification accuracy and robustness. As far as several universal quality evaluation indexes are concerned, the experimental results on Indian Pines and Pavia University demonstrate the superiority of our method compared with the state-of-the-art competitors.

A target detection multi-layer matched filter for color and hyperspectral cameras

NASA Astrophysics Data System (ADS)

Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

2018-05-01

In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

Human high intelligence is involved in spectral redshift of biophotonic activities in the brain

PubMed Central

Wang, Niting; Li, Zehua; Xiao, Fangyan; Dai, Jiapei

2016-01-01

Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain. PMID:27432962

Mineral Potential in India Using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) Data

NASA Astrophysics Data System (ADS)

Oommen, T.; Chatterjee, S.

2017-12-01

NASA and the Indian Space Research Organization (ISRO) are generating Earth surface features data using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) within 380 to 2500 nm spectral range. This research focuses on the utilization of such data to better understand the mineral potential in India and to demonstrate the application of spectral data in rock type discrimination and mapping for mineral exploration by using automated mapping techniques. The primary focus area of this research is the Hutti-Maski greenstone belt, located in Karnataka, India. The AVIRIS-NG data was integrated with field analyzed data (laboratory scaled compositional analysis, mineralogy, and spectral library) to characterize minerals and rock types. An expert system was developed to produce mineral maps from AVIRIS-NG data automatically. The ground truth data from the study areas was obtained from the existing literature and collaborators from India. The Bayesian spectral unmixing algorithm was used in AVIRIS-NG data for endmember selection. The classification maps of the minerals and rock types were developed using support vector machine algorithm. The ground truth data was used to verify the mineral maps.

Broadband optical equalizer using fault tolerant digital micromirrors.

PubMed

Riza, Nabeel; Mughal, M Junaid

2003-06-30

For the first time, the design and demonstration of a near continuous spectral processing mode broadband equalizer is described using the earlier proposed macro-pixel spatial approach for multiwavelength fiber-optic attenuation in combination with a high spectral resolution broadband transmissive volume Bragg grating. The demonstrated design features low loss and low polarization dependent loss with broadband operation. Such an analog mode spectral processor can impact optical applications ranging from test and instrumentation to dynamic alloptical networks.

Imaging Spectroscopy Enables Novel Applications and Continuity with the Landsat Record to Sustain Legacy Applications: An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Landsat 8 OLI Case Study

NASA Astrophysics Data System (ADS)

Stavros, E. N.; Seidel, F.; Cable, M. L.; Green, R. O.; Freeman, A.

2017-12-01

While, imaging spectrometers offer additional information that provide value added products for applications that are otherwise underserved, there is need to demonstrate their ability to augment the multi-spectral (e.g., Landsat) optical record by both providing more frequent temporal revisit and lengthening the existing record. Here we test the hypothesis that imaging spectroscopic optical data is compatible with multi-spectral data to within ±5% radiometric accuracy, as desirable to continue the long-term Landsat data record. We use a coincident Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flight with over-passing Operational Land Imager (OLI) data on Landsat 8 to document a procedure for simulating OLI multi-spectral bands from AVIRIS, evaluate influencing factors on the observed radiance, and assess AVIRIS radiometric accuracy compared to OLI. The procedure for simulating OLI data includes spectral convolution, accounting for atmospheric effects introduced by different sensor altitude and viewing geometries, and spatial resampling. After accounting for these influences, we expect the remaining differences between the simulated and the real OLI data result from differences in sensor calibration, surface bi-directional reflectance, from the different viewing geometries, and spatial sampling. The median radiometric percent difference for each band in the data used range from 0.6% to 8.3%. After bias-correction to minimize potential calibration discrepancies, we find no more than 1.2% radiometric percent difference for any OLI band. This analysis therefore successfully demonstrates that imaging spectrometer data can not only address novel applications, but also contribute to the Landsat-type or other multi-spectral data records to sustain legacy applications.

Heart rate variability in the standing position reflects training adaptation in professional soccer players.

PubMed

Ravé, Guillaume; Fortrat, Jacques-Olivier

2016-08-01

To show that heart rate variability (HRV) in the standing position better reflects the way in which athletes adapt to training in so-called intermittent sports than the indicator of resting parasympathetic tone usually employed in endurance sports. Twenty professional soccer players (intermittent sport) took part in a 5-week training session divided into three successive periods: "Warm-up", "Intensive training" and "Tapering". At the beginning and end of each of the three periods, a stand test was carried out and the heart rate was recorded, beat by beat (Polar Team 2). We analysed HRV to determine the indicator mostly used to demonstrate training adaptation in endurance sports (lnRMSSD supine, natural logarithm of root mean square of the successive differences) as well as indicators obtained by means of spectral analysis in both supine and standing position. A decrease in heart rate was observed in the supine position at rest during training (-5.2 ± 1.3 bpm) while lnRMSSD and spectral analysis indicators remained unchanged. The "Warm-up" caused an increase in spectral analysis total power in standing position which was further highlighted by "Tapering" (3.39 ± 0.09, 3.61 ± 0.08 and 3.65 ± 0.09 log ms(2), respectively). However, the autonomic changes are probably more complex than a change in autonomic activity or balance since spectral analysis autonomic indicators remained unchanged. HRV in the standing position could monitor training adaptation in intermittent sports contrary to the indicator usually employed in endurance sports. However, the significance of the HRV change in the standing position during training remains unclear.

Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index

PubMed Central

Pu, Ruiliang; Gong, Peng; Yu, Qian

2008-01-01

In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data. PMID:27879906

Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index.

PubMed

Pu, Ruiliang; Gong, Peng; Yu, Qian

2008-06-06

In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Advanced materials for multilayer mirrors for extreme ultraviolet solar astronomy.

PubMed

Bogachev, S A; Chkhalo, N I; Kuzin, S V; Pariev, D E; Polkovnikov, V N; Salashchenko, N N; Shestov, S V; Zuev, S Y

2016-03-20

We provide an analysis of contemporary multilayer optics for extreme ultraviolet (EUV) solar astronomy in the wavelength ranges: λ=12.9-13.3  nm, λ=17-21  nm, λ=28-33  nm, and λ=58.4  nm. We found new material pairs, which will make new spaceborne experiments possible due to the high reflection efficiencies, spectral resolution, and long-term stabilities of the proposed multilayer coatings. In the spectral range λ=13  nm, Mo/Be multilayer mirrors were shown to demonstrate a better ratio of reflection efficiency and spectral resolution compared with the commonly used Mo/Si. In the spectral range λ=17-21  nm, a new multilayer structure Al/Si was proposed, which had higher spectral resolution along with comparable reflection efficiency compared with the commonly used Al/Zr multilayer structures. In the spectral range λ=30  nm, the Si/B₄C/Mg/Cr multilayer structure turned out to best obey reflection efficiency and long-term stability. The B₄C and Cr layers prevented mutual diffusion of the Si and Mg layers. For the spectral range λ=58  nm, a new multilayer Mo/Mg-based structure was developed; its reflection efficiency and long-term stability have been analyzed. We also investigated intrinsic stresses inherent for most of the multilayer structures and proposed possibilities for stress elimination.

Automated system for the on-line monitoring of powder blending processes using near-infrared spectroscopy. Part I. System development and control.

PubMed

Hailey, P A; Doherty, P; Tapsell, P; Oliver, T; Aldridge, P K

1996-03-01

An automated system for the on-line monitoring of powder blending processes is described. The system employs near-infrared (NIR) spectroscopy using fibre-optics and a graphical user interface (GUI) developed in the LabVIEW environment. The complete supervisory control and data analysis (SCADA) software controls blender and spectrophotometer operation and performs statistical spectral data analysis in real time. A data analysis routine using standard deviation is described to demonstrate an approach to the real-time determination of blend homogeneity.

Mid-IR Spectral Investigation of Normal and Malignant Breast and Cervical Tissue Samples Using a Quantum Cascade Laser-Based Microscope

NASA Astrophysics Data System (ADS)

Haugen, Paul

Mid-infrared (MIR) spectroscopy has been a tool used to identify specific features of normal and malignant tissue samples by utilizing MIR characteristics, specifically in the "fingerprint" region. The fingerprint region is a biologically significant spectral region typically identified between 1500 and 500 cm-1. MIR spectroscopy can be used to study molecular changes and variations occurring in samples, which can then be used to fingerprint specific spectral characteristics and biomarkers in order to categorize the specimens. The most common instruments currently used in this analysis are Fourier transform infrared (FTIR) spectrometers, although properties inherent in these instruments, such as slow data collection time and an inability to specify sample location for the spectral data collection, have placed a ceiling on the clinical practicality of their use for specimen classification and identification. In this thesis, we use a prototype of an infrared hyperspectral imaging microscopy platform based around tunable quantum cascade laser (QCL) technology that has a spectral coverage from 1800-900 cm-1. The quantum cascade lasers are coupled with a series of MIR refractive objectives and an uncooled microbolometer camera. The speed of spectral imaging improves to 30 frames per second, and the high magnification objective has a 1.34 microm pixel resolution with a 0.70 numerical aperture and 4.3 microm spatial resolution. We are able to specify data collection at specific discrete wavelengths as opposed to the full spectrum, which improves the data collection time and de-clutters the data for analysis expediency. Finally, we perform spectral imaging real-time, which aides in selecting precise regions of interest on the target sample. This thesis demonstrates the advantages of exploiting the capabilities of the QCL microscope to advance MIR spectroscopy in the identification of distinguishing traits of normal and malignant breast and cervical tissue samples.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

Local Environment and Interactions of Liquid and Solid Interfaces Revealed by Spectral Line Shape of Surface Selective Nonlinear Vibrational Probe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Shun-Li; Fu, Li; Chase, Zizwe A.

Vibrational spectral lineshape contains important detailed information of molecular vibration and reports its specific interactions and couplings to its local environment. In this work, recently developed sub-1 cm-1 high-resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS) was used to measure the -C≡N stretch vibration in the 4-n-octyl-4’-cyanobiphenyl (8CB) Langmuir or Langmuir-Blodgett (LB) monolayer as a unique vibrational probe, and the spectral lineshape analysis revealed the local environment and interactions at the air/water, air/glass, air/calcium fluoride and air/-quartz interfaces for the first time. The 8CB Langmuir or LB film is uniform and the vibrational spectral lineshape of its -C≡N group hasmore » been well characterized, making it a good choice as the surface vibrational probe. Lineshape analysis of the 8CB -C≡N stretch SFG vibrational spectra suggests the coherent vibrational dynamics and the structural and dynamic inhomogeneity of the -C≡N group at each interface are uniquely different. In addition, it is also found that there are significantly different roles for water molecules in the LB films on different substrate surfaces. These results demonstrated the novel capabilities of the surface nonlinear spectroscopy in characterization and in understanding the specific structures and chemical interactions at the liquid and solid interfaces in general.« less

[Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

PubMed

Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

2010-04-01

Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.

[State Recognition of Solid Fermentation Process Based on Near Infrared Spectroscopy with Adaboost and Spectral Regression Discriminant Analysis].

PubMed

Yu, Shuang; Liu, Guo-hai; Xia, Rong-sheng; Jiang, Hui

2016-01-01

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris II), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct recognition rate of the Adaboost-SRDA-NN model achieved 100% in the validation set. The overall results demonstrate that SRDA algorithm can effectively achieve the spectral feature information extraction to the spectral dimension reduction in model calibration process of qualitative analysis of NIR spectroscopy. In addition, the Adaboost lifting algorithm can improve the classification accuracy of the final model. The results obtained in this work can provide research foundation for developing online monitoring instruments for the monitoring of SSF process.

Linear Spectral Analysis of Plume Emissions Using an Optical Matrix Processor

NASA Technical Reports Server (NTRS)

Gary, C. K.

1992-01-01

Plume spectrometry provides a means to monitor the health of a burning rocket engine, and optical matrix processors provide a means to analyze the plume spectra in real time. By observing the spectrum of the exhaust plume of a rocket engine, researchers have detected anomalous behavior of the engine and have even determined the failure of some equipment before it would normally have been noticed. The spectrum of the plume is analyzed by isolating information in the spectrum about the various materials present to estimate what materials are being burned in the engine. Scientists at the Marshall Space Flight Center (MSFC) have implemented a high resolution spectrometer to discriminate the spectral peaks of the many species present in the plume. Researchers at the Stennis Space Center Demonstration Testbed Facility (DTF) have implemented a high resolution spectrometer observing a 1200-lb. thrust engine. At this facility, known concentrations of contaminants can be introduced into the burn, allowing for the confirmation of diagnostic algorithms. While the high resolution of the measured spectra has allowed greatly increased insight into the functioning of the engine, the large data flows generated limit the ability to perform real-time processing. The use of an optical matrix processor and the linear analysis technique described below may allow for the detailed real-time analysis of the engine's health. A small optical matrix processor can perform the required mathematical analysis both quicker and with less energy than a large electronic computer dedicated to the same spectral analysis routine.

Broadband interferometric characterization of divergence and spatial chirp.

PubMed

Meier, Amanda K; Iliev, Marin; Squier, Jeff A; Durfee, Charles G

2015-09-01

We demonstrate a spectral interferometric method to characterize lateral and angular spatial chirp to optimize intensity localization in spatio-temporally focused ultrafast beams. Interference between two spatially sheared beams in an interferometer will lead to straight fringes if the wavefronts are curved. To produce reference fringes, we delay one arm relative to another in order to measure fringe rotation in the spatially resolved spectral interferogram. With Fourier analysis, we can obtain frequency-resolved divergence. In another arrangement, we spatially flip one beam relative to the other, which allows the frequency-dependent beamlet direction (angular spatial chirp) to be measured. Blocking one beam shows the spatial variation of the beamlet position with frequency (i.e., the lateral spatial chirp).

Dielectric spectroscopy in benzophenone: the beta relaxation and its relation to the mode-coupling Cole-Cole peak.

PubMed

Pardo, L C; Lunkenheimer, P; Loidl, A

2007-09-01

We report a thorough characterization of the glassy dynamics of benzophenone by broadband dielectric spectroscopy. We detect a well-pronounced beta relaxation peak developing into an excess wing with increasing temperature. A previous analysis of results from Optical-Kerr-effect measurements of this material within the mode-coupling theory revealed a high-frequency Cole-Cole peak. We address the question if this phenomenon also may explain the Johari-Goldstein beta relaxation, a so-far unexplained spectral feature inherent to glass-forming matter, mainly observed in dielectric spectra. Our results demonstrate that according to the present status of theory, both spectral features seem not to be directly related.

Observation of asymmetric spectrum broadening induced by silver nanoparticles in a heavy-metal oxide glass

NASA Astrophysics Data System (ADS)

Zhavoronkov, N.; Driben, R.; Bregadiolli, B. A.; Nalin, M.; Malomed, B. A.

2011-05-01

We demonstrate experimentally and support by a theoretical analysis an effect of asymmetric spectrum broadening, which results from doping of silver nanoparticles into a heavy-glass matrix, 90(0.5WO3-0.3SbPO4-0.2PbO)-10AgCl. The strong dispersion of the effective nonlinear coefficient of the composite significantly influences the spectral broadening via the self-phase modulation, and leads to a blue upshift of the spectrum. Further extension of the spectrum towards shorter wavelengths is suppressed by a growing loss caused by the plasmon resonance in the silver particles. The red-edge spectral broadening is dominated by the stimulated Raman scattering.

Spectral studies of cosmic X-ray sources

NASA Astrophysics Data System (ADS)

Blissett, R. J.

1980-01-01

The conventional "indirect" method of reduction and data analysis of spectral data from non-dispersive X-ray detectors, by the fitting of assumed spectral models, is examined. The limitations of this procedure are presented, and alternative schemes are considered in which the derived spectra are not biased to an astrophysical source model. A new method is developed in detail to directly restore incident photon spectra from the detected count histograms. This Spectral Restoration Technique allows an increase in resolution, to a degree dependent on the statistical precision of the data. This is illustrated by numerical simulations. Proportional counter data from Ariel 5 are analysed using this technique. The results obtained for the sources Cas A and the Crab Nebula are consistent with previous analyses and show that increases in resolution of up to a factor three are possible in practice. The source Cyg X-3 is closely examined. Complex spectral variability is found, with the continuum and iron-line emission modulated with the 4.8 hour period of the source. The data suggest multi-component emission in the source. Comparing separate Ariel 5 observations and published data from other experiments, a correlation between the spectral shape and source intensity is evident. The source behaviour is discussed with reference to proposed source models. Data acquired by the low-energy detectors on-board HEAO-1 are analysed using the Spectral Restoration Technique. This treatment explicitly demonstrates the existence of oxygen K-absorption edges in the soft X-ray spectra of the Crab Nebula and Sco X-1. These results are considered with reference to current theories of the interstellar medium. The thesis commences with a review of cosmic X-ray sources and the mechanisms responsible for their spectral signatures, and continues with a discussion of the instruments appropriate for spectral studies in X-ray astronomy.

Spectral and spread-spectral teleportation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Humble, Travis S.

2010-06-15

We report how quantum information encoded into the spectral degree of freedom of a single-photon state may be teleported using a finite spectrally entangled biphoton state. We further demonstrate how the bandwidth of the teleported wave form can be controllably and coherently dilated using a spread-spectral variant of teleportation. We calculate analytical expressions for the fidelities of spectral and spread-spectral teleportation when complex-valued Gaussian states are transferred using a proposed experimental approach. Finally, we discuss the utility of these techniques for integrating broad-bandwidth photonic qubits with narrow-bandwidth receivers in quantum communication systems.

Discrimination between Bacillus and Alicyclobacillus isolates in apple juice by Fourier transform infrared spectroscopy and multivariate analysis.

PubMed

Al-Holy, Murad A; Lin, Mengshi; Alhaj, Omar A; Abu-Goush, Mahmoud H

2015-02-01

Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between 4 Alicyclobacillus strains and 4 Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm(-1) reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (for example, principal component analysis and soft independent modeling of class analogy) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these 2 genera. © 2015 Institute of Food Technologists®

Demonstrating Principles of Spectrophotometry by Constructing a Simple, Low-Cost, Functional Spectrophotometer Utilizing the Light Sensor on a Smartphone

ERIC Educational Resources Information Center

Hosker, Bill S.

2018-01-01

A highly simplified variation on the do-it-yourself spectrophotometer using a smartphone's light sensor as a detector and an app to calculate and display absorbance values was constructed and tested. This simple version requires no need for electronic components or postmeasurement spectral analysis. Calibration graphs constructed from two…

Report to the U.S. Congress on the National Oceanographic Partnership Program

DTIC Science & Technology

1999-01-01

security, advancing economic development, protecting quality of life, and strengthening science education and communication through improved knowledge of... nitrate analyzers, and spectral optical sensors) will be tested on testbed moorings near Bermuda and Monterey Bay. The newly developed systems...design, systems integration, interdisciplinary multiscale data assimilation and interactive processes. real-time demonstration of concept and analysis of

Risk Management using Dependency Stucture Matrix

NASA Astrophysics Data System (ADS)

Petković, Ivan

2011-09-01

An efficient method based on dependency structure matrix (DSM) analysis is given for ranking risks in a complex system or process whose entities are mutually dependent. This rank is determined according to the element's values of the unique positive eigenvector which corresponds to the matrix spectral radius modeling the considered engineering system. For demonstration, the risk problem of NASA's robotic spacecraft is analyzed.

Resolving Spectral Lines with a Periscope-Type DVD Spectroscope

ERIC Educational Resources Information Center

Wakabayashi, Fumitaka

2008-01-01

A new type of DVD spectroscope, the periscope type, is described and the numerical analysis of the observed emission and absorption spectra is demonstrated. A small and thin mirror is put inside and an eighth part of a DVD is used as a grating. Using this improved DVD spectroscope, one can observe and photograph visible spectra more easily and…

Identification of recently handled materials by analysis of latent human fingerprints using infrared spectromicroscopy.

PubMed

Grant, Ashleigh; Wilkinson, T J; Holman, Derek R; Martin, Michael C

2005-09-01

Analysis of fingerprints has predominantly focused on matching the pattern of ridges to a specific person as a form of identification. The present work focuses on identifying extrinsic materials that are left within a person's fingerprint after recent handling of such materials. Specifically, we employed infrared spectromicroscopy to locate and positively identify microscopic particles from a mixture of common materials in the latent human fingerprints of volunteer subjects. We were able to find and correctly identify all test substances based on their unique infrared spectral signatures. Spectral imaging is demonstrated as a method for automating recognition of specific substances in a fingerprint. We also demonstrate the use of attenuated total reflectance (ATR) and synchrotron-based infrared spectromicroscopy for obtaining high-quality spectra from particles that were too thick or too small, respectively, for reflection/absorption measurements. We believe the application of this rapid, nondestructive analytical technique to the forensic study of latent human fingerprints has the potential to add a new layer of information available to investigators. Using fingerprints to not only identify who was present at a crime scene, but also to link who was handling key materials, will be a powerful investigative tool.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thornhill, Tom Finley, III; Reinhart, William Dodd; Lawrence, Raymond Jeffery Jr.

Kill assessment continues to be a major problem for the nation's missile defense program. A potential approach for addressing this issue involves spectral and temporal analysis of the short-time impact flash that occurs when a kill vehicle intercepts and engages a target missile. This can provide identification of the materials involved in the impact event, which will, in turn, yield the data necessary for target identification, engagement analysis, and kill assessment. This report describes the first phases of a project under which we are providing laboratory demonstrations of the feasibility and effectiveness of this approach. We are using two majormore » Sandia facilities, the Z-Pinch accelerator, and the two- and three-stage gas guns at the Shock Thermodynamics and Applied Research (STAR) facility. We have looked at the spectral content of impact flash at velocities up to 25 km/s on the Z-Pinch machine to establish the capability for spectroscopy for these types of events, and are looking at similar experiments at velocities from 6 to 11 km/s on the gas guns to demonstrate a similar capability for a variety of research-oriented and applied materials. The present report describes only the work performed on the Z machine.« less

Power spectral analysis of the sleep electroencephalogram in heartburn patients with or without gastroesophageal reflux disease: a feasibility study.

PubMed

Budhiraja, Rohit; Quan, Stuart F; Punjabi, Naresh M; Drake, Christopher L; Dickman, Ram; Fass, Ronnie

2010-02-01

Determine the feasibility of using power spectrum of the sleep electroencephalogram (EEG) as a more sensitive tool than sleep architecture to evaluate the relationship between gastroesophageal reflux disease (GERD) and sleep. GERD has been shown to adversely affect subjective sleep reports but not necessarily objective sleep parameters. Data were prospectively collected from symptomatic patients with heartburn. All symptomatic patients underwent upper endoscopy. Patients without erosive esophagitis underwent pH testing. Sleep was polygraphically recorded in the laboratory. Spectral analysis was performed to determine the power spectrum in 4 bandwidths: delta (0.8 to 4.0 Hz), theta (4.1 to 8.0 Hz), alpha (8.1 to 13.0 Hz), and beta (13.1 to 20.0 Hz). Eleven heartburn patients were included in the GERD group (erosive esophagitis) and 6 heartburn patients in the functional heartburn group (negative endoscopy, pH test, response to proton pump inhibitors). The GERD patients had evidence of lower average delta-power than functional heartburn patients. Patients with GERD had greater overall alpha-power in the latter half of the night (3 hours after sleep onset) than functional heartburn patients. No significant differences were noted in conventional sleep stage summaries between the 2 groups. Among heartburn patients with GERD, EEG spectral power during sleep is shifted towards higher frequencies compared with heartburn patients without GERD despite similar sleep architecture. This feasibility study demonstrated that EEG spectral power during sleep might be the preferred tool to provide an objective analysis about the effect of GERD on sleep.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Physiological basis for noninvasive skin cancer diagnosis using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Yao; Markey, Mia K.; Tunnell, James W.

2017-02-01

Diffuse reflectance spectroscopy offers a noninvasive, fast, and low-cost alternative to visual screening and biopsy for skin cancer diagnosis. We have previously acquired reflectance spectra from 137 lesions in 76 patients and determined the capability of spectral diagnosis using principal component analysis (PCA). However, it is not well elucidated why spectral analysis enables tissue classification. To provide the physiological basis, we used the Monte Carlo look-up table (MCLUT) model to extract physiological parameters from those clinical data. The MCLUT model results in the following physiological parameters: oxygen saturation, hemoglobin concentration, melanin concentration, vessel radius, and scattering parameters. Physiological parameters show that cancerous skin tissue has lower scattering and larger vessel radii, compared to normal tissue. These results demonstrate the potential of diffuse reflectance spectroscopy for detection of early precancerous changes in tissue. In the future, a diagnostic algorithm that combines these physiological parameters could be enable non-invasive diagnosis of skin cancer.

Spectral analysis based on fast Fourier transformation (FFT) of surveillance data: the case of scarlet fever in China.

PubMed

Zhang, T; Yang, M; Xiao, X; Feng, Z; Li, C; Zhou, Z; Ren, Q; Li, X

2014-03-01

Many infectious diseases exhibit repetitive or regular behaviour over time. Time-domain approaches, such as the seasonal autoregressive integrated moving average model, are often utilized to examine the cyclical behaviour of such diseases. The limitations for time-domain approaches include over-differencing and over-fitting; furthermore, the use of these approaches is inappropriate when the assumption of linearity may not hold. In this study, we implemented a simple and efficient procedure based on the fast Fourier transformation (FFT) approach to evaluate the epidemic dynamic of scarlet fever incidence (2004-2010) in China. This method demonstrated good internal and external validities and overcame some shortcomings of time-domain approaches. The procedure also elucidated the cycling behaviour in terms of environmental factors. We concluded that, under appropriate circumstances of data structure, spectral analysis based on the FFT approach may be applicable for the study of oscillating diseases.

Statistical mapping of zones of focused groundwater/surface-water exchange using fiber-optic distributed temperature sensing

USGS Publications Warehouse

Mwakanyamale, Kisa; Day-Lewis, Frederick D.; Slater, Lee D.

2013-01-01

Fiber-optic distributed temperature sensing (FO-DTS) increasingly is used to map zones of focused groundwater/surface-water exchange (GWSWE). Previous studies of GWSWE using FO-DTS involved identification of zones of focused GWSWE based on arbitrary cutoffs of FO-DTS time-series statistics (e.g., variance, cross-correlation between temperature and stage, or spectral power). New approaches are needed to extract more quantitative information from large, complex FO-DTS data sets while concurrently providing an assessment of uncertainty associated with mapping zones of focused GSWSE. Toward this end, we present a strategy combining discriminant analysis (DA) and spectral analysis (SA). We demonstrate the approach using field experimental data from a reach of the Columbia River adjacent to the Hanford 300 Area site. Results of the combined SA/DA approach are shown to be superior to previous results from qualitative interpretation of FO-DTS spectra alone.

FLASH free-electron laser single-shot temporal diagnostic: terahertz-field-driven streaking.

PubMed

Ivanov, Rosen; Liu, Jia; Brenner, Günter; Brachmanski, Maciej; Düsterer, Stefan

2018-01-01

The commissioning of a terahertz-field-driven streak camera installed at the free-electron laser (FEL) FLASH at DESY in Hamburg, being able to deliver photon pulse duration as well as arrival time information with ∼10 fs resolution for each single XUV FEL pulse, is reported. Pulse durations between 300 fs and <15 fs have been measured for different FLASH FEL settings. A comparison between the XUV pulse arrival time and the FEL electron bunch arrival time measured at the FLASH linac section exhibits a correlation width of 20 fs r.m.s., thus demonstrating the excellent operation stability of FLASH. In addition, the terahertz-streaking setup was operated simultaneously to an alternative method to determine the FEL pulse duration based on spectral analysis. FLASH pulse duration derived from simple spectral analysis is in good agreement with that from terahertz-streaking measurement.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lebrat, J. F.; Plaschy, M.; Tommasi, J.

This paper presents the analysis of some selected experiments of the MUSE-4 program with the ERANOS-2.1 code system using either the JEF-2.2 library or the more recent JEFF-3.1 one; focus has been given to the reactivities calculations and to the spectral indices of the MUSE-4-Reference and SC3-Pb core configurations. Both libraries provide comparable results on the k{sub eff} of the Reference configuration due to large negative and positive compensating reactivity effects, whereas there is a -400 pcm effect on SC3-Pb. A perturbation analysis demonstrates that the large negative total reactivity effect in this configuration comes from the increase of themore » lead contribution and from the decrease of the sodium contribution. The new library improves the C/E for all the spectral indices in the fuel zone and for most of them in the lead zone except for {sup 238}U and {sup 243}Am. (authors)« less

Snapshot Hyperspectral Volumetric Microscopy

NASA Astrophysics Data System (ADS)

Wu, Jiamin; Xiong, Bo; Lin, Xing; He, Jijun; Suo, Jinli; Dai, Qionghai

2016-04-01

The comprehensive analysis of biological specimens brings about the demand for capturing the spatial, temporal and spectral dimensions of visual information together. However, such high-dimensional video acquisition faces major challenges in developing large data throughput and effective multiplexing techniques. Here, we report the snapshot hyperspectral volumetric microscopy that computationally reconstructs hyperspectral profiles for high-resolution volumes of ~1000 μm × 1000 μm × 500 μm at video rate by a novel four-dimensional (4D) deconvolution algorithm. We validated the proposed approach with both numerical simulations for quantitative evaluation and various real experimental results on the prototype system. Different applications such as biological component analysis in bright field and spectral unmixing of multiple fluorescence are demonstrated. The experiments on moving fluorescent beads and GFP labelled drosophila larvae indicate the great potential of our method for observing multiple fluorescent markers in dynamic specimens.

Constrained spectral clustering under a local proximity structure assumption

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Xu, Qianjun; des Jardins, Marie

2005-01-01

This work focuses on incorporating pairwise constraints into a spectral clustering algorithm. A new constrained spectral clustering method is proposed, as well as an active constraint acquisition technique and a heuristic for parameter selection. We demonstrate that our constrained spectral clustering method, CSC, works well when the data exhibits what we term local proximity structure.

Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Adams, John B.; Smith, Milton O.

1992-01-01

The conditions that affect the spectral detection of target materials at the subpixel scale are examined. Two levels of spectral mixture analysis for determining threshold detection limits of target materials in a spectral mixture are presented, the cases where the target is detected as: (1) a component of a spectral mixture (continuum threshold analysis) and (2) residuals (residual threshold analysis). The results of these two analyses are compared under various measurement conditions. The examples illustrate the general approach that can be used for evaluating the spectral detectability of terrestrial and planetary targets at the subpixel scale.

Microburger Biochemistry: Extraction and Spectral Characterization of Myoglyobin from Hamburger

NASA Astrophysics Data System (ADS)

Bylkas, Sheri A.; Andersson, Laura A.

1997-04-01

This experiment provides a demonstration of useful biochemical methods at a Basic or Advanced Level, depending upon the available spectrophotometric equipment. The protocol combines protein extraction, ox-i-dation and reduction, and simple spectroscopic analysis, as well as gel filtration chromatography and generation/analysis of spectral scans. Mammalian myoglobin (Mb) is a monomeric O2-binding protein that functions in muscle to store oxygen. The single iron protoporphyrin IX (heme) group is bound to protein by the amino acid Histidine93. The common, stable forms, Met-Mb and Oxy-Mb are studied because in a non-living system, red Oxy-Mb is converted to brown Met-Mb as bound O2 molecule is released. Mb is easily extracted from steak, to illustrate and address why fresh meat is red and aged meat is brown; the protein has unique spectral properties that are diagnostic for characterization of sample identity. After application of heme redox chemical methods, the MetMb or OxyMb samples can be studied spectroscopically. The color change between Oxy-Mb and Met-Mb is dramatic (illustrating bright red fresh meat vs. brown older meat), and method(s) used in this laboratory are simple, inexpensive, and non-harmful to the student.

Spectral decomposition of nonlinear systems with memory

NASA Astrophysics Data System (ADS)

Svenkeson, Adam; Glaz, Bryan; Stanton, Samuel; West, Bruce J.

2016-02-01

We present an alternative approach to the analysis of nonlinear systems with long-term memory that is based on the Koopman operator and a Lévy transformation in time. Memory effects are considered to be the result of interactions between a system and its surrounding environment. The analysis leads to the decomposition of a nonlinear system with memory into modes whose temporal behavior is anomalous and lacks a characteristic scale. On average, the time evolution of a mode follows a Mittag-Leffler function, and the system can be described using the fractional calculus. The general theory is demonstrated on the fractional linear harmonic oscillator and the fractional nonlinear logistic equation. When analyzing data from an ill-defined (black-box) system, the spectral decomposition in terms of Mittag-Leffler functions that we propose may uncover inherent memory effects through identification of a small set of dynamically relevant structures that would otherwise be obscured by conventional spectral methods. Consequently, the theoretical concepts we present may be useful for developing more general methods for numerical modeling that are able to determine whether observables of a dynamical system are better represented by memoryless operators, or operators with long-term memory in time, when model details are unknown.

Wide spectral-range imaging spectroscopy of photonic crystal microbeads for multiplex biomolecular assay applications

NASA Astrophysics Data System (ADS)

Li, Jianping

2014-05-01

Suspension assay using optically color-encoded microbeads is a novel way to increase the reaction speed and multiplex of biomolecular detection and analysis. To boost the detection speed, a hyperspectral imaging (HSI) system is of great interest for quickly decoding the color codes of the microcarriers. Imaging Fourier transform spectrometer (IFTS) is a potential candidate for this task due to its advantages in HSI measurement. However, conventional IFTS is only popular in IR spectral bands because it is easier to track its scanning mirror position in longer wavelengths so that the fundamental Nyquist criterion can be satisfied when sampling the interferograms; the sampling mechanism for shorter wavelengths IFTS used to be very sophisticated, high-cost and bulky. In order to overcome this handicap and take better usage of its advantages for HSI applications, a new wide spectral range IFTS platform is proposed based on an optical beam-folding position-tracking technique. This simple technique has successfully extended the spectral range of an IFTS to cover 350-1000nm. Test results prove that the system has achieved good spectral and spatial resolving performances with instrumentation flexibilities. Accurate and fast measurement results on novel colloidal photonic crystal microbeads also demonstrate its practical potential for high-throughput and multiplex suspension molecular assays.

Film thickness measurement based on nonlinear phase analysis using a Linnik microscopic white-light spectral interferometer.

PubMed

Guo, Tong; Chen, Zhuo; Li, Minghui; Wu, Juhong; Fu, Xing; Hu, Xiaotang

2018-04-20

Based on white-light spectral interferometry and the Linnik microscopic interference configuration, the nonlinear phase components of the spectral interferometric signal were analyzed for film thickness measurement. The spectral interferometric signal was obtained using a Linnik microscopic white-light spectral interferometer, which includes the nonlinear phase components associated with the effective thickness, the nonlinear phase error caused by the double-objective lens, and the nonlinear phase of the thin film itself. To determine the influence of the effective thickness, a wavelength-correction method was proposed that converts the effective thickness into a constant value; the nonlinear phase caused by the effective thickness can then be determined and subtracted from the total nonlinear phase. A method for the extraction of the nonlinear phase error caused by the double-objective lens was also proposed. Accurate thickness measurement of a thin film can be achieved by fitting the nonlinear phase of the thin film after removal of the nonlinear phase caused by the effective thickness and by the nonlinear phase error caused by the double-objective lens. The experimental results demonstrated that both the wavelength-correction method and the extraction method for the nonlinear phase error caused by the double-objective lens improve the accuracy of film thickness measurements.

Discrimination of periodontal diseases using diffuse reflectance spectral intensity ratios

NASA Astrophysics Data System (ADS)

Chandra Sekhar, Prasanth; Betsy, Joseph; Presanthila, Janam; Subhash, Narayanan

2012-02-01

This clinical study was to demonstrate the applicability of diffuse reflectance (DR) intensity ratio R620/R575 in the quantification and discrimination of periodontitis and gingivitis from healthy gingiva. DR spectral measurements were carried out with white-light illumination from 70 healthy sites in 30 healthy volunteers, and 63 gingivitis- and 58 periodontitis-infected sites in 60 patients. Clinical parameters such as probing pocket depth, clinical attachment level, and gingival index were recorded in patient population. Diagnostic accuracies for discrimination of gingivitis and periodontitis from healthy gingiva were determined by comparison of spectral signatures with clinical parameters. Divergence of average DR spectral intensity ratio between control and test groups was studied using analysis of variance. The mean DR spectrum on normalization at 620 nm showed marked differences between healthy tissue, gingivitis, and periodontitis. Hemoglobin concentration and apparent SO2 (oxygen saturation) were also calculated for healthy, gingivitis, and periodontitis sites. DR spectral intensities at 545 and 575 nm showed a decreasing trend with progression of disease. Among the various DR intensity ratios studied, the R620/R575 ratio provided a sensitivity of 90% and specificity of 94% for discrimination of healthy tissues from gingivitis and a sensitivity of 91% and specificity of 100% for discrimination of gingivitis from periodontitis.

Nonphotosynthetic Pigments as Potential Biosignatures

PubMed Central

Cockell, Charles S.; Meadows, Victoria S.

2015-01-01

Abstract Previous work on possible surface reflectance biosignatures for Earth-like planets has typically focused on analogues to spectral features produced by photosynthetic organisms on Earth, such as the vegetation red edge. Although oxygenic photosynthesis, facilitated by pigments evolved to capture photons, is the dominant metabolism on our planet, pigmentation has evolved for multiple purposes to adapt organisms to their environment. We present an interdisciplinary study of the diversity and detectability of nonphotosynthetic pigments as biosignatures, which includes a description of environments that host nonphotosynthetic biologically pigmented surfaces, and a lab-based experimental analysis of the spectral and broadband color diversity of pigmented organisms on Earth. We test the utility of broadband color to distinguish between Earth-like planets with significant coverage of nonphotosynthetic pigments and those with photosynthetic or nonbiological surfaces, using both 1-D and 3-D spectral models. We demonstrate that, given sufficient surface coverage, nonphotosynthetic pigments could significantly impact the disk-averaged spectrum of a planet. However, we find that due to the possible diversity of organisms and environments, and the confounding effects of the atmosphere and clouds, determination of substantial coverage by biologically produced pigments would be difficult with broadband colors alone and would likely require spectrally resolved data. Key Words: Biosignatures—Exoplanets—Halophiles—Pigmentation—Reflectance spectroscopy—Spectral models. Astrobiology 15, 341–361. PMID:25941875

Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

NASA Astrophysics Data System (ADS)

Zhong, Ming

In this dissertation, we focus on extending classical spectral shape analysis by incorporating spectral graph wavelets and sparsity-seeking algorithms. Defined with the graph Laplacian eigenbasis, the spectral graph wavelets are localized both in the vertex domain and graph spectral domain, and thus are very effective in describing local geometry. With a rich dictionary of elementary vectors and forcing certain sparsity constraints, a real life signal can often be well approximated by a very sparse coefficient representation. The many successful applications of sparse signal representation in computer vision and image processing inspire us to explore the idea of employing sparse modeling techniques with dictionary of spectral basis to solve various shape modeling problems. Conventional spectral mesh compression uses the eigenfunctions of mesh Laplacian as shape bases, which are highly inefficient in representing local geometry. To ameliorate, we advocate an innovative approach to 3D mesh compression using spectral graph wavelets as dictionary to encode mesh geometry. The spectral graph wavelets are locally defined at individual vertices and can better capture local shape information than Laplacian eigenbasis. The multi-scale SGWs form a redundant dictionary as shape basis, so we formulate the compression of 3D shape as a sparse approximation problem that can be readily handled by greedy pursuit algorithms. Surface inpainting refers to the completion or recovery of missing shape geometry based on the shape information that is currently available. We devise a new surface inpainting algorithm founded upon the theory and techniques of sparse signal recovery. Instead of estimating the missing geometry directly, our novel method is to find this low-dimensional representation which describes the entire original shape. More specifically, we find that, for many shapes, the vertex coordinate function can be well approximated by a very sparse coefficient representation with respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

Molecular differentiation of five Cinnamomum camphora chemotypes using desorption atmospheric pressure chemical ionization mass spectrometry of raw leaves

PubMed Central

Guo, Xiali; Cui, Meng; Deng, Min; Liu, Xingxing; Huang, Xueyong; Zhang, Xinglei; Luo, Liping

2017-01-01

Five chemotypes, the isoborneol-type, camphora-type, cineole-type, linalool-type and borneol-type of Cinnamomum camphora (L.) Presl have been identified at the molecular level based on the multivariate analysis of mass spectral fingerprints recorded from a total of 750 raw leaf samples (i.e., 150 leaves equally collected for each chemotype) using desorption atmospheric pressure chemical ionization mass spectrometry (DAPCI-MS). Both volatile and semi-volatile metabolites of the fresh leaves of C. camphora were simultaneously detected by DAPCI-MS without any sample pretreatment, reducing the analysis time from half a day using conventional methods (e.g., GC-MS) down to 30 s. The pattern recognition results obtained using principal component analysis (PCA) was cross-checked by cluster analysis (CA), showing that the difference visualized by the DAPCI-MS spectral fingerprints was validated with 100% accuracy. The study demonstrates that DAPCI-MS meets the challenging requirements for accurate differentiation of all the five chemotypes of C. camphora leaves, motivating more advanced application of DAPCI-MS in plant science and forestry studies. PMID:28425482

Analysis of wave motion in one-dimensional structures through fast-Fourier-transform-based wavelet finite element method

NASA Astrophysics Data System (ADS)

Shen, Wei; Li, Dongsheng; Zhang, Shuaifang; Ou, Jinping

2017-07-01

This paper presents a hybrid method that combines the B-spline wavelet on the interval (BSWI) finite element method and spectral analysis based on fast Fourier transform (FFT) to study wave propagation in One-Dimensional (1D) structures. BSWI scaling functions are utilized to approximate the theoretical wave solution in the spatial domain and construct a high-accuracy dynamic stiffness matrix. Dynamic reduction on element level is applied to eliminate the interior degrees of freedom of BSWI elements and substantially reduce the size of the system matrix. The dynamic equations of the system are then transformed and solved in the frequency domain through FFT-based spectral analysis which is especially suitable for parallel computation. A comparative analysis of four different finite element methods is conducted to demonstrate the validity and efficiency of the proposed method when utilized in high-frequency wave problems. Other numerical examples are utilized to simulate the influence of crack and delamination on wave propagation in 1D rods and beams. Finally, the errors caused by FFT and their corresponding solutions are presented.

Imaging acoustic vibrations in an ear model using spectrally encoded interferometry

NASA Astrophysics Data System (ADS)

Grechin, Sveta; Yelin, Dvir

2018-01-01

Imaging vibrational patterns of the tympanic membrane would allow an accurate measurement of its mechanical properties and provide early diagnosis of various hearing disorders. Various optical technologies have been suggested to address this challenge and demonstrated in vitro using point scanning and full-field interferometry. Spectrally encoded imaging has been previously demonstrated capable of imaging tissue acoustic vibrations with high spatial resolution, including two-dimensional phase and amplitude mapping. In this work, we demonstrate a compact optical apparatus for imaging acoustic vibrations that could be incorporated into a commercially available digital otoscope. By transmitting harmonic sound waves through the otoscope insufflation port and analyzing the spectral interferograms using custom-built software, we demonstrate high-resolution vibration imaging of a circular rubber membrane within an ear model.

Practical considerations in experimental computational sensing

NASA Astrophysics Data System (ADS)

Poon, Phillip K.

Computational sensing has demonstrated the ability to ameliorate or eliminate many trade-offs in traditional sensors. Rather than attempting to form a perfect image, then sampling at the Nyquist rate, and reconstructing the signal of interest prior to post-processing, the computational sensor attempts to utilize a priori knowledge, active or passive coding of the signal-of-interest combined with a variety of algorithms to overcome the trade-offs or to improve various task-specific metrics. While it is a powerful approach to radically new sensor architectures, published research tends to focus on architecture concepts and positive results. Little attention is given towards the practical issues when faced with implementing computational sensing prototypes. I will discuss the various practical challenges that I encountered while developing three separate applications of computational sensors. The first is a compressive sensing based object tracking camera, the SCOUT, which exploits the sparsity of motion between consecutive frames while using no moving parts to create a psuedo-random shift variant point-spread function. The second is a spectral imaging camera, the AFSSI-C, which uses a modified version of Principal Component Analysis with a Bayesian strategy to adaptively design spectral filters for direct spectral classification using a digital micro-mirror device (DMD) based architecture. The third demonstrates two separate architectures to perform spectral unmixing by using an adaptive algorithm or a hybrid techniques of using Maximum Noise Fraction and random filter selection from a liquid crystal on silicon based computational spectral imager, the LCSI. All of these applications demonstrate a variety of challenges that have been addressed or continue to challenge the computational sensing community. One issue is calibration, since many computational sensors require an inversion step and in the case of compressive sensing, lack of redundancy in the measurement data. Another issue is over multiplexing, as more light is collected per sample, the finite amount of dynamic range and quantization resolution can begin to degrade the recovery of the relevant information. A priori knowledge of the sparsity and or other statistics of the signal or noise is often used by computational sensors to outperform their isomorphic counterparts. This is demonstrated in all three of the sensors I have developed. These challenges and others will be discussed using a case-study approach through these three applications.

Generalization of the Lyot filter and its application to snapshot spectral imaging.

PubMed

Gorman, Alistair; Fletcher-Holmes, David William; Harvey, Andrew Robert

2010-03-15

A snapshot multi-spectral imaging technique is described which employs multiple cascaded birefringent interferometers to simultaneously spectrally filter and demultiplex multiple spectral images onto a single detector array. Spectral images are recorded directly without the need for inversion and without rejection of light and so the technique offers the potential for high signal-to-noise ratio. An example of an eight-band multi-spectral movie sequence is presented; we believe this is the first such demonstration of a technique able to record multi-spectral movie sequences without the need for computer reconstruction.

Radiometric calibration of optical microscopy and microspectroscopy apparata over a broad spectral range using a special thin-film luminescence standard

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valenta, J., E-mail: jan.valenta@mff.cuni.cz; Greben, M.

2015-04-15

Application capabilities of optical microscopes and microspectroscopes can be considerably enhanced by a proper calibration of their spectral sensitivity. We propose and demonstrate a method of relative and absolute calibration of a microspectroscope over an extraordinary broad spectral range covered by two (parallel) detection branches in visible and near-infrared spectral regions. The key point of the absolute calibration of a relative spectral sensitivity is application of the standard sample formed by a thin layer of Si nanocrystals with stable and efficient photoluminescence. The spectral PL quantum yield and the PL spatial distribution of the standard sample must be characterized bymore » separate experiments. The absolutely calibrated microspectroscope enables to characterize spectral photon emittance of a studied object or even its luminescence quantum yield (QY) if additional knowledge about spatial distribution of emission and about excitance is available. Capabilities of the calibrated microspectroscope are demonstrated by measuring external QY of electroluminescence from a standard poly-Si solar-cell and of photoluminescence of Er-doped Si nanocrystals.« less

Spectral Learning for Supervised Topic Models.

PubMed

Ren, Yong; Wang, Yining; Zhu, Jun

2018-03-01

Supervised topic models simultaneously model the latent topic structure of large collections of documents and a response variable associated with each document. Existing inference methods are based on variational approximation or Monte Carlo sampling, which often suffers from the local minimum defect. Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees. This paper investigates the possibility of applying spectral methods to recover the parameters of supervised LDA (sLDA). We first present a two-stage spectral method, which recovers the parameters of LDA followed by a power update method to recover the regression model parameters. Then, we further present a single-phase spectral algorithm to jointly recover the topic distribution matrix as well as the regression weights. Our spectral algorithms are provably correct and computationally efficient. We prove a sample complexity bound for each algorithm and subsequently derive a sufficient condition for the identifiability of sLDA. Thorough experiments on synthetic and real-world datasets verify the theory and demonstrate the practical effectiveness of the spectral algorithms. In fact, our results on a large-scale review rating dataset demonstrate that our single-phase spectral algorithm alone gets comparable or even better performance than state-of-the-art methods, while previous work on spectral methods has rarely reported such promising performance.

Using RIXS to uncover elementary charge and spin excitations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jia, Chunjing; Wohlfeld, Krzysztof; Wang, Yao

2016-05-13

Despite significant progress in resonant inelastic x-ray scattering (RIXS) experiments on cuprates at the Cu L-edge, a theoretical understanding of the cross section remains incomplete in terms of elementary excitations and the connection to both charge and spin structure factors. Here, we use state-of-the-art, unbiased numerical calculations to study the low-energy excitations probed by RIXS in the Hubbard model, relevant to the cuprates. The results highlight the importance of scattering geometry, in particular, both the incident and scattered x-ray photon polarization, and they demonstrate that on a qualitative level the RIXS spectral shape in the cross-polarized channel approximates that ofmore » the spin dynamical structure factor. Furthermore, in the parallel-polarized channel, the complexity of the RIXS process beyond a simple two-particle response complicates the analysis and demonstrates that approximations and expansions that attempt to relate RIXS to less complex correlation functions cannot reproduce the full diversity of RIXS spectral features.« less

High-Frequency Electron Paramagnetic Resonance Spectroscopy of Nitroxide-Functionalized Nanodiamonds in Aqueous Solution.

PubMed

Akiel, R D; Stepanov, V; Takahashi, S

2017-06-01

Nanodiamond (ND) is an attractive class of nanomaterial for fluorescent labeling, magnetic sensing of biological molecules, and targeted drug delivery. Many of those applications require tethering of target biological molecules on the ND surface. Even though many approaches have been developed to attach macromolecules to the ND surface, it remains challenging to characterize dynamics of tethered molecule. Here, we show high-frequency electron paramagnetic resonance (HF EPR) spectroscopy of nitroxide-functionalized NDs. Nitroxide radical is a commonly used spin label to investigate dynamics of biological molecules. In the investigation, we developed a sample holder to overcome water absorption of HF microwave. Then, we demonstrated HF EPR spectroscopy of nitroxide-functionalized NDs in aqueous solution and showed clear spectral distinction of ND and nitroxide EPR signals. Moreover, through EPR spectral analysis, we investigate dynamics of nitroxide radicals on the ND surface. The demonstration sheds light on the use of HF EPR spectroscopy to investigate biological molecule-functionalized nanoparticles.

ASPECT spectral imaging satellite proposal to AIDA/AIM CubeSat payload

NASA Astrophysics Data System (ADS)

Kohout, Tomas; Näsilä, Antti; Tikka, Tuomas; Penttilä, Antti; Muinonen, Karri; Kestilä, Antti; Granvik, Mikael; Kallio, Esa

2016-04-01

ASPECT (Asteroid Spectral Imaging Mission) is a part of AIDA/AIM project and aims to study the composition of the Didymos binary asteroid and the effects of space weathering and shock metamorphism in order to gain understanding of the formation and evolution of the Solar System. The joint ESA/NASA AIDA (Asteroid Impact & Deflection Assessment) mission to binary asteroid Didymos consists of AIM (Asteroid Impact Mission, ESA) and DART (Double Asteroid Redirection Test, NASA). DART is targeted to impact Didymos secondary component (Didymoon) and serve as a kinetic impactor to demonstrate deflection of potentially hazardous asteroids. AIM will serve as an observational spacecraft to evaluate the effects of the impact and resulting changes in the Didymos dynamic parameters. The AIM mission will also carry two CubeSat miniaturized satellites, released in Didymoon proximity. This arrangement opens up a possibility for secondary scientific experiments. ASPECT is one of the proposed CubeSat payloads. Whereas Didymos is a space-weathered binary asteroid, the DART impactor is expected to produce a crater and excavate fresh material from the secondary component (Didymoon). Spectral comparison of the mature surface to the freshly exposed material will allow to directly deter-mine space weathering effects. It will be also possible to study spectral shock effects within the impact crater. ASPECT will also demonstrate for the first time the joint spacecraft - CubeSat operations in asteroid proximity and miniature spectral imager operation in deep-space environment. Science objectives: 1. Study of the surface composition of the Didymos system. 2. Photometric observations (and modeling) under varying phase angle and distance. 3. Study of space weathering effects on asteroids (comparison of mature / freshly exposed material). 4. Study of shock effects (spectral properties of crater interior). 5. Observations during the DART impact. Engineering objectives: 1. Demonstration of CubeSat semi-autonomous operations in deep space environment. 2. Navigation in the vicinity of a binary asteroid. 3. Demonstration of a satellite survival during impact. 4. Demonstration of joint spacecraft - CubeSat operations. ASPECT is a 3U CubeSat (size of 3 units, Fig. 1) equipped with a spectral imager from 500 nm to 1600 nm (spatial resolution < 2 m, spectral resolution 10 - 30 nm; VIS channel 512 x 512 pixels, NIR channel 256 x 256 pixels), and a non-imaging spectrometer from 1600 - 2500 nm. The design is based on the Aalto-1 CubeSat Spectral Imager heritage. ASPECT will also demonstrate the capabilities of a CubeSat and a miniature spectral imager for the first time in deep-space environment. Acknowledgements: This work is done under Sys-Nova: R&D Studies Competition for Innovation contract with ESA.

High speed parallel spectral-domain OCT using spectrally encoded line-field illumination

NASA Astrophysics Data System (ADS)

Lee, Kye-Sung; Hur, Hwan; Bae, Ji Yong; Kim, I. Jong; Kim, Dong Uk; Nam, Ki-Hwan; Kim, Geon-Hee; Chang, Ki Soo

2018-01-01

We report parallel spectral-domain optical coherence tomography (OCT) at 500 000 A-scan/s. This is the highest-speed spectral-domain (SD) OCT system using a single line camera. Spectrally encoded line-field scanning is proposed to increase the imaging speed in SD-OCT effectively, and the tradeoff between speed, depth range, and sensitivity is demonstrated. We show that three imaging modes of 125k, 250k, and 500k A-scan/s can be simply switched according to the sample to be imaged considering the depth range and sensitivity. To demonstrate the biological imaging performance of the high-speed imaging modes of the spectrally encoded line-field OCT system, human skin and a whole leaf were imaged at the speed of 250k and 500k A-scan/s, respectively. In addition, there is no sensitivity dependence in the B-scan direction, which is implicit in line-field parallel OCT using line focusing of a Gaussian beam with a cylindrical lens.

Possibility of successive SRXFA use along with chemical-spectral methods for palladium analysis in geological samples

NASA Astrophysics Data System (ADS)

Kislov, E. V.; Kulikov, A. A.; Kulikova, A. B.

1989-10-01

Samples of basit-ultrabasit rocks and NiCu ores of the Ioko-Dovyren and Chaya massifs were analysed by SRXFA and a chemical-spectral method. SRXFA perfectly satisfies the quantitative noble-metals analysis of ore-free rocks. Combination of SRXFA and chemical-spectral analysis has good prospects. After analysis of a great number of samples by SRXFA it is necessary to select samples which would show minimal and maximal results for the chemical-spectral method.

Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2015-03-01

Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge.

Integration, Testing, and Analysis of Multispectral Imager on Small Unmanned Aerial System for Skin Detection

DTIC Science & Technology

2014-03-01

U.S. Air Force, and others have demonstrated the utility of SUAS in natural disasters such as the Fukushima Daiichi meltdown to take photographs at...factor. Multispectral Imagery (MSI) has proven capable of dismount detection with several distinct wavelengths. This research proposes a spectral...Epipolar lines depicted in blue, show the geometric relationship between the two cameras after stereo rectification

2.3 µm laser potential of TeO2 based glasses

NASA Astrophysics Data System (ADS)

Denker, B. I.; Dorofeev, V. V.; Galagan, B. I.; Motorin, S. E.; Sverchkov, S. E.

2017-09-01

Tm3+ doped TeO2-based well-dehydrated glasses were synthesized and investigated. The analysis of their spectral and relaxation properties have showed that these glasses can be a suitable host for bulk and fiber lasers emitting at ~2.3 µm wavelength (3H4-3H5 Tm3+ transition). Laser action in the bulk glass sample was demonstrated.

Hyper-spectral imaging: A promising tool for quantitative pigment analysis of varved lake sediments

NASA Astrophysics Data System (ADS)

Butz, Christoph; Grosjean, Martin; Tylmann, Wojciech

2015-04-01

Varved lake sediments are good archives for past environmental and climate conditions from annual to multi-millennial scales. Among other proxies, concentrations of sedimentary photopigments have been used for temperature reconstructions. However, obtaining well calibrated annually resolved records from sediments still remains challenging. Most laboratory methods used to analyse lake sediments require physical subsampling and are destructive in the process. Hence, temporal resolution and number of data are limited by the amount of material available in the core. Furthermore, for very low sediment accumulation rates annual subsampling is often very difficult or even impossible. To address these problems we explore hyper-spectral imaging as a non-destructive method to analyse lake sediments based on their reflectance spectra in the visible and near infrared spectrum. In contrast to other scanning methods like X-ray fluorescence, VIS/NIR reflectance spectrometry distinguishes between biogeochemical substances rather than single elements. Among others Rein (2003) has shown that VIS-RS can be used to detect relative concentrations of sedimentary photopigments (e.g. chlorins, carotenoids) and clay minerals. In this study hyper-spectral imaging is used to infer ecological proxy data from reflectance spectra of varved lake sediments. Hyper-spectral imaging permits the measurement of an entire sediment core in a single run at high spatial (30x30µm/pixel) and spectral resolutions (~2.8nm) within the visual to near infrared spectrum (400-1000nm). This allows the analysis of data time series and spatial mapping of sedimentary substances (e.g. chlorophylls/bacterio-chlorophylls and diagenetic products) at sub-varve scales. The method is demonstrated on two varved lake sediments from northern Poland showing the distributions of relative concentrations of two types of sedimentary pigments (Chlorophyll-a + derivatives and Bacterio-pheophytin-a) within individual varve years. The relative concentrations from the spectral data set have then been calibrated with absolute concentrations derived by High-Performance-Liquid-Chromatography (HPLC). This results in very high-resolution data sets of absolute sedimentary pigment concentrations suitable for the analysis of seasonal pigment variations.

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Broadband Spectral Investigations of SGR J1550-5418 Bursts

NASA Technical Reports Server (NTRS)

Lin, Lin; Goegues, Ersin; Baring, Matthew G.; Granot, Jonathan; Kouveliotou, Chryssa; Kaneko, Yuki; van der Horst, Alexander; Gruber, David; von Kienlin, Andreas; Younes, George;

Resolution of coi-dominant phytoplankton species in a eutrophiclake using synchrotron-based Fourier transform infraredspectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dean, A.P.; Martin, Michael C.; Sigee, D.C.

2006-10-09

Synchrotron-based Fourier-transform infrared (FTIR)microspectroscopy was used to distinguish micropopulations of thecodominant algae Microcystis aeruginosa (Cyanophyceae) and Ceratiumhirundinella (Dinophyceae) in mixed phytoplankton samples taken from thewater column of a stratified eutrophic lake (Rostherne Mere, UK). FTIRspectra of the two algae showed a closely similar sequence of 10 bandsover the wave-number range 4000-900 cm-1. These were assigned to a rangeof vibrationally active chemical groups using published band assignmentsand on the basis of correlation and factor analysis. In both algae,intracellular concentrations of macromolecular components (determined asband intensity) varied considerably within the same population,indicating substantial intraspecific heterogeneity. Interspecificdifferences were separately analysed in relation tomore » discrete bands and bymultivariate analysis of the entire spectral region 1750-900 cm-1. Interms of discrete bands, comparison of individual intensities (normalisedto amide 1) demonstrated significant (99 percent probability level)differences in relation to six bands between the two algal species. Keyinterspecific differences were also noted in relation to the positions ofbands 2, 10 (carbohydrate) and 7 (protein) and in the 3-D plots derivedby principal component analysis (PCA) of the sequence of bandintensities. PCA of entire spectral regions showed clear resolutionofspecies in the PCA plot, with indication of separation on the basis ofprotein (region 1700-1500 cm1) and carbohydrate (region 1150-900 cm1)composition in the loading plot. Hierarchical cluster analysis (Wardalgorithm) of entire spectral regions also showed clear discrimination ofthe two species within the resulting dendrogram.« less

Multicolour LEDs in educational demonstrations of physics and optometry

NASA Astrophysics Data System (ADS)

Paulins, Paulis; Ozolinsh, Maris

2014-07-01

LED light sources are used to design experimental setup for university courses teaching human color vision. The setup allows to demonstrate various vision characteristics and to apply for student practical exercises to study eye spectral sensitivity in different spectral range using heterochromatic flicker photometry. Technique can be used in laboratory works for students to acquire knowledge in visual perception, basics of electronics and measuring, or it can be applied as fully computer control experiment. Besides studies of the eye spectral sensitivity students can practice in trichromatic color matching and other visual perception tasks

A framework for evaluating mixture analysis algorithms

NASA Astrophysics Data System (ADS)

Dasaratha, Sridhar; Vignesh, T. S.; Shanmukh, Sarat; Yarra, Malathi; Botonjic-Sehic, Edita; Grassi, James; Boudries, Hacene; Freeman, Ivan; Lee, Young K.; Sutherland, Scott

2010-04-01

In recent years, several sensing devices capable of identifying unknown chemical and biological substances have been commercialized. The success of these devices in analyzing real world samples is dependent on the ability of the on-board identification algorithm to de-convolve spectra of substances that are mixtures. To develop effective de-convolution algorithms, it is critical to characterize the relationship between the spectral features of a substance and its probability of detection within a mixture, as these features may be similar to or overlap with other substances in the mixture and in the library. While it has been recognized that these aspects pose challenges to mixture analysis, a systematic effort to quantify spectral characteristics and their impact, is generally lacking. In this paper, we propose metrics that can be used to quantify these spectral features. Some of these metrics, such as a modification of variance inflation factor, are derived from classical statistical measures used in regression diagnostics. We demonstrate that these metrics can be correlated to the accuracy of the substance's identification in a mixture. We also develop a framework for characterizing mixture analysis algorithms, using these metrics. Experimental results are then provided to show the application of this framework to the evaluation of various algorithms, including one that has been developed for a commercial device. The illustration is based on synthetic mixtures that are created from pure component Raman spectra measured on a portable device.

Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data

NASA Astrophysics Data System (ADS)

Ghrefat, Habes A.; Goodell, Philip C.

2011-08-01

The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen analysis between the various datasets helped to uncover the most optimum spatial-spectral-temporal and radiometric-resolution sensor characteristics for remote sensing based on monitoring of seasonal land cover, surface water, groundwater, and alluvial sediment input changes within the basin. The results demonstrated good agreement between ground truth data and XRD analysis of samples, and the results of Matched Filtering (MF) mapping method.

Conceptual DFT analysis of the fragility spectra of atoms along the minimum energy reaction coordinate.

PubMed

Ordon, Piotr; Komorowski, Ludwik; Jedrzejewski, Mateusz

2017-10-07

Theoretical justification has been provided to the method for monitoring the sequence of chemical bonds' rearrangement along a reaction path, by tracing the evolution of the diagonal elements of the Hessian matrix. Relations between the divergences of Hellman-Feynman forces and the energy and electron density derivatives have been demonstrated. By the proof presented on the grounds of the conceptual density functional theory formalism, the spectral amplitude observed on the atomic fragility spectra [L. Komorowski et al., Phys. Chem. Chem. Phys. 18, 32658 (2016)] reflects selectively the electron density modifications in bonds of an atom. In fact the spectral peaks for an atom reveal changes of the electron density occurring with bonds creation, breaking, or varying with the reaction progress.

Conceptual DFT analysis of the fragility spectra of atoms along the minimum energy reaction coordinate

NASA Astrophysics Data System (ADS)

Ordon, Piotr; Komorowski, Ludwik; Jedrzejewski, Mateusz

2017-10-01

Theoretical justification has been provided to the method for monitoring the sequence of chemical bonds' rearrangement along a reaction path, by tracing the evolution of the diagonal elements of the Hessian matrix. Relations between the divergences of Hellman-Feynman forces and the energy and electron density derivatives have been demonstrated. By the proof presented on the grounds of the conceptual density functional theory formalism, the spectral amplitude observed on the atomic fragility spectra [L. Komorowski et al., Phys. Chem. Chem. Phys. 18, 32658 (2016)] reflects selectively the electron density modifications in bonds of an atom. In fact the spectral peaks for an atom reveal changes of the electron density occurring with bonds creation, breaking, or varying with the reaction progress.

Fluctuation Diagnostics of the Electron Self-Energy: Origin of the Pseudogap Physics.

PubMed

Gunnarsson, O; Schäfer, T; LeBlanc, J P F; Gull, E; Merino, J; Sangiovanni, G; Rohringer, G; Toschi, A

2015-06-12

We demonstrate how to identify which physical processes dominate the low-energy spectral functions of correlated electron systems. We obtain an unambiguous classification through an analysis of the equation of motion for the electron self-energy in its charge, spin, and particle-particle representations. Our procedure is then employed to clarify the controversial physics responsible for the appearance of the pseudogap in correlated systems. We illustrate our method by examining the attractive and repulsive Hubbard model in two dimensions. In the latter, spin fluctuations are identified as the origin of the pseudogap, and we also explain why d-wave pairing fluctuations play a marginal role in suppressing the low-energy spectral weight, independent of their actual strength.

Spectral composition of inhomogeneities of intensity of laser beam translucent the supersonic jet near the nozzle

NASA Astrophysics Data System (ADS)

Marakasov, Dmitri A.; Melnikov, Nikolai G.; Sazanovich, Valentina M.; Tsvyk, Ruvim Sh.; Shesternin, Andrei N.

2014-11-01

The analysis of results of experiments on laser transillumination of the flooded supersonic jet on the wind tunnel of Institute of theoretical and applied mechanics SB RAS is fulfilled. The time spectra of fluctuations of the received power at different values of pressure in the chamber as well as the transformation of the spectra for the initial part of the jet with increasing distance from the nozzle are discussed. The change in the slope of the high-frequency part of the spectrum when lifting beam above the nozzle is demonstrated. Local maxima of the spectral density at frequencies corresponding to the discrete frequencies of acoustic tones generated by the stream are found.

Design concepts of monolithic metamorphic vertical-cavity surface-emitting lasers for the 1300–1550 nm spectral range

DOE Office of Scientific and Technical Information (OSTI.GOV)

Egorov, A. Yu., E-mail: anton@beam.ioffe.ru; Karachinsky, L. Ya.; Novikov, I. I.

Possible design concepts for long-wavelength vertical-cavity surface-emitting lasers for the 1300–1550 nm spectral range on GaAs substrates are suggested. It is shown that a metamorphic GaAs–InGaAs heterostructure with a thin buffer layer providing rapid transition from the lattice constant of GaAs to that of In{sub x}Ga{sub 1–x}As with an indium fraction of x < 0.3 can be formed by molecular-beam epitaxy. Analysis by transmission electron microscopy demonstrated the effective localization of mismatch dislocations in the thin buffer layer and full suppression of their penetration into the overlying InGaAs metamorphic layer.

Spherical Harmonic Analysis of Particle Velocity Distribution Function: Comparison of Moments and Anisotropies using Cluster Data

NASA Technical Reports Server (NTRS)

Gurgiolo, Chris; Vinas, Adolfo F.

2009-01-01

This paper presents a spherical harmonic analysis of the plasma velocity distribution function using high-angular, energy, and time resolution Cluster data obtained from the PEACE spectrometer instrument to demonstrate how this analysis models the particle distribution function and its moments and anisotropies. The results show that spherical harmonic analysis produced a robust physical representation model of the velocity distribution function, resolving the main features of the measured distributions. From the spherical harmonic analysis, a minimum set of nine spectral coefficients was obtained from which the moment (up to the heat flux), anisotropy, and asymmetry calculations of the velocity distribution function were obtained. The spherical harmonic method provides a potentially effective "compression" technique that can be easily carried out onboard a spacecraft to determine the moments and anisotropies of the particle velocity distribution function for any species. These calculations were implemented using three different approaches, namely, the standard traditional integration, the spherical harmonic (SPH) spectral coefficients integration, and the singular value decomposition (SVD) on the spherical harmonic methods. A comparison among the various methods shows that both SPH and SVD approaches provide remarkable agreement with the standard moment integration method.

Potential of far-ultraviolet absorption spectroscopy as a highly sensitive qualitative and quantitative analysis method for polymer films, part I: classification of commercial food wrap films.

PubMed

Sato, Harumi; Higashi, Noboru; Ikehata, Akifumi; Koide, Noriko; Ozaki, Yukihiro

2007-07-01

The aim of the present study is to propose a totally new technique for the utilization of far-ultraviolet (UV) spectroscopy in polymer thin film analysis. Far-UV spectra in the 120-300 nm region have been measured in situ for six kinds of commercial polymer wrap films by use of a novel type of far-UV spectrometer that does not need vacuum evaporation. These films can be straightforwardly classified into three groups, polyethylene (PE) films, polyvinyl chloride (PVC) films, and polyvinylidene chloride (PVDC) films, by using the raw spectra. The differences in the wavelength of the absorption band due to the sigma-sigma* transition of the C-C bond have been used for the classification of the six kinds of films. Using this method, it was easy to distinguish the three kinds of PE films and to separate the two kinds of PVDC films. Compared with other spectroscopic methods, the advantages of this technique include nondestructive analysis, easy spectral measurement, high sensitivity, and simple spectral analysis. The present study has demonstrated that far-UV spectroscopy is a very promising technique for polymer film analysis.

Comparison of multivariate analysis methods for extracting the paraffin component from the paraffin-embedded cancer tissue spectra for Raman imaging

NASA Astrophysics Data System (ADS)

Meksiarun, Phiranuphon; Ishigaki, Mika; Huck-Pezzei, Verena A. C.; Huck, Christian W.; Wongravee, Kanet; Sato, Hidetoshi; Ozaki, Yukihiro

2017-03-01

This study aimed to extract the paraffin component from paraffin-embedded oral cancer tissue spectra using three multivariate analysis (MVA) methods; Independent Component Analysis (ICA), Partial Least Squares (PLS) and Independent Component - Partial Least Square (IC-PLS). The estimated paraffin components were used for removing the contribution of paraffin from the tissue spectra. These three methods were compared in terms of the efficiency of paraffin removal and the ability to retain the tissue information. It was found that ICA, PLS and IC-PLS could remove the paraffin component from the spectra at almost the same level while Principal Component Analysis (PCA) was incapable. In terms of retaining cancer tissue spectral integrity, effects of PLS and IC-PLS on the non-paraffin region were significantly less than that of ICA where cancer tissue spectral areas were deteriorated. The paraffin-removed spectra were used for constructing Raman images of oral cancer tissue and compared with Hematoxylin and Eosin (H&E) stained tissues for verification. This study has demonstrated the capability of Raman spectroscopy together with multivariate analysis methods as a diagnostic tool for the paraffin-embedded tissue section.

High-speed high-sensitivity infrared spectroscopy using mid-infrared swept lasers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Childs, David T. D.; Groom, Kristian M.; Hogg, Richard A.; Revin, Dmitry G.; Cockburn, John W.; Rehman, Ihtesham U.; Matcher, Stephen J.

2016-03-01

Infrared spectroscopy is a highly attractive read-out technology for compositional analysis of biomedical specimens because of its unique combination of high molecular sensitivity without the need for exogenous labels. Traditional techniques such as FTIR and Raman have suffered from comparatively low speed and sensitivity however recent innovations are challenging this situation. Direct mid-IR spectroscopy is being speeded up by innovations such as MEMS-based FTIR instruments with very high mirror speeds and supercontinuum sources producing very high sample irradiation levels. Here we explore another possible method - external cavity quantum cascade lasers (EC-QCL's) with high cavity tuning speeds (mid-IR swept lasers). Swept lasers have been heavily developed in the near-infrared where they are used for non-destructive low-coherence imaging (OCT). We adapt these concepts in two ways. Firstly by combining mid-IR quantum cascade gain chips with external cavity designs adapted from OCT we achieve spectral acquisition rates approaching 1 kHz and demonstrate potential to reach 100 kHz. Secondly we show that mid-IR swept lasers share a fundamental sensitivity advantage with near-IR OCT swept lasers. This makes them potentially able to achieve the same spectral SNR as an FTIR instrument in a time x N shorter (N being the number of spectral points) under otherwise matched conditions. This effect is demonstrated using measurements of a PDMS sample. The combination of potentially very high spectral acquisition rates, fundamental SNR advantage and the use of low-cost detector systems could make mid-IR swept lasers a powerful technology for high-throughput biomedical spectroscopy.

Intraoperative optical biopsy for brain tumors using spectro-lifetime properties of intrinsic fluorophores

NASA Astrophysics Data System (ADS)

Vasefi, Fartash; Kittle, David S.; Nie, Zhaojun; Falcone, Christina; Patil, Chirag G.; Chu, Ray M.; Mamelak, Adam N.; Black, Keith L.; Butte, Pramod V.

2016-04-01

We have developed and tested a system for real-time intra-operative optical identification and classification of brain tissues using time-resolved fluorescence spectroscopy (TRFS). A supervised learning algorithm using linear discriminant analysis (LDA) employing selected intrinsic fluorescence decay temporal points in 6 spectral bands was employed to maximize statistical significance difference between training groups. The linear discriminant analysis on in vivo human tissues obtained by TRFS measurements (N = 35) were validated by histopathologic analysis and neuronavigation correlation to pre-operative MRI images. These results demonstrate that TRFS can differentiate between normal cortex, white matter and glioma.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data

USGS Publications Warehouse

Kokaly, Raymond F.; Despain, Don G.; Clark, Roger N.; Livo, K. Eric

2003-01-01

Knowledge of the distribution of vegetation on the landscape can be used to investigate ecosystem functioning. The sizes and movements of animal populations can be linked to resources provided by different plant species. This paper demonstrates the application of imaging spectroscopy to the study of vegetation in Yellowstone National Park (Yellowstone) using spectral feature analysis of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data, acquired on August 7, 1996, were calibrated to surface reflectance using a radiative transfer model and field reflectance measurements of a ground calibration site. A spectral library of canopy reflectance signatures was created by averaging pixels of the calibrated AVIRIS data over areas of known forest and nonforest vegetation cover types in Yellowstone. Using continuum removal and least squares fitting algorithms in the US Geological Survey's Tetracorder expert system, the distributions of these vegetation types were determined by comparing the absorption features of vegetation in the spectral library with the spectra from the AVIRIS data. The 0.68 μm chlorophyll absorption feature and leaf water absorption features, centered near 0.98 and 1.20 μm, were analyzed. Nonforest cover types of sagebrush, grasslands, willows, sedges, and other wetland vegetation were mapped in the Lamar Valley of Yellowstone. Conifer cover types of lodgepole pine, whitebark pine, Douglas fir, and mixed Engelmann spruce/subalpine fir forests were spectrally discriminated and their distributions mapped in the AVIRIS images. In the Mount Washburn area of Yellowstone, a comparison of the AVIRIS map of forest cover types to a map derived from air photos resulted in an overall agreement of 74.1% (kappa statistic=0.62).

Broadband hyperspectral coherent anti-Stokes Raman scattering microscopy for stain-free histological imaging with principal component analysis

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Guo, Baoshan; Wong, Kenneth K. Y.; Tsia, Kevin K.

2014-02-01

Routine procedures in standard histopathology involve laborious steps of tissue processing and staining for final examination. New techniques which can bypass these procedures and thus minimize the tissue handling error would be of great clinical value. Coherent anti-Stokes Raman scattering (CARS) microscopy is an attractive tool for label-free biochemical-specific characterization of biological specimen. However, a vast majority of prior works on CARS (or stimulated Raman scattering (SRS)) bioimaging restricted analyses on a narrowband or well-distinctive Raman spectral signatures. Although hyperspectral SRS/CARS imaging has recently emerged as a better solution to access wider-band spectral information in the image, studies mostly focused on a limited spectral range, e.g. CH-stretching vibration of lipids, or non-biological samples. Hyperspectral image information in the congested fingerprint spectrum generally remains untapped for biological samples. In this regard, we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with the goal of exploring its utility in stain-free clinical histopathology. Using the supercontinuum Stokes, our system can access the CARS spectral window as wide as >2000cm-1. In order to unravel the congested CARS spectra particularly in the fingerprint region, we first employ a spectral phase-retrieval algorithm based on Kramers-Kronig (KK) transform to minimize the non-resonant background in the CARS spectrum. We then apply principal component analysis (PCA) to identify and map the spatial distribution of different biochemical components in the tissues. We demonstrate chemoselective HM-CARS imaging of a colon tissue section which displays the key cellular structures that correspond well with standard stained-tissue observation.

3D Spatial and Spectral Fusion of Terrestrial Hyperspectral Imagery and Lidar for Hyperspectral Image Shadow Restoration Applied to a Geologic Outcrop

NASA Astrophysics Data System (ADS)

Hartzell, P. J.; Glennie, C. L.; Hauser, D. L.; Okyay, U.; Khan, S.; Finnegan, D. C.

2016-12-01

Recent advances in remote sensing technology have expanded the acquisition and fusion of active lidar and passive hyperspectral imagery (HSI) from an exclusively airborne technique to terrestrial modalities. This enables high resolution 3D spatial and spectral quantification of vertical geologic structures for applications such as virtual 3D rock outcrop models for hydrocarbon reservoir analog analysis and mineral quantification in open pit mining environments. In contrast to airborne observation geometry, the vertical surfaces observed by horizontal-viewing terrestrial HSI sensors are prone to extensive topography-induced solar shadowing, which leads to reduced pixel classification accuracy or outright removal of shadowed pixels from analysis tasks. Using a precisely calibrated and registered offset cylindrical linear array camera model, we demonstrate the use of 3D lidar data for sub-pixel HSI shadow detection and the restoration of the shadowed pixel spectra via empirical methods that utilize illuminated and shadowed pixels of similar material composition. We further introduce a new HSI shadow restoration technique that leverages collocated backscattered lidar intensity, which is resistant to solar conditions, obtained by projecting the 3D lidar points through the HSI camera model into HSI pixel space. Using ratios derived from the overlapping lidar laser and HSI wavelengths, restored shadow pixel spectra are approximated using a simple scale factor. Simulations of multiple lidar wavelengths, i.e., multi-spectral lidar, indicate the potential for robust HSI spectral restoration that is independent of the complexity and costs associated with rigorous radiometric transfer models, which have yet to be developed for horizontal-viewing terrestrial HSI sensors. The spectral restoration performance is quantified through HSI pixel classification consistency between full sun and partial sun exposures of a single geologic outcrop.

Low-Loss Coupling of Quantum Cascade Lasers into Hollow-Core Waveguides with Single-Mode Output in the 3.7-7.6 μm Spectral Range.

PubMed

Patimisco, Pietro; Sampaolo, Angelo; Mihai, Laura; Giglio, Marilena; Kriesel, Jason; Sporea, Dan; Scamarcio, Gaetano; Tittel, Frank K; Spagnolo, Vincenzo

2016-04-13

We demonstrated low-loss and single-mode laser beam delivery through hollow-core waveguides (HCWs) operating in the 3.7-7.6 μm spectral range. The employed HCWs have a circular cross section with a bore diameter of 200 μm and metallic/dielectric internal coatings deposited inside a glass capillary tube. The internal coatings have been produced to enhance the spectral response of the HCWs in the range 3.5-12 µm. We demonstrated Gaussian-like outputs throughout the 4.5-7.6 µm spectral range. A quasi single-mode output beam with only small beam distortions was achieved when the wavelength was reduced to 3.7 μm. With a 15-cm-long HCW and optimized coupling conditions, we measured coupling efficiencies of >88% and transmission losses of <1 dB in the investigated infrared spectral range.

Radiation anomaly detection algorithms for field-acquired gamma energy spectra

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ron; Guss, Paul; Mitchell, Stephen

2015-08-01

The Remote Sensing Laboratory (RSL) is developing a tactical, networked radiation detection system that will be agile, reconfigurable, and capable of rapid threat assessment with high degree of fidelity and certainty. Our design is driven by the needs of users such as law enforcement personnel who must make decisions by evaluating threat signatures in urban settings. The most efficient tool available to identify the nature of the threat object is real-time gamma spectroscopic analysis, as it is fast and has a very low probability of producing false positive alarm conditions. Urban radiological searches are inherently challenged by the rapid and large spatial variation of background gamma radiation, the presence of benign radioactive materials in terms of the normally occurring radioactive materials (NORM), and shielded and/or masked threat sources. Multiple spectral anomaly detection algorithms have been developed by national laboratories and commercial vendors. For example, the Gamma Detector Response and Analysis Software (GADRAS) a one-dimensional deterministic radiation transport software capable of calculating gamma ray spectra using physics-based detector response functions was developed at Sandia National Laboratories. The nuisance-rejection spectral comparison ratio anomaly detection algorithm (or NSCRAD), developed at Pacific Northwest National Laboratory, uses spectral comparison ratios to detect deviation from benign medical and NORM radiation source and can work in spite of strong presence of NORM and or medical sources. RSL has developed its own wavelet-based gamma energy spectral anomaly detection algorithm called WAVRAD. Test results and relative merits of these different algorithms will be discussed and demonstrated.

Optical spectral imaging of degeneration of articular cartilage

NASA Astrophysics Data System (ADS)

Kinnunen, Jussi; Jurvelin, Jukka S.; Mäkitalo, Jaana; Hauta-Kasari, Markku; Vahimaa, Pasi; Saarakkala, Simo

2010-07-01

Osteoarthritis (OA) is a common musculoskeletal disorder often diagnosed during arthroscopy. In OA, visual color changes of the articular cartilage surface are typically observed. We demonstrate in vitro the potential of visible light spectral imaging (420 to 720 nm) to quantificate these color changes. Intact bovine articular cartilage samples (n=26) are degraded both enzymatically using the collagenase and mechanically using the emery paper (P60 grit, 269 μm particle size). Spectral images are analyzed by using standard CIELAB color coordinates and the principal component analysis (PCA). After collagenase digestion, changes in the CIELAB coordinates and projection of the spectra to PCA eigenvector are statistically significant (p<0.05). After mechanical degradation, the grinding tracks could not be visualized in the RGB presentation, i.e., in the visual appearance of the sample to the naked eye under the D65 illumination. However, after projecting to the chosen eigenvector, the grinding tracks are revealed. The tracks are also seen by using only one wavelength, i.e., 469 nm, however, the contrast in the projection image is 1.6 to 2.5 times higher. Our results support the idea that the spectral imaging can be used for evaluation of the integrity of the cartilage surface.

Correlation Analysis of Prompt Emission from Gamma Ray Bursts

NASA Astrophysics Data System (ADS)

Pothapragada, Sriharsha

Prompt emission from gamma-ray bursts (GRBs) exhibits very rapid, complicated temporal and spectral evolution. This diverse variability in the light-curves reflects the complicated nature of the underlying physics, in which inter-penetrating relativistic shells in the outflow are believed to generate strong magnetic fields that vary over very small scales. We use the theory of jitter radiation to model the emission from such regions and the resulting overall prompt gamma ray emission from a series of relativistic collisionless shocks. We present simulated GRB light-curves developed as a series of "pulses" corresponding to instantaneously illuminated "thin-shell" regions emitting via the jitter radiation mechanism. The effects of various geometries, viewing angles, and bulk Lorentz factor profiles of the radiating outflow jets on the spectral features and evolution of these light-curves are explored. Our results demonstrate how an anisotropic jitter radiation pattern, in conjunction with relativistic shock kinematics, can produce certain features observed in the GRB prompt emission spectra, such as the occurrence of hard, synchrotron violating spectra, the "tracking" of observed flux with spectral parameters, and spectral softening below peak energy within individual episodes of the light curve. We highlight predictions in the light of recent advances in the observational sphere of GRBs.

Variation in the Humification Degree of Dissolved Organic Matter from Cattle Manure during Composting as Analyzed by Ultraviolet-Visible and Fluorescence Spectroscopy.

PubMed

Chen, Yukun; Jiang, Zhao; Zhang, Xiuyuan; Cao, Bo; Yang, Fan; Wang, Ziyi; Zhang, Ying

2017-11-01

This study investigated the degree of humification of dissolved organic matter (DOM) during different periods of cattle manure composting using ultraviolet-visible (UV-vis) and fluorescence spectroscopy (emission, synchronous scan, and excitation-emission matrix) and determined which method is more suitable for analysis of the humification degree of DOM. Two composting piles were prepared by mixing manure and corn straw. One pile (Pile A [PA]) contained inoculated exogenous composite agents at a ratio of 2% (v/v), and a pile without the addition of inoculants (PNA) served as the control treatment. The results showed that ultraviolet integrated absorption intensities in the range of 226 to 400 nm and 260 to 280 nm and specific ultraviolet absorbances at 254 and 280 nm of both PA and PNA gradually increased with composting time. Based on the fluorescence regional integration analysis and parallel factor analysis, the humic-like substances became the main components of the DOM after composting. Our study demonstrated that the humification degree of DOM was enhanced during composting and that the inoculation composite agent was beneficial for the humification of DOM at the mesophilic and thermophilic phases of the composting process. Moreover, the results of correlation analysis and principal component analysis demonstrated that the fluorescence spectral parameters evaluated the humification degree of DOM during the whole cattle manure composting process better than the UV-vis spectral parameters. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.

A hyperspectral image projector for hyperspectral imagers

NASA Astrophysics Data System (ADS)

Rice, Joseph P.; Brown, Steven W.; Neira, Jorge E.; Bousquet, Robert R.

2007-04-01

We have developed and demonstrated a Hyperspectral Image Projector (HIP) intended for system-level validation testing of hyperspectral imagers, including the instrument and any associated spectral unmixing algorithms. HIP, based on the same digital micromirror arrays used in commercial digital light processing (DLP*) displays, is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. We use a scheme whereby one micromirror array is used to produce light having the spectra of endmembers (i.e. vegetation, water, minerals, etc.), and a second micromirror array, optically in series with the first, projects any combination of these arbitrarily-programmable spectra into the pixels of a 1024 x 768 element spatial image, thereby producing temporally-integrated images having spectrally mixed pixels. HIP goes beyond conventional DLP projectors in that each spatial pixel can have an arbitrary spectrum, not just arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a hyperspectral imager will measure during its use. Also, the spectral radiance of the projected scenes can be measured with a calibrated spectroradiometer, such that the spectral radiance projected into each pixel of the hyperspectral imager can be accurately known. Use of such projected scenes in a controlled laboratory setting would alleviate expensive field testing of instruments, allow better separation of environmental effects from instrument effects, and enable system-level performance testing and validation of hyperspectral imagers as used with analysis algorithms. For example, known mixtures of relevant endmember spectra could be projected into arbitrary spatial pixels in a hyperspectral imager, enabling tests of how well a full system, consisting of the instrument + calibration + analysis algorithm, performs in unmixing (i.e. de-convolving) the spectra in all pixels. We discuss here the performance of a visible prototype HIP. The technology is readily extendable to the ultraviolet and infrared spectral ranges, and the scenes can be static or dynamic.

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

Joint Biological Standoff Detection System increment II: Field Demonstration - SINBAHD Performances

DTIC Science & Technology

2007-12-01

of a dispersive element and a range-gated ICCD that limits the spectral information within the selected volume. This technique has showed an...bioaerosols. This LIF signal is spectrally collected by the combination of a dispersive element and a range-gated ICCD that records spectral...2001 in order to underline the robustness of the spectral signature of a particular biomaterial but of different origin, preparation and dispersion

The Relationship Between Spectral Modulation Detection and Speech Recognition: Adult Versus Pediatric Cochlear Implant Recipients

PubMed Central

Noble, Jack H.; Camarata, Stephen M.; Sunderhaus, Linsey W.; Dwyer, Robert T.; Dawant, Benoit M.; Dietrich, Mary S.; Labadie, Robert F.

2018-01-01

Adult cochlear implant (CI) recipients demonstrate a reliable relationship between spectral modulation detection and speech understanding. Prior studies documenting this relationship have focused on postlingually deafened adult CI recipients—leaving an open question regarding the relationship between spectral resolution and speech understanding for adults and children with prelingual onset of deafness. Here, we report CI performance on the measures of speech recognition and spectral modulation detection for 578 CI recipients including 477 postlingual adults, 65 prelingual adults, and 36 prelingual pediatric CI users. The results demonstrated a significant correlation between spectral modulation detection and various measures of speech understanding for 542 adult CI recipients. For 36 pediatric CI recipients, however, there was no significant correlation between spectral modulation detection and speech understanding in quiet or in noise nor was spectral modulation detection significantly correlated with listener age or age at implantation. These findings suggest that pediatric CI recipients might not depend upon spectral resolution for speech understanding in the same manner as adult CI recipients. It is possible that pediatric CI users are making use of different cues, such as those contained within the temporal envelope, to achieve high levels of speech understanding. Further investigation is warranted to investigate the relationship between spectral and temporal resolution and speech recognition to describe the underlying mechanisms driving peripheral auditory processing in pediatric CI users. PMID:29716437

Spectroscopic studies of different brands of cigarettes using laser-induced breakdown spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sayyad, M. H.; Saleem, M.; Shah, M.

In this work the technique of laser-induced breakdown spectroscopy (LIBS) has been used for the elemental analysis of cigarettes. For this purpose emission spectra have been measured of eleven different kinds of cigarette brands sold and/or produced in Pakistan. Analysis of the spectral peaks observed shows that Na, Mg, Al, K, Ca, Cr, Fe, Sr and Ba are contained in all brands. Exhibiting the LIBS results, the powerful potential of this method for the identification of the elemental content of cigarettes is demonstrated.

Spectroscopic studies of different brands of cigarettes using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Sayyad, M. H.; Saleem, M.; Shah, M.; Shaikh, N. M.; Baig, M. A.

2008-05-01

In this work the technique of laser-induced breakdown spectroscopy (LIBS) has been used for the elemental analysis of cigarettes. For this purpose emission spectra have been measured of eleven different kinds of cigarette brands sold and/or produced in Pakistan. Analysis of the spectral peaks observed shows that Na, Mg, Al, K, Ca, Cr, Fe, Sr and Ba are contained in all brands. Exhibiting the LIBS results, the powerful potential of this method for the identification of the elemental content of cigarettes is demonstrated.

Accurate determination of Brillouin frequency based on cross recurrence plot analysis in Brillouin distributed fiber sensor

NASA Astrophysics Data System (ADS)

Haneef, Shahna M.; Srijith, K.; Venkitesh, D.; Srinivasan, B.

2017-04-01

We propose and demonstrate the use of cross recurrence plot analysis (CRPA) to accurately determine the Brillouin shift due to strain and temperature in a Brillouin distributed fiber sensor. This signal processing technique, which is implemented in Brillouin sensors for the first time relies on apriori data i.e, the lineshape of the Brillouin gain spectrum and its similarity with the spectral features measured at different locations along the fiber. Analytical and experimental investigation of the proposed scheme is presented in this paper.

Application of TIMS data in stratigraphic analysis

NASA Technical Reports Server (NTRS)

Lang, H. R.

1986-01-01

An in-progress study demonstrates the utility of Thermal Infrared Multispectral Scanner (TIMS) data for unraveling the stratigraphic sequence of a western interior, North American foreland basin. The TIMS data can be used to determine the stratigraphic distribution of minerals that are diagnostic of specific depositional distribution. The thematic mapper (TM) and TIMS data were acquired in the Wind River/Bighorn area of central Wyoming in November 1982, and July 1983, respectively. Combined image processing, photogeologic, and spectral analysis methods were used to: map strata; construct stratigraphic columns; correlate data; and identify mineralogical facies.

Fresnel zone plate light field spectral imaging simulation

NASA Astrophysics Data System (ADS)

Hallada, Francis D.; Franz, Anthony L.; Hawks, Michael R.

2017-05-01

Through numerical simulation, we have demonstrated a novel snapshot spectral imaging concept using binary diffractive optics. Binary diffractive optics, such as Fresnel zone plates (FZP) or photon sieves, can be used as the single optical element in a spectral imager that conducts both imaging and dispersion. In previous demonstrations of spectral imaging with diffractive optics, the detector array was physically translated along the optic axis to measure different image formation planes. In this new concept the wavelength-dependent images are constructed synthetically, by using integral photography concepts commonly applied to light field (plenoptic) cameras. Light field cameras use computational digital refocusing methods after exposure to make images at different object distances. Our concept refocuses to make images at different wavelengths instead of different object distances. The simulations in this study demonstrate this concept for an imager designed with a FZP. Monochromatic light from planar sources is propagated through the system to a measurement plane using wave optics in the Fresnel approximation. Simple images, placed at optical infinity, are illuminated by monochromatic sources and then digitally refocused to show different spectral bins. We show the formation of distinct images from different objects, illuminated by monochromatic sources in the VIS/NIR spectrum. Additionally, this concept could easily be applied to imaging in the MWIR and LWIR ranges. In conclusion, this new type of imager offers a rugged and simple optical design for snapshot spectral imaging and warrants further development.

Design of a modified endoscope illuminator for spectral imaging of colorectal tissues

NASA Astrophysics Data System (ADS)

Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.

2017-02-01

The gold standard for locating colonic polyps is a white light endoscope in a colonoscopy, however, polyps smaller than 5 mm can be easily missed. Modified procedures such as narrow band imaging have shown only marginal increases in detection rates. Spectral imaging is a potential solution to improve the sensitivity and specificity of colonoscopies by providing the ability to distinguish molecular fluorescence differences in tissues. The goal of this work is to implement a spectral endoscopic light source to acquire spectral image data of colorectal tissues. A beta-version endoscope light source was developed, by retrofitting a white light endoscope light source (Olympus, CLK-4) with 16 narrow band LEDs. This redesigned, beta-prototype uses high-power LEDs with a minimum output of 500 mW to provide sufficient spectral output (0.5 mW) through the endoscope. A mounting apparatus was designed to provide sufficient heat dissipation. Here, we report recent results of our tests to characterize the intensity output through the light source and endoscope to determine the flat spectral output for imaging and intensity losses through the endoscope. We also report preliminary spectral imaging data from transverse pig colon that demonstrates the ability to result in working practical spectral data. Preliminary results of this revised prototype spectral endoscope system demonstrate that there is sufficient power to allow the imaging process to continue and potentially determine spectral differences in cancerous and normal tissue from imaging ex vivo pairs. Future work will focus on building a spectral library for the colorectal region and refining the user interface the system for in vivo use.

Spectral and Temporal Laser Fluorescence Analysis Such as for Natural Aquatic Environments

NASA Technical Reports Server (NTRS)

Chekalyuk, Alexander (Inventor)

2015-01-01

An Advanced Laser Fluorometer (ALF) can combine spectrally and temporally resolved measurements of laser-stimulated emission (LSE) for characterization of dissolved and particulate matter, including fluorescence constituents, in liquids. Spectral deconvolution (SDC) analysis of LSE spectral measurements can accurately retrieve information about individual fluorescent bands, such as can be attributed to chlorophyll-a (Chl-a), phycobiliprotein (PBP) pigments, or chromophoric dissolved organic matter (CDOM), among others. Improved physiological assessments of photosynthesizing organisms can use SDC analysis and temporal LSE measurements to assess variable fluorescence corrected for SDC-retrieved background fluorescence. Fluorescence assessments of Chl-a concentration based on LSE spectral measurements can be improved using photo-physiological information from temporal measurements. Quantitative assessments of PBP pigments, CDOM, and other fluorescent constituents, as well as basic structural characterizations of photosynthesizing populations, can be performed using SDC analysis of LSE spectral measurements.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.

PubMed

Boskamp, Tobias; Lachmund, Delf; Oetjen, Janina; Cordero Hernandez, Yovany; Trede, Dennis; Maass, Peter; Casadonte, Rita; Kriegsmann, Jörg; Warth, Arne; Dienemann, Hendrik; Weichert, Wilko; Kriegsmann, Mark

2017-07-01

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

A scoring metric for multivariate data for reproducibility analysis using chemometric methods

PubMed Central

Sheen, David A.; de Carvalho Rocha, Werickson Fortunato; Lippa, Katrice A.; Bearden, Daniel W.

2017-01-01

Process quality control and reproducibility in emerging measurement fields such as metabolomics is normally assured by interlaboratory comparison testing. As a part of this testing process, spectral features from a spectroscopic method such as nuclear magnetic resonance (NMR) spectroscopy are attributed to particular analytes within a mixture, and it is the metabolite concentrations that are returned for comparison between laboratories. However, data quality may also be assessed directly by using binned spectral data before the time-consuming identification and quantification. Use of the binned spectra has some advantages, including preserving information about trace constituents and enabling identification of process difficulties. In this paper, we demonstrate the use of binned NMR spectra to conduct a detailed interlaboratory comparison and composition analysis. Spectra of synthetic and biologically-obtained metabolite mixtures, taken from a previous interlaboratory study, are compared with cluster analysis using a variety of distance and entropy metrics. The individual measurements are then evaluated based on where they fall within their clusters, and a laboratory-level scoring metric is developed, which provides an assessment of each laboratory’s individual performance. PMID:28694553

Extraction and prediction of indices for monsoon intraseasonal oscillations: an approach based on nonlinear Laplacian spectral analysis

NASA Astrophysics Data System (ADS)

Sabeerali, C. T.; Ajayamohan, R. S.; Giannakis, Dimitrios; Majda, Andrew J.

2017-11-01

An improved index for real-time monitoring and forecast verification of monsoon intraseasonal oscillations (MISOs) is introduced using the recently developed nonlinear Laplacian spectral analysis (NLSA) technique. Using NLSA, a hierarchy of Laplace-Beltrami (LB) eigenfunctions are extracted from unfiltered daily rainfall data from the Global Precipitation Climatology Project over the south Asian monsoon region. Two modes representing the full life cycle of the northeastward-propagating boreal summer MISO are identified from the hierarchy of LB eigenfunctions. These modes have a number of advantages over MISO modes extracted via extended empirical orthogonal function analysis including higher memory and predictability, stronger amplitude and higher fractional explained variance over the western Pacific, Western Ghats, and adjoining Arabian Sea regions, and more realistic representation of the regional heat sources over the Indian and Pacific Oceans. Real-time prediction of NLSA-derived MISO indices is demonstrated via extended-range hindcasts based on NCEP Coupled Forecast System version 2 operational output. It is shown that in these hindcasts the NLSA MISO indices remain predictable out to ˜3 weeks.

Classification of river water pollution using Hyperion data

NASA Astrophysics Data System (ADS)

Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

2016-06-01

A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.

Automatic classification of spectral units in the Aristarchus plateau

NASA Astrophysics Data System (ADS)

Erard, S.; Le Mouelic, S.; Langevin, Y.

1999-09-01

A reduction scheme has been recently proposed for the NIR images of Clementine (Le Mouelic et al, JGR 1999). This reduction has been used to build an integrated UVvis-NIR image cube of the Aristarchus region, from which compositional and maturity variations can be studied (Pinet et al, LPSC 1999). We will present an analysis of this image cube, providing a classification in spectral types and spectral units. The image cube is processed with Gmode analysis using three different data sets: Normalized spectra provide a classification based mainly on spectral slope variations (ie. maturity and volcanic glasses). This analysis discriminates between craters plus ejecta, mare basalts, and DMD. Olivine-rich areas and Aristarchus central peak are also recognized. Continuum-removed spectra provide a classification more related to compositional variations, which correctly identifies olivine and pyroxenes-rich areas (in Aristarchus, Krieger, Schiaparelli\\ldots). A third analysis uses spectral parameters related to maturity and Fe composition (reflectance, 1 mu m band depth, and spectral slope) rather than intensities. It provides the most spatially consistent picture, but fails in detecting Vallis Schroeteri and DMDs. A supplementary unit, younger and rich in pyroxene, is found on Aristarchus south rim. In conclusion, Gmode analysis can discriminate between different spectral types already identified with more classic methods (PCA, linear mixing\\ldots). No previous assumption is made on the data structure, such as endmembers number and nature, or linear relationship between input variables. The variability of the spectral types is intrinsically accounted for, so that the level of analysis is always restricted to meaningful limits. A complete classification should integrate several analyses based on different sets of parameters. Gmode is therefore a powerful light toll to perform first look analysis of spectral imaging data. This research has been partly founded by the French Programme National de Planetologie.

Demonstration of Airborne Wide Area Assessment Technologies at Pueblo Precision Bombing Ranges, Colorado. Hyperspectral Imaging, Version 2.0

DTIC Science & Technology

2007-09-27

the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets

Common Prairie feeds with different soluble and insoluble fractions used for CPM diet formulation in dairy cattle: impact of carbohydrate-protein matrix structure on protein and other primary nutrient digestion.

PubMed

Peng, Quanhui; Wang, Zhisheng; Zhang, Xuewei; Yu, Peiqiang

2014-01-01

An experiment was conducted to investigate the relationship of carbohydrates molecular spectral characteristics to rumen degradability of primary nutrients in Prairie feeds in dairy cattle. In total, 12 different types of feeds were selected, each type of feed was from three different source with total 37 samples. Six types of them were energy-sourced feeds and the others were protein-sourced feeds. The carbohydrates molecular spectral intensity of various functional groups were collected using Fourier transform infrared attenuated total reflectance (ATR-FT/IR) spectroscopy. In the in situ study, the results showed that the rumen digestibility and digestible fractions of primary nutrients (DM, OM, NCP, and CP) were significantly different (P<0.05) among the feeds. The spectral bands features were significantly different (P<0.05) among the feeds. Spectral intensities of A_Cell, H_1415 and H_1370 were weakly positively correlated with in situ rumen digestibility and digestible fractions of DM, OM and NCP. Spectral intensities of H_1150, H_1015, A_1, and A_3 were weakly negatively associated with in situ rumen degradation of CP. Spectral intensities of A_1240 and H_1240, mainly associated with cellulosic compounds, were correlated with rumen CP degradation. The multiple regression analysis demonstrated that the spectral intensities of A_3 and H_1415 played the most important role and could be used as a potential tool to predict rumen protein degradation of feeds in dairy cattle. In conclusion, this study showed that the carbohydrates as a whole have an effect on protein rumen degradation, rather than cellulose alone, indicating carbohydrate-protein matrix structure impact protein utilization in dairy cattle. The non-invasive molecular spectral technique (ATR-FT/IR) could be used as a rapid potential tool to predict rumen protein degradation of feedstuffs by using molecular spectral bands intensities in carbohydrate fingerprint region. Copyright © 2013 Elsevier B.V. All rights reserved.

Common Prairie feeds with different soluble and insoluble fractions used for CPM diet formulation in dairy cattle: Impact of carbohydrate-protein matrix structure on protein and other primary nutrient digestion

NASA Astrophysics Data System (ADS)

Peng, Quanhui; Wang, Zhisheng; Zhang, Xuewei; Yu, Peiqiang

2014-03-01

An experiment was conducted to investigate the relationship of carbohydrates molecular spectral characteristics to rumen degradability of primary nutrients in Prairie feeds in dairy cattle. In total, 12 different types of feeds were selected, each type of feed was from three different source with total 37 samples. Six types of them were energy-sourced feeds and the others were protein-sourced feeds. The carbohydrates molecular spectral intensity of various functional groups were collected using Fourier transform infrared attenuated total reflectance (ATR-FT/IR) spectroscopy. In the in situ study, the results showed that the rumen digestibility and digestible fractions of primary nutrients (DM, OM, NCP, and CP) were significantly different (P < 0.05) among the feeds. The spectral bands features were significantly different (P < 0.05) among the feeds. Spectral intensities of A_Cell, H_1415 and H_1370 were weakly positively correlated with in situ rumen digestibility and digestible fractions of DM, OM and NCP. Spectral intensities of H_1150, H_1015, A_1, and A_3 were weakly negatively associated with in situ rumen degradation of CP. Spectral intensities of A_1240 and H_1240, mainly associated with cellulosic compounds, were correlated with rumen CP degradation. The multiple regression analysis demonstrated that the spectral intensities of A_3 and H_1415 played the most important role and could be used as a potential tool to predict rumen protein degradation of feeds in dairy cattle. In conclusion, this study showed that the carbohydrates as a whole have an effect on protein rumen degradation, rather than cellulose alone, indicating carbohydrate-protein matrix structure impact protein utilization in dairy cattle. The non-invasive molecular spectral technique (ATR-FT/IR) could be used as a rapid potential tool to predict rumen protein degradation of feedstuffs by using molecular spectral bands intensities in carbohydrate fingerprint region.

Autonomous frequency domain identification: Theory and experiment

NASA Technical Reports Server (NTRS)

Yam, Yeung; Bayard, D. S.; Hadaegh, F. Y.; Mettler, E.; Milman, M. H.; Scheid, R. E.

1989-01-01

The analysis, design, and on-orbit tuning of robust controllers require more information about the plant than simply a nominal estimate of the plant transfer function. Information is also required concerning the uncertainty in the nominal estimate, or more generally, the identification of a model set within which the true plant is known to lie. The identification methodology that was developed and experimentally demonstrated makes use of a simple but useful characterization of the model uncertainty based on the output error. This is a characterization of the additive uncertainty in the plant model, which has found considerable use in many robust control analysis and synthesis techniques. The identification process is initiated by a stochastic input u which is applied to the plant p giving rise to the output. Spectral estimation (h = P sub uy/P sub uu) is used as an estimate of p and the model order is estimated using the produce moment matrix (PMM) method. A parametric model unit direction vector p is then determined by curve fitting the spectral estimate to a rational transfer function. The additive uncertainty delta sub m = p - unit direction vector p is then estimated by the cross spectral estimate delta = P sub ue/P sub uu where e = y - unit direction vectory y is the output error, and unit direction vector y = unit direction vector pu is the computed output of the parametric model subjected to the actual input u. The experimental results demonstrate the curve fitting algorithm produces the reduced-order plant model which minimizes the additive uncertainty. The nominal transfer function estimate unit direction vector p and the estimate delta of the additive uncertainty delta sub m are subsequently available to be used for optimization of robust controller performance and stability.

Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements

PubMed Central

Kapucu, Fikret E.; Välkki, Inkeri; Mikkonen, Jarno E.; Leone, Chiara; Lenk, Kerstin; Tanskanen, Jarno M. A.; Hyttinen, Jari A. K.

2016-01-01

Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from different network regions. The method is based on the correlation of time varying spectral entropies (SEs). SE assesses the regularity, or complexity, of a time series by quantifying the uniformity of the frequency spectrum distribution. It has been previously employed, e.g., in electroencephalogram analysis. Here, we revisit our correlated spectral entropy method (CorSE), providing evidence of its justification, usability, and benefits. Here, CorSE is assessed with simulations and in vitro microelectrode array (MEA) data. CorSE is first demonstrated with a specifically tailored toy simulation to illustrate how it can identify synchronized populations. To provide a form of validation, the method was tested with simulated data from integrate-and-fire model based computational neuronal networks. To demonstrate the analysis of real data, CorSE was applied on in vitro MEA data measured from rat cortical cell cultures, and the results were compared with three known event based synchronization measures. Finally, we show the usability by tracking the development of networks in dissociated mouse cortical cell cultures. The results show that temporal correlations in frequency spectrum distributions reflect the network relations of neuronal populations. In the simulated data, CorSE unraveled the synchronizations. With the real in vitro MEA data, CorSE produced biologically plausible results. Since CorSE analyses continuous data, it is not affected by possibly poor spike or other event detection quality. We conclude that CorSE can reveal neuronal network synchronization based on in vitro MEA field potential measurements. CorSE is expected to be equally applicable also in the analysis of corresponding in vivo and ex vivo data analysis. PMID:27803660

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

Depth resolved hyperspectral imaging spectrometer based on structured light illumination and Fourier transform interferometry

PubMed Central

Choi, Heejin; Wadduwage, Dushan; Matsudaira, Paul T.; So, Peter T.C.

2014-01-01

A depth resolved hyperspectral imaging spectrometer can provide depth resolved imaging both in the spatial and the spectral domain. Images acquired through a standard imaging Fourier transform spectrometer do not have the depth-resolution. By post processing the spectral cubes (x, y, λ) obtained through a Sagnac interferometer under uniform illumination and structured illumination, spectrally resolved images with depth resolution can be recovered using structured light illumination algorithms such as the HiLo method. The proposed scheme is validated with in vitro specimens including fluorescent solution and fluorescent beads with known spectra. The system is further demonstrated in quantifying spectra from 3D resolved features in biological specimens. The system has demonstrated depth resolution of 1.8 μm and spectral resolution of 7 nm respectively. PMID:25360367

Development and Demonstration of a Field-Deployable fast Chromotomographic Imager

DTIC Science & Technology

2010-03-01

contrast environment. Next, results and analyses of an extended static broadband spectrum scene are presented. Chapter 5 ends with the spectral ... spectral and spatial contrast were chosen to facilitate confirmation of the spectral results the algorithm provided. An American flag, because of the...s of nm apart is an example of a scene with high spectral contrast . Prior to the collection of any data, the focusing lens was focused and then

PlanetServer: Innovative approaches for the online analysis of hyperspectral satellite data from Mars

NASA Astrophysics Data System (ADS)

Oosthoek, J. H. P.; Flahaut, J.; Rossi, A. P.; Baumann, P.; Misev, D.; Campalani, P.; Unnithan, V.

2014-06-01

PlanetServer is a WebGIS system, currently under development, enabling the online analysis of Compact Reconnaissance Imaging Spectrometer (CRISM) hyperspectral data from Mars. It is part of the EarthServer project which builds infrastructure for online access and analysis of huge Earth Science datasets. Core functionality consists of the rasdaman Array Database Management System (DBMS) for storage, and the Open Geospatial Consortium (OGC) Web Coverage Processing Service (WCPS) for data querying. Various WCPS queries have been designed to access spatial and spectral subsets of the CRISM data. The client WebGIS, consisting mainly of the OpenLayers javascript library, uses these queries to enable online spatial and spectral analysis. Currently the PlanetServer demonstration consists of two CRISM Full Resolution Target (FRT) observations, surrounding the NASA Curiosity rover landing site. A detailed analysis of one of these observations is performed in the Case Study section. The current PlanetServer functionality is described step by step, and is tested by focusing on detecting mineralogical evidence described in earlier Gale crater studies. Both the PlanetServer methodology and its possible use for mineralogical studies will be further discussed. Future work includes batch ingestion of CRISM data and further development of the WebGIS and analysis tools.

A Spatially Offset Raman Spectroscopy Method for Non-Destructive Detection of Gelatin-Encapsulated Powders

PubMed Central

Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Peng, Yankun; Schmidt, Walter F.; Kim, Moon S.; Chan, Diane E.

2017-01-01

Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS) method to detect and identify urea, ibuprofen, and acetaminophen powders contained within one or more (up to eight) layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785-nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. As the offset distance was increased, the spectral contribution from the subsurface powder gradually outweighed that of the surface capsule layers, allowing for detection of the encapsulated powders. Containing mixed contributions from the powder and capsule, the SORS spectra for each sample were resolved into pure component spectra using self-modeling mixture analysis (SMA) and the corresponding components were identified using spectral information divergence values. As demonstrated here for detecting chemicals contained inside thick capsule layers, this SORS measurement technique coupled with SMA has the potential to be a reliable non-destructive method for subsurface inspection and authentication of foods, health supplements, and pharmaceutical products that are prepared or packaged with semi-transparent materials. PMID:28335453

Field Utilization and Analysis of AIS 128-channel Imagery Using Microcomputers: Application to Yerington, Nevada Field Area

NASA Technical Reports Server (NTRS)

Lyon, R. J. P.; Lanz, K.

1985-01-01

Geologists in exploration need to be able to determine the mineral composition of a given outcrop, and then proceed to another in order to carry out the process of geologic mapping. Since April 1984 researchers have been developing a portable microcomputer-based imaging system (with a grey-scale of 16 shades of amber), which were demonstrated during the November 1984 GSA field trip in the field at Yerington, NV. A color-version of the same technology was recently demonstrated. The portable computer selected is a COLBY 10-Megabyte, hard disk-equipped repackaged-IBM/XT, which operates on either 110/220 VAC or on 12VDC from the cigarette lighter in a field vehicle. A COMPAQ PLUS or an IBM Portable will also work on modified software. The underlying concept is that the atmospheric transmission and surface albedo/slope terms are multiplicative, relating the spectral irradiance to the spectral color of the surface materials. Thus, the spectral color of a pixel remains after averaged log-albedo and log-irradiance have been estimated. All these steps can be carried out on the COLBY microcomputer, using 80 image lines of the 128-channel, 12-bit imagery. Results are shown for such an 80-line segment, showing the identification of an O-H bearing mineral group (of slightly varying specific characters) on the flight line.

Dynamic metabolic imaging of hyperpolarized [2-(13) C]pyruvate using spiral chemical shift imaging with alternating spectral band excitation.

PubMed

Josan, Sonal; Hurd, Ralph; Park, Jae Mo; Yen, Yi-Fen; Watkins, Ron; Pfefferbaum, Adolf; Spielman, Daniel; Mayer, Dirk

2014-06-01

In contrast to [1-(13) C]pyruvate, hyperpolarized [2-(13) C]pyruvate permits the ability to follow the (13) C label beyond flux through pyruvate dehydrogenase complex and investigate the incorporation of acetyl-coenzyme A into different metabolic pathways. However, chemical shift imaging (CSI) with [2-(13) C]pyruvate is challenging owing to the large spectral dispersion of the resonances, which also leads to severe chemical shift displacement artifacts for slice-selective acquisitions. This study introduces a sequence for three-dimensional CSI of [2-(13) C]pyruvate using spectrally selective excitation of limited frequency bands containing a subset of metabolites. Dynamic CSI data were acquired alternately from multiple frequency bands in phantoms for sequence testing and in vivo in rat heart. Phantom experiments verified the radiofrequency pulse design and demonstrated that the signal behavior of each group of resonances was unaffected by excitation of the other frequency bands. Dynamic three-dimensional (13) C CSI data demonstrated the sequence capability to image pyruvate, lactate, acetylcarnitine, glutamate, and acetoacetate, enabling the analysis of organ-specific spectra and metabolite time courses. The presented method allows CSI of widely separated resonances without chemical shift displacement artifact, acquiring multiple frequency bands alternately to obtain dynamic time-course information. This approach enables robust imaging of downstream metabolic products of acetyl-coenzyme A with hyperpolarized [2-(13) C]pyruvate. Copyright © 2013 Wiley Periodicals, Inc.

Automated Big Data Analysis in Bottom-up and Targeted Proteomics

PubMed Central

van der Plas-Duivesteijn, Suzanne; Domański, Dominik; Smith, Derek; Borchers, Christoph; Palmblad, Magnus; Mohamme, Yassene

2014-01-01

Similar to other data intensive sciences, analyzing mass spectrometry-based proteomics data involves multiple steps and diverse software using different algorithms and data formats and sizes. Besides that the distributed and evolving nature of the data in online repositories, another challenge is that a scientists have to deal with many steps of analysis pipelines. A documented data processing is also becoming an essential part for the overall reproducibility of the results. Thanks to different e-Science initiatives, scientific workflow engines have become a means for automated, sharable and reproducible data processing. While these are designed as general tools, they can be employed to solve different challenges that we are facing in handling our Big Data. Here we present three use cases: improving the performance of different spectral search engines by decomposing input data and recomposing the resulting files, building spectral libraries from more than 20 million spectra, and integrating information from multiple resources to select most appropriate peptides for targeted proteomics analyses. The three use cases demonstrate different challenges in exploiting proteomics data analysis. In the first we integrate local and cloud processing resources in order to obtain better performance resulting in more than 30-fold speed improvement. By considering search engines as legacy software our solution is applicable to multiple search algorithms. The second use case is an example of automated processing of many data files of different sizes and locations, starting with raw data and ending with the final, ready-to-use library. This demonstrates the robustness and fault tolerance when dealing with huge amount data stored in multiple files. The third use case demonstrates retrieval and integration of information and data from multiple online repositories. In addition to the diversity of data formats and Web interfaces, this use case also illustrates how to deal with incomplete data.

Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

NASA Astrophysics Data System (ADS)

Lazcano, R.; Madroñal, D.; Fabelo, H.; Ortega, S.; Salvador, R.; Callicó, G. M.; Juárez, E.; Sanz, C.

2017-10-01

Hyperspectral Imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVCCAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one-band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

Rare-earth-doped materials with application to optical signal processing, quantum information science, and medical imaging technology

NASA Astrophysics Data System (ADS)

Cone, R. L.; Thiel, C. W.; Sun, Y.; Böttger, Thomas; Macfarlane, R. M.

2012-02-01

Unique spectroscopic properties of isolated rare earth ions in solids offer optical linewidths rivaling those of trapped single atoms and enable a variety of recent applications. We design rare-earth-doped crystals, ceramics, and fibers with persistent or transient "spectral hole" recording properties for applications including high-bandwidth optical signal processing where light and our solids replace the high-bandwidth portion of the electronics; quantum cryptography and information science including the goal of storage and recall of single photons; and medical imaging technology for the 700-900 nm therapeutic window. Ease of optically manipulating rare-earth ions in solids enables capturing complex spectral information in 105 to 108 frequency bins. Combining spatial holography and spectral hole burning provides a capability for processing high-bandwidth RF and optical signals with sub-MHz spectral resolution and bandwidths of tens to hundreds of GHz for applications including range-Doppler radar and high bandwidth RF spectral analysis. Simply stated, one can think of these crystals as holographic recording media capable of distinguishing up to 108 different colors. Ultra-narrow spectral holes also serve as a vibration-insensitive sub-kHz frequency reference for laser frequency stabilization to a part in 1013 over tens of milliseconds. The unusual properties and applications of spectral hole burning of rare earth ions in optical materials are reviewed. Experimental results on the promising Tm3+:LiNbO3 material system are presented and discussed for medical imaging applications. Finally, a new application of these materials as dynamic optical filters for laser noise suppression is discussed along with experimental demonstrations and theoretical modeling of the process.

Analysis of noise in quorum sensing.

PubMed

Cox, Chris D; Peterson, Gregory D; Allen, Michael S; Lancaster, Joseph M; McCollum, James M; Austin, Derek; Yan, Ling; Sayler, Gary S; Simpson, Michael L

2003-01-01

Noise may play a pivotal role in gene circuit functionality, as demonstrated for the genetic switch in the bacterial phage lambda. Like the lambda switch, bacterial quorum sensing (QS) systems operate within a population and contain a bistable switching element, making it likely that noise plays a functional role in QS circuit operation. Therefore, a detailed analysis of the noise behavior of QS systems is needed. We have developed a set of tools generally applicable to the analysis of gene circuits, with an emphasis on investigations in the frequency domain (FD), that we apply here to the QS system in the marine bacterium Vibrio fischeri. We demonstrate that a tight coupling between exact stochastic simulation and FD analysis provides insights into the structure/function relationships in the QS circuit. Furthermore, we argue that a noise analysis is incomplete without consideration of the power spectral densities (PSDs) of the important molecular output signals. As an example we consider reversible reactions in the QS circuit, and show through analysis and exact stochastic simulation that these circuits make significant and dynamic modifications to the noise spectra. In particular, we demonstrate a "whitening" effect, which occurs as the noise is processed through these reversible reactions.

Novel selective TOCSY method enables NMR spectral elucidation of metabolomic mixtures

NASA Astrophysics Data System (ADS)

MacKinnon, Neil; While, Peter T.; Korvink, Jan G.

2016-11-01

Complex mixture analysis is routinely encountered in NMR-based investigations. With the aim of component identification, spectral complexity may be addressed chromatographically or spectroscopically, the latter being favored to reduce sample handling requirements. An attractive experiment is selective total correlation spectroscopy (sel-TOCSY), which is capable of providing tremendous spectral simplification and thereby enhancing assignment capability. Unfortunately, isolating a well resolved resonance is increasingly difficult as the complexity of the mixture increases and the assumption of single spin system excitation is no longer robust. We present TOCSY optimized mixture elucidation (TOOMIXED), a technique capable of performing spectral assignment particularly in the case where the assumption of single spin system excitation is relaxed. Key to the technique is the collection of a series of 1D sel-TOCSY experiments as a function of the isotropic mixing time (τm), resulting in a series of resonance intensities indicative of the underlying molecular structure. By comparing these τm -dependent intensity patterns with a library of pre-determined component spectra, one is able to regain assignment capability. After consideration of the technique's robustness, we tested TOOMIXED firstly on a model mixture. As a benchmark we were able to assign a molecule with high confidence in the case of selectively exciting an isolated resonance. Assignment confidence was not compromised when performing TOOMIXED on a resonance known to contain multiple overlapping signals, and in the worst case the method suggested a follow-up sel-TOCSY experiment to confirm an ambiguous assignment. TOOMIXED was then demonstrated on two realistic samples (whisky and urine), where under our conditions an approximate limit of detection of 0.6 mM was determined. Taking into account literature reports for the sel-TOCSY limit of detection, the technique should reach on the order of 10 μ M sensitivity. We anticipate this technique will be highly attractive to various analytical fields facing mixture analysis, including metabolomics, foodstuff analysis, pharmaceutical analysis, and forensics.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

NASA Astrophysics Data System (ADS)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Neutron spectrometry for UF 6 enrichment verification in storage cylinders

DOE PAGES

Mengesha, Wondwosen; Kiff, Scott D.

2015-01-29

Verification of declared UF 6 enrichment and mass in storage cylinders is of great interest in nuclear material nonproliferation. Nondestructive assay (NDA) techniques are commonly used for safeguards inspections to ensure accountancy of declared nuclear materials. Common NDA techniques used include gamma-ray spectrometry and both passive and active neutron measurements. In the present study, neutron spectrometry was investigated for verification of UF 6 enrichment in 30B storage cylinders based on an unattended and passive measurement approach. MCNP5 and Geant4 simulated neutron spectra, for selected UF 6 enrichments and filling profiles, were used in the investigation. The simulated neutron spectra weremore » analyzed using principal component analysis (PCA). The PCA technique is a well-established technique and has a wide area of application including feature analysis, outlier detection, and gamma-ray spectral analysis. Results obtained demonstrate that neutron spectrometry supported by spectral feature analysis has potential for assaying UF 6 enrichment in storage cylinders. Thus the results from the present study also showed that difficulties associated with the UF 6 filling profile and observed in other unattended passive neutron measurements can possibly be overcome using the approach presented.« less

[Rapid multi-elemental analysis on four precious Tibetan medicines based on LIBS technique].

PubMed

Liu, Xiao-na; Shi, Xin-yuan; Jia, Shuai-yun; Zhao, Na; Wu, Zhi-sheng; Qiao, Yan-jiang

2015-06-01

The laser-induced breakdown spectroscopy (LIBS) was applied to perform a qualitative elementary analysis on four precious Tibetan medicines, i. e. Renqing Mangjue, Renqing Changjue, 25-herb coral pills and 25-herb pearl pills. The specific spectra of the four Tibetan medicines were established. In the experiment, Nd: YAG and 1 064 nm-baseband pulse laser were adopted to collect the spectra. A laser beam focused on the surface of the samples to generate plasma. Its spectral signal was detected by using spectrograph. Based on the National Institute of Standard and Technology (NIST) database, LIBS spectral lines were indentified. The four Tibetan medicines mainly included Ca, Na, K, Mg and other elements and C-N molecular band. Specifically, Fe was detected in Renqing Changjue and 25-herb pearl pills; heavy mental elements Hg and Cu were shown in Renqing Mangjue and Renqing Changjue; Ag was found in Renqing Changjue. The results demonstrated that LIBS is a reliable and rapid multi-element analysis on the four Tibetan medicines. With Real-time, rapid and nondestructive advantages, LIBS has a wide application prospect in the element analysis on ethnic medicines.

An Improved Spectral Analysis Method for Fatigue Damage Assessment of Details in Liquid Cargo Tanks

NASA Astrophysics Data System (ADS)

Zhao, Peng-yuan; Huang, Xiao-ping

2018-03-01

Errors will be caused in calculating the fatigue damages of details in liquid cargo tanks by using the traditional spectral analysis method which is based on linear system, for the nonlinear relationship between the dynamic stress and the ship acceleration. An improved spectral analysis method for the assessment of the fatigue damage in detail of a liquid cargo tank is proposed in this paper. Based on assumptions that the wave process can be simulated by summing the sinusoidal waves in different frequencies and the stress process can be simulated by summing the stress processes induced by these sinusoidal waves, the stress power spectral density (PSD) is calculated by expanding the stress processes induced by the sinusoidal waves into Fourier series and adding the amplitudes of each harmonic component with the same frequency. This analysis method can take the nonlinear relationship into consideration and the fatigue damage is then calculated based on the PSD of stress. Take an independent tank in an LNG carrier for example, the accuracy of the improved spectral analysis method is proved much better than that of the traditional spectral analysis method by comparing the calculated damage results with the results calculated by the time domain method. The proposed spectral analysis method is more accurate in calculating the fatigue damages in detail of ship liquid cargo tanks.

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

NASA Technical Reports Server (NTRS)

Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.

2012-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Spectral analysis of GEOS-3 altimeter data and frequency domain collocation. [to estimate gravity anomalies

NASA Technical Reports Server (NTRS)

Eren, K.

1980-01-01

The mathematical background in spectral analysis as applied to geodetic applications is summarized. The resolution (cut-off frequency) of the GEOS 3 altimeter data is examined by determining the shortest wavelength (corresponding to the cut-off frequency) recoverable. The data from some 18 profiles are used. The total power (variance) in the sea surface topography with respect to the reference ellipsoid as well as with respect to the GEM-9 surface is computed. A fast inversion algorithm for matrices of simple and block Toeplitz matrices and its application to least squares collocation is explained. This algorithm yields a considerable gain in computer time and storage in comparison with conventional least squares collocation. Frequency domain least squares collocation techniques are also introduced and applied to estimating gravity anomalies from GEOS 3 altimeter data. These techniques substantially reduce the computer time and requirements in storage associated with the conventional least squares collocation. Numerical examples given demonstrate the efficiency and speed of these techniques.

Optical characterization of agricultural pest insects: a methodological study in the spectral and time domains

NASA Astrophysics Data System (ADS)

Li, Y. Y.; Zhang, H.; Duan, Z.; Lian, M.; Zhao, G. Y.; Sun, X. H.; Hu, J. D.; Gao, L. N.; Feng, H. Q.; Svanberg, S.

2016-08-01

Identification of agricultural pest insects is an important aspect in insect research and agricultural monitoring. We have performed a methodological study of how spectroscopic techniques and wing-beat frequency analysis might provide relevant information. An optical system based on the combination of close-range remote sensing and reflectance spectroscopy was developed to study the optical characteristics of different flying insects, collected in Southern China. The results demonstrate that the combination of wing-beat frequency assessment and reflectance spectral analysis has the potential to successfully differentiate between insect species. Further, studies of spectroscopic characteristics of fixed specimen of insects, also from Central China, showed the possibility of refined agricultural pest identification. Here, in addition to reflectance recordings also laser-induced fluorescence spectra were investigated for all the species of insects under study and found to provide complementary information to optically distinguish insects. In order to prove the practicality of the techniques explored, clearly fieldwork aiming at elucidating the variability of parameters, even within species, must be performed.

Hyperspectral imaging in SWIR: from stain-free microscopy to deep tissue imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Berezin, Mikhail Y.

2016-03-01

Recent advances in relatively unexplored short wave infrared (SWIR) range from 800-1600 nm detectors make wide-field imaging in this spectral range attractive to biology. The distinct advantages of SWIR region over the visible and near infrared (NIR) in tissue analysis are two-fold: (i) high abundance endogenous chromophores (i.e. water and lipids) enable tissue component differentiation based on wavelength-dependent absorption properties and (ii) the weak scattering of tissue permits better resolution of imaging in thick specimens. When combined with high spectral resolution, SWIR imaging produces a spectroscopic image, where every pixel corresponds to the entire high-resolution spectrum. This hyperspectral (HS) approach provides rich information about the relative abundance of individual chromophores and their interactions that contribute to the intensity and location of the optical signal. The presentation discusses the challenges in the SWIR-HS instrument design and data analysis and demonstrates some of the promising applications of this technology in life science and medicine.

Spectral Regression Discriminant Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Pan, Y.; Wu, J.; Huang, H.; Liu, J.

2012-08-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.

Phenol homeostasis is ensured in vanilla fruit by storage under solid form in a new chloroplast-derived organelle, the phenyloplast

PubMed Central

Conéjéro, Geneviève

2014-01-01

A multiple cell imaging approach combining immunofluorescence by confocal microscopy, fluorescence spectral analysis by multiphotonic microscopy, and transmission electron microscopy identified the site of accumulation of 4-O-(3-methoxybenzaldehyde) β-d-glucoside, a phenol glucoside massively stockpiled by vanilla fruit. The glucoside is sufficiently abundant to be detected by spectral analysis of its autofluorescence. The convergent results obtained by these different techniques demonstrated that the phenol glucoside accumulates in the inner volume of redifferentiating chloroplasts as solid amorphous deposits, thus ensuring phenylglucoside cell homeostasis. Redifferentiation starts with the generation of loculi between thylakoid membranes which are progressively filled with the glucoside until a fully matured organelle is obtained. This peculiar mode of storage of a phenolic secondary metabolite is suspected to occur in other plants and its generalization in the Plantae could be considered. This new chloroplast-derived organelle is referred to as a ‘phenyloplast’. PMID:24683183

Phenol homeostasis is ensured in vanilla fruit by storage under solid form in a new chloroplast-derived organelle, the phenyloplast.

PubMed

Brillouet, Jean-Marc; Verdeil, Jean-Luc; Odoux, Eric; Lartaud, Marc; Grisoni, Michel; Conéjéro, Geneviève

2014-06-01

A multiple cell imaging approach combining immunofluorescence by confocal microscopy, fluorescence spectral analysis by multiphotonic microscopy, and transmission electron microscopy identified the site of accumulation of 4-O-(3-methoxybenzaldehyde) β-d-glucoside, a phenol glucoside massively stockpiled by vanilla fruit. The glucoside is sufficiently abundant to be detected by spectral analysis of its autofluorescence. The convergent results obtained by these different techniques demonstrated that the phenol glucoside accumulates in the inner volume of redifferentiating chloroplasts as solid amorphous deposits, thus ensuring phenylglucoside cell homeostasis. Redifferentiation starts with the generation of loculi between thylakoid membranes which are progressively filled with the glucoside until a fully matured organelle is obtained. This peculiar mode of storage of a phenolic secondary metabolite is suspected to occur in other plants and its generalization in the Plantae could be considered. This new chloroplast-derived organelle is referred to as a 'phenyloplast'. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Near-infrared hyperspectral imaging for quality analysis of agricultural and food products

NASA Astrophysics Data System (ADS)

Singh, C. B.; Jayas, D. S.; Paliwal, J.; White, N. D. G.

2010-04-01

Agricultural and food processing industries are always looking to implement real-time quality monitoring techniques as a part of good manufacturing practices (GMPs) to ensure high-quality and safety of their products. Near-infrared (NIR) hyperspectral imaging is gaining popularity as a powerful non-destructive tool for quality analysis of several agricultural and food products. This technique has the ability to analyse spectral data in a spatially resolved manner (i.e., each pixel in the image has its own spectrum) by applying both conventional image processing and chemometric tools used in spectral analyses. Hyperspectral imaging technique has demonstrated potential in detecting defects and contaminants in meats, fruits, cereals, and processed food products. This paper discusses the methodology of hyperspectral imaging in terms of hardware, software, calibration, data acquisition and compression, and development of prediction and classification algorithms and it presents a thorough review of the current applications of hyperspectral imaging in the analyses of agricultural and food products.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hornemann, Andrea, E-mail: andrea.hornemann@ptb.de; Hoehl, Arne, E-mail: arne.hoehl@ptb.de; Ulm, Gerhard, E-mail: gerhard.ulm@ptb.de

Bio-diagnostic assays of high complexity rely on nanoscaled assay recognition elements that can provide unique selectivity and design-enhanced sensitivity features. High throughput performance requires the simultaneous detection of various analytes combined with appropriate bioassay components. Nanoparticle induced sensitivity enhancement, and subsequent multiplexed capability Surface-Enhanced InfraRed Absorption (SEIRA) assay formats are fitting well these purposes. SEIRA constitutes an ideal platform to isolate the vibrational signatures of targeted bioassay and active molecules. The potential of several targeted biolabels, here fluorophore-labeled antibody conjugates, chemisorbed onto low-cost biocompatible gold nano-aggregates substrates have been explored for their use in assay platforms. Dried films were analyzedmore » by synchrotron radiation based FTIR/SEIRA spectro-microscopy and the resulting complex hyperspectral datasets were submitted to automated statistical analysis, namely Principal Components Analysis (PCA). The relationships between molecular fingerprints were put in evidence to highlight their spectral discrimination capabilities. We demonstrate that robust spectral encoding via SEIRA fingerprints opens up new opportunities for fast, reliable and multiplexed high-end screening not only in biodiagnostics but also in vitro biochemical imaging.« less

Spectral singularities of complex scattering potentials and infinite reflection and transmission coefficients at real energies.

PubMed

Mostafazadeh, Ali

2009-06-05

Spectral singularities are spectral points that spoil the completeness of the eigenfunctions of certain non-Hermitian Hamiltonian operators. We identify spectral singularities of complex scattering potentials with the real energies at which the reflection and transmission coefficients tend to infinity, i.e., they correspond to resonances having a zero width. We show that a waveguide modeled using such a potential operates like a resonator at the frequencies of spectral singularities. As a concrete example, we explore the spectral singularities of an imaginary PT-symmetric barrier potential and demonstrate the above resonance phenomenon for a certain electromagnetic waveguide.

Spectral Singularities of Complex Scattering Potentials and Infinite Reflection and Transmission Coefficients at Real Energies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mostafazadeh, Ali

2009-06-05

Spectral singularities are spectral points that spoil the completeness of the eigenfunctions of certain non-Hermitian Hamiltonian operators. We identify spectral singularities of complex scattering potentials with the real energies at which the reflection and transmission coefficients tend to infinity, i.e., they correspond to resonances having a zero width. We show that a waveguide modeled using such a potential operates like a resonator at the frequencies of spectral singularities. As a concrete example, we explore the spectral singularities of an imaginary PT-symmetric barrier potential and demonstrate the above resonance phenomenon for a certain electromagnetic waveguide.

Application of Raman Spectroscopy for the Detection of Acetone Dissolved in Transformer Oil

NASA Astrophysics Data System (ADS)

Gu, Z.; Chen, W.; Du, L.; Shi, H.; Wan, F.

2018-05-01

The CLRS detection characteristics of acetone dissolved in transformer oil were analyzed. Raman spectral peak at 780 cm-1 was used as the characteristic spectral peak for qualitative and quantitative analyses. The effect of the detection depth and the temperature was investigated in order to obtain good Raman signals. The optimal detection depth and temperature were set as 3 mm and room temperature. A quantitative model relation between concentration and the Raman peak intensity ratio I 780/I 893 was constructed via the least-squares method. The results demonstrated that CLRS can quantitatively detect the concentration of acetone in transformer oil and CLRS has potential as a useful alternative for accelerating the in-situ analysis of the concentration of acetone in transformer oil.

Application of Raman Spectroscopy for the Detection of Acetone Dissolved in Transformer Oil

NASA Astrophysics Data System (ADS)

Gu, Z.; Chen, W.; Du, L.; Shi, H.; Wan, F.

2018-05-01

The CLRS detection characteristics of acetone dissolved in transformer oil were analyzed. Raman spectral peak at 780 cm-1 was used as the characteristic spectral peak for qualitative and quantitative analyses. The effect of the detection depth and the temperature was investigated in order to obtain good Raman signals. The optimal detection depth and temperature were set as 3 mm and room temperature. A quantitative model relation between concentration and the Raman peak intensity ratio I 780/ I 893 was constructed via the least-squares method. The results demonstrated that CLRS can quantitatively detect the concentration of acetone in transformer oil and CLRS has potential as a useful alternative for accelerating the in-situ analysis of the concentration of acetone in transformer oil.

Optimal design of similariton fiber lasers without gain-bandwidth limitation.

PubMed

Li, Xingliang; Zhang, Shumin; Yang, Zhenjun

2017-07-24

We have numerically investigated broadband high-energy similariton fiber lasers, demonstrated that the self-similar evolution of pulses can locate in a segment of photonic crystal fiber without gain-bandwidth limitation. The effects of various parameters, including the cavity length, the spectral filter bandwidth, the pump power, the length of the photonic crystal fiber and the output coupling ratio have also been studied in detail. Using the optimal parameters, a single pulse with spectral width of 186.6 nm, pulse energy of 23.8 nJ, dechirped pulse duration of 22.5 fs and dechirped pulse peak power of 1.26 MW was obtained. We believe that this detailed analysis of the behaviour of pulses in the similariton regime may have major implications in the development of broadband high-energy fiber lasers.

Spectral ophthalmoscopy based on supercontinuum

NASA Astrophysics Data System (ADS)

Cheng, Yueh-Hung; Yu, Jiun-Yann; Wu, Han-Hsuan; Huang, Bo-Jyun; Chu, Shi-Wei

2010-02-01

Confocal scanning laser ophthalmoscope (CSLO) has been established to be an important diagnostic tool for retinopathies like age-related macular degeneration, glaucoma and diabetes. Compared to a confocal laser scanning microscope, CSLO is also capable of providing optical sectioning on retina with the aid of a pinhole, but the microscope objective is replaced by the optics of eye. Since optical spectrum is the fingerprint of local chemical composition, it is attractive to incorporate spectral acquisition into CSLO. However, due to the limitation of laser bandwidth and chromatic/geometric aberration, the scanning systems in current CSLO are not compatible with spectral imaging. Here we demonstrate a spectral CSLO by combining a diffraction-limited broadband scanning system and a supercontinuum laser source. Both optical sectioning capability and sub-cellular resolution are demonstrated on zebrafish's retina. To our knowledge, it is also the first time that CSLO is applied onto the study of fish vision. The versatile spectral CSLO system will be useful to retinopathy diagnosis and neuroscience research.

Low-Loss Coupling of Quantum Cascade Lasers into Hollow-Core Waveguides with Single-Mode Output in the 3.7–7.6 μm Spectral Range

PubMed Central

Patimisco, Pietro; Sampaolo, Angelo; Mihai, Laura; Giglio, Marilena; Kriesel, Jason; Sporea, Dan; Scamarcio, Gaetano; Tittel, Frank K.; Spagnolo, Vincenzo

2016-01-01

We demonstrated low-loss and single-mode laser beam delivery through hollow-core waveguides (HCWs) operating in the 3.7–7.6 μm spectral range. The employed HCWs have a circular cross section with a bore diameter of 200 μm and metallic/dielectric internal coatings deposited inside a glass capillary tube. The internal coatings have been produced to enhance the spectral response of the HCWs in the range 3.5–12 µm. We demonstrated Gaussian-like outputs throughout the 4.5–7.6 µm spectral range. A quasi single-mode output beam with only small beam distortions was achieved when the wavelength was reduced to 3.7 μm. With a 15-cm-long HCW and optimized coupling conditions, we measured coupling efficiencies of >88% and transmission losses of <1 dB in the investigated infrared spectral range. PMID:27089343

Spectral Demultiplexing in Holographic and Fluorescent On-chip Microscopy

NASA Astrophysics Data System (ADS)

Sencan, Ikbal; Coskun, Ahmet F.; Sikora, Uzair; Ozcan, Aydogan

2014-01-01

Lensfree on-chip imaging and sensing platforms provide compact and cost-effective designs for various telemedicine and lab-on-a-chip applications. In this work, we demonstrate computational solutions for some of the challenges associated with (i) the use of broadband, partially-coherent illumination sources for on-chip holographic imaging, and (ii) multicolor detection for lensfree fluorescent on-chip microscopy. Specifically, we introduce spectral demultiplexing approaches that aim to digitally narrow the spectral content of broadband illumination sources (such as wide-band light emitting diodes or even sunlight) to improve spatial resolution in holographic on-chip microscopy. We also demonstrate the application of such spectral demultiplexing approaches for wide-field imaging of multicolor fluorescent objects on a chip. These computational approaches can be used to replace e.g., thin-film interference filters, gratings or other optical components used for spectral multiplexing/demultiplexing, which can form a desirable solution for cost-effective and compact wide-field microscopy and sensing needs on a chip.

Multi-spectral confocal microendoscope for in-vivo imaging

NASA Astrophysics Data System (ADS)

Rouse, Andrew Robert

The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

Gauge invariant spectral Cauchy characteristic extraction

NASA Astrophysics Data System (ADS)

Handmer, Casey J.; Szilágyi, Béla; Winicour, Jeffrey

2015-12-01

We present gauge invariant spectral Cauchy characteristic extraction. We compare gravitational waveforms extracted from a head-on black hole merger simulated in two different gauges by two different codes. We show rapid convergence, demonstrating both gauge invariance of the extraction algorithm and consistency between the legacy Pitt null code and the much faster spectral Einstein code (SpEC).

Spectral Domain RF Fingerprinting for 802.11 Wireless Devices

DTIC Science & Technology

2010-03-01

induce unintentional modulation effects . If these effects (features) are sufficiently unique, it becomes possible to identify a device us- ing its...Previous AFIT research has demonstrated the effectiveness of RF Fin- gerprinting using 802.11A signals with 1) spectral correlation on Power Spectral...32 4.5. SD Intra-manufacturer Classification: Effects of Burst Location Error

ALA-mediated PDT of melanoma tumors: light-sensitizer interactions determined by a novel spectral imaging system

NASA Astrophysics Data System (ADS)

Malik, Zvi; Dishi, M.

1995-05-01

The subcellular localization of endogenous protoporphyrin (endo- PP) during photosensitization in B-16 melanoma cells was analyzed by a novel spectral imaging system, the SpectraCube 1000. The melanoma cells were incubated with 5-aminolevulinic acid (ALA), and then the fluorescence of endo-PP was recorded in individual living cells by three modes: conventional fluorescence imaging, multipixel point by point fluorescence spectroscopy, and image processing, by operating a function of spectral similarity mapping and reconstructing new images derived from spectral information. The fluorescence image of ALA-treated cells revealed vesicular distribution of endo-PP all over the cytosol, with mitochondrial, lysosomal, as well as endoplasmic reticulum cisternael accumulation. Two main spectral fluorescence peaks were demonstrated at 635 and 705 nm, with intensities that differed from one subcellular site to another. Photoirradiation of the cells included point-specific subcellular fluorescence spectrum changes and demonstrated photoproduct formation. Spectral image reconstruction revealed the local distribution of a chosen spectrum in the photosensitized cells. On the other hand, B 16 cells treated with exogenous protoporphyrin (exo-PP) showed a dominant fluorescence peak at 670 nm and a minor peak at 630 nm. Fluorescence was localized at a perinuclear=Golgi region. Light exposure induced photobleaching and photoproduct-spectral changes followed by relocalization. The new localization at subcellular compartments showed pH dependent spectral shifts and photoproduct formation on a subcellular level.

Spectral Reconstruction for Obtaining Virtual Hyperspectral Images

NASA Astrophysics Data System (ADS)

Perez, G. J. P.; Castro, E. C.

2016-12-01

Hyperspectral sensors demonstrated its capabalities in identifying materials and detecting processes in a satellite scene. However, availability of hyperspectral images are limited due to the high development cost of these sensors. Currently, most of the readily available data are from multi-spectral instruments. Spectral reconstruction is an alternative method to address the need for hyperspectral information. The spectral reconstruction technique has been shown to provide a quick and accurate detection of defects in an integrated circuit, recovers damaged parts of frescoes, and it also aids in converting a microscope into an imaging spectrometer. By using several spectral bands together with a spectral library, a spectrum acquired by a sensor can be expressed as a linear superposition of elementary signals. In this study, spectral reconstruction is used to estimate the spectra of different surfaces imaged by Landsat 8. Four atmospherically corrected surface reflectance from three visible bands (499 nm, 585 nm, 670 nm) and one near-infrared band (872 nm) of Landsat 8, and a spectral library of ground elements acquired from the United States Geological Survey (USGS) are used. The spectral library is limited to 420-1020 nm spectral range, and is interpolated at one nanometer resolution. Singular Value Decomposition (SVD) is used to calculate the basis spectra, which are then applied to reconstruct the spectrum. The spectral reconstruction is applied for test cases within the library consisting of vegetation communities. This technique was successful in reconstructing a hyperspectral signal with error of less than 12% for most of the test cases. Hence, this study demonstrated the potential of simulating information at any desired wavelength, creating a virtual hyperspectral sensor without the need for additional satellite bands.

GRAFT-VERSUS-HOST DISEASE PANUVEITIS AND BILATERAL SEROUS DETACHMENTS: MULTIMODAL IMAGING ANALYSIS.

PubMed

Jung, Jesse J; Chen, Michael H; Rofagha, Soraya; Lee, Scott S

2017-01-01

To report the multimodal imaging findings and follow-up of a case of graft-versus-host disease-induced bilateral panuveitis and serous retinal detachments after allogenic bone marrow transplant for acute myeloid leukemia. A 75-year-old black man presented with acute decreased vision in both eyes for 1 week. Clinical examination and multimodal imaging, including spectral domain optical coherence tomography, fundus autofluorescence, fluorescein angiography, and swept-source optical coherence tomography angiography (Investigational Device; Carl Zeiss Meditec Inc) were performed. Clinical examination of the patient revealed anterior and posterior inflammation and bilateral serous retinal detachments. Ultra-widefield fundus autofluorescence demonstrated hyperautofluorescence secondary to subretinal fluid; and fluorescein angiography revealed multiple areas of punctate hyperfluorescence, leakage, and staining of the optic discs. Spectral domain and enhanced depth imaging optical coherence tomography demonstrated subretinal fluid, a thickened, undulating retinal pigment epithelium layer, and a thickened choroid in both eyes. En-face swept-source optical coherence tomography angiography did not show any retinal vascular abnormalities but did demonstrate patchy areas of decreased choriocapillaris flow. An extensive systemic infectious and malignancy workup was negative and the patient was treated with high-dose oral prednisone immunosuppression. Subsequent 6-month follow-up demonstrated complete resolution of the inflammation and bilateral serous detachments after completion of the prednisone taper over a 3-month period. Graft-versus-host disease panuveitis and bilateral serous retinal detachments are rare complications of allogenic bone marrow transplant for acute myeloid leukemia and can be diagnosed with clinical and multimodal imaging analysis. This form of autoimmune inflammation may occur after the recovery of T-cell activity within the donor graft targeting the host. Infectious and recurrent malignancy must be ruled out before initiation of immunosuppression, which can affectively treat this form of graft-versus-host disease.

Bandwidth-variable tunable optical filter unit for illumination and spectral imaging systems using thin-film optical band-pass filters.

PubMed

Hennig, Georg; Brittenham, Gary M; Sroka, Ronald; Kniebühler, Gesa; Vogeser, Michael; Stepp, Herbert

2013-04-01

An optical filter unit is demonstrated, which uses two successively arranged tunable thin-film optical band-pass filters and allows for simultaneous adjustment of the central wavelength in the spectral range 522-555 nm and of the spectral bandwidth in the range 3-16 nm with a wavelength switching time of 8 ms∕nm. Different spectral filter combinations can cover the complete visible spectral range. The transmitted intensity was found to decrease only linearly with the spectral bandwidth for bandwidths >6 nm, allowing a high maximum transmission efficiency of >75%. The image of a fiber bundle was spectrally filtered and analyzed in terms of position-dependency of the transmitted bandwidth and central wavelength.

Characterizing Non-Resolved Debris Through Spectral and Photometric Ground-Based Telescopic Data: What Can Laboratory Ground-truth Data Do for You?

NASA Technical Reports Server (NTRS)

Lederer, Susan

2017-01-01

NASA's ODPO has recently collected data of unresolved objects at GEO with the 3.8m UKIRT infrared telescope on Mauna Kea and the 1.3m MCAT visible telescope on Ascension Island. Analyses of SWIR data of rocket bodies and HS-376 solar-panel covered buses demonstrate the uniqueness of spectral signatures. Data of 3 classes of rocket bodies show similarities amongst a given class, but distinct differences from one class to another, suggesting that infrared reflectance spectra could effectively be used toward characterizing and constraining potential parent bodies of uncorrelated targets (UCTs). The Optical Measurements Center (OMC) at NASA JSC is designed to collect photometric signatures in the laboratory that can be used for comparison with telescopic data. NASA also has a spectral database of spacecraft materials for use with spectral unmixing models. Spectral unmixing of the HS-376 bus data demonstrates how absorption features and slopes can be used to constrain material characteristics of debris. Broadband photometry likewise can be compared with MCAT data of non-resolved debris images. Similar studies have been applied to IDCSP satellites to demonstrate how color-color photometry can be compared with lab data to constrain bulk materials signatures of spacecraft and debris.

Processing and analysis of commercial satellite image data of the nuclear accident near Chernobyl, U.S.S.R.

USGS Publications Warehouse

Sadowski, Franklin G.; Covington, Steven J.

1987-01-01

Advanced digital processing techniques were applied to Landsat-5 Thematic Mapper (TM) data and SPOT highresolution visible (HRV) panchromatic data to maximize the utility of images of a nuclear powerplant emergency at Chernobyl in the Soviet Ukraine. The images demonstrate the unique interpretive capabilities provided by the numerous spectral bands of the Thematic Mapper and the high spatial resolution of the SPOT HRV sensor.

GaAs homojunction solar cell development

NASA Technical Reports Server (NTRS)

Flood, D. J.; Swartz, C. K.; Hart, R. E., Jr.

1980-01-01

The Lincoln Laboratory n(+)/p/p(+) GaAs shallow homojunction cell structure was successfully demonstrated on 2 by 2 cm GaAs substrates. Air mass zero efficiencies of the seven cells produced to date range from 13.6 to 15.6 percent. Current voltage (I-V) characteristics, spectral response, and measurements were made on all seven cells. Preliminary analysis of 1 MeV electron radiation damage data indicate excellent radiation resistance for these cells.

Avian reflex and electroencephalogram responses in different states of consciousness.

PubMed

Sandercock, Dale A; Auckburally, Adam; Flaherty, Derek; Sandilands, Victoria; McKeegan, Dorothy E F

2014-06-22

Defining states of clinical consciousness in animals is important in veterinary anaesthesia and in studies of euthanasia and welfare assessment at slaughter. The aim of this study was to validate readily observable reflex responses in relation to different conscious states, as confirmed by EEG analysis, in two species of birds under laboratory conditions (35-week-old layer hens (n=12) and 11-week-old turkeys (n=10)). We evaluated clinical reflexes and characterised electroencephalograph (EEG) activity (as a measure of brain function) using spectral analyses in four different clinical states of consciousness: conscious (fully awake), semi-conscious (sedated), unconscious-optimal (general anaesthesia), unconscious-sub optimal (deep hypnotic state), as well as assessment immediately following euthanasia. Jaw or neck muscle tone was the most reliable reflex measure distinguishing between conscious and unconscious states. Pupillary reflex was consistently observed until respiratory arrest. Nictitating membrane reflex persisted for a short time (<1 min) after respiratory arrest and brain death (isoelectric EEG). The results confirm that the nictitating membrane reflex is a conservative measure of death in poultry. Using spectral analyses of the EEG waveforms it was possible to readily distinguish between the different states of clinical consciousness. In all cases, when birds progressed from a conscious to unconscious state; total spectral power (PTOT) significantly increased, whereas median (F50) and spectral edge (F95) frequencies significantly decreased. This study demonstrates that EEG analysis can differentiate between clinical states (and loss of brain function at death) in birds and provides a unique integration of reflex responses and EEG activity. Copyright © 2014 Elsevier Inc. All rights reserved.

Different event-related patterns of gamma-band power in brain waves of fast- and slow-reacting subjects.

PubMed Central

Jokeit, H; Makeig, S

1994-01-01

Fast- and slow-reacting subjects exhibit different patterns of gamma-band electroencephalogram (EEG) activity when responding as quickly as possible to auditory stimuli. This result appears to confirm long-standing speculations of Wundt that fast- and slow-reacting subjects produce speeded reactions in different ways and demonstrates that analysis of event-related changes in the amplitude of EEG activity recorded from the human scalp can reveal information about event-related brain processes unavailable using event-related potential measures. Time-varying spectral power in a selected (35- to 43-Hz) gamma frequency band was averaged across trials in two experimental conditions: passive listening and speeded reacting to binaural clicks, forming 40-Hz event-related spectral responses. Factor analysis of between-subject event-related spectral response differences split subjects into two near-equal groups composed of faster- and slower-reacting subjects. In faster-reacting subjects, 40-Hz power peaked near 200 ms and 400 ms poststimulus in the react condition, whereas in slower-reacting subjects, 40-Hz power just before stimulus delivery was larger in the react condition. These group differences were preserved in separate averages of relatively long and short reaction-time epochs for each group. gamma-band (20-60 Hz)-filtered event-related potential response averages did not differ between the two groups or conditions. Because of this and because gamma-band power in the auditory event-related potential is small compared with the EEG, the observed event-related spectral response features must represent gamma-band EEG activity reliably induced by, but not phase-locked to, experimental stimuli or events. PMID:8022783

Spectral analysis using the CCD Chirp Z-transform

NASA Technical Reports Server (NTRS)

Eversole, W. L.; Mayer, D. J.; Bosshart, P. W.; Dewit, M.; Howes, C. R.; Buss, D. D.

1978-01-01

The charge coupled device (CCD) Chirp Z transformation (CZT) spectral analysis techniques were reviewed and results on state-of-the-art CCD CZT technology are presented. The CZT algorithm was examined and the advantages of CCD implementation are discussed. The sliding CZT which is useful in many spectral analysis applications is described, and the performance limitations of the CZT are studied.

Standoff detection of turbulent chemical mixture plumes using a swept external cavity quantum cascade laser

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Mark C.; Brumfield, Brian E.

We demonstrate standoff detection of turbulent mixed-chemical plumes using a broadly-tunable external cavity quantum cascade laser (ECQCL). The ECQCL was directed through plumes of mixed methanol/ethanol vapor to a partially-reflective surface located 10 m away. The reflected power was measured as the ECQCL was swept over its tuning range of 930-1065 cm-1 (9.4-10.8 µm) at rates up to 200 Hz. Analysis of the transmission spectra though the plume was performed to determine chemical concentrations with time resolution of 0.005 s. Comparison of multiple spectral sweep rates of 2 Hz, 20 Hz, and 200 Hz shows that higher sweep rates reducemore » effects of atmospheric and source turbulence, resulting in lower detection noise and more accurate measurement of the rapidly-changing chemical concentrations. Detection sensitivities of 0.13 ppm*m for MeOH and 1.2 ppm*m for EtOH are demonstrated for a 200 Hz spectral sweep rate, normalized to 1 s detection time.« less

Acoustic detection, tracking, and characterization of three tornadoes.

PubMed

Frazier, William Garth; Talmadge, Carrick; Park, Joseph; Waxler, Roger; Assink, Jelle

2014-04-01

Acoustic data recorded at 1000 samples per second by two sensor arrays located at ranges of 1-113 km from three tornadoes that occurred on 24 May 2011 in Oklahoma are analyzed. Accurate bearings to the tornadoes have been obtained using beamforming methods applied to the data at infrasonic frequencies. Beamforming was not viable at audio frequencies, but the data demonstrate the ability to detect significant changes in the shape of the estimated power spectral density in the band encompassing 10 Hz to approximately 100 Hz at distances of practical value from the sensors. This suggests that arrays of more closely spaced sensors might provide better bearing accuracy at practically useful distances from a tornado. Additionally, a mathematical model, based on established relationships of aeroacoustic turbulence, is demonstrated to provide good agreement to the estimated power spectra produced by the tornadoes at different times and distances from the sensors. The results of this analysis indicate that, qualitatively, an inverse relationship appears to exist between the frequency of an observed peak of the power spectral density and the reported tornado intensity.

Mononuclear Pd(II) complex as a new therapeutic agent: Synthesis, characterization, biological activity, spectral and DNA binding approaches

NASA Astrophysics Data System (ADS)

Saeidifar, Maryam; Mirzaei, Hamidreza; Ahmadi Nasab, Navid; Mansouri-Torshizi, Hassan

2017-11-01

The binding ability between a new water-soluble palladium(II) complex [Pd(bpy)(bez-dtc)]Cl (where bpy is 2,2‧-bipyridine and bez-dtc is benzyl dithiocarbamate), as an antitumor agent, and calf thymus DNA was evaluated using various physicochemical methods, such as UV-Vis absorption, Competitive fluorescence studies, viscosity measurement, zeta potential and circular dichroism (CD) spectroscopy. The Pd(II) complex was synthesized and characterized using elemental analysis, molar conductivity measurements, FT-IR, 1H NMR, 13C NMR and electronic spectra studies. The anticancer activity against HeLa cell lines demonstrated lower cytotoxicity than cisplatin. The binding constants and the thermodynamic parameters were determined at different temperatures (300 K, 310 K and 320 K) and shown that the complex can bind to DNA via electrostatic forces. Furthermore, this result was confirmed by the viscosity and zeta potential measurements. The CD spectral results demonstrated that the binding of Pd(II) complex to DNA induced conformational changes in DNA. We hope that these results will provide a basis for further studies and practical clinical use of anticancer drugs.

Fast ultra-wideband microwave spectral scanning utilizing photonic wavelength- and time-division multiplexing.

PubMed

Li, Yihan; Kuse, Naoya; Fermann, Martin

2017-08-07

A high-speed ultra-wideband microwave spectral scanning system is proposed and experimentally demonstrated. Utilizing coherent dual electro-optical frequency combs and a recirculating optical frequency shifter, the proposed system realizes wavelength- and time-division multiplexing at the same time, offering flexibility between scan speed and size, weight and power requirements (SWaP). High-speed spectral scanning spanning from ~1 to 8 GHz with ~1.2 MHz spectral resolution is achieved experimentally within 14 µs. The system can be easily scaled to higher bandwidth coverage, faster scanning speed or finer spectral resolution with suitable hardware.

Coded aperture coherent scatter spectral imaging for assessment of breast cancers: an ex-vivo demonstration

NASA Astrophysics Data System (ADS)

Spencer, James R.; Carter, Joshua E.; Leung, Crystal K.; McCall, Shannon J.; Greenberg, Joel A.; Kapadia, Anuj J.

2017-03-01

A Coded Aperture Coherent Scatter Spectral Imaging (CACSSI) system was developed in our group to differentiate cancer and healthy tissue in the breast. The utility of the experimental system was previously demonstrated using anthropomorphic breast phantoms and breast biopsy specimens. Here we demonstrate CACSSI utility in identifying tumor margins in real time using breast lumpectomy specimens. Fresh lumpectomy specimens were obtained from Surgical Pathology with the suspected cancerous area designated on the specimen. The specimens were scanned using CACSSI to obtain spectral scatter signatures at multiple locations within the tumor and surrounding tissue. The spectral reconstructions were matched with literature form-factors to classify the tissue as cancerous or non-cancerous. The findings were then compared against pathology reports to confirm the presence and location of the tumor. The system was found to be capable of consistently differentiating cancerous and healthy regions in the breast with spatial resolution of 5 mm. Tissue classification results from the scanned specimens could be correlated with pathology results. We now aim to develop CACSSI as a clinical imaging tool to aid breast cancer assessment and other diagnostic purposes.

Analysis of the Characteristics of Inertia-Gravity Waves during an Orographic Precipitation Event

NASA Astrophysics Data System (ADS)

Liu, Lu; Ran, Lingkun; Gao, Shouting

2018-05-01

A numerical experiment was performed using the Weather Research and Forecasting (WRF) model to analyze the generation and propagation of inertia-gravity waves during an orographic rainstorm that occurred in the Sichuan area on 17 August 2014. To examine the spatial and temporal structures of the inertia-gravity waves and identify the wave types, three wavenumber-frequency spectral analysis methods (Fourier analysis, cross-spectral analysis, and wavelet cross-spectrum analysis) were applied. During the storm, inertia-gravity waves appeared at heights of 10-14 km, with periods of 80-100 min and wavelengths of 40-50 km. These waves were generated over a mountain and propagated eastward at an average speed of 15-20 m s-1. Meanwhile, comparison between the reconstructed inertia-gravity waves and accumulated precipitation showed there was a mutual promotion process between them. The Richardson number and Scorer parameter were used to demonstrate that the eastward-moving inertia-gravity waves were trapped in an effective atmospheric ducting zone with favorable reflector and critical level conditions, which were the primary causes of the long lives of the waves. Finally, numerical experiments to test the sensitivity to terrain and diabatic heating were conducted, and the results suggested a cooperative effect of terrain and diabatic heating contributed to the propagation and enhancement of the waves.

A novel analysis method for near infrared spectroscopy based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Yang, Hongyu; Liu, Yun; Ruan, Zongcai; Luo, Qingming; Gong, Hui; Lu, Zuhong

2007-05-01

Near Infrared Imager (NIRI) has been widely used to access the brain functional activity non-invasively. We use a portable, multi-channel and continuous-wave NIR topography instrument to measure the concentration changes of each hemoglobin species and map cerebral cortex functional activation. By extracting some essential features from the BOLD signals, optical tomography is able to be a new way of neuropsychological studies. Fourier spectral analysis provides a common framework for examining the distribution of global energy in the frequency domain. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. The hemoglobin species concentration changes are of such kind. In this work we develop a new signal processing method using Hilbert-Huang transform to perform spectral analysis of the functional NIRI signals. Compared with wavelet based multi-resolution analysis (MRA), we demonstrated the extraction of task related signal for observation of activation in the prefrontal cortex (PFC) in vision stimulation experiment. This method provides a new analysis tool for functional NIRI signals. Our experimental results show that the proposed approach provides the unique method for reconstructing target signal without losing original information and enables us to understand the episode of functional NIRI more precisely.

Spectral analysis of variable-length coded digital signals

NASA Astrophysics Data System (ADS)

Cariolaro, G. L.; Pierobon, G. L.; Pupolin, S. G.

1982-05-01

A spectral analysis is conducted for a variable-length word sequence by an encoder driven by a stationary memoryless source. A finite-state sequential machine is considered as a model of the line encoder, and the spectral analysis of the encoded message is performed under the assumption that the sourceword sequence is composed of independent identically distributed words. Closed form expressions for both the continuous and discrete parts of the spectral density are derived in terms of the encoder law and sourceword statistics. The jump part exhibits jumps at multiple integers of per lambda(sub 0)T, where lambda(sub 0) is the greatest common divisor of the possible codeword lengths, and T is the symbol period. The derivation of the continuous part can be conveniently factorized, and the theory is applied to the spectral analysis of BnZS and HDBn codes.

Short communication: Suitability of fluorescence spectroscopy for characterization of commercial milk of different composition and origin.

PubMed

Ntakatsane, M P; Yang, X Q; Lin, M; Liu, X M; Zhou, P

2011-11-01

Thirteen milk brands comprising 76 pasteurized and UHT milk samples of various compositions (whole, reduced fat, skimmed, low lactose, and high protein) were obtained from local supermarkets, and milk samples manufactured in various countries were discriminated using front-face fluorescence spectroscopy (FFFS) coupled with chemometric tools. The emission spectra of Maillard reaction products and riboflavin (MRP/RF; 400 to 600 nm) and tryptophan (300 to 400 nm) were recorded using FFFS, and the excitation wavelengths were set at 360 nm for MRP/RF and 290 nm for tryptophan. Principal component analysis (PCA) was applied to analyze the normalized spectra. The PCA of spectral information from MRP/RF discriminated the milk samples originating in different countries, and PCA of spectral information from tryptophan discriminated the samples according to composition. The fluorescence spectral data were compared with liquid chromatography-mass spectrometry results for the glycation extent of the milk samples, and a positive association (R(2)=0.84) was found between the degree of glycation of α-lactalbumin and the MRP/RF spectral data. This study demonstrates the ability and sensitivity of FFFS to rapidly discriminate and classify commercial milk with various compositions and processing conditions. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The central star candidate of the planetary nebula Sh2-71: photometric and spectroscopic variability

NASA Astrophysics Data System (ADS)

Močnik, T.; Lloyd, M.; Pollacco, D.; Street, R. A.

2015-07-01

We present the analysis of several newly obtained and archived photometric and spectroscopic data sets of the intriguing and yet poorly understood 13.5 mag central star candidate of the bipolar planetary nebula Sh2-71. Photometric observations confirmed the previously determined quasi-sinusoidal light curve with a period of 68 d and also indicated periodic sharp brightness dips, possibly eclipses, with a period of 17.2 d. In addition, the comparison between U and V light curves revealed that the 68 d brightness variations are accompanied by a variable reddening effect of ΔE(U - V) = 0.38. Spectroscopic data sets demonstrated pronounced variations in spectral profiles of Balmer, helium and singly ionized metal lines and indicated that these variations occur on a time-scale of a few days. The most accurate verification to date revealed that spectral variability is not correlated with the 68 d brightness variations. The mean radial velocity of the observed star was measured to be ˜26 km s-1 with an amplitude of ±40 km s-1. The spectral type was determined to be B8V through spectral comparison with synthetic and standard spectra. The newly proposed model for the central star candidate is a Be binary with a misaligned precessing disc.

Hyper-Spectral Image Analysis With Partially Latent Regression and Spatial Markov Dependencies

NASA Astrophysics Data System (ADS)

Deleforge, Antoine; Forbes, Florence; Ba, Sileye; Horaud, Radu

2015-09-01

Hyper-spectral data can be analyzed to recover physical properties at large planetary scales. This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between physical parameters and spectra has been established in a data-driven fashion, the learned relationship can be used to estimate physical parameters for new hyper-spectral observations. Within this framework, we propose a spatially-constrained and partially-latent regression method which maps high-dimensional inputs (hyper-spectral images) onto low-dimensional responses (physical parameters such as the local chemical composition of the soil). The proposed regression model comprises two key features. Firstly, it combines a Gaussian mixture of locally-linear mappings (GLLiM) with a partially-latent response model. While the former makes high-dimensional regression tractable, the latter enables to deal with physical parameters that cannot be observed or, more generally, with data contaminated by experimental artifacts that cannot be explained with noise models. Secondly, spatial constraints are introduced in the model through a Markov random field (MRF) prior which provides a spatial structure to the Gaussian-mixture hidden variables. Experiments conducted on a database composed of remotely sensed observations collected from the Mars planet by the Mars Express orbiter demonstrate the effectiveness of the proposed model.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

TESTING RELATIVISTIC REFLECTION AND RESOLVING OUTFLOWS IN PG 1211+143 WITH XMM-NEWTON AND NuSTAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lobban, A. P.; Pounds, K.; Vaughan, S.

We analyze the broad-band X-ray spectrum (0.3–50 keV) of the luminous Seyfert 1/quasar PG 1211+143—the archetypal source for high-velocity X-ray outflows—using near-simultaneous XMM-Newton and NuSTAR observations. We compare pure relativistic reflection models with a model including the strong imprint of photoionized emission and absorption from a high-velocity wind, finding a spectral fit that extrapolates well over the higher photon energies covered by NuSTAR . Inclusion of the high signal-to-noise ratio XMM-Newton spectrum provides much tighter constraints on the model parameters, with a much harder photon index/lower reflection fraction compared to that from the NuSTAR data alone. We show that puremore » relativistic reflection models are not able to account for the spectral complexity of PG 1211+143 and that wind absorption models are strongly required to match the data in both the soft X-ray and Fe K spectral regions. In confirming the significance of previously reported ionized absorption features, the new analysis provides a further demonstration of the power of combining the high throughput and resolution of long-look XMM-Newton observations with the unprecedented spectral coverage of NuSTAR .« less

Terrestrial hyperspectral image shadow restoration through fusion with terrestrial lidar

NASA Astrophysics Data System (ADS)

Hartzell, Preston J.; Glennie, Craig L.; Finnegan, David C.; Hauser, Darren L.

2017-05-01

Recent advances in remote sensing technology have expanded the acquisition and fusion of active lidar and passive hyperspectral imagery (HSI) from exclusively airborne observations to include terrestrial modalities. In contrast to airborne collection geometry, hyperspectral imagery captured from terrestrial cameras is prone to extensive solar shadowing on vertical surfaces leading to reductions in pixel classification accuracies or outright removal of shadowed areas from subsequent analysis tasks. We demonstrate the use of lidar spatial information for sub-pixel HSI shadow detection and the restoration of shadowed pixel spectra via empirical methods that utilize sunlit and shadowed pixels of similar material composition. We examine the effectiveness of radiometrically calibrated lidar intensity in identifying these similar materials in sun and shade conditions and further evaluate a restoration technique that leverages ratios derived from the overlapping lidar laser and HSI wavelengths. Simulations of multiple lidar wavelengths, i.e., multispectral lidar, indicate the potential for HSI spectral restoration that is independent of the complexity and costs associated with rigorous radiometric transfer models, which have yet to be developed for horizontal-viewing terrestrial HSI sensors. The spectral restoration performance of shadowed HSI pixels is quantified for imagery of a geologic outcrop through improvements in spectral shape, spectral scale, and HSI band correlation.

Three-dimensional arbitrary voxel shapes in spectroscopy with submillisecond TEs.

PubMed

Snyder, Jeff; Haas, Martin; Dragonu, Iulius; Hennig, Jürgen; Zaitsev, Maxim

2012-08-01

A novel spectroscopic method for submillisecond TEs and three-dimensional arbitrarily shaped voxels was developed and applied to phantom and in vivo measurements, with additional parallel excitation (PEX) implementation. A segmented spherical shell excitation trajectory was used in combination with appropriate radiofrequency weights for target selection in three dimensions. Measurements in a two-compartment phantom realized a TE of 955 µs, excellent spectral quality and comparable signal-to-noise ratios between accelerated (R = 2) and nonaccelerated modes. The two-compartment model allowed a comparison of the spectral suppression qualities of the method and, although outer volume signals were suppressed by factors of 1434 and 2246 compared with the theoretical unsuppressed case for the clinical and PEX modes, respectively, incomplete suppression of the outer volume (935 cm(3) compared with a target volume of 5.86 cm(3) ) resulted in a spectral contamination of 10.2% and 6.5% compared with the total signal. The method was also demonstrated in vivo in human brain on a clinical system at TE = 935 µs with good signal-to-noise ratio and spatial and spectral selection, and included LCModel relative quantification analysis. Eight metabolites showed significant fitting accuracy, including aspartate, N-acetylaspartylglutamate, glutathione and glutamate. Copyright © 2012 John Wiley & Sons, Ltd.

Effect of musical training on static and dynamic measures of spectral-pattern discrimination.

PubMed

Sheft, Stanley; Smayda, Kirsten; Shafiro, Valeriy; Maddox, W Todd; Chandrasekaran, Bharath

2013-06-01

Both behavioral and physiological studies have demonstrated enhanced processing of speech in challenging listening environments attributable to musical training. The relationship, however, of this benefit to auditory abilities as assessed by psychoacoustic measures remains unclear. Using tasks previously shown to relate to speech-in-noise perception, the present study evaluated discrimination ability for static and dynamic spectral patterns by 49 listeners grouped as either musicians or nonmusicians. The two static conditions measured the ability to detect a change in the phase of a logarithmic sinusoidal spectral ripple of wideband noise with ripple densities of 1.5 and 3.0 cycles per octave chosen to emphasize either timbre or pitch distinctions, respectively. The dynamic conditions assessed temporal-pattern discrimination of 1-kHz pure tones frequency modulated by different lowpass noise samples with thresholds estimated in terms of either stimulus duration or signal-to-noise ratio. Musicians performed significantly better than nonmusicians on all four tasks. Discriminant analysis showed that group membership was correctly predicted for 88% of the listeners with the structure coefficient of each measure greater than 0.51. Results suggest that enhanced processing of static and dynamic spectral patterns defined by low-rate modulation may contribute to the relationship between musical training and speech-in-noise perception. [Supported by NIH.].

Spectral classifying base on color of live corals and dead corals covered with algae

NASA Astrophysics Data System (ADS)

Nurdin, Nurjannah; Komatsu, Teruhisa; Barille, Laurent; Akbar, A. S. M.; Sawayama, Shuhei; Fitrah, Muh. Nur; Prasyad, Hermansyah

2016-05-01

Pigments in the host tissues of corals can make a significant contribution to their spectral signature and can affect their apparent color as perceived by a human observer. The aim of this study is classifying the spectral reflectance of corals base on different color. It is expected that they can be used as references in discriminating between live corals, dead coral covered with algae Spectral reflectance data was collected in three small islands, Spermonde Archipelago, Indonesia by using a hyperspectral radiometer underwater. First and second derivative analysis resolved the wavelength locations of dominant features contributing to reflectance in corals and support the distinct differences in spectra among colour existed. Spectral derivative analysis was used to determine the specific wavelength regions ideal for remote identification of substrate type. The analysis results shown that yellow, green, brown and violet live corals are spectrally separable from each other, but they are similar with dead coral covered with algae spectral.

Interference-free coherence dynamics of gas-phase molecules using spectral focusing.

PubMed

Wrzesinski, Paul J; Roy, Sukesh; Gord, James R

2012-10-08

Spectral focusing using broadband femtosecond pulses to achieve highly selective measurements has been employed for numerous applications in spectroscopy and microspectroscopy. In this work we highlight the use of spectral focusing for selective excitation and detection of gas-phase species. Furthermore, we demonstrate that spectral focusing, coupled with time-resolved measurements based upon probe delay, allows the observation of interference-free coherence dynamics of multiple molecules and gas-phase temperature making this technique ideal for gas-phase measurements of reacting flows and combustion processes.

Time-Spectral Rotorcraft Simulations on Overset Grids

NASA Technical Reports Server (NTRS)

Leffell, Joshua I.; Murman, Scott M.; Pulliam, Thomas H.

2014-01-01

The Time-Spectral method is derived as a Fourier collocation scheme and applied to NASA's overset Reynolds-averaged Navier-Stokes (RANS) solver OVERFLOW. The paper outlines the Time-Spectral OVERFLOWimplementation. Successful low-speed laminar plunging NACA 0012 airfoil simulations demonstrate the capability of the Time-Spectral method to resolve the highly-vortical wakes typical of more expensive three-dimensional rotorcraft configurations. Dealiasing, in the form of spectral vanishing viscosity (SVV), facilitates the convergence of Time-Spectral calculations of high-frequency flows. Finally, simulations of the isolated V-22 Osprey tiltrotor for both hover and forward (edgewise) flight validate the three-dimensional Time-Spectral OVERFLOW implementation. The Time-Spectral hover simulation matches the time-accurate calculation using a single harmonic. Significantly more temporal modes and SVV are required to accurately compute the forward flight case because of its more active, high-frequency wake.

Demonstration of spectral correlation control in a source of polarization-entangled photon pairs at telecom wavelength.

PubMed

Lutz, Thomas; Kolenderski, Piotr; Jennewein, Thomas

2014-03-15

Spectrally correlated photon pairs can be used to improve the performance of long-range fiber-based quantum communication protocols. We present a source based on spontaneous parametric downconversion, which allows one to control spectral correlations within the entangled photon pair without spectral filtering by changing the pump-pulse duration or the characteristics of the coupled spatial modes. The spectral correlations and polarization entanglement are characterized. We find that the generated photon pairs can feature both positive spectral correlations, decorrelation, or negative correlations at the same time as polarization entanglement with a high fidelity of 0.97 (no background subtraction) with the expected Bell state.

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

NASA Technical Reports Server (NTRS)

Figueroa-Vinas, Adolfo

2013-01-01

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Spectral methods for partial differential equations

NASA Technical Reports Server (NTRS)

Hussaini, M. Y.; Streett, C. L.; Zang, T. A.

1983-01-01

Origins of spectral methods, especially their relation to the Method of Weighted Residuals, are surveyed. Basic Fourier, Chebyshev, and Legendre spectral concepts are reviewed, and demonstrated through application to simple model problems. Both collocation and tau methods are considered. These techniques are then applied to a number of difficult, nonlinear problems of hyperbolic, parabolic, elliptic, and mixed type. Fluid dynamical applications are emphasized.

Advanced spectral processing of broadband light using acousto-optic devices with arbitrary transmission functions.

PubMed

Molchanov, Vladimir Ya; Yushkov, Konstantin B

2014-06-30

In the paper, we developed a dispersive method for transmission function synthesis of collinear and quasi-collinear acousto-optic tunable filters. General theoretical consideration was performed, and modelling was made for broadband and narrowband signals. Experimental results on spectral shaping of femtosecond laser emission were obtained. Binary spectral encoding of broadband emission was demonstrated.

Recent applications of spectral methods in fluid dynamics

NASA Technical Reports Server (NTRS)

Zang, T. A.; Hussaini, M. Y.

1985-01-01

Origins of spectral methods, especially their relation to the method of weighted residuals, are surveyed. Basic Fourier and Chebyshev spectral concepts are reviewed and demonstrated through application to simple model problems. Both collocation and tau methods are considered. These techniques are then applied to a number of difficult, nonlinear problems of hyperbolic, parabolic, elliptic and mixzed type. Fluid dynamical applications are emphasized.

Assessing FRET using Spectral Techniques

PubMed Central

Leavesley, Silas J.; Britain, Andrea L.; Cichon, Lauren K.; Nikolaev, Viacheslav O.; Rich, Thomas C.

2015-01-01

Förster resonance energy transfer (FRET) techniques have proven invaluable for probing the complex nature of protein–protein interactions, protein folding, and intracellular signaling events. These techniques have traditionally been implemented with the use of one or more fluorescence band-pass filters, either as fluorescence microscopy filter cubes, or as dichroic mirrors and band-pass filters in flow cytometry. In addition, new approaches for measuring FRET, such as fluorescence lifetime and acceptor photobleaching, have been developed. Hyperspectral techniques for imaging and flow cytometry have also shown to be promising for performing FRET measurements. In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral unmixing with a correction for direct acceptor excitation. All methods are estimates of FRET efficiency, except for one-filter set and three-filter set FRET indices, which are included for consistency with prior literature. In the first part of this study, spectrofluorimetric data were collected from a CFP–Epac–YFP FRET probe that has been used for intracellular cAMP measurements. All comparisons were performed using the same spectrofluorimetric datasets as input data, to provide a relevant comparison. Linear spectral unmixing resulted in measurements with the lowest coefficient of variation (0.10) as well as accurate fits using the Hill equation. FRET efficiency methods produced coefficients of variation of less than 0.20, while FRET indices produced coefficients of variation greater than 8.00. These results demonstrate that spectral FRET measurements provide improved response over standard, filter-based measurements. Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. Results from these studies confirmed that spectral imaging is effective for measuring subcellular, time-dependent FRET dynamics and that additional fluorescent signals can be readily separated from FRET signals, enabling multilabel studies of molecular interactions. PMID:23929684

Assessing FRET using spectral techniques.

PubMed

Leavesley, Silas J; Britain, Andrea L; Cichon, Lauren K; Nikolaev, Viacheslav O; Rich, Thomas C

2013-10-01

Förster resonance energy transfer (FRET) techniques have proven invaluable for probing the complex nature of protein-protein interactions, protein folding, and intracellular signaling events. These techniques have traditionally been implemented with the use of one or more fluorescence band-pass filters, either as fluorescence microscopy filter cubes, or as dichroic mirrors and band-pass filters in flow cytometry. In addition, new approaches for measuring FRET, such as fluorescence lifetime and acceptor photobleaching, have been developed. Hyperspectral techniques for imaging and flow cytometry have also shown to be promising for performing FRET measurements. In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral unmixing with a correction for direct acceptor excitation. All methods are estimates of FRET efficiency, except for one-filter set and three-filter set FRET indices, which are included for consistency with prior literature. In the first part of this study, spectrofluorimetric data were collected from a CFP-Epac-YFP FRET probe that has been used for intracellular cAMP measurements. All comparisons were performed using the same spectrofluorimetric datasets as input data, to provide a relevant comparison. Linear spectral unmixing resulted in measurements with the lowest coefficient of variation (0.10) as well as accurate fits using the Hill equation. FRET efficiency methods produced coefficients of variation of less than 0.20, while FRET indices produced coefficients of variation greater than 8.00. These results demonstrate that spectral FRET measurements provide improved response over standard, filter-based measurements. Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. Results from these studies confirmed that spectral imaging is effective for measuring subcellular, time-dependent FRET dynamics and that additional fluorescent signals can be readily separated from FRET signals, enabling multilabel studies of molecular interactions. © 2013 International Society for Advancement of Cytometry. Copyright © 2013 International Society for Advancement of Cytometry.

Demonstrating the limitations of line ratio temperature diagnostic using Fe X and Fe XIV spectral line intensity observations

NASA Technical Reports Server (NTRS)

Brickhouse, Nancy; Esser, Ruth; Habbal, Shadia R.

1995-01-01

The electron temperature in the inner corona can be derived from spectral line intensity measurements by comparing the ratio of the measured intensities of two spectral lines to the ratio calculated from theoretical models. In a homogeneous plasma the line ratio technique can be used for any two lines if the ratio of the intensities is independent of the density. The corona, however, is far from homogeneous. Even large coronal holes present at the solar poles at solar minimum can be partly or completely obscured by emission from hotter and denser surrounding regions. In this paper we investigate the effect of these surrounding regions on coronal hole temperatures. using daily intensity measurements at 1.15 Rs of the Fe XIV 5303 A and Fe X 6374 A spectral lines carried out at the National Solar Observatory at Sacramento Peak. We show that the temperatures derived using the line ratio technique for these two spectral lines can vary by more than 0.8 x 10(exp 6) K due to the contribution from surrounding regions. This example demonstrates the inadequacy of spectral lines with widely separate peak temperatures for temperature diagnostic.

Field Measured Spectral Albedo-Four Years of Data from the Western U.S. Prairie

NASA Astrophysics Data System (ADS)

Michalsky, Joseph J.; Hodges, Gary B.

2013-01-01

This paper presents an initial look at four years of spectral measurements used to calculate albedo for the Colorado prairie just east of the Rocky Mountain range foothills. Some issues associated with calculating broadband albedo from thermopile sensors are discussed demonstrating that uncorrected instrument issues have led to incorrect conclusions. Normalized Difference Vegetative Index (NDVI) is defined for the spectral instruments in this study and used to demonstrate the dramatic changes that can be monitored with this very sensitive product. Examples of albedo wavelength and solar-zenith angle dependence for different stages of vegetative growth and senescence are presented. The spectral albedo of fresh snow and its spectral and solar-zenith angle dependence are discussed and contrasted with other studies of these dependencies. We conclude that fresh snow is consistent with a Lambertian reflector over the solar incidence angles measured; this is contrary to most snow albedo results. Even a slope of a degree or two in the viewed surface can explain the asymmetry in the morning and afternoon albedos for snow and vegetation. Plans for extending these spectral measurements for albedo to longer wavelengths and to additional sites are described.

Detection of contamination on selected apple cultivars using reflectance hyperspectral and multispectral analysis

NASA Astrophysics Data System (ADS)

Mehl, Patrick M.; Chao, Kevin; Kim, Moon S.; Chen, Yud-Ren

2001-03-01

Presence of natural or exogenous contaminations on apple cultivars is a food safety and quality concern touching the general public and strongly affecting this commodity market. Accumulations of human pathogens are usually observed on surface lesions of commodities. Detections of either lesions or directly of the pathogens are essential for assuring the quality and safety of commodities. We are presenting the application of hyperspectral image analysis towards the development of multispectral techniques for the detection of defects on chosen apple cultivars, such as Golden Delicious, Red Delicious, and Gala apples. Separate apple cultivars possess different spectral characteristics leading to different approaches for analysis. General preprocessing analysis with morphological treatments is followed by different image treatments and condition analysis for highlighting lesions and contaminations on the apple cultivars. Good isolations of scabs, fungal and soil contaminations and bruises are observed with hyperspectral imaging processing either using principal component analysis or utilizing the chlorophyll absorption peak. Applications of hyperspectral results to a multispectral detection are limited by the spectral capabilities of our RGB camera using either specific band pass filters and using direct neutral filters. Good separations of defects are obtained for Golden Delicious apples. It is however limited for the other cultivars. Having an extra near infrared channel will increase the detection level utilizing the chlorophyll absorption band for detection as demonstrated by the present hyperspectral imaging analysis

Scaling dimensions in spectroscopy of soil and vegetation

NASA Astrophysics Data System (ADS)

Malenovský, Zbyněk; Bartholomeus, Harm M.; Acerbi-Junior, Fausto W.; Schopfer, Jürg T.; Painter, Thomas H.; Epema, Gerrit F.; Bregt, Arnold K.

2007-05-01

The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote sensing techniques are reviewed: (1) radiative transfer, (2) spectral (un)mixing, and (3) data fusion. Relevant case studies are given in the context of their up- and/or down-scaling abilities over the soil/vegetation surfaces and a multi-source approach is proposed for their integration. Radiative transfer (RT) models are described to show their capacity for spatial, spectral up-scaling, and directional down-scaling within a heterogeneous environment. Spectral information and spectral derivatives, like vegetation indices (e.g. TCARI/OSAVI), can be scaled and even tested by their means. Radiative transfer of an experimental Norway spruce ( Picea abies (L.) Karst.) research plot in the Czech Republic was simulated by the Discrete Anisotropic Radiative Transfer (DART) model to prove relevance of the correct object optical properties scaled up to image data at two different spatial resolutions. Interconnection of the successive modelling levels in vegetation is shown. A future development in measurement and simulation of the leaf directional spectral properties is discussed. We describe linear and/or non-linear spectral mixing techniques and unmixing methods that demonstrate spatial down-scaling. Relevance of proper selection or acquisition of the spectral endmembers using spectral libraries, field measurements, and pure pixels of the hyperspectral image is highlighted. An extensive list of advanced unmixing techniques, a particular example of unmixing a reflective optics system imaging spectrometer (ROSIS) image from Spain, and examples of other mixture applications give insight into the present status of scaling capabilities. Simultaneous spatial and temporal down-scaling by means of a data fusion technique is described. A demonstrative example is given for the moderate resolution imaging spectroradiometer (MODIS) and LANDSAT Thematic Mapper (TM) data from Brazil. Corresponding spectral bands of both sensors were fused via a pyramidal wavelet transform in Fourier space. New spectral and temporal information of the resultant image can be used for thematic classification or qualitative mapping. All three described scaling techniques can be integrated as the relevant methodological steps within a complex multi-source approach. We present this concept of combining numerous optical remote sensing data and methods to generate inputs for ecosystem process models.

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1992-01-01

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

Hierarchical Processing of Auditory Objects in Humans

PubMed Central

Kumar, Sukhbinder; Stephan, Klaas E; Warren, Jason D; Friston, Karl J; Griffiths, Timothy D

2007-01-01

This work examines the computational architecture used by the brain during the analysis of the spectral envelope of sounds, an important acoustic feature for defining auditory objects. Dynamic causal modelling and Bayesian model selection were used to evaluate a family of 16 network models explaining functional magnetic resonance imaging responses in the right temporal lobe during spectral envelope analysis. The models encode different hypotheses about the effective connectivity between Heschl's Gyrus (HG), containing the primary auditory cortex, planum temporale (PT), and superior temporal sulcus (STS), and the modulation of that coupling during spectral envelope analysis. In particular, we aimed to determine whether information processing during spectral envelope analysis takes place in a serial or parallel fashion. The analysis provides strong support for a serial architecture with connections from HG to PT and from PT to STS and an increase of the HG to PT connection during spectral envelope analysis. The work supports a computational model of auditory object processing, based on the abstraction of spectro-temporal “templates” in the PT before further analysis of the abstracted form in anterior temporal lobe areas. PMID:17542641

An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method

NASA Astrophysics Data System (ADS)

Tang, J.

2012-01-01

Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.

Demonstration of Wavelet Techniques in the Spectral Analysis of Bypass Transition Data

NASA Technical Reports Server (NTRS)

Lewalle, Jacques; Ashpis, David E.; Sohn, Ki-Hyeon

1997-01-01

A number of wavelet-based techniques for the analysis of experimental data are developed and illustrated. A multiscale analysis based on the Mexican hat wavelet is demonstrated as a tool for acquiring physical and quantitative information not obtainable by standard signal analysis methods. Experimental data for the analysis came from simultaneous hot-wire velocity traces in a bypass transition of the boundary layer on a heated flat plate. A pair of traces (two components of velocity) at one location was excerpted. A number of ensemble and conditional statistics related to dominant time scales for energy and momentum transport were calculated. The analysis revealed a lack of energy-dominant time scales inside turbulent spots but identified transport-dominant scales inside spots that account for the largest part of the Reynolds stress. Momentum transport was much more intermittent than were energetic fluctuations. This work is the first step in a continuing study of the spatial evolution of these scale-related statistics, the goal being to apply the multiscale analysis results to improve the modeling of transitional and turbulent industrial flows.

Simulating return signals of a spaceborne high-spectral resolution lidar channel at 532 nm

NASA Astrophysics Data System (ADS)

Xiao, Yu; Binglong, Chen; Min, Min; Xingying, Zhang; Lilin, Yao; Yiming, Zhao; Lidong, Wang; Fu, Wang; Xiaobo, Deng

2018-06-01

High spectral resolution lidar (HSRL) system employs a narrow spectral filter to separate the particulate (cloud/aerosol) and molecular scattering components in lidar return signals, which improves the quality of the retrieved cloud/aerosol optical properties. To better develop a future spaceborne HSRL system, a novel simulation technique was developed to simulate spaceborne HSRL return signals at 532 nm using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud/aerosol extinction coefficients product and numerical weather prediction data. For validating simulated data, a mathematical particulate extinction coefficient retrieval method for spaceborne HSRL return signals is described here. We compare particulate extinction coefficient profiles from the CALIPSO operational product with simulated spaceborne HSRL data. Further uncertainty analysis shows that relative uncertainties are acceptable for retrieving the optical properties of cloud and aerosol. The final results demonstrate that they agree well with each other. It indicates that the return signals of the spaceborne HSRL molecular channel at 532 nm will be suitable for developing operational algorithms supporting a future spaceborne HSRL system.

Effect of critical-band smoothing of musical instrument spectral data

NASA Astrophysics Data System (ADS)

Beauchamp, James W.; Horner, Andrew B.

2005-04-01

It has been found that second-order harmonic smoothing of musical instrument spectral data can have a significant effect on timbral perception, depending on the instrument tested [McAdams et al., J. Acoust. Soc. Am. 102, 882-897 (1999)]. With critical-band smoothing, the lower harmonics, since they are in different critical bands, retain their individual amplitudes and temporal envelopes. Thus, it is hypothesized that critical-band smoothing has a lesser perceptual effect on most instrument tones than harmonic smoothing. On the other hand, upper critical bands consist of groups of harmonics. It is hypothesized that it is difficult to hear out individual harmonics within critical bands. Thus, for each band the independent harmonic temporal envelopes can be replaced by a composite rms-amplitude envelope. Spectra within bands can be replaced by time-averaged spectra. Alternatively, time-dependent amplitude versus Bark-frequency spectral envelopes can be smoothed for each individual analysis frame. Further, amplitudes can be averaged in dB or linear units. Results for various processing combinations and various musical instrument sounds will be given and demonstrated.

Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography

PubMed Central

Cong, Wenxiang; Shen, Haiou; Wang, Ge

2011-01-01

The nanophosphors, or other similar materials, emit near-infrared (NIR) light upon x-ray excitation. They were designed as optical probes for in vivo visualization and analysis of molecular and cellular targets, pathways, and responses. Based on the previous work on x-ray fluorescence computed tomography (XFCT) and x-ray luminescence computed tomography (XLCT), here we propose a spectrally-resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography (SXLCT or SXFCT) approach to quantify a spatial distribution of nanophosphors (other similar materials or chemical elements) within a biological object. In this paper, the x-ray scattering is taken into account in the reconstruction algorithm. The NIR scattering is described in the diffusion approximation model. Then, x-ray excitations are applied with different spectra, and NIR signals are measured in a spectrally resolving fashion. Finally, a linear relationship is established between the nanophosphor distribution and measured NIR data using the finite element method and inverted using the compressive sensing technique. The numerical simulation results demonstrate the feasibility and merits of the proposed approach. PMID:21721815

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding

PubMed Central

Lobos, Gustavo A.; Poblete-Echeverría, Carlos

2017-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules. PMID:28119705

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.

PubMed

Lobos, Gustavo A; Poblete-Echeverría, Carlos

2016-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Simulation of time-dispersion spectral device with sample spectra accumulation

NASA Astrophysics Data System (ADS)

Zhdanov, Arseny; Khansuvarov, Ruslan; Korol, Georgy

2014-09-01

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF - major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

USDA-ARS?s Scientific Manuscript database

Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...

What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology

NASA Astrophysics Data System (ADS)

Schaefli, B.; Maraun, D.; Holschneider, M.

2007-12-01

Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.

Non-invasive assessment of thromboembolism in rotary blood pumps: case study

NASA Astrophysics Data System (ADS)

Gawlikowski, Maciej; Kustosz, Roman; Głowacki, Maciej; Pydziński, Paweł; Kubacki, Krzysztof; Zakliczyński, Michał; Copik, Izabela; Pacholewicz, Jerzy

2017-08-01

Thromboembolic complications are one of the major problems in mechanical heart support of patients suffering from critical heart failure. The goal of the study was to present and discuss methodology of non-invasive assessment of embolization in rotary blood pumps. The study was carried out based on power consumption trend analysis as well as spectral analysis of acoustic signal produced by the pump during its operation. It has been demonstrated that the trend of power rising and presence of 3rd harmonic in acoustic spectrum corresponds to the clinical symptoms of pump embolization.

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

PubMed Central

Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

PubMed

Wu, Hau-Tieng; Wu, Han-Kuei; Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

Qualitative analysis of pure and adulterated canola oil via SIMCA

NASA Astrophysics Data System (ADS)

Basri, Katrul Nadia; Khir, Mohd Fared Abdul; Rani, Rozina Abdul; Sharif, Zaiton; Rusop, M.; Zoolfakar, Ahmad Sabirin

2018-05-01

This paper demonstrates the utilization of near infrared (NIR) spectroscopy to classify pure and adulterated sample of canola oil. Soft Independent Modeling Class Analogies (SIMCA) algorithm was implemented to discriminate the samples to its classes. Spectral data obtained was divided using Kennard Stone algorithm into training and validation dataset by a fixed ratio of 7:3. The model accuracy obtained based on the model built is 0.99 whereas the sensitivity and precision are 0.92 and 1.00. The result showed the classification model is robust to perform qualitative analysis of canola oil for future application.

Age-dependent loss of the C-terminal amino acid from alpha crystallin

NASA Technical Reports Server (NTRS)

Emmons, T.; Takemoto, L.; Spooner, B. S. (Principal Investigator)

1992-01-01

Antiserum made against the C-terminal region of alpha-A crystallin was used to monitor the purification of a tryptic peptide containing the C-terminus of the molecule from fetal versus adult bovine lenses. Mass spectral analysis of the peptide preparations obtained from these lenses demonstrated the presence of a peptide (T20) containing an intact C-terminus from fetal lenses and the presence of an additional peptide (T20') from older lenses that contained a cleaved C-terminal serine. These results demonstrate an age-dependent processing of alpha-A crystallin in the bovine lens, resulting in removal of the C-terminal amino acid residue.

Optical Characterization of Paper Aging Based on Laser-Induced Fluorescence (LIF) Spectroscopy.

PubMed

Zhang, Hao; Wang, Shun; Chang, Keke; Sun, Haifeng; Guo, Qingqian; Ma, Liuzheng; Yang, Yatao; Zou, Caihong; Wang, Ling; Hu, Jiandong

2018-06-01

Paper aging and degradation are growing concerns for those who are responsible for the conservation of documents, archives, and libraries. In this study, the paper aging was investigated using laser-induced fluorescence spectroscopy (LIFS), where the fluorescence properties of 47 paper samples with different ages were explored. The paper exhibits fluorescence in the blue-green spectral region with two peaks at about 448 nm and 480 nm under the excitation of 405 nm laser. Both fluorescence peaks changed in absolute intensities and thus the ratio of peak intensities was also influenced with the increasing ages. By applying principal component analysis (PCA) and k-means clustering algorithm, all 47 paper samples were classified into nine groups based on the differences in paper age. Then the first-derivative fluorescence spectral curves were proposed to figure out the relationship between the spectral characteristic and the paper age, and two quantitative models were established based on the changes of first-derivative spectral peak at 443 nm, where one is an exponential fitting curve with an R-squared value of 0.99 and another is a linear fitting curve with an R-squared value of 0.88. The results demonstrated that the combination of fluorescence spectroscopy and PCA can be used for the classification of paper samples with different ages. Moreover, the first-derivative fluorescence spectral curves can be used to quantitatively evaluate the age-related changes of paper samples.

Fast Infrared Chemical Imaging with a Quantum Cascade Laser

PubMed Central

2015-01-01

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm–1) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues. PMID:25474546

Fast infrared chemical imaging with a quantum cascade laser.

PubMed

Yeh, Kevin; Kenkel, Seth; Liu, Jui-Nung; Bhargava, Rohit

2015-01-06

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm(-1)) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues.

Investigation of computational and spectral analysis methods for aeroacoustic wave propagation

NASA Technical Reports Server (NTRS)

Vanel, Florence O.

1995-01-01

Most computational fluid dynamics (CFD) schemes are not adequately accurate for solving aeroacoustics problems, which have wave amplitudes several orders of magnitude smaller yet with frequencies larger than the flow field variations generating the sound. Hence, a computational aeroacoustics (CAA) algorithm should have minimal dispersion and dissipation features. A dispersion relation preserving (DRP) scheme is, therefore, applied to solve the linearized Euler equations in order to simulate the propagation of three types of waves, namely: acoustic, vorticity, and entropy waves. The scheme is derived using an optimization procedure to ensure that the numerical derivatives preserve the wave number and angular frequency of the partial differential equations being discretized. Consequently, simulated waves propagate with the correct wave speeds and exhibit their appropriate properties. A set of radiation and outflow boundary conditions, compatible with the DRP scheme and derived from the asymptotic solutions of the governing equations, are also implemented. Numerical simulations are performed to test the effectiveness of the DRP scheme and its boundary conditions. The computed solutions are shown to agree favorably with the exact solutions. The major restriction appears to be that the dispersion relations can be preserved only for waves with wave lengths longer than four or five spacings. The boundary conditions are found to be transparent to the outgoing disturbances. However, when the disturbance source is placed closer to a boundary, small acoustic reflections start appearing. CAA generates enormous amounts of temporal data which needs to be reduced to understand the physical problem being simulated. Spectral analysis is one approach that helps us in extracting information which often can not be easily interpreted in the time domain. Thus, three different methods for the spectral analysis of numerically generated aeroacoustic data are studied. First, the capabilities of two traditional methods for spectral analysis, namely, the Blackman-Tukey method and periodogram method, are compared in estimating the spectra of a simple-periodic process. The periodogram is then applied to analyze transitory-deterministic processes. Finally, these two methods are compared with a more recent method, referred as the Weighted-Overlapped-Segment-Averaging (WOSA) method, in estimating the spectra of a chaotic (random-like) process. From the demonstrative case for the spectral analyses of data generated by simple-periodic process, the periodogram method is found to give a better estimate of the steep-sloped spectra than the Blackman-Tukey method. Also, for this problem, the Hanning window is found to perform better with the periodogram method than with the Blackman-Tukey method. Finally, for the spectral analysis of data generated by the chaotic process, the periodogram method does not perform well, whereas, the WOSA and Blackman-Tukey methods give equivalently good results.

Digital techniques for ULF wave polarization analysis

NASA Technical Reports Server (NTRS)

Arthur, C. W.

1979-01-01

Digital power spectral and wave polarization analysis are powerful techniques for studying ULF waves in the earth's magnetosphere. Four different techniques for using the spectral matrix to perform such an analysis have been presented in the literature. Three of these techniques are similar in that they require transformation of the spectral matrix to the principal axis system prior to performing the polarization analysis. The differences in the three techniques lie in the manner in which determine this transformation. A comparative study of these three techniques using both simulated and real data has shown them to be approximately equal in quality of performance. The fourth technique does not require transformation of the spectral matrix. Rather, it uses the measured spectral matrix and state vectors for a desired wave type to design a polarization detector function in the frequency domain. The design of various detector functions and their application to both simulated and real data will be presented.

Global spectral graph wavelet signature for surface analysis of carpal bones

NASA Astrophysics Data System (ADS)

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.

2018-02-01

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Global spectral graph wavelet signature for surface analysis of carpal bones.

PubMed

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A

2018-02-05

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Spectral implementation of some quantum algorithms by one- and two-dimensional nuclear magnetic resonance

NASA Astrophysics Data System (ADS)

Das, Ranabir; Kumar, Anil

2004-10-01

Quantum information processing has been effectively demonstrated on a small number of qubits by nuclear magnetic resonance. An important subroutine in any computing is the readout of the output. "Spectral implementation" originally suggested by Z. L. Madi, R. Bruschweiler, and R. R. Ernst [J. Chem. Phys. 109, 10603 (1999)], provides an elegant method of readout with the use of an extra "observer" qubit. At the end of computation, detection of the observer qubit provides the output via the multiplet structure of its spectrum. In spectral implementation by two-dimensional experiment the observer qubit retains the memory of input state during computation, thereby providing correlated information on input and output, in the same spectrum. Spectral implementation of Grover's search algorithm, approximate quantum counting, a modified version of Berstein-Vazirani problem, and Hogg's algorithm are demonstrated here in three- and four-qubit systems.

Acousto-optical tunable filter for combined wideband, spectral, and optical coherence microscopy.

PubMed

Machikhin, Alexander S; Pozhar, Vitold E; Viskovatykh, Alexander V; Burmak, Ludmila I

2015-09-01

A multimodal technique for inspection of microscopic objects by means of wideband optical microscopy, spectral microscopy, and optical coherence microscopy is described, implemented, and tested. The key feature is the spectral selection of light in the output arm of an interferometer with use of the specialized imaging acousto-optical tunable filter. In this filter, two interfering optical beams are diffracted via the same ultrasound wave without destruction of interference image structure. The basic requirements for the acousto-optical tunable filter are defined, and mathematical formulas for calculation of its parameters are derived. Theoretical estimation of the achievable accuracy of the 3D image reconstruction is presented and experimental proofs are given. It is demonstrated that spectral imaging can also be accompanied by measurement of the quantitative reflectance spectra. Examples of inspection of optically transparent and nontransparent samples demonstrate the applicability of the technique.

Scalable fabrication of coupled NV center - photonic crystal cavity systems by self-aligned N ion implantation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schröder, T.; Walsh, M.; Zheng, J.

2017-04-06

Towards building large-scale integrated photonic systems for quantum information processing, spatial and spectral alignment of single quantum systems to photonic nanocavities is required. In this paper, we demonstrate spatially targeted implantation of nitrogen vacancy (NV) centers into the mode maximum of 2-d diamond photonic crystal cavities with quality factors up to 8000, achieving an average of 1.1 ± 0.2 NVs per cavity. Nearly all NV-cavity systems have significant emission intensity enhancement, reaching a cavity-fed spectrally selective intensity enhancement, F int, of up to 93. Although spatial NV-cavity overlap is nearly guaranteed within about 40 nm, spectral tuning of the NV’smore » zero-phonon-line (ZPL) is still necessary after fabrication. To demonstrate spectral control, we temperature tune a cavity into an NV ZPL, yielding F ZPL int~5 at cryogenic temperatures.« less

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

Environmental Electrometry with Luminescent Carbon Nanotubes.

PubMed

Noé, Jonathan C; Nutz, Manuel; Reschauer, Jonathan; Morell, Nicolas; Tsioutsios, Ioannis; Reserbat-Plantey, Antoine; Watanabe, Kenji; Taniguchi, Takashi; Bachtold, Adrian; Högele, Alexander

2018-06-25

We demonstrate that localized excitons in luminescent carbon nanotubes can be utilized to study electrostatic fluctuations in the nanotube environment with sensitivity down to the elementary charge. By monitoring the temporal evolution of the cryogenic photoluminescence from individual carbon nanotubes grown on silicon oxide and hexagonal boron nitride, we characterize the dynamics of charge trap defects for both dielectric supports. We find a one order of magnitude reduction in the photoluminescence spectral wandering for nanotubes on extended atomically flat terraces of hexagonal boron nitride. For nanotubes on hexagonal boron nitride with pronounced spectral fluctuations, our analysis suggests proximity to terrace ridges where charge fluctuators agglomerate to exhibit areal densities exceeding those of silicon oxide. Our results establish carbon nanotubes as sensitive probes of environmental charge fluctuations and highlight their potential for applications in electrometric nanodevices with all-optical readout.

Apparatus and method for the spectrochemical analysis of liquids using the laser spark

DOEpatents

Cremers, David A.; Radziemski, Leon J.; Loree, Thomas R.

1990-01-01

A method and apparatus for the qualitative and quantitative spectroscopic investigation of elements present in a liquid sample using the laser spark. A series of temporally closely spaced spark pairs is induced in the liquid sample utilizing pulsed electromagnetic radiation from a pair of lasers. The light pulses are not significantly absorbed by the sample so that the sparks occur inside of the liquid. The emitted light from the breakdown events is spectrally and temporally resolved, and the time period between the two laser pulses in each spark pair is adjusted to maximize the signal-to-noise ratio of the emitted signals. In comparison with the single pulse technique, a substantial reduction in the limits of detectability for many elements has been demonstrated. Narrowing of spectral features results in improved discrimination against interfering species.

Apparatus and method for the spectrochemical analysis of liquids using the laser spark

DOEpatents

Cremers, D.A.; Radziemski, L.J.; Loree, T.R.

1984-05-01

A method and apparatus are disclosed for the qualitative and quantitative spectroscopic investigation of elements present in a liquid sample using the laser spark. A series of temporally closely spaced spark pairs is induced in the liquid sample utilizing pulsed electromagnetic radiation from a pair of lasers. The light pulses are not significantly absorbed by the sample so that the sparks occur inside of the liquid. The emitted light from the breakdown events is spectrally and temporally resolved, and the time period between the two laser pulses in each spark pair is adjusted to maximize the signal-to-noise ratio of the emitted signals. In comparison with the single pulse technique, a substantial reduction in the limits of detectability for many elements has been demonstrated. Narrowing of spectral features results in improved discrimination against interfering species.

New whole-body sensory-motor gradients revealed using phase-locked analysis and verified using multivoxel pattern analysis and functional connectivity.

PubMed

Zeharia, Noa; Hertz, Uri; Flash, Tamar; Amedi, Amir

2015-02-18

Topographic organization is one of the main principles of organization in the human brain. Specifically, whole-brain topographic mapping using spectral analysis is responsible for one of the greatest advances in vision research. Thus, it is intriguing that although topography is a key feature also in the motor system, whole-body somatosensory-motor mapping using spectral analysis has not been conducted in humans outside M1/SMA. Here, using this method, we were able to map a homunculus in the globus pallidus, a key target area for deep brain stimulation, which has not been mapped noninvasively or in healthy subjects. The analysis clarifies contradictory and partial results regarding somatotopy in the caudal-cingulate zone and rostral-cingulate zone in the medial wall and in the putamen. Most of the results were confirmed at the single-subject level and were found to be compatible with results from animal studies. Using multivoxel pattern analysis, we could predict movements of individual body parts in these homunculi, thus confirming that they contain somatotopic information. Using functional connectivity, we demonstrate interhemispheric functional somatotopic connectivity of these homunculi, such that the somatotopy in one hemisphere could have been found given the connectivity pattern of the corresponding regions of interest in the other hemisphere. When inspecting the somatotopic and nonsomatotopic connectivity patterns, a similarity index indicated that the pattern of connected and nonconnected regions of interest across different homunculi is similar for different body parts and hemispheres. The results show that topographical gradients are even more widespread than previously assumed in the somatosensory-motor system. Spectral analysis can thus potentially serve as a gold standard for defining somatosensory-motor system areas for basic research and clinical applications. Copyright © 2015 the authors 0270-6474/15/352845-15$15.00/0.

Time-resolved confocal fluorescence microscopy: novel technical features and applications for FLIM, FRET and FCS using a sophisticated data acquisition concept in TCSPC

NASA Astrophysics Data System (ADS)

Koberling, Felix; Krämer, Benedikt; Kapusta, Peter; Patting, Matthias; Wahl, Michael; Erdmann, Rainer

2007-05-01

In recent years time-resolved fluorescence measurement and analysis techniques became a standard in single molecule microscopy. However, considering the equipment and experimental implementation they are typically still an add-on and offer only limited possibilities to study the mutual dependencies with common intensity and spectral information. In contrast, we are using a specially designed instrument with an unrestricted photon data acquisition approach which allows to store spatial, temporal, spectral and intensity information in a generalized format preserving the full experimental information. This format allows us not only to easily study dependencies between various fluorescence parameters but also to use, for example, the photon arrival time for sorting and weighting the detected photons to improve the significance in common FCS and FRET analysis schemes. The power of this approach will be demonstrated for different techniques: In FCS experiments the concentration determination accuracy can be easily improved by a simple time-gated photon analysis to suppress the fast decaying background signal. A more detailed analysis of the arrival times allows even to separate FCS curves for species which differ in their fluorescence lifetime but, for example, cannot be distinguished spectrally. In multichromophoric systems like a photonic wire which undergoes unidirectional multistep FRET the lifetime information complements significantly the intensity based analysis and helps to assign the respective FRET partners. Moreover, together with pulsed excitation the time-correlated analysis enables directly to take advantage of alternating multi-colour laser excitation. This pulsed interleaved excitation (PIE) can be used to identify and rule out inactive FRET molecules which cause interfering artefacts in standard FRET efficiency analysis. We used a piezo scanner based confocal microscope with compact picosecond diode lasers as excitation sources. The timing performance can be significantly increased by using new SPAD detectors which enable, in conjunction with new TCSPC electronics, an overall IRF width of less than 120 ps maintaining single molecule sensitivity.

The gamut of alkoxy radicals

NASA Astrophysics Data System (ADS)

Box, Harold C.; Budzinski, Edwin E.; Freund, Harold G.

1984-12-01

It is shown that various radicals exhibiting diverse ESR and ENDOR spectral characteristics are nonetheless a closely related family of alkoxy radicals. The relationship is established by correlating the g tensor with crystal structure and by relating dihedral angles inferred from proton hyperfine couplings to dihedral angles inferred from the g tensor and crystal structure. The analysis also serves to demonstrate that an ESR absorption observed in x-irradiated single crystals of uridine 5'-monophosphate is due to an alkoxy radical.

Cancer diagnosis by infrared spectroscopy: methodological aspects

NASA Astrophysics Data System (ADS)

Jackson, Michael; Kim, Keith; Tetteh, John; Mansfield, James R.; Dolenko, Brion; Somorjai, Raymond L.; Orr, F. W.; Watson, Peter H.; Mantsch, Henry H.

1998-04-01

IR spectroscopy is proving to be a powerful tool for the study and diagnosis of cancer. The application of IR spectroscopy to the analysis of cultured tumor cells and grading of breast cancer sections is outlined. Potential sources of error in spectral interpretation due to variations in sample histology and artifacts associated with sample storage and preparation are discussed. The application of statistical techniques to assess differences between spectra and to non-subjectively classify spectra is demonstrated.

Hyper-spectral imaging in scanning-confocal-fluorescence microscopy using a novel broadband diffractive optic

NASA Astrophysics Data System (ADS)

Wang, Peng; Ebeling, Carl G.; Gerton, Jordan; Menon, Rajesh

In this paper, we demonstrate hyper-spectral imaging of fluorescent microspheres in a scanning-confocal-fluorescence microscope by spatially dispersing the spectra using a novel broadband diffractive optic, and applying a nonlinear optimization technique to extract the full-incident spectra. This broadband diffractive optic has a designed optical efficiency of over 90% across the entire visible spectrum. We used this technique to create two-color images of two fluorophores and also extracted their emission spectra with good fidelity. This method can be extended to image both spatially and spectrally overlapping fluorescent samples. Full control in the number of emission spectra and the feasibility of enhanced imaging speed are demonstrated as well.

Real Time Monitoring and Prediction of the Monsoon Intraseasonal Oscillations: An index based on Nonlinear Laplacian Spectral Analysis Technique

NASA Astrophysics Data System (ADS)

Cherumadanakadan Thelliyil, S.; Ravindran, A. M.; Giannakis, D.; Majda, A.

2016-12-01

An improved index for real time monitoring and forecast verification of monsoon intraseasonal oscillations (MISO) is introduced using the recently developed Nonlinear Laplacian Spectral Analysis (NLSA) algorithm. Previous studies has demonstrated the proficiency of NLSA in capturing low frequency variability and intermittency of a time series. Using NLSA a hierarchy of Laplace-Beltrami (LB) eigen functions are extracted from the unfiltered daily GPCP rainfall data over the south Asian monsoon region. Two modes representing the full life cycle of complex northeastward propagating boreal summer MISO are identified from the hierarchy of Laplace-Beltrami eigen functions. These two MISO modes have a number of advantages over the conventionally used Extended Empirical Orthogonal Function (EEOF) MISO modes including higher memory and better predictability, higher fractional variance over the western Pacific, Western Ghats and adjoining Arabian Sea regions and more realistic representation of regional heat sources associated with the MISO. The skill of NLSA based MISO indices in real time prediction of MISO is demonstrated using hindcasts of CFSv2 extended range prediction runs. It is shown that these indices yield a higher prediction skill than the other conventional indices supporting the use of NLSA in real time prediction of MISO. Real time monitoring and prediction of MISO finds its application in agriculture, construction and hydro-electric power sectors and hence an important component of monsoon prediction.

Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

NASA Astrophysics Data System (ADS)

August, Isaac; Oiknine, Yaniv; Abuleil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

2016-03-01

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder.

PubMed

August, Isaac; Oiknine, Yaniv; AbuLeil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

2016-03-23

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

Color reproduction of human skin by spectral reflectance using RGB images and the Wiener estimation method

NASA Astrophysics Data System (ADS)

Sato, Kiyomi; Miyazawa, Shota; Funamizu, Hideki; Yuasa, Tomonori; Nishidate, Izumi; Aizu, Yoshihisa

2017-04-01

Skin measurements based on spectral reflectance are widely studied in the fields of medical care and cosmetics. It has the advantage that several skin properties can be estimated in the non-invasive and non-contacting manner. In this study, we demonstrate the color reproduction of human skin by spectral reflectance using RGB images and the Wiener estimation method.

SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.

Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity.

PubMed

Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H

2016-09-01

Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time-varying spectral amplitudes in the frequency band 0.08-0.24 Hz were used as the index of sympathetic tone, termed TVSymp. TVSymp was found to be overall the most sensitive to the stimuli, as evidenced by a low coefficient of variation (0.54), and higher consistency (intra-class correlation, 0.96) and sensitivity (Youden's index > 0.75), area under the receiver operating characteristic (ROC) curve (>0.8, accuracy > 0.88) compared with time-domain and time-invariant spectral indices, including heart rate variability. Copyright © 2016 the American Physiological Society.

Spectral Analysis of Rich Network Topology in Social Networks

ERIC Educational Resources Information Center

Wu, Leting

2013-01-01

Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

Multivariate Analysis of Two-Dimensional 1H, 13C Methyl NMR Spectra of Monoclonal Antibody Therapeutics To Facilitate Assessment of Higher Order Structure.

PubMed

Arbogast, Luke W; Delaglio, Frank; Schiel, John E; Marino, John P

2017-11-07

Two-dimensional (2D) 1 H- 13 C methyl NMR provides a powerful tool to probe the higher order structure (HOS) of monoclonal antibodies (mAbs), since spectra can readily be acquired on intact mAbs at natural isotopic abundance, and small changes in chemical environment and structure give rise to observable changes in corresponding spectra, which can be interpreted at atomic resolution. This makes it possible to apply 2D NMR spectral fingerprinting approaches directly to drug products in order to systematically characterize structure and excipient effects. Systematic collections of NMR spectra are often analyzed in terms of the changes in specifically identified peak positions, as well as changes in peak height and line widths. A complementary approach is to apply principal component analysis (PCA) directly to the matrix of spectral data, correlating spectra according to similarities and differences in their overall shapes, rather than according to parameters of individually identified peaks. This is particularly well-suited for spectra of mAbs, where some of the individual peaks might not be well resolved. Here we demonstrate the performance of the PCA method for discriminating structural variation among systematic sets of 2D NMR fingerprint spectra using the NISTmAb and illustrate how spectral variability identified by PCA may be correlated to structure.