Spectral Unmixing With Multiple Dictionaries

NASA Astrophysics Data System (ADS)

Cohen, Jeremy E.; Gillis, Nicolas

2018-02-01

Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral or multispectral image, along with their abundances. A typical assumption is that the image contains one pure pixel per endmember, in which case spectral unmixing reduces to identifying these pixels. Many fully automated methods have been proposed in recent years, but little work has been done to allow users to select areas where pure pixels are present manually or using a segmentation algorithm. Additionally, in a non-blind approach, several spectral libraries may be available rather than a single one, with a fixed number (or an upper or lower bound) of endmembers to chose from each. In this paper, we propose a multiple-dictionary constrained low-rank matrix approximation model that address these two problems. We propose an algorithm to compute this model, dubbed M2PALS, and its performance is discussed on both synthetic and real hyperspectral images.

Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar

NASA Astrophysics Data System (ADS)

Fedrigo, Melissa; Newnham, Glenn J.; Coops, Nicholas C.; Culvenor, Darius S.; Bolton, Douglas K.; Nitschke, Craig R.

2018-02-01

Light detection and ranging (lidar) data have been increasingly used for forest classification due to its ability to penetrate the forest canopy and provide detail about the structure of the lower strata. In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms. Our results demonstrated that both random forest and linear unmixing models identified a distribution of rainforest and eucalypt stands that was comparable to existing ecological vegetation class (EVC) maps based primarily on manual interpretation of high resolution aerial imagery. Rainforest stands were also identified in the region that have not previously been identified in the EVC maps. The transition between stand types was better characterised by the random forest modelling approach. In contrast, the linear unmixing model placed greater emphasis on field plots selected as endmembers which may not have captured the variability in stand structure within a single stand type. The random forest model had the highest overall accuracy (84%) and Cohen's kappa coefficient (0.62). However, the classification accuracy was only marginally better than linear unmixing. The random forest model was applied to a region in the Central Highlands of south-eastern Australia to produce maps of stand type probability, including areas of transition (the 'ecotone') between rainforest and eucalypt forest. The resulting map provided a detailed delineation of forest classes, which specifically recognised the coalescing of stand types at the landscape scale. This represents a key step towards mapping the structural and spatial complexity of these ecosystems, which is important for both their management and conservation.

Source apportionment of PM2.5 at the Lin'an regional background site in China with three receptor models

NASA Astrophysics Data System (ADS)

Deng, Junjun; Zhang, Yanru; Qiu, Yuqing; Zhang, Hongliang; Du, Wenjiao; Xu, Lingling; Hong, Youwei; Chen, Yanting; Chen, Jinsheng

2018-04-01

Source apportionment of fine particulate matter (PM2.5) were conducted at the Lin'an Regional Atmospheric Background Station (LA) in the Yangtze River Delta (YRD) region in China from July 2014 to April 2015 with three receptor models including principal component analysis combining multiple linear regression (PCA-MLR), UNMIX and Positive Matrix Factorization (PMF). The model performance, source identification and source contribution of the three models were analyzed and inter-compared. Source apportionment of PM2.5 was also conducted with the receptor models. Good correlations between the reconstructed and measured concentrations of PM2.5 and its major chemical species were obtained for all models. PMF resolved almost all masses of PM2.5, while PCA-MLR and UNMIX explained about 80%. Five, four and seven sources were identified by PCA-MLR, UNMIX and PMF, respectively. Combustion, secondary source, marine source, dust and industrial activities were identified by all the three receptor models. Combustion source and secondary source were the major sources, and totally contributed over 60% to PM2.5. The PMF model had a better performance on separating the different combustion sources. These findings improve the understanding of PM2.5 sources in background region.

Unmixing AVHRR Imagery to Assess Clearcuts and Forest Regrowth in Oregon

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Spanner, Michael A.

1995-01-01

Advanced Very High Resolution Radiometer imagery provides frequent and low-cost coverage of the earth, but its coarse spatial resolution (approx. 1.1 km by 1.1 km) does not lend itself to standard techniques of automated categorization of land cover classes because the pixels are generally mixed; that is, the extent of the pixel includes several land use/cover classes. Unmixing procedures were developed to extract land use/cover class signatures from mixed pixels, using Landsat Thematic Mapper data as a source for the training set, and to estimate fractions of class coverage within pixels. Application of these unmixing procedures to mapping forest clearcuts and regrowth in Oregon indicated that unmixing is a promising approach for mapping major trends in land cover with AVHRR bands 1 and 2. Including thermal bands by unmixing AVHRR bands 1-4 did not lead to significant improvements in accuracy, but experiments with unmixing these four bands did indicate that use of weighted least squares techniques might lead to improvements in other applications of unmixing.

UNMIX Methods Applied to Characterize Sources of Volatile Organic Compounds in Toronto, Ontario

PubMed Central

Porada, Eugeniusz; Szyszkowicz, Mieczysław

2016-01-01

UNMIX, a sensor modeling routine from the U.S. Environmental Protection Agency (EPA), was used to model volatile organic compound (VOC) receptors in four urban sites in Toronto, Ontario. VOC ambient concentration data acquired in 2000–2009 for 175 VOC species in four air quality monitoring stations were analyzed. UNMIX, by performing multiple modeling attempts upon varying VOC menus—while rejecting the results that were not reliable—allowed for discriminating sources by their most consistent chemical characteristics. The method assessed occurrences of VOCs in sources typical of the urban environment (traffic, evaporative emissions of fuels, banks of fugitive inert gases), industrial point sources (plastic-, polymer-, and metalworking manufactures), and in secondary sources (releases from water, sediments, and contaminated urban soil). The remote sensing and robust modeling used here produces chemical profiles of putative VOC sources that, if combined with known environmental fates of VOCs, can be used to assign physical sources’ shares of VOCs emissions into the atmosphere. This in turn provides a means of assessing the impact of environmental policies on one hand, and industrial activities on the other hand, on VOC air pollution. PMID:29051416

Application of hierarchical Bayesian unmixing models in river sediment source apportionment

NASA Astrophysics Data System (ADS)

Blake, Will; Smith, Hugh; Navas, Ana; Bodé, Samuel; Goddard, Rupert; Zou Kuzyk, Zou; Lennard, Amy; Lobb, David; Owens, Phil; Palazon, Leticia; Petticrew, Ellen; Gaspar, Leticia; Stock, Brian; Boeckx, Pacsal; Semmens, Brice

2016-04-01

Fingerprinting and unmixing concepts are used widely across environmental disciplines for forensic evaluation of pollutant sources. In aquatic and marine systems, this includes tracking the source of organic and inorganic pollutants in water and linking problem sediment to soil erosion and land use sources. It is, however, the particular complexity of ecological systems that has driven creation of the most sophisticated mixing models, primarily to (i) evaluate diet composition in complex ecological food webs, (ii) inform population structure and (iii) explore animal movement. In the context of the new hierarchical Bayesian unmixing model, MIXSIAR, developed to characterise intra-population niche variation in ecological systems, we evaluate the linkage between ecological 'prey' and 'consumer' concepts and river basin sediment 'source' and sediment 'mixtures' to exemplify the value of ecological modelling tools to river basin science. Recent studies have outlined advantages presented by Bayesian unmixing approaches in handling complex source and mixture datasets while dealing appropriately with uncertainty in parameter probability distributions. MixSIAR is unique in that it allows individual fixed and random effects associated with mixture hierarchy, i.e. factors that might exert an influence on model outcome for mixture groups, to be explored within the source-receptor framework. This offers new and powerful ways of interpreting river basin apportionment data. In this contribution, key components of the model are evaluated in the context of common experimental designs for sediment fingerprinting studies namely simple, nested and distributed catchment sampling programmes. Illustrative examples using geochemical and compound specific stable isotope datasets are presented and used to discuss best practice with specific attention to (1) the tracer selection process, (2) incorporation of fixed effects relating to sample timeframe and sediment type in the modelling process, (3) deriving and using informative priors in sediment fingerprinting context and (4) transparency of the process and replication of model results by other users.

Arctic lead detection using a waveform unmixing algorithm from CryoSat-2 data

NASA Astrophysics Data System (ADS)

Lee, S.; Im, J.

2016-12-01

Arctic areas consist of ice floes, leads, and polynyas. While leads and polynyas account for small parts in the Arctic Ocean, they play a key role in exchanging heat flux, moisture, and momentum between the atmosphere and ocean in wintertime because of their huge temperature difference In this study, a linear waveform unmixing approach was proposed to detect lead fraction. CryoSat-2 waveforms for pure leads, sea ice, and ocean were used as end-members based on visual interpretation of MODIS images coincident with CryoSat-2 data. The unmixing model produced lead, sea ice, and ocean abundances and a threshold (> 0.7) was applied to make a binary classification between lead and sea ice. The unmixing model produced better results than the existing models in the literature, which are based on simple thresholding approaches. The results were also comparable with our previous research using machine learning based models (i.e., decision trees and random forest). A monthly lead fraction was calculated, dividing the number of detected leads by the total number of measurements. The lead fraction around Beaufort Sea and Fram strait was high due to the anti-cyclonic rotation of Beaufort Gyre and the outflows of sea ice to the Atlantic. The lead fraction maps produced in this study were matched well with monthly lead fraction maps in the literature. The areas with thin sea ice identified from our previous research correspond to the high lead fraction areas in the present study. Furthermore, sea ice roughness from ASCAT scatterometer was compared to a lead fraction map to see the relationship between surface roughness and lead distribution.

Component Analysis of Remanent Magnetization Curves: A Revisit with a New Model Distribution

NASA Astrophysics Data System (ADS)

Zhao, X.; Suganuma, Y.; Fujii, M.

2017-12-01

Geological samples often consist of several magnetic components that have distinct origins. As the magnetic components are often indicative of their underlying geological and environmental processes, it is therefore desirable to identify individual components to extract associated information. This component analysis can be achieved using the so-called unmixing method, which fits a mixture model of certain end-member model distribution to the measured remanent magnetization curve. In earlier studies, the lognormal, skew generalized Gaussian and skewed Gaussian distributions have been used as the end-member model distribution in previous studies, which are performed on the gradient curve of remanent magnetization curves. However, gradient curves are sensitive to measurement noise as the differentiation of the measured curve amplifies noise, which could deteriorate the component analysis. Though either smoothing or filtering can be applied to reduce the noise before differentiation, their effect on biasing component analysis is vaguely addressed. In this study, we investigated a new model function that can be directly applied to the remanent magnetization curves and therefore avoid the differentiation. The new model function can provide more flexible shape than the lognormal distribution, which is a merit for modeling the coercivity distribution of complex magnetic component. We applied the unmixing method both to model and measured data, and compared the results with those obtained using other model distributions to better understand their interchangeability, applicability and limitation. The analyses on model data suggest that unmixing methods are inherently sensitive to noise, especially when the number of component is over two. It is, therefore, recommended to verify the reliability of component analysis by running multiple analyses with synthetic noise. Marine sediments and seafloor rocks are analyzed with the new model distribution. Given the same component number, the new model distribution can provide closer fits than the lognormal distribution evidenced by reduced residuals. Moreover, the new unmixing protocol is automated so that the users are freed from the labor of providing initial guesses for the parameters, which is also helpful to improve the subjectivity of component analysis.

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.

EPA UNMIX 6.0 USER GUIDE

EPA Science Inventory

The underlying philosophy of Unmix is to let the data speak for itself. Unmix seeks to solve the general mixture problem where the data are assumed to be a linear combination of an unknown number of sources of unknown composition, which contribute an unknown amount to each sample...

Estimation of tissue optical parameters with hyperspectral imaging and spectral unmixing

NASA Astrophysics Data System (ADS)

Lu, Guolan; Qin, Xulei; Wang, Dongsheng; Chen, Zhuo G.; Fei, Baowei

2015-03-01

Early detection of oral cancer and its curable precursors can improve patient survival and quality of life. Hyperspectral imaging (HSI) holds the potential for noninvasive early detection of oral cancer. The quantification of tissue chromophores by spectral unmixing of hyperspectral images could provide insights for evaluating cancer progression. In this study, non-negative matrix factorization has been applied for decomposing hyperspectral images into physiologically meaningful chromophore concentration maps. The approach has been validated by computer-simulated hyperspectral images and in vivo tumor hyperspectral images from a head and neck cancer animal model.

Quadratic Blind Linear Unmixing: A Graphical User Interface for Tissue Characterization

PubMed Central

Gutierrez-Navarro, O.; Campos-Delgado, D.U.; Arce-Santana, E. R.; Jo, Javier A.

2016-01-01

Spectral unmixing is the process of breaking down data from a sample into its basic components and their abundances. Previous work has been focused on blind unmixing of multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) datasets under a linear mixture model and quadratic approximations. This method provides a fast linear decomposition and can work without a limitation in the maximum number of components or end-members. Hence this work presents an interactive software which implements our blind end-member and abundance extraction (BEAE) and quadratic blind linear unmixing (QBLU) algorithms in Matlab. The options and capabilities of our proposed software are described in detail. When the number of components is known, our software can estimate the constitutive end-members and their abundances. When no prior knowledge is available, the software can provide a completely blind solution to estimate the number of components, the end-members and their abundances. The characterization of three case studies validates the performance of the new software: ex-vivo human coronary arteries, human breast cancer cell samples, and in-vivo hamster oral mucosa. The software is freely available in a hosted webpage by one of the developing institutions, and allows the user a quick, easy-to-use and efficient tool for multi/hyper-spectral data decomposition. PMID:26589467

Quadratic blind linear unmixing: A graphical user interface for tissue characterization.

PubMed

Gutierrez-Navarro, O; Campos-Delgado, D U; Arce-Santana, E R; Jo, Javier A

2016-02-01

Spectral unmixing is the process of breaking down data from a sample into its basic components and their abundances. Previous work has been focused on blind unmixing of multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) datasets under a linear mixture model and quadratic approximations. This method provides a fast linear decomposition and can work without a limitation in the maximum number of components or end-members. Hence this work presents an interactive software which implements our blind end-member and abundance extraction (BEAE) and quadratic blind linear unmixing (QBLU) algorithms in Matlab. The options and capabilities of our proposed software are described in detail. When the number of components is known, our software can estimate the constitutive end-members and their abundances. When no prior knowledge is available, the software can provide a completely blind solution to estimate the number of components, the end-members and their abundances. The characterization of three case studies validates the performance of the new software: ex-vivo human coronary arteries, human breast cancer cell samples, and in-vivo hamster oral mucosa. The software is freely available in a hosted webpage by one of the developing institutions, and allows the user a quick, easy-to-use and efficient tool for multi/hyper-spectral data decomposition. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Distributed Unmixing of Hyperspectral Datawith Sparsity Constraint

NASA Astrophysics Data System (ADS)

Khoshsokhan, S.; Rajabi, R.; Zayyani, H.

2017-09-01

Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in a blind problem, nonnegative matrix factorization (NMF) and its developments are used widely in the SU problem. One of the constraints which was added to NMF is sparsity constraint that was regularized by L1/2 norm. In this paper, a new algorithm based on distributed optimization has been used for spectral unmixing. In the proposed algorithm, a network including single-node clusters has been employed. Each pixel in hyperspectral images considered as a node in this network. The distributed unmixing with sparsity constraint has been optimized with diffusion LMS strategy, and then the update equations for fractional abundance and signature matrices are obtained. Simulation results based on defined performance metrics, illustrate advantage of the proposed algorithm in spectral unmixing of hyperspectral data compared with other methods. The results show that the AAD and SAD of the proposed approach are improved respectively about 6 and 27 percent toward distributed unmixing in SNR=25dB.

Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yang, Jian; He, Yuhong

2017-02-01

Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.

Accuracy assessment of linear spectral mixture model due to terrain undulation

NASA Astrophysics Data System (ADS)

Wang, Tianxing; Chen, Songlin; Ma, Ya

2008-12-01

Mixture spectra are common in remote sensing due to the limitations of spatial resolution and the heterogeneity of land surface. During the past 30 years, a lot of subpixel model have developed to investigate the information within mixture pixels. Linear spectral mixture model (LSMM) is a simper and more general subpixel model. LSMM also known as spectral mixture analysis is a widely used procedure to determine the proportion of endmembers (constituent materials) within a pixel based on the endmembers' spectral characteristics. The unmixing accuracy of LSMM is restricted by variety of factors, but now the research about LSMM is mostly focused on appraisement of nonlinear effect relating to itself and techniques used to select endmembers, unfortunately, the environment conditions of study area which could sway the unmixing-accuracy, such as atmospheric scatting and terrain undulation, are not studied. This paper probes emphatically into the accuracy uncertainty of LSMM resulting from the terrain undulation. ASTER dataset was chosen and the C terrain correction algorithm was applied to it. Based on this, fractional abundances for different cover types were extracted from both pre- and post-C terrain illumination corrected ASTER using LSMM. Simultaneously, the regression analyses and the IKONOS image were introduced to assess the unmixing accuracy. Results showed that terrain undulation could dramatically constrain the application of LSMM in mountain area. Specifically, for vegetation abundances, a improved unmixing accuracy of 17.6% (regression against to NDVI) and 18.6% (regression against to MVI) for R2 was achieved respectively by removing terrain undulation. Anyway, this study indicated in a quantitative way that effective removal or minimization of terrain illumination effects was essential for applying LSMM. This paper could also provide a new instance for LSMM applications in mountainous areas. In addition, the methods employed in this study could be effectively used to evaluate different algorithms of terrain undulation correction for further study.

Mapping target signatures via partial unmixing of AVIRIS data

NASA Technical Reports Server (NTRS)

Boardman, Joseph W.; Kruse, Fred A.; Green, Robert O.

1995-01-01

A complete spectral unmixing of a complicated AVIRIS scene may not always be possible or even desired. High quality data of spectrally complex areas are very high dimensional and are consequently difficult to fully unravel. Partial unmixing provides a method of solving only that fraction of the data inversion problem that directly relates to the specific goals of the investigation. Many applications of imaging spectrometry can be cast in the form of the following question: 'Are my target signatures present in the scene, and if so, how much of each target material is present in each pixel?' This is a partial unmixing problem. The number of unmixing endmembers is one greater than the number of spectrally defined target materials. The one additional endmember can be thought of as the composite of all the other scene materials, or 'everything else'. Several workers have proposed partial unmixing schemes for imaging spectrometry data, but each has significant limitations for operational application. The low probability detection methods described by Farrand and Harsanyi and the foreground-background method of Smith et al are both examples of such partial unmixing strategies. The new method presented here builds on these innovative analysis concepts, combining their different positive attributes while attempting to circumvent their limitations. This new method partially unmixes AVIRIS data, mapping apparent target abundances, in the presence of an arbitrary and unknown spectrally mixed background. It permits the target materials to be present in abundances that drive significant portions of the scene covariance. Furthermore it does not require a priori knowledge of the background material spectral signatures. The challenge is to find the proper projection of the data that hides the background variance while simultaneously maximizing the variance amongst the targets.

Rotational Spectral Unmixing of Exoplanets: Degeneracies between Surface Colors and Geography

NASA Astrophysics Data System (ADS)

Fujii, Yuka; Lustig-Yaeger, Jacob; Cowan, Nicolas B.

2017-11-01

Unmixing the disk-integrated spectra of exoplanets provides hints about heterogeneous surfaces that we cannot directly resolve in the foreseeable future. It is particularly important for terrestrial planets with diverse surface compositions like Earth. Although previous work on unmixing the spectra of Earth from disk-integrated multi-band light curves appeared successful, we point out a mathematical degeneracy between the surface colors and their spatial distributions. Nevertheless, useful constraints on the spectral shape of individual surface types may be obtained from the premise that albedo is everywhere between 0 and 1. We demonstrate the degeneracy and the possible constraints using both mock data based on a toy model of Earth, as well as real observations of Earth. Despite the severe degeneracy, we are still able to recover an approximate albedo spectrum for an ocean. In general, we find that surfaces are easier to identify when they cover a large fraction of the planet and when their spectra approach zero or unity in certain bands.

Rotational Spectral Unmixing of Exoplanets: Degeneracies between Surface Colors and Geography

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

Fujii, Yuka; Lustig-Yaeger, Jacob; Cowan, Nicolas B., E-mail: yuka.fujii.ebihara@gmail.com

Unmixing the disk-integrated spectra of exoplanets provides hints about heterogeneous surfaces that we cannot directly resolve in the foreseeable future. It is particularly important for terrestrial planets with diverse surface compositions like Earth. Although previous work on unmixing the spectra of Earth from disk-integrated multi-band light curves appeared successful, we point out a mathematical degeneracy between the surface colors and their spatial distributions. Nevertheless, useful constraints on the spectral shape of individual surface types may be obtained from the premise that albedo is everywhere between 0 and 1. We demonstrate the degeneracy and the possible constraints using both mock datamore » based on a toy model of Earth, as well as real observations of Earth. Despite the severe degeneracy, we are still able to recover an approximate albedo spectrum for an ocean. In general, we find that surfaces are easier to identify when they cover a large fraction of the planet and when their spectra approach zero or unity in certain bands.« less

Rotational Spectral Unmixing of Exoplanets: Degeneracies Between Surface Colors and Geography

NASA Technical Reports Server (NTRS)

Fujii, Yuka; Lustig-Yaeger, Jacob; Cowan, Nicolas B.

2017-01-01

Unmixing the disk-integrated spectra of exoplanets provides hints about heterogeneous surfaces that we cannot directly resolve in the foreseeable future. It is particularly important for terrestrial planets with diverse surface compositions like Earth. Although previous work on unmixing the spectra of Earth from disk-integrated multi-band light curves appeared successful, we point out a mathematical degeneracy between the surface colors and their spatial distributions. Nevertheless, useful constraints on the spectral shape of individual surface types may be obtained from the premise that albedo is everywhere between 0 and 1. We demonstrate the degeneracy and the possible constraints using both mock data based on a toy model of Earth, as well as real observations of Earth. Despite the severe degeneracy, we are still able to recover an approximate albedo spectrum for an ocean. In general, we find that surfaces are easier to identify when they cover a large fraction of the planet and when their spectra approach zero or unity in certain bands.

Fingerprinting Sources of Suspended Sediment in a Canadian Agricultural Watershed Using the MixSIAR Bayesian Unmixing Model

NASA Astrophysics Data System (ADS)

Smith, J. P.; Owens, P. N.; Gaspar, L.; Lobb, D. A.; Petticrew, E. L.

2015-12-01

An understanding of sediment redistribution processes and the main sediment sources within a watershed is needed to support watershed management strategies. The fingerprinting technique is increasingly being recognized as a method for establishing the source of the sediment transported within watersheds. However, the different behaviour of the various fingerprinting properties has been recognized as a major limitation of the technique, and the uncertainty associated with tracer selection needs to be addressed. There are also questions associated with which modelling approach (frequentist or Bayesian) is the best to unmix complex environmental mixtures, such as river sediment. This study aims to compare and evaluate the differences between fingerprinting predictions provided by a Bayesian unmixing model (MixSIAR) using different groups of tracer properties for use in sediment source identification. We used fallout radionuclides (e.g. 137Cs) and geochemical elements (e.g. As) as conventional fingerprinting properties, and colour parameters as emerging properties; both alone and in combination. These fingerprinting properties are being used (i.e. Koiter et al., 2013; Barthod et al., 2015) to determine the proportional contributions of fine sediment in the South Tobacco Creek Watershed, an agricultural watershed located in Manitoba, Canada. We show that the unmixing model using a combination of fallout radionuclides and geochemical tracers gave similar results to the model based on colour parameters. Furthermore, we show that a model that combines all tracers (i.e. radionuclide/geochemical and colour) gave similar results, showing that sediment sources change from predominantly topsoil in the upper reaches of the watershed to channel bank and bedrock outcrop material in the lower reaches. Barthod LRM et al. (2015). Selecting color-based tracers and classifying sediment sources in the assessment of sediment dynamics using sediment source fingerprinting. J Environ Qual. Doi:10.2134/jeq2015.01.0043 Koiter AJ et al. (2013). Investigating the role of connectivity and scale in assessing the sources of sediment in an agricultural watershed in the Canadian prairies using sediment source fingerprinting. J Soils Sediments, 13, 1676-1691.

Sediment unmixing using detrital geochronology

USGS Publications Warehouse

Sharman, Glenn R.; Johnstone, Samuel

2017-01-01

Sediment mixing within sediment routing systems can exert a strong influence on the preservation of provenance signals that yield insight into the influence of environmental forcings (e.g., tectonism, climate) on the earth’s surface. Here we discuss two approaches to unmixing detrital geochronologic data in an effort to characterize complex changes in the sedimentary record. First we summarize ‘top-down’ mixing, which has been successfully employed in the past to characterize the different fractions of prescribed source distributions (‘parents’) that characterize a derived sample or set of samples (‘daughters’). Second we propose the use of ‘bottom-up’ methods, previously used primarily for grain size distributions, to model parent distributions and the abundances of these parents within a set of daughters. We demonstrate the utility of both top-down and bottom-up approaches to unmixing detrital geochronologic data within a well-constrained sediment routing system in central California. Use of a variety of goodness-of-fit metrics in top-down modeling reveals the importance of considering the range of allowable mixtures over any single best-fit mixture calculation. Bottom-up modeling of 12 daughter samples from beaches and submarine canyons yields modeled parent distributions that are remarkably similar to those expected from the geologic context of the sediment-routing system. In general, mixture modeling has potential to supplement more widely applied approaches in comparing detrital geochronologic data by casting differences between samples as differing proportions of geologically meaningful end-member provenance categories.

Sediment unmixing using detrital geochronology

NASA Astrophysics Data System (ADS)

Sharman, Glenn R.; Johnstone, Samuel A.

2017-11-01

Sediment mixing within sediment routing systems can exert a strong influence on the preservation of provenance signals that yield insight into the effect of environmental forcing (e.g., tectonism, climate) on the Earth's surface. Here, we discuss two approaches to unmixing detrital geochronologic data in an effort to characterize complex changes in the sedimentary record. First, we summarize 'top-down' mixing, which has been successfully employed in the past to characterize the different fractions of prescribed source distributions ('parents') that characterize a derived sample or set of samples ('daughters'). Second, we propose the use of 'bottom-up' methods, previously used primarily for grain size distributions, to model parent distributions and the abundances of these parents within a set of daughters. We demonstrate the utility of both top-down and bottom-up approaches to unmixing detrital geochronologic data within a well-constrained sediment routing system in central California. Use of a variety of goodness-of-fit metrics in top-down modeling reveals the importance of considering the range of allowable that is well mixed over any single best-fit mixture calculation. Bottom-up modeling of 12 daughter samples from beaches and submarine canyons yields modeled parent distributions that are remarkably similar to those expected from the geologic context of the sediment-routing system. In general, mixture modeling has the potential to supplement more widely applied approaches in comparing detrital geochronologic data by casting differences between samples as differing proportions of geologically meaningful end-member provenance categories.

Comparison of receptor models for source apportionment of the PM10 in Zaragoza (Spain).

PubMed

Callén, M S; de la Cruz, M T; López, J M; Navarro, M V; Mastral, A M

2009-08-01

Receptor models are useful to understand the chemical and physical characteristics of air pollutants by identifying their sources and by estimating contributions of each source to receptor concentrations. In this work, three receptor models based on principal component analysis with absolute principal component scores (PCA-APCS), Unmix and positive matrix factorization (PMF) were applied to study for the first time the apportionment of the airborne particulate matter less or equal than 10microm (PM10) in Zaragoza, Spain, during 1year sampling campaign (2003-2004). The PM10 samples were characterized regarding their concentrations in inorganic components: trace elements and ions and also organic components: polycyclic aromatic hydrocarbons (PAH) not only in the solid phase but also in the gas phase. A comparison of the three receptor models was carried out in order to do a more robust characterization of the PM10. The three models predicted that the major sources of PM10 in Zaragoza were related to natural sources (60%, 75% and 47%, respectively, for PCA-APCS, Unmix and PMF) although anthropogenic sources also contributed to PM10 (28%, 25% and 39%). With regard to the anthropogenic sources, while PCA and PMF allowed high discrimination in the sources identification associated with different combustion sources such as traffic and industry, fossil fuel, biomass and fuel-oil combustion, heavy traffic and evaporative emissions, the Unmix model only allowed the identification of industry and traffic emissions, evaporative emissions and heavy-duty vehicles. The three models provided good correlations between the experimental and modelled PM10 concentrations with major precision and the closest agreement between the PMF and PCA models.

ℓ0 -based sparse hyperspectral unmixing using spectral information and a multi-objectives formulation

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei; Pan, Bin

2018-07-01

Sparse unmixing aims at recovering pure materials from hyperpspectral images and estimating their abundance fractions. Sparse unmixing is actually ℓ0 problem which is NP-h ard, and a relaxation is often used. In this paper, we attempt to deal with ℓ0 problem directly via a multi-objective based method, which is a non-convex manner. The characteristics of hyperspectral images are integrated into the proposed method, which leads to a new spectra and multi-objective based sparse unmixing method (SMoSU). In order to solve the ℓ0 norm optimization problem, the spectral library is encoded in a binary vector, and a bit-wise flipping strategy is used to generate new individuals in the evolution process. However, a multi-objective method usually produces a number of non-dominated solutions, while sparse unmixing requires a single solution. How to make the final decision for sparse unmixing is challenging. To handle this problem, we integrate the spectral characteristic of hyperspectral images into SMoSU. By considering the spectral correlation in hyperspectral data, we improve the Tchebycheff decomposition function in SMoSU via a new regularization item. This regularization item is able to enforce the individual divergence in the evolution process of SMoSU. In this way, the diversity and convergence of population is further balanced, which is beneficial to the concentration of individuals. In the experiments part, three synthetic datasets and one real-world data are used to analyse the effectiveness of SMoSU, and several state-of-art sparse unmixing algorithms are compared.

Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2015-10-01

In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.

Terahertz spectral unmixing based method for identifying gastric cancer

NASA Astrophysics Data System (ADS)

Cao, Yuqi; Huang, Pingjie; Li, Xian; Ge, Weiting; Hou, Dibo; Zhang, Guangxin

2018-02-01

At present, many researchers are exploring biological tissue inspection using terahertz time-domain spectroscopy (THz-TDS) techniques. In this study, based on a modified hard modeling factor analysis method, terahertz spectral unmixing was applied to investigate the relationships between the absorption spectra in THz-TDS and certain biomarkers of gastric cancer in order to systematically identify gastric cancer. A probability distribution and box plot were used to extract the distinctive peaks that indicate carcinogenesis, and the corresponding weight distributions were used to discriminate the tissue types. The results of this work indicate that terahertz techniques have the potential to detect different levels of cancer, including benign tumors and polyps.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

SOURCE APPORTIONMENT RESULTS, UNCERTAINTIES, AND MODELING TOOLS

EPA Science Inventory

Advanced multivariate receptor modeling tools are available from the U.S. Environmental Protection Agency (EPA) that use only speciated sample data to identify and quantify sources of air pollution. EPA has developed both EPA Unmix and EPA Positive Matrix Factorization (PMF) and ...

Spectral Unmixing Based Construction of Lunar Mineral Abundance Maps

NASA Astrophysics Data System (ADS)

Bernhardt, V.; Grumpe, A.; Wöhler, C.

2017-07-01

In this study we apply a nonlinear spectral unmixing algorithm to a nearly global lunar spectral reflectance mosaic derived from hyper-spectral image data acquired by the Moon Mineralogy Mapper (M3) instrument. Corrections for topographic effects and for thermal emission were performed. A set of 19 laboratory-based reflectance spectra of lunar samples published by the Lunar Soil Characterization Consortium (LSCC) were used as a catalog of potential endmember spectra. For a given spectrum, the multi-population population-based incremental learning (MPBIL) algorithm was used to determine the subset of endmembers actually contained in it. However, as the MPBIL algorithm is computationally expensive, it cannot be applied to all pixels of the reflectance mosaic. Hence, the reflectance mosaic was clustered into a set of 64 prototype spectra, and the MPBIL algorithm was applied to each prototype spectrum. Each pixel of the mosaic was assigned to the most similar prototype, and the set of endmembers previously determined for that prototype was used for pixel-wise nonlinear spectral unmixing using the Hapke model, implemented as linear unmixing of the single-scattering albedo spectrum. This procedure yields maps of the fractional abundances of the 19 endmembers. Based on the known modal abundances of a variety of mineral species in the LSCC samples, a conversion from endmember abundances to mineral abundances was performed. We present maps of the fractional abundances of plagioclase, pyroxene and olivine and compare our results with previously published lunar mineral abundance maps.

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

PubMed

Kannan, R; Ievlev, A V; Laanait, N; Ziatdinov, M A; Vasudevan, R K; Jesse, S; Kalinin, S V

2018-01-01

Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

Electrotransport-induced unmixing and decomposition of ternary oxides

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

Chun, Jakyu; Yoo, Han-Ill, E-mail: hiyoo@snu.ac.kr; Martin, Manfred

A general expectation is that in a uniform oxygen activity atmosphere, cation electrotransport induces a ternary or higher oxide, e.g., AB{sub 1+ξ}O{sub 3+δ}, to kinetically unmix unless the electrochemical mobilities of, say, A{sup 2+}and B{sup 4+} cations are identically equal, and eventually to decompose into the component oxides AO and BO{sub 2} once the extent of unmixing exceeds the stability range of its nonmolecularity ξ. It has, however, earlier been reported [Yoo et al., Appl. Phys. Lett. 92, 252103 (2008)] that even a massive cation electrotransport induces BaTiO{sub 3} to neither unmix nor decompose even at a voltage far exceedingmore » the so-called decomposition voltage U{sub d}, a measure of the standard formation free energy of the oxide (|ΔG{sub f}{sup o}| = nFU{sub d}). Here, we report that as expected, NiTiO{sub 3} unmixes at any voltage and even decomposes if the voltage applied exceeds seemingly a threshold value larger than U{sub d}. We demonstrate experimentally that the electrochemical mobilities of Ni{sup 2+} and Ti{sup 4+} should be necessarily unequal for unmixing. Also, we show theoretically that equal cation mobilities appear to be a sufficiency for BaTiO{sub 3} only for a thermodynamic reason.« less

Multi-objective based spectral unmixing for hyperspectral images

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei

2017-02-01

Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

EPA Unmix 6.0 Fundamentals & User Guide

EPA Pesticide Factsheets

Unmix seeks to solve the general mixture problem where the data are assumed to be a linear combination of an unknown number of sources of unknown composition, which contribute an unknown amount to each sample.

A novel highly parallel algorithm for linearly unmixing hyperspectral images

NASA Astrophysics Data System (ADS)

Guerra, Raúl; López, Sebastián.; Callico, Gustavo M.; López, Jose F.; Sarmiento, Roberto

2014-10-01

Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operations involved in these time-consuming processes. This work proposes an algorithm to estimate the endmembers of a hyperspectral image under analysis and its abundances at the same time. The main advantage of this algorithm is its high parallelization degree and the mathematical simplicity of the operations implemented. This algorithm estimates the endmembers as virtual pixels. In particular, the proposed algorithm performs the descent gradient method to iteratively refine the endmembers and the abundances, reducing the mean square error, according with the linear unmixing model. Some mathematical restrictions must be added so the method converges in a unique and realistic solution. According with the algorithm nature, these restrictions can be easily implemented. The results obtained with synthetic images demonstrate the well behavior of the algorithm proposed. Moreover, the results obtained with the well-known Cuprite dataset also corroborate the benefits of our proposal.

Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms using Gamma Markov Random Fields

DOE PAGES

Altmann, Yoann; Maccarone, Aurora; McCarthy, Aongus; ...

2017-05-10

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the mainmore » materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).« less

Sparsely-sampled hyperspectral stimulated Raman scattering microscopy: a theoretical investigation

NASA Astrophysics Data System (ADS)

Lin, Haonan; Liao, Chien-Sheng; Wang, Pu; Huang, Kai-Chih; Bouman, Charles A.; Kong, Nan; Cheng, Ji-Xin

2017-02-01

A hyperspectral image corresponds to a data cube with two spatial dimensions and one spectral dimension. Through linear un-mixing, hyperspectral images can be decomposed into spectral signatures of pure components as well as their concentration maps. Due to this distinct advantage on component identification, hyperspectral imaging becomes a rapidly emerging platform for engineering better medicine and expediting scientific discovery. Among various hyperspectral imaging techniques, hyperspectral stimulated Raman scattering (HSRS) microscopy acquires data in a pixel-by-pixel scanning manner. Nevertheless, current image acquisition speed for HSRS is insufficient to capture the dynamics of freely moving subjects. Instead of reducing the pixel dwell time to achieve speed-up, which would inevitably decrease signal-to-noise ratio (SNR), we propose to reduce the total number of sampled pixels. Location of sampled pixels are carefully engineered with triangular wave Lissajous trajectory. Followed by a model-based image in-painting algorithm, the complete data is recovered for linear unmixing. Simulation results show that by careful selection of trajectory, a fill rate as low as 10% is sufficient to generate accurate linear unmixing results. The proposed framework applies to any hyperspectral beam-scanning imaging platform which demands high acquisition speed.

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

Calder, Stuart A; Cao, Guixin; Okamoto, Satoshi

The J_eff=1/2 state is manifested in systems with large cubic crystal field splitting and spin-orbit coupling that are comparable to the on-site Coulomb interaction, U. 5d transition metal oxides host parameters in this regime and strong evidence for this state in Sr2IrO4, and additional iridates, has been presented. All the candidates, however, deviate from the cubic crystal field required to provide an unmixed canonical J_eff=1/2 state, impacting the development of a robust model of this novel insulating and magnetic state. We present experimental and theoretical results that not only show Ca4IrO6 hosts the state, but furthermore uniquely resides in themore » limit required for a canonical unmixed J_eff=1/2 state.« less

PM2.5 pollution from household solid fuel burning practices in Central India: 2. Application of receptor models for source apportionment.

PubMed

Matawle, Jeevan Lal; Pervez, Shamsh; Deb, Manas Kanti; Shrivastava, Anjali; Tiwari, Suresh

2018-02-01

USEPA's UNMIX, positive matrix factorization (PMF) and effective variance-chemical mass balance (EV-CMB) receptor models were applied to chemically speciated profiles of 125 indoor PM 2.5 measurements, sampled longitudinally during 2012-2013 in low-income group households of Central India which uses solid fuels for cooking practices. Three step source apportionment studies were carried out to generate more confident source characterization. Firstly, UNMIX6.0 extracted initial number of source factors, which were used to execute PMF5.0 to extract source-factor profiles in second step. Finally, factor analog locally derived source profiles were supplemented to EV-CMB8.2 with indoor receptor PM 2.5 chemical profile to evaluate source contribution estimates (SCEs). The results of combined use of three receptor models clearly describe that UNMIX and PMF are useful tool to extract types of source categories within small receptor dataset and EV-CMB can pick those locally derived source profiles for source apportionment which are analog to PMF-extracted source categories. The source apportionment results have also shown three fold higher relative contribution of solid fuel burning emissions to indoor PM 2.5 compared to those measurements reported for normal households with LPG stoves. The previously reported influential source marker species were found to be comparatively similar to those extracted from PMF fingerprint plots. The comparison between PMF and CMB SCEs results were also found to be qualitatively similar. The performance fit measures of all three receptor models were cross-verified and validated and support each other to gain confidence in source apportionment results.

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.

Spectral Unmixing Modeling of the Aristarchus Pyroclastic Deposit: Assessing the Eruptive History of Glass-Rich Regional Lunar Pyroclastic Deposits

NASA Astrophysics Data System (ADS)

Jawin, E. R.; Head, J. W., III; Cannon, K.

2017-12-01

The Aristarchus pyroclastic deposit in central Oceanus Procellarum is understood to have formed in a gas-rich explosive volcanic eruption, and has been observed to contain abundant volcanic glass. However, the interpreted color (and therefore composition) of the glass has been debated. In addition, previous analyses of the pyroclastic deposit have been performed using lower resolution data than are currently available. In this work, a nonlinear spectral unmixing model was applied to Moon Mineralogy Mapper (M3) data of the Aristarchus plateau to investigate the detailed mineralogic and crystalline nature of the Aristarchus pyroclastic deposit by using spectra of laboratory endmembers including a suite of volcanic glasses returned from the Apollo 15 and 17 missions (green, orange, black beads), as well as synthetic lunar glasses (orange, green, red, yellow). Preliminary results of the M3 unmixing model suggest that spectra of the pyroclastic deposit can be modeled by a mixture composed predominantly of a featureless endmember approximating space weathering and a smaller component of glass. The modeled spectra were most accurate with a synthetic orange glass endmember, relative to the other glasses analyzed in this work. The results confirm that there is a detectable component of glass in the Aristarchus pyroclastic deposit which may be similar to the high-Ti orange glass seen in other regional pyroclastic deposits, with only minimal contributions of other crystalline minerals. The presence of volcanic glass in the pyroclastic deposit, with the low abundance of crystalline material, would support the model that the Aristarchus pyroclastic deposit formed in a long-duration, hawaiian-style fire fountain eruption. No significant detection of devitrified black beads in the spectral modeling results (as was observed at the Apollo 17 landing site in the Taurus-Littrow pyroclastic deposit), suggests the optical density of the eruptive plume remained low throughout the eruption.

Use of airborne hyperspectral data to estimate residual heavy metal contamination and acidification potential in the Guadiamar floodplain Andalusia, Spain after the Aznacollar mining accident

NASA Astrophysics Data System (ADS)

Kemper, Thomas; Sommer, Stefan

2004-10-01

Field and airborne hyperspectral data was used to map residual contamination after a mining accident, by applying spectral mixture modelling. Test case was the Aznalcollar Mine (Southern Spain) accident, where heavy metal bearing sludge from a tailings pond was distributed over large areas of the Guadiamar flood plain. Although the sludge and the contaminated topsoils have been removed mechanically in the whole affected area, still high abundance of pyritic material remained on the ground. During dedicated field campaigns in two subsequent years soil samples were collected for geochemical and spectral laboratory analysis and spectral field measurements were carried out in parallel to data acquisition with the HyMap sensor. A Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) tool was used providing possibilities of multiple endmember unmixing, aiming to estimate the quantities and distribution of the remaining tailings material. A spectrally based zonal partition of the area was introduced to allow the application of different submodels to the selected areas. Based on an iterative feedback process, the unmixing performance could be improved in each stage until an optimum level was reached. The sludge abundances obtained by unmixing the hyperspectral spectral data were confirmed by the field observations and chemical measurements of samples taken in the area. The semi-quantitative sludge abundances of residual pyritic material could be transformed into quantitative information for an assessment of acidification risk and distribution of residual heavy metal contamination based on an artificial mixture experiment. The unmixing of the second year images allowed identification of secondary minerals of pyrite as indicators of pyrite oxidation and associated acidification.

Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning.

PubMed

Pisharady, Pramod Kumar; Sotiropoulos, Stamatios N; Duarte-Carvajalino, Julio M; Sapiro, Guillermo; Lenglet, Christophe

2018-02-15

We present a sparse Bayesian unmixing algorithm BusineX: Bayesian Unmixing for Sparse Inference-based Estimation of Fiber Crossings (X), for estimation of white matter fiber parameters from compressed (under-sampled) diffusion MRI (dMRI) data. BusineX combines compressive sensing with linear unmixing and introduces sparsity to the previously proposed multiresolution data fusion algorithm RubiX, resulting in a method for improved reconstruction, especially from data with lower number of diffusion gradients. We formulate the estimation of fiber parameters as a sparse signal recovery problem and propose a linear unmixing framework with sparse Bayesian learning for the recovery of sparse signals, the fiber orientations and volume fractions. The data is modeled using a parametric spherical deconvolution approach and represented using a dictionary created with the exponential decay components along different possible diffusion directions. Volume fractions of fibers along these directions define the dictionary weights. The proposed sparse inference, which is based on the dictionary representation, considers the sparsity of fiber populations and exploits the spatial redundancy in data representation, thereby facilitating inference from under-sampled q-space. The algorithm improves parameter estimation from dMRI through data-dependent local learning of hyperparameters, at each voxel and for each possible fiber orientation, that moderate the strength of priors governing the parameter variances. Experimental results on synthetic and in-vivo data show improved accuracy with a lower uncertainty in fiber parameter estimates. BusineX resolves a higher number of second and third fiber crossings. For under-sampled data, the algorithm is also shown to produce more reliable estimates. Copyright © 2017 Elsevier Inc. All rights reserved.

SOURCE APPORTIONMENT OF PM2.5 AT AN URBAN IMPROVE SITE IN SEATTLE, WA

EPA Science Inventory

The multivariate receptor models Positive Matrix Factorization (PMF) and Unmix were used along with EPA's Chemical Mass Balance model to deduce the sources of PM2.5 at a centrally located urban site in Seattle, Washington. A total of 289 filter samples were obtained with an IM...

A novel edge-preserving nonnegative matrix factorization method for spectral unmixing

NASA Astrophysics Data System (ADS)

Bao, Wenxing; Ma, Ruishi

2015-12-01

Spectral unmixing technique is one of the key techniques to identify and classify the material in the hyperspectral image processing. A novel robust spectral unmixing method based on nonnegative matrix factorization(NMF) is presented in this paper. This paper used an edge-preserving function as hypersurface cost function to minimize the nonnegative matrix factorization. To minimize the hypersurface cost function, we constructed the updating functions for signature matrix of end-members and abundance fraction respectively. The two functions are updated alternatively. For evaluation purpose, synthetic data and real data have been used in this paper. Synthetic data is used based on end-members from USGS digital spectral library. AVIRIS Cuprite dataset have been used as real data. The spectral angle distance (SAD) and abundance angle distance(AAD) have been used in this research for assessment the performance of proposed method. The experimental results show that this method can obtain more ideal results and good accuracy for spectral unmixing than present methods.

Geometric Mixing, Peristalsis, and the Geometric Phase of the Stomach.

PubMed

Arrieta, Jorge; Cartwright, Julyan H E; Gouillart, Emmanuelle; Piro, Nicolas; Piro, Oreste; Tuval, Idan

2015-01-01

Mixing fluid in a container at low Reynolds number--in an inertialess environment--is not a trivial task. Reciprocating motions merely lead to cycles of mixing and unmixing, so continuous rotation, as used in many technological applications, would appear to be necessary. However, there is another solution: movement of the walls in a cyclical fashion to introduce a geometric phase. We show using journal-bearing flow as a model that such geometric mixing is a general tool for using deformable boundaries that return to the same position to mix fluid at low Reynolds number. We then simulate a biological example: we show that mixing in the stomach functions because of the "belly phase," peristaltic movement of the walls in a cyclical fashion introduces a geometric phase that avoids unmixing.

Geometric Mixing, Peristalsis, and the Geometric Phase of the Stomach

PubMed Central

Arrieta, Jorge; Cartwright, Julyan H. E.; Gouillart, Emmanuelle; Piro, Nicolas; Piro, Oreste; Tuval, Idan

2015-01-01

Mixing fluid in a container at low Reynolds number— in an inertialess environment—is not a trivial task. Reciprocating motions merely lead to cycles of mixing and unmixing, so continuous rotation, as used in many technological applications, would appear to be necessary. However, there is another solution: movement of the walls in a cyclical fashion to introduce a geometric phase. We show using journal-bearing flow as a model that such geometric mixing is a general tool for using deformable boundaries that return to the same position to mix fluid at low Reynolds number. We then simulate a biological example: we show that mixing in the stomach functions because of the “belly phase,” peristaltic movement of the walls in a cyclical fashion introduces a geometric phase that avoids unmixing. PMID:26154384

Linear unmixing of multidate hyperspectral imagery for crop yield estimation

USDA-ARS?s Scientific Manuscript database

In this paper, we have evaluated an unsupervised unmixing approach, vertex component analysis (VCA), for the application of crop yield estimation. The results show that abundance maps of the vegetation extracted by the approach are strongly correlated to the yield data (the correlation coefficients ...

A fast fully constrained geometric unmixing of hyperspectral images

NASA Astrophysics Data System (ADS)

Zhou, Xin; Li, Xiao-run; Cui, Jian-tao; Zhao, Liao-ying; Zheng, Jun-peng

2014-11-01

A great challenge in hyperspectral image analysis is decomposing a mixed pixel into a collection of endmembers and their corresponding abundance fractions. This paper presents an improved implementation of Barycentric Coordinate approach to unmix hyperspectral images, integrating with the Most-Negative Remove Projection method to meet the abundance sum-to-one constraint (ASC) and abundance non-negativity constraint (ANC). The original barycentric coordinate approach interprets the endmember unmixing problem as a simplex volume ratio problem, which is solved by calculate the determinants of two augmented matrix. One consists of all the members and the other consist of the to-be-unmixed pixel and all the endmembers except for the one corresponding to the specific abundance that is to be estimated. In this paper, we first modified the algorithm of Barycentric Coordinate approach by bringing in the Matrix Determinant Lemma to simplify the unmixing process, which makes the calculation only contains linear matrix and vector operations. So, the matrix determinant calculation of every pixel, as the original algorithm did, is avoided. By the end of this step, the estimated abundance meet the ASC constraint. Then, the Most-Negative Remove Projection method is used to make the abundance fractions meet the full constraints. This algorithm is demonstrated both on synthetic and real images. The resulting algorithm yields the abundance maps that are similar to those obtained by FCLS, while the runtime is outperformed as its computational simplicity.

Unmixing Magnetic Hysteresis Loops

NASA Astrophysics Data System (ADS)

Heslop, D.; Roberts, A. P.

2012-04-01

Magnetic hysteresis loops provide important information in rock and environmental magnetic studies. Natural samples often contain an assemblage of magnetic particles composed of components with different origins. Each component potentially carries important environmental information. Hysteresis loops, however, provide information concerning the bulk magnetic assemblage, which makes it difficult to isolate the specific contributions from different sources. For complex mineral assemblages an unmixing strategy with which to separate hysteresis loops into their component parts is therefore essential. Previous methods to unmix hysteresis data have aimed at separating individual loops into their constituent parts using libraries of type-curves thought to correspond to specific mineral types. We demonstrate an alternative approach, which rather than decomposing a single loop into monomineralic contributions, examines a collection of loops to determine their constituent source materials. These source materials may themselves be mineral mixtures, but they provide a genetically meaningful decomposition of a magnetic assemblage in terms of the processes that controlled its formation. We show how an empirically derived hysteresis mixing space can be created, without resorting to type-curves, based on the co-variation within a collection of measured loops. Physically realistic end-members, which respect the expected behaviour and symmetries of hysteresis loops, can then be extracted from the mixing space. These end-members allow the measured loops to be described as a combination of invariant parts that are assumed to represent the different sources in the mixing model. Particular attention is paid to model selection and estimating the complexity of the mixing model, specifically, how many end-members should be included. We demonstrate application of this approach using lake sediments from Butte Valley, northern California. Our method successfully separates the hysteresis loops into sources with a variety of terrigenous and authigenic origins.

Bulk mineralogy of the NE Syrtis and Jezero crater regions of Mars derived through thermal infrared spectral analyses

NASA Astrophysics Data System (ADS)

Salvatore, M. R.; Goudge, T. A.; Bramble, M. S.; Edwards, C. S.; Bandfield, J. L.; Amador, E. S.; Mustard, J. F.; Christensen, P. R.

2018-02-01

We investigated the area to the northwest of the Isidis impact basin (hereby referred to as "NW Isidis") using thermal infrared emission datasets to characterize and quantify bulk surface mineralogy throughout this region. This area is home to Jezero crater and the watershed associated with its two deltaic deposits in addition to NE Syrtis and the strong and diverse visible/near-infrared spectral signatures observed in well-exposed stratigraphic sections. The spectral signatures throughout this region show a diversity of primary and secondary surface mineralogies, including olivine, pyroxene, smectite clays, sulfates, and carbonates. While previous thermal infrared investigations have sought to characterize individual mineral groups within this region, none have systematically assessed bulk surface mineralogy and related these observations to visible/near-infrared studies. We utilize an iterative spectral unmixing method to statistically evaluate our linear thermal infrared spectral unmixing models to derive surface mineralogy. All relevant primary and secondary phases identified in visible/near-infrared studies are included in the unmixing models and their modeled spectral contributions are discussed in detail. While the stratigraphy and compositional diversity observed in visible/near-infrared spectra are much better exposed and more diverse than most other regions of Mars, our thermal infrared analyses suggest the dominance of basaltic compositions with less observed variability in the amount and diversity of alteration phases. These results help to constrain the mineralogical context of these previously reported visible/near-infrared spectral identifications. The results are also discussed in the context of future in situ investigations, as the NW Isidis region has long been promoted as a region of paleoenvironmental interest on Mars.

Applying spectral unmixing and support vector machine to airborne hyperspectral imagery for detecting giant reed

USDA-ARS?s Scientific Manuscript database

This study evaluated linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and support vector machine (SVM) techniques for detecting and mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern ...

Retrieving the hydrous minerals on Mars by sparse unmixing and the Hapke model using MRO/CRISM data

NASA Astrophysics Data System (ADS)

Lin, Honglei; Zhang, Xia

2017-05-01

The hydrous minerals on Mars preserve records of potential past aqueous activity. Quantitative information regarding mineralogical composition would enable a better understanding of the formation processes of these hydrous minerals, and provide unique insights into ancient habitable environments and the geological evolution of Mars. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has the advantage of both a high spatial and spectral resolution, which makes it suitable for the quantitative analysis of minerals on Mars. However, few studies have attempted to quantitatively retrieve the mineralogical composition of hydrous minerals on Mars using visible-infrared (VISIR) hyperspectral data due to their distribution characteristics (relatively low concentrations, located primarily in Noachian terrain, and unclear or unknown background minerals) and limitations of the spectral unmixing algorithms. In this study, we developed a modified sparse unmixing (MSU) method, combining the Hapke model with sparse unmixing. The MSU method considers the nonlinear mixed effects of minerals and avoids the difficulty of determining the spectra and number of endmembers from the image. The proposed method was tested successfully using laboratory mixture spectra and an Airborne Visible Infrared Imaging Spectrometer (AVIRIS) image of the Cuprite site (Nevada, USA). Then it was applied to CRISM hyperspectral images over Gale crater. Areas of hydrous mineral distribution were first identified by spectral features of water and hydroxyl absorption. The MSU method was performed on these areas, and the abundances were retrieved. The results indicated that the hydrous minerals consisted mostly of hydrous silicates, with abundances of up to 35%, as well as hydrous sulfates, with abundances ≤10%. Several main subclasses of hydrous minerals (e.g., Fe/Mg phyllosilicate, prehnite, and kieserite) were retrieved. Among these, Fe/Mg- phyllosilicate was the most abundant, with abundances ranging up to almost 30%, followed by prehnite and kieserite, with abundances lower than 15%. Our results are consistent with related research and in situ analyses of data from the rover Curiosity; thus, our method has the potential to be widely used for quantitative mineralogical mapping at the global scale of the surface of Mars.

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

NASA Astrophysics Data System (ADS)

Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

Encoding Strategy Changes and Spacing Effects in the Free Recall of Unmixed Lists

ERIC Educational Resources Information Center

Delaney, P.F.; Knowles, M.E.

2005-01-01

Memory for repeated items often improves when repetitions are separated by other items-a phenomenon called the spacing effect. In two experiments, we explored the complex interaction between study strategies, serial position, and spacing effects. When people studied several unmixed lists, they initially used mainly rote rehearsal, but some people…

Continental Spatio-Temporal Data Analysis with Linear Spectral Mixture Model Using FOSS

NASA Technical Reports Server (NTRS)

Kumar, Uttam; Nemani, Ramakrishna; Ganguly, Sangram; Milesi, Cristina; Raja, Kumar; Wang, Weile; Votava, Petr; Michaelis, Andrew

2015-01-01

This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS) unmixing model developed in C++ programming language with OpenCV package and boost C++ libraries in the NASA Earth Exchange (NEX). Visualization of the results is supported by GRASS GIS and statistical analysis is carried in R in a Linux system environment. FCLS was first tested on computer simulated data with Gaussian noise of various signal-to-noise ratio, and Landsat data of an agricultural scenario and an urban environment using a set of global end members of substrate (soils, sediments, rocks, and non-photosynthetic vegetation), vegetation that includes green photosynthetic plants and dark objects which encompasses absorptive substrate materials, clear water, deep shadows, etc. For the agricultural scenario, a spectrally diverse collection of 11 scenes of Level 1 terrain corrected, cloud free Landsat-5 TM data of Fresno, California, USA were unmixed and the results were validated with the corresponding ground data. To study an urbanized landscape, a clear sky Landsat-5 TM data were unmixed and validated with coincident World View-2 abundance maps (of 2 m spatial resolution) for an area of San Francisco, California, USA. The results were evaluated using descriptive statistics, correlation coefficient, RMSE, probability of success, boxplot and bivariate distribution function. Finally, FCLS was used for sub-pixel land cover analysis of the monthly WELD (Wen-enabled Landsat data) repository from 2008 to 2011 of North America. The abundance maps in conjunction with DMSP-OLS nighttime lights data were used to extract the urban land cover features and analyze their spatial-temporal growth.

Probability of Unmixed Young Groundwater (defined using chlorofluorocarbon-11 concentrations and tritium activities) in the Eagle River Watershed Valley-Fill Aquifer, Eagle County, North-Central Colorado, 2006-2007

USGS Publications Warehouse

Rupert, Michael G.; Plummer, Niel

2009-01-01

This raster data set delineates the predicted probability of unmixed young groundwater (defined using chlorofluorocarbon-11 concentrations and tritium activities) in groundwater in the Eagle River watershed valley-fill aquifer, Eagle County, North-Central Colorado, 2006-2007. This data set was developed by a cooperative project between the U.S. Geological Survey, Eagle County, the Eagle River Water and Sanitation District, the Town of Eagle, the Town of Gypsum, and the Upper Eagle Regional Water Authority. This project was designed to evaluate potential land-development effects on groundwater and surface-water resources so that informed land-use and water management decisions can be made. This groundwater probability map and its associated probability maps were developed as follows: (1) A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic (related to human activities) and hydrogeologic data by using a geographic information system to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Statistical models predicting the probability of elevated nitrate concentrations, the probability of unmixed young water (using chlorofluorocarbon-11 concentrations and tritium activities), and the probability of elevated volatile organic compound concentrations were developed using logistic regression techniques. (3) The statistical models were entered into a GIS and the probability map was constructed.

Continental Spatio-temporal Data Analysis with Linear Spectral Mixture Model using FOSS

NASA Astrophysics Data System (ADS)

Kumar, U.; Nemani, R. R.; Ganguly, S.; Milesi, C.; Raja, K. S.; Wang, W.; Votava, P.; Michaelis, A.

2015-12-01

This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS) unmixing model developed in C++ programming language with OpenCV package and boost C++ libraries in the NASA Earth Exchange (NEX). Visualization of the results is supported by GRASS GIS and statistical analysis is carried in R in a Linux system environment. FCLS was first tested on computer simulated data with Gaussian noise of various signal-to-noise ratio, and Landsat data of an agricultural scenario and an urban environment using a set of global endmembers of substrate (soils, sediments, rocks, and non-photosynthetic vegetation), vegetation that includes green photosynthetic plants and dark objects which encompasses absorptive substrate materials, clear water, deep shadows, etc. For the agricultural scenario, a spectrally diverse collection of 11 scenes of Level 1 terrain corrected, cloud free Landsat-5 TM data of Fresno, California, USA were unmixed and the results were validated with the corresponding ground data. To study an urbanized landscape, a clear sky Landsat-5 TM data were unmixed and validated with coincident World View-2 abundance maps (of 2 m spatial resolution) for an area of San Francisco, California, USA. The results were evaluated using descriptive statistics, correlation coefficient, RMSE, probability of success, boxplot and bivariate distribution function. Finally, FCLS was used for sub-pixel land cover analysis of the monthly WELD (Wen-enabled Landsat data) repository from 2008 to 2011 of North America. The abundance maps in conjunction with DMSP-OLS nighttime lights data were used to extract the urban land cover features and analyze their spatial-temporal growth.

Multiphoton spectral analysis of benzo[a]pyrene uptake and metabolism in a rat liver cell line

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

Barhoumi, Rola, E-mail: rmouneimne@cvm.tamu.edu; Mouneimne, Youssef; Ramos, Ernesto

2011-05-15

Dynamic analysis of the uptake and metabolism of polycyclic aromatic hydrocarbons (PAHs) and their metabolites within live cells in real time has the potential to provide novel insights into genotoxic and non-genotoxic mechanisms of cellular injury caused by PAHs. The present work, combining the use of metabolite spectra generated from metabolite standards using multiphoton spectral analysis and an 'advanced unmixing process', identifies and quantifies the uptake, partitioning, and metabolite formation of one of the most important PAHs (benzo[a]pyrene, BaP) in viable cultured rat liver cells over a period of 24 h. The application of the advanced unmixing process resulted inmore » the simultaneous identification of 8 metabolites in live cells at any single time. The accuracy of this unmixing process was verified using specific microsomal epoxide hydrolase inhibitors, glucuronidation and sulfation inhibitors as well as several mixtures of metabolite standards. Our findings prove that the two-photon microscopy imaging surpasses the conventional fluorescence imaging techniques and the unmixing process is a mathematical technique that seems applicable to the analysis of BaP metabolites in living cells especially for analysis of changes of the ultimate carcinogen benzo[a]pyrene-r-7,t-8-dihydrodiol-t-9,10-epoxide. Therefore, the combination of the two-photon acquisition with the unmixing process should provide important insights into the cellular and molecular mechanisms by which BaP and other PAHs alter cellular homeostasis.« less

On the Use of FOSS4G in Land Cover Fraction Estimation with Unmixing Algorithms

NASA Astrophysics Data System (ADS)

Kumar, U.; Milesi, C.; Raja, K.; Ganguly, S.; Wang, W.; Zhang, G.; Nemani, R. R.

2014-12-01

The popularity and usage of FOSS4G (FOSS for Geoinformatics) has increased drastically in the last two decades with increasing benefits that facilitate spatial data analysis, image processing, graphics and map production, spatial modeling and visualization. The objective of this paper is to use FOSS4G to implement and perform a quantitative analysis of three different unmixing algorithms: Constraint Least-Square (CLS), Unconstraint Least-Square, and Orthogonal Subspace Projection to estimate land cover (LC) fraction estimates from RS data. The LC fractions obtained by unmixing of mixed pixels represent mixture of more than one class per pixel rendering more accurate LC abundance estimates. The algorithms were implemented in C++ programming language with OpenCV package (http://opencv.org/) and boost C++ libraries (www.boost.org) in the NASA Earth Exchange at the NASA Advanced Supercomputing Facility. GRASS GIS was used for visualization of results and statistical analysis was carried in R in a Linux system environment. A set of global endmembers for substrate, vegetation and dark objects were used to unmix the data using the three algorithms and were compared with Singular Value decomposition unmixed outputs available in ENVI image processing software. First, computer simulated data of different signal to noise ratio were used to evaluate the algorithms. The second set of experiments was carried out in an agricultural set-up with a spectrally diverse collection of 11 Landsat-5 scenes (acquired in 2008) for an agricultural setup in Frenso, California and the ground data were collected on those specific dates when the satellite passed through the site. Finally, in the third set of experiments, a pair of coincident clear sky Landsat and World View 2 data for an urbanized area of San Francisco were used to assess the algorithm. Validation of the results using descriptive statistics, correlation coefficient (cc), RMSE, boxplot and bivariate distribution function indicated that with the computer simulated data, CLS was better than other techniques. With the real world data of an agricultural landscape, CLS was superior to other techniques with a mean absolute error for all four methods close to 7.3%. For the urban setup, CLS demonstrated highest average cc of 0.64 and lowest average RMSE of 0.19 for all the endmembers.

Quantitative detection of settled dust over green canopy

NASA Astrophysics Data System (ADS)

Brook, Anna

2016-04-01

The main task of environmental and geoscience applications are efficient and accurate quantitative classification of earth surfaces and spatial phenomena. In the past decade, there has been a significant interest in employing hyperspectral unmixing in order to retrieve accurate quantitative information latent in hyperspectral imagery data. Recently, the ground-truth and laboratory measured spectral signatures promoted by advanced algorithms are proposed as a new path toward solving the unmixing problem of hyperspectral imagery in semi-supervised fashion. This paper suggests that the sensitivity of sparse unmixing techniques provides an ideal approach to extract and identify dust settled over/upon green vegetation canopy using hyperspectral airborne data. Atmospheric dust transports a variety of chemicals, some of which pose a risk to the ecosystem and human health (Kaskaoutis, et al., 2008). Many studies deal with the impact of dust on particulate matter (PM) and atmospheric pollution. Considering the potential impact of industrial pollutants, one of the most important considerations is the fact that suspended PM can have both a physical and a chemical impact on plants, soils, and water bodies. Not only can the particles covering surfaces cause physical distortion, but particles of diverse origin and different chemistries can also serve as chemical stressors and cause irreversible damage. Sediment dust load in an indoor environment can be spectrally assessed using reflectance spectroscopy (Chudnovsky and Ben-Dor, 2009). Small amounts of particulate pollution that may carry a signature of a forthcoming environmental hazard are of key interest when considering the effects of pollution. According to the most basic distribution dynamics, dust consists of suspended particulate matter in a fine state of subdivision that are raised and carried by wind. In this context, it is increasingly important to first, understand the distribution dynamics of pollutants, and subsequently develop dedicated tools and measures to control and monitor pollutants in the free environment. The earliest effect of settled polluted dust particles is not always reflected through poor conditions of vegetation or soils, or any visible damages. In most of the cases, it has a quite long accumulation process that graduates from a polluted condition to long-term environmental hazard. Although conducted experiments with pollutant analog powders under controlled conditions have tended to confirm the findings from field studies (Brook, 2014), a major criticism of all these experiments is their short duration. The resulting conclusion is that it is difficult, if not impossible, to determine the implications of long-term exposure to realistic concentrations of pollutants from such short-term studies. Hyperspectral remote sensing (HRS) has become a common tool for environmental and geoscience applications. HRS has promoted new opportunities for exploring a wide range of materials and evaluating a variety of natural processes due to its detailed, specific, and extensive information on spectral and spatial disseminations. Hyperspectral unmixing (HU) is the technique of presuming the category type, which constitutes the mix-pixel, and its mixing ratio (Keshava and Mustard, 2002). In general, the task of unmixing is to decompose the reflectance spectrum of each pixel into a set of endmembers or principal combined spectra and their corresponding abundances (Bioucas-Dias et al., 2012). This study suggests that the sensitivity of sparse unmixing techniques provides an ideal approach to extract and identify dust settled over/upon green vegetation canopy using hyperspectral airborne data. Among the available techniques, this study present results of seven linear and non-linear unmixing algorithms: 1) Non-negative Matrix Factorization (NMF), 2) L1 sparsity-constrained NMF (L1-NMF), 3) L1/2 sparsity-constrained NMF (L1/2-NMF), 4) Graph regularized NMF (G-NMF), 5) Structured Sparse NMF (SS-NMF), 6) Alternating Least-Square (ALS), and 2) Lin's Projected Gradient (LPG). The performance is evaluated on real hyperspectral imagery data via detailed experimental assessment. The study showed that in certain compression tasks content-adapted sparse representation is provided by state-of-the-art solutions. The NMF algorithm estimates endmembers that are used to remove spurious information. If computationally feasible, it should include interaction terms to make the model more flexible. The optimal NMF algorithms, such as ALS and LPG, are assumed to be the simplest methods that achieve the minimum error on the test set. In summary, this work shows that sediment dust can be assessed using airborne HSI data, making it a potentially powerful tool for environmental studies. References Keshava, N., Mustard, J. (2002). Spectral unmixing. IEEE Signal Process. Mag., 19(1), 44-57. Chudnovsky, A., & Ben-Dor, E. (2009). Reflectance spectroscopy as a tool for settled dust monitoring in office environment. International Journal of Environment and Waste Management, 4(1), 32-49. Brook, A. (2014). Quantitative Detection of Settled dust over Green Canopy using Sparse Unmixing of Airborne Hyperspectral Data. IEEE-Whispers 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014, Switzerland, 4-8. Keshava, N., Mustard, J. (2002). Spectral unmixing. IEEE Signal Process. Mag., 19(1), 44-57. Bioucas-Dias et al. (2012). Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(2), 354 -379.

An Improved STARFM with Help of an Unmixing-Based Method to Generate High Spatial and Temporal Resolution Remote Sensing Data in Complex Heterogeneous Regions.

PubMed

Xie, Dengfeng; Zhang, Jinshui; Zhu, Xiufang; Pan, Yaozhong; Liu, Hongli; Yuan, Zhoumiqi; Yun, Ya

2016-02-05

Remote sensing technology plays an important role in monitoring rapid changes of the Earth's surface. However, sensors that can simultaneously provide satellite images with both high temporal and spatial resolution haven't been designed yet. This paper proposes an improved spatial and temporal adaptive reflectance fusion model (STARFM) with the help of an Unmixing-based method (USTARFM) to generate the high spatial and temporal data needed for the study of heterogeneous areas. The results showed that the USTARFM had higher accuracy than STARFM methods in two aspects of analysis: individual bands and of heterogeneity analysis. Taking the predicted NIR band as an example, the correlation coefficients (r) for the USTARFM, STARFM and unmixing methods were 0.96, 0.95, 0.90, respectively (p-value < 0.001); Root Mean Square Error (RMSE) values were 0.0245, 0.0300, 0.0401, respectively; and ERGAS values were 0.5416, 0.6507, 0.8737, respectively. The USTARM showed consistently higher performance than STARM when the degree of heterogeneity ranged from 2 to 10, highlighting that the use of this method provides the capacity to solve the data fusion problems faced when using STARFM. Additionally, the USTARFM method could help researchers achieve better performance than STARFM at a smaller window size from its heterogeneous land surface quantitative representation.

M-estimation for robust sparse unmixing of hyperspectral images

NASA Astrophysics Data System (ADS)

Toomik, Maria; Lu, Shijian; Nelson, James D. B.

2016-10-01

Hyperspectral unmixing methods often use a conventional least squares based lasso which assumes that the data follows the Gaussian distribution. The normality assumption is an approximation which is generally invalid for real imagery data. We consider a robust (non-Gaussian) approach to sparse spectral unmixing of remotely sensed imagery which reduces the sensitivity of the estimator to outliers and relaxes the linearity assumption. The method consists of several appropriate penalties. We propose to use an lp norm with 0 < p < 1 in the sparse regression problem, which induces more sparsity in the results, but makes the problem non-convex. On the other hand, the problem, though non-convex, can be solved quite straightforwardly with an extensible algorithm based on iteratively reweighted least squares. To deal with the huge size of modern spectral libraries we introduce a library reduction step, similar to the multiple signal classification (MUSIC) array processing algorithm, which not only speeds up unmixing but also yields superior results. In the hyperspectral setting we extend the traditional least squares method to the robust heavy-tailed case and propose a generalised M-lasso solution. M-estimation replaces the Gaussian likelihood with a fixed function ρ(e) that restrains outliers. The M-estimate function reduces the effect of errors with large amplitudes or even assigns the outliers zero weights. Our experimental results on real hyperspectral data show that noise with large amplitudes (outliers) often exists in the data. This ability to mitigate the influence of such outliers can therefore offer greater robustness. Qualitative hyperspectral unmixing results on real hyperspectral image data corroborate the efficacy of the proposed method.

Scalar entrainment in the mixing layer

NASA Technical Reports Server (NTRS)

Sandham, N. D.; Mungal, M. G.; Broadwell, J. E.; Reynolds, W. C.

1988-01-01

New definitions of entrainment and mixing based on the passive scalar field in the plane mixing layer are proposed. The definitions distinguish clearly between three fluid states: (1) unmixed fluid, (2) fluid engulfed in the mixing layer, trapped between two scalar contours, and (3) mixed fluid. The difference betwen (2) and (3) is the amount of fluid which has been engulfed during the pairing process, but has not yet mixed. Trends are identified from direct numerical simulations and extensions to high Reynolds number mixing layers are made in terms of the Broadwell-Breidenthal mixing model. In the limit of high Peclet number (Pe = ReSc) it is speculated that engulfed fluid rises in steps associated with pairings, introducing unmixed fluid into the large scale structures, where it is eventually mixed at the Kolmogorov scale. From this viewpoint, pairing is a prerequisite for mixing in the turbulent plane mixing layer.

Unmixing the SNCs: Chemical, Isotopic, and Petrologic Components of the Martian Meteorites

NASA Technical Reports Server (NTRS)

2002-01-01

This volume contains abstracts that have been accepted for presentation at the conference on Unmixing the SNCs: Chemical, Isotopic, and Petrologic Components of Martian Meteorites, September 11-12, 2002, in Houston, Texas. Administration and publications support for this meeting were provided by the staff of the Publications and Program Services Department at the Lunar and Planetary Institute.

A Gaussian Mixture Model Representation of Endmember Variability in Hyperspectral Unmixing

NASA Astrophysics Data System (ADS)

Zhou, Yuan; Rangarajan, Anand; Gader, Paul D.

2018-05-01

Hyperspectral unmixing while considering endmember variability is usually performed by the normal compositional model (NCM), where the endmembers for each pixel are assumed to be sampled from unimodal Gaussian distributions. However, in real applications, the distribution of a material is often not Gaussian. In this paper, we use Gaussian mixture models (GMM) to represent the endmember variability. We show, given the GMM starting premise, that the distribution of the mixed pixel (under the linear mixing model) is also a GMM (and this is shown from two perspectives). The first perspective originates from the random variable transformation and gives a conditional density function of the pixels given the abundances and GMM parameters. With proper smoothness and sparsity prior constraints on the abundances, the conditional density function leads to a standard maximum a posteriori (MAP) problem which can be solved using generalized expectation maximization. The second perspective originates from marginalizing over the endmembers in the GMM, which provides us with a foundation to solve for the endmembers at each pixel. Hence, our model can not only estimate the abundances and distribution parameters, but also the distinct endmember set for each pixel. We tested the proposed GMM on several synthetic and real datasets, and showed its potential by comparing it to current popular methods.

Spectral unmixing of hyperspectral data to map bauxite deposits

NASA Astrophysics Data System (ADS)

Shanmugam, Sanjeevi; Abhishekh, P. V.

2006-12-01

This paper presents a study about the potential of remote sensing in bauxite exploration in the Kolli hills of Tamilnadu state, southern India. ASTER image (acquired in the VNIR and SWIR regions) has been used in conjunction with SRTM - DEM in this study. A new approach of spectral unmixing of ASTER image data delineated areas rich in alumina. Various geological and geomorphological parameters that control bauxite formation were also derived from the ASTER image. All these information, when integrated, showed that there are 16 cappings (including the existing mines) that satisfy most of the conditions favouring bauxitization in the Kolli Hills. The study concludes that spectral unmixing of hyperspectral satellite data in the VNIR and SWIR regions may be combined with the terrain parameters to get accurate information about bauxite deposits, including their quality.

Investigation on Constrained Matrix Factorization for Hyperspectral Image Analysis

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for

SOURCE APPORTIONMENT OF SEATTLE PM 2.5: A COMPARISON OF IMPROVE AND ENHANCED STN DATA SETS

EPA Science Inventory

Seattle, WA, STN and IMPROVE data sets with STN temperature resolved carbon peaks were analyzed with both the PMF and Unmix receptor models. In addition, the IMPROVE trace element data was combined with the major STN species to examine the role of IMPROVE metals. To compare the ...

Chemical compositions and source identification of PM₂.₅ aerosols for estimation of a diesel source surrogate.

PubMed

Sahu, Manoranjan; Hu, Shaohua; Ryan, Patrick H; Le Masters, Grace; Grinshpun, Sergey A; Chow, Judith C; Biswas, Pratim

2011-06-01

Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach. Published by Elsevier B.V.

PM2.5 Source Apportionment: Reconciling Receptor Models for U.S. Nonurban and Urban Long-Term Networks.

PubMed

Chen, L-W Antony; Watson, John G; Chow, Judith C; DuBois, Dave W; Herschberger, Lisa

2011-11-01

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5 ) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM 2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM 2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps. [Box: see text].

Application of a combined approach including contamination indexes, geographic information system and multivariate statistical models in levels, distribution and sources study of metals in soils in Northern China

PubMed Central

Huang, Kuixian; Luo, Xingzhang

2018-01-01

The purpose of this study is to recognize the contamination characteristics of trace metals in soils and apportion their potential sources in Northern China to provide a scientific basis for basic of soil environment management and pollution control. The data set of metals for 12 elements in surface soil samples was collected. The enrichment factor and geoaccumulation index were used to identify the general geochemical characteristics of trace metals in soils. The UNMIX and positive matrix factorizations (PMF) models were comparatively applied to apportion their potential sources. Furthermore, geostatistical tools were used to study the spatial distribution of pollution characteristics and to identify the affected regions of sources that were derived from apportionment models. The soils were contaminated by Cd, Hg, Pb and Zn to varying degree. Industrial activities, agricultural activities and natural sources were identified as the potential sources determining the contents of trace metals in soils with contributions of 24.8%–24.9%, 33.3%–37.2% and 38.0%–41.8%, respectively. The slightly different results obtained from UNMIX and PMF might be caused by the estimations of uncertainty and different algorithms within the models. PMID:29474412

The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

NASA Astrophysics Data System (ADS)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China

NASA Astrophysics Data System (ADS)

Gu, Lingjia; Ren, Ruizhi; Zhao, Kai; Li, Xiaofeng

2014-01-01

The precision of snow parameter retrieval is unsatisfactory for current practical demands. The primary reason is because of the problem of mixed pixels that are caused by low spatial resolution of satellite passive microwave data. A snow passive microwave unmixing method is proposed in this paper, based on land cover type data and the antenna gain function of passive microwaves. The land cover type of Northeast China is partitioned into grass, farmland, bare soil, forest, and water body types. The component brightness temperatures (CBT), namely unmixed data, with 1 km data resolution are obtained using the proposed unmixing method. The snow depth determined by the CBT and three snow depth retrieval algorithms are validated through field measurements taken in forest and farmland areas of Northeast China in January 2012 and 2013. The results show that the overall of the retrieval precision of the snow depth is improved by 17% in farmland areas and 10% in forest areas when using the CBT in comparison with the mixed pixels. The snow cover results based on the CBT are compared with existing MODIS snow cover products. The results demonstrate that more snow cover information can be obtained with up to 86% accuracy.

Multi-tissue partial volume quantification in multi-contrast MRI using an optimised spectral unmixing approach.

PubMed

Collewet, Guylaine; Moussaoui, Saïd; Deligny, Cécile; Lucas, Tiphaine; Idier, Jérôme

2018-06-01

Multi-tissue partial volume estimation in MRI images is investigated with a viewpoint related to spectral unmixing as used in hyperspectral imaging. The main contribution of this paper is twofold. It firstly proposes a theoretical analysis of the statistical optimality conditions of the proportion estimation problem, which in the context of multi-contrast MRI data acquisition allows to appropriately set the imaging sequence parameters. Secondly, an efficient proportion quantification algorithm based on the minimisation of a penalised least-square criterion incorporating a regularity constraint on the spatial distribution of the proportions is proposed. Furthermore, the resulting developments are discussed using empirical simulations. The practical usefulness of the spectral unmixing approach for partial volume quantification in MRI is illustrated through an application to food analysis on the proving of a Danish pastry. Copyright © 2018 Elsevier Inc. All rights reserved.

Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis

NASA Astrophysics Data System (ADS)

Pu, Huangsheng; Zhang, Guanglei; He, Wei; Liu, Fei; Guang, Huizhi; Zhang, Yue; Bai, Jing; Luo, Jianwen

2014-09-01

It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.

Quantitative detection of settled coal dust over green canopy

NASA Astrophysics Data System (ADS)

Brook, Anna; Sahar, Nir

2017-04-01

The main task of environmental and geoscience applications are efficient and accurate quantitative classification of earth surfaces and spatial phenomena. In the past decade, there has been a significant interest in employing spectral unmixing in order to retrieve accurate quantitative information latent in in situ data. Recently, the ground-truth and laboratory measured spectral signatures promoted by advanced algorithms are proposed as a new path toward solving the unmixing problem in semi-supervised fashion. This study presents a practical implementation of field spectroscopy as a quantitative tool to detect settled coal dust over green canopy in free/open environment. Coal dust is a fine powdered form of coal, which is created by the crushing, grinding, and pulverizing of coal. Since the inelastic nature of coal, coal dust can be created during transportation, or by mechanically handling coal. Coal dust, categorized at silt-clay particle size, of particular concern due to heavy metals (lead, mercury, nickel, tin, cadmium, mercury, antimony, arsenic, isotopes of thorium and strontium) which are toxic also at low concentrations. This hazard exposes risk on both environment and public health. It has been identified by medical scientist around the world as causing a range of diseases and health problems, mainly heart and respiratory diseases like asthma and lung cancer. It is due to the fact that the fine invisible coal dust particles (less than 2.5 microns) long lodge in the lungs and are not naturally expelled, so long-term exposure increases the risk of health problems. Numerus studies reported that data to conduct study of geographic distribution of the very fine coal dust (smaller than PM 2.5) and related health impacts from coal exports, is not being collected. Sediment dust load in an indoor environment can be spectrally assessed using reflectance spectroscopy (Chudnovsky and Ben-Dor, 2009). Small amounts of particulate pollution that may carry a signature of a forthcoming environmental hazard are of key interest when considering the effects of pollution. According to the most basic distribution dynamics, dust consists of suspended particulate matter in a fine state of subdivision that are raised and carried by wind. In this context, it is increasingly important to first, understand the distribution dynamics of pollutants, and subsequently develop dedicated tools and measures to control and monitor pollutants in the free environment. The earliest effect of settled polluted dust particles is not always reflected through poor conditions of vegetation or soils, or any visible damages. In most of the cases, it has a quite long accumulation process that graduates from a polluted condition to long-term environmental and health related hazard. Although conducted experiments with pollutant analog powders under controlled conditions have tended to con- firm the findings from field studies (Brook, 2014; Brook and Ben-Dor 2016; Brook, 2016), a major criticism of all these experiments is their short duration. The resulting conclusion is that it is difficult, if not impossible, to determine the implications of long-term exposure to realistic concentrations of pollutants from such short-term studies. In general, the task of unmixing is to decompose the reflectance spectrum into a set of endmembers or principal combined spectra and their corresponding abundances (Bioucas-Dias et al., 2012). This study suggests that the sensitivity of sparse unmixing techniques provides an ideal approach to extract and identify coal dust settled over/upon green vegetation canopy using in situ spectral data collected by portable spectrometer. The optimal NMF algorithms, such as ALS and LPG, are assumed to be the simplest methods that achieve the minimum error. The suggested practical approach includes the following stages: 1. In situ spectral measurements, 2. Near-real-time spectral data analysis, 3. Estimated concentration of coal dust reported as mg/sq m. The stage 2 is completed by calculating: 1. Unmixing between the green canopy and the settle dust extraction only coal dust fraction, 2. Converting spectral feature of coal dust to concentration via PLSR spectral model. The spectral model was trained and validated PLSR model developed at laboratory using spectra across MIR (FTIR reflectance spectra) and NIR regions and XRD analysis. The obtained RMSE was satisfying for both spectral regions. Thus, it was concluded that field spectroscopy can be used for this purpose, and it can provide fully quantitative measures of settle coal dust. Nowadays this approach (both spectrometer and algorithm) has been accepted as a practical operational tool for environmental monitoring near power station Orot Rabin in Hadera and will be used by the Sharon-Carmel Districts Municipal Association for Environmental Protection, Israel as a regulatory tool. In summary, this work shows that coal dust can be assessed using in situ spectroscopy, making it a potentially powerful tool for environmental studies. References Chudnovsky, A., & Ben-Dor, E. (2009). Reflectance spectroscopy as a tool for settled dust monitoring in office environment. International Journal of Environment and Waste Management, 4(1), 32-49. Brook, A. (2014). Quantitative Detection of Settled dust over Green Canopy using Sparse Unmixing of Airborne Hyperspectral Data. IEEE-Whispers 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014, Switzerland, 4-8. Brook, A. and Ben-Dor, E. (2016). Quantitative detection of settled dust over Green Canopy using sparse unmixing of airborne hyperspectral data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(2), pp.884-897. Brook, A. (2016). Quantitative Detection and Long-Term Monitoring of Settle Dust Using Semisupervised Learning for Spectral Data. Water, Air, & Soil Pollution, 227(3), pp.1-9. Bioucas-Dias, J.M., Plaza, A., Dobigeon, N., Parente, M., Du, Q., Gader, P. and Chanussot, J. (2012). Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(2), pp.354-379. Keshava, N., Mustard, J. (2002). Spectral unmixing. IEEE Signal Process. Mag., 19(1), 44-57. Bioucas-Dias et al. (2012). Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(2), 354 -379.

Long-term retention as a function of word concreteness under conditions of free recall.

PubMed

Postman, L; Burns, S

1974-07-01

Acquisition and long-term retention of concrete (C) and abstract (A) words were investigated under conditions of multiple-trial free recall. Both unmixed and mixed lists were used in original learning. Retention was tested either 1 rain or 1 week after attainment of the learning criterion. Acquisition was faster and retention was higher for C than for A words. These differences were more pronounced for mixed than for unmixed lists.

Correlation between prescription of various dextropropoxyphene preparations and their involvement in fatal poisonings.

PubMed

Jonasson, U; Jonasson, B; Saldeen, T

1999-07-26

In Sweden, the frequency of fatal poisoning by dextropropoxyphene (DXP) ingestion is constantly high. There are seven preparations containing DXP on the Swedish market; in three of them DXP is the sole analgesic ingredient, while four of them are combinations of analgesics. In an attempt to assess the death rate attributable to each DXP preparation on the basis of toxicological analyses, altogether 834 cases of dextropropoxyphene-related death over a 5-year period (1992-1996) in Sweden have been reviewed. The ratio between number of fatal poisonings and prescription of defined daily dose/1000 inhabitants during a 12-month period (DDD) was determined. The highest ratio, 27, was attributed to unmixed preparations. The ratio for DXP + paracetamol-related deaths was 6.3, and for DXP + phenazone, 6.4, while the lowest ratio, 2, was found among the DXP + chlorzoxazone cases. The unmixed preparations, representing 26% of all DXP prescriptions during the study years, were implicated in 62% of the DXP fatalities, a considerable over-representation. Unmixed preparations, with their higher content of DXP, may be more attractive for many consumers because of their narcotic (euphoric) effects rather than for any analgetic superiority. Another possibility is that unmixed preparations may erroneously have been regarded as safer than when combined with paracetamol, as reports of poisoning with compounds containing DXP + paracetamol have been most frequently reported, probably due to their predominance on the market.

What Stroop tasks can tell us about selective attention from childhood to adulthood.

PubMed

Wright, Barlow C

2017-08-01

A rich body of research concerns causes of Stroop effects plus applications of Stroop. However, several questions remain. We included assessment of errors with children and adults (N = 316), who sat either a task wherein each block employed only trials of one type (unmixed task) or where every block comprised of a mix of the congruent, neutral, and incongruent trials. Children responded slower than adults and made more errors on each task. Contrary to some previous studies, interference (the difference between neutral and incongruent condition) showed no reaction time (RT) differences by group or task, although there were differences in errors. By contrast, facilitation (the difference between neutral and congruent condition) was greater in children than adults, and greater on the unmixed task than the mixed task. After considering a number of theoretical accounts, we settle on the inadvertent word-reading hypothesis, whereby facilitation stems from children and the unmixed task promoting inadvertent reading particularly in the congruent condition. Stability of interference RT is explained by fixed semantic differences between neutral and incongruent conditions, for children versus adults and for unmixed versus mixed task. We conclude that utilizing two tasks together may reveal more about how attention is affected in other groups. © 2016 The Authors. British Journal of Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

Zoning and exsolution in cumulate alkali feldspars from the eruption (12.9 Ka) of Laacher see volcano (Western Germany) as an indicator of time-scales and dynamics of carbonate-silicate unmixing

NASA Astrophysics Data System (ADS)

Sourav Rout, Smruti; Wörner, Gerhard

2017-04-01

Time-scales extracted from the detailed analysis of chemically zoned minerals provide insights into crystal ages, magma storage and compositional evolution, including mixing and unmixing events. This allows having a better understanding of pre-eruptive history of large and potentially dangerous magma chambers. We present a comprehensive study of chemical diffusion across zoning and exsolution patterns of alkali feldspars in carbonatite-bearing cognate syenites from the 6.3 km3 (D.R.E) phonolitic Laacher See Tephra (LST) eruption 12.9 ka ago. The Laacher See volcano is located in the Quaternary East Eifel volcanic field of the Paleozoic Rhenish Massif in Western Germany and has produced a compositionally variable sequence in a single eruption from a magma chamber that was zoned from mafic phonolite at the base to highly evolved, actively degassing phonolite magma at the top. Diffusion chronometry is applied to major and trace element compositions obtained on alkali feldspars from carbonate-bearing syenitic cumulates. Methods used were laser ablation inductively coupled plasma mass spectrometry (LA ICP-MS) in combination with energy-dispersive and wavelength-dispersive electron microprobe analyses (EDS & WDS-EMPA). The grey scale values extracted from multiple accumulations of back-scattered electron images represent the K/Na ratio owing to the extremely low concentrations of Ba and Sr (<30 ppm). The numerical grey scale profiles and the quantitative compositional profiles are anatomized using three different fitting models in MATLAB®, Mathematica® and Origin® to estimate related time-scales with minimized error for a temperature range of 750 deg C to 800 deg C (on the basis of existing experimental data on phase transition and phase separation). A distinctive uphill diffusive analysis is used specifically for the phase separation in the case of exsolution features (comprising of albite- and orthoclase-rich phases) in sanidines. The error values are aggregates of propagated error through calculations and the uncertainty in temperature values. Trace element compositional data of distinct feldspar compositions that are assumed to have grown before and after silicate-carbonate unmixing are used to estimate partition coefficients between carbonate and silicate melt. The resulting values correlate well with available experimental data from the literature. We will present a genetic model based on the compositional data on feldspar zonation for the process and timing of silicate-carbonate unmixing prior to eruption of the host phonolite magma.

Sensitive Dual Color in vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase

DTIC Science & Technology

2011-04-01

Sensitive Dual Color In Vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase Laura...20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that...spectral emissions using a suitable spectral unmixing algorithm . This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future

Unmixed fuel processors and methods for using the same

DOEpatents

Kulkarni, Parag Prakash; Cui, Zhe

2010-08-24

Disclosed herein are unmixed fuel processors and methods for using the same. In one embodiment, an unmixed fuel processor comprises: an oxidation reactor comprising an oxidation portion and a gasifier, a CO.sub.2 acceptor reactor, and a regeneration reactor. The oxidation portion comprises an air inlet, effluent outlet, and an oxygen transfer material. The gasifier comprises a solid hydrocarbon fuel inlet, a solids outlet, and a syngas outlet. The CO.sub.2 acceptor reactor comprises a water inlet, a hydrogen outlet, and a CO.sub.2 sorbent, and is configured to receive syngas from the gasifier. The regeneration reactor comprises a water inlet and a CO.sub.2 stream outlet. The regeneration reactor is configured to receive spent CO.sub.2 adsorption material from the gasification reactor and to return regenerated CO.sub.2 adsorption material to the gasification reactor, and configured to receive oxidized oxygen transfer material from the oxidation reactor and to return reduced oxygen transfer material to the oxidation reactor.

Spectral unmixing of multi-color tissue specific in vivo fluorescence in mice

NASA Astrophysics Data System (ADS)

Zacharakis, Giannis; Favicchio, Rosy; Garofalakis, Anikitos; Psycharakis, Stylianos; Mamalaki, Clio; Ripoll, Jorge

2007-07-01

Fluorescence Molecular Tomography (FMT) has emerged as a powerful tool for monitoring biological functions in vivo in small animals. It provides the means to determine volumetric images of fluorescent protein concentration by applying the principles of diffuse optical tomography. Using different probes tagged to different proteins or cells, different biological functions and pathways can be simultaneously imaged in the same subject. In this work we present a spectral unmixing algorithm capable of separating signal from different probes when combined with the tomographic imaging modality. We show results of two-color imaging when the algorithm is applied to separate fluorescence activity originating from phantoms containing two different fluorophores, namely CFSE and SNARF, with well separated emission spectra, as well as Dsred- and GFP-fused cells in F5-b10 transgenic mice in vivo. The same algorithm can furthermore be applied to tissue-specific spectroscopy data. Spectral analysis of a variety of organs from control, DsRed and GFP F5/B10 transgenic mice showed that fluorophore detection by optical systems is highly tissue-dependent. Spectral data collected from different organs can provide useful insight into experimental parameter optimisation (choice of filters, fluorophores, excitation wavelengths) and spectral unmixing can be applied to measure the tissue-dependency, thereby taking into account localized fluorophore efficiency. Summed up, tissue spectral unmixing can be used as criteria in choosing the most appropriate tissue targets as well as fluorescent markers for specific applications.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

a Maximum Entropy Model of the Bearded Capuchin Monkey Habitat Incorporating Topography and Spectral Unmixing Analysis

NASA Astrophysics Data System (ADS)

Howard, A. M.; Bernardes, S.; Nibbelink, N.; Biondi, L.; Presotto, A.; Fragaszy, D. M.; Madden, M.

2012-07-01

Movement patterns of bearded capuchin monkeys (Cebus (Sapajus) libidinosus) in northeastern Brazil are likely impacted by environmental features such as elevation, vegetation density, or vegetation type. Habitat preferences of these monkeys provide insights regarding the impact of environmental features on species ecology and the degree to which they incorporate these features in movement decisions. In order to evaluate environmental features influencing movement patterns and predict areas suitable for movement, we employed a maximum entropy modelling approach, using observation points along capuchin monkey daily routes as species presence points. We combined these presence points with spatial data on important environmental features from remotely sensed data on land cover and topography. A spectral mixing analysis procedure was used to generate fraction images that represent green vegetation, shade and soil of the study area. A Landsat Thematic Mapper scene of the area of study was geometrically and atmospherically corrected and used as input in a Minimum Noise Fraction (MNF) procedure and a linear spectral unmixing approach was used to generate the fraction images. These fraction images and elevation were the environmental layer inputs for our logistic MaxEnt model of capuchin movement. Our models' predictive power (test AUC) was 0.775. Areas of high elevation (>450 m) showed low probabilities of presence, and percent green vegetation was the greatest overall contributor to model AUC. This work has implications for predicting daily movement patterns of capuchins in our field site, as suitability values from our model may relate to habitat preference and facility of movement.

Estimating the formation age distribution of continental crust by unmixing zircon ages

NASA Astrophysics Data System (ADS)

Korenaga, Jun

2018-01-01

Continental crust provides first-order control on Earth's surface environment, enabling the presence of stable dry landmasses surrounded by deep oceans. The evolution of continental crust is important for atmospheric evolution, because continental crust is an essential component of deep carbon cycle and is likely to have played a critical role in the oxygenation of the atmosphere. Geochemical information stored in the mineral zircon, known for its resilience to diagenesis and metamorphism, has been central to ongoing debates on the genesis and evolution of continental crust. However, correction for crustal reworking, which is the most critical step when estimating original formation ages, has been incorrectly formulated, undermining the significance of previous estimates. Here I suggest a simple yet promising approach for reworking correction using the global compilation of zircon data. The present-day distribution of crustal formation age estimated by the new "unmixing" method serves as the lower bound to the true crustal growth, and large deviations from growth models based on mantle depletion imply the important role of crustal recycling through the Earth history.

Multispectral analysis tools can increase utility of RGB color images in histology

NASA Astrophysics Data System (ADS)

Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

2018-04-01

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Ejecta patterns of Meteor Crater, Arizona derived from the linear un-mixing of TIMS data and laboratory thermal emission spectra

NASA Technical Reports Server (NTRS)

Ramsey, Michael S.; Christensen, Philip R.

1992-01-01

Accurate interpretation of thermal infrared data depends upon the understanding and removal of complicating effects. These effects may include physical mixing of various mineralogies and particle sizes, atmospheric absorption and emission, surficial coatings, geometry effects, and differential surface temperatures. The focus is the examination of the linear spectral mixing of individual mineral or endmember spectra. Linear addition of spectra, for particles larger than the wavelength, allows for a straight-forward method of deconvolving the observed spectra, predicting a volume percent of each endmember. The 'forward analysis' of linear mixing (comparing the spectra of physical mixtures to numerical mixtures) has received much attention. The reverse approach of un-mixing thermal emission spectra was examined with remotely sensed data, but no laboratory verification exists. Understanding of the effects of spectral mixing on high resolution laboratory spectra allows for the extrapolation to lower resolution, and often more complicated, remotely gathered data. Thermal Infrared Multispectral Scanner (TIMS) data for Meteor Crater, Arizona were acquired in Sep. 1987. The spectral un-mixing of these data gives a unique test of the laboratory results. Meteor Crater (1.2 km in diameter and 180 m deep) is located in north-central Arizona, west of Canyon Diablo. The arid environment, paucity of vegetation, and low relief make the region ideal for remote data acquisition. Within the horizontal sedimentary sequence that forms the upper Colorado Plateau, the oldest unit sampled by the impact crater was the Permian Coconino Sandstone. A thin bed of the Toroweap Formation, also of Permian age, conformably overlays the Coconino. Above the Toroweap lies the Permian Kiabab Limestone which, in turn, is covered by a thin veneer of the Moenkopi Formation. The Moenkopi is Triassic in age and has two distinct sub-units in the vicinity of the crater. The lower Wupatki member is a fine-grained sandstone, while the upper Moqui member is a fissile siltstone. Ejecta from these units are preserved as inverted stratigraphy up to 2 crater radii from the rim. The mineralogical contrast between the units, relative lack of post-emplacement erosion and ejecta mixing provide a unique site to apply the un-mixing model. Selection of the aforementioned units as endmembers reveals distinct patterns in the ejecta of the crater.

Unmixing of spectral components affecting AVIRIS imagery of Tampa Bay

NASA Astrophysics Data System (ADS)

Carder, Kendall L.; Lee, Z. P.; Chen, Robert F.; Davis, Curtiss O.

1993-09-01

According to Kirk's as well as Morel and Gentili's Monte Carlo simulations, the popular simple expression, R approximately equals 0.33 bb/a, relating subsurface irradiance reflectance (R) to the ratio of the backscattering coefficient (bb) to absorption coefficient (a), is not valid for bb/a > 0.25. This means that it may no longer be valid for values of remote-sensing reflectance (above-surface ratio of water-leaving radiance to downwelling irradiance) where Rrs4/ > 0.01. Since there has been no simple Rrs expression developed for very turbid waters, we developed one based in part on Monte Carlo simulations and empirical adjustments to an Rrs model and applied it to rather turbid coastal waters near Tampa Bay to evaluate its utility for unmixing the optical components affecting the water- leaving radiance. With the high spectral (10 nm) and spatial (20 m2) resolution of Airborne Visible-InfraRed Imaging Spectrometer (AVIRIS) data, the water depth and bottom type were deduced using the model for shallow waters. This research demonstrates the necessity of further research to improve interpretations of scenes with highly variable turbid waters, and it emphasizes the utility of high spectral-resolution data as from AVIRIS for better understanding complicated coastal environments such as the west Florida shelf.

Generation, Validation, and Application of Abundance Map Reference Data for Spectral Unmixing

NASA Astrophysics Data System (ADS)

Williams, McKay D.

Reference data ("ground truth") maps traditionally have been used to assess the accuracy of imaging spectrometer classification algorithms. However, these reference data can be prohibitively expensive to produce, often do not include sub-pixel abundance estimates necessary to assess spectral unmixing algorithms, and lack published validation reports. Our research proposes methodologies to efficiently generate, validate, and apply abundance map reference data (AMRD) to airborne remote sensing scenes. We generated scene-wide AMRD for three different remote sensing scenes using our remotely sensed reference data (RSRD) technique, which spatially aggregates unmixing results from fine scale imagery (e.g., 1-m Ground Sample Distance (GSD)) to co-located coarse scale imagery (e.g., 10-m GSD or larger). We validated the accuracy of this methodology by estimating AMRD in 51 randomly-selected 10 m x 10 m plots, using seven independent methods and observers, including field surveys by two observers, imagery analysis by two observers, and RSRD using three algorithms. Results indicated statistically-significant differences between all versions of AMRD, suggesting that all forms of reference data need to be validated. Given these significant differences between the independent versions of AMRD, we proposed that the mean of all (MOA) versions of reference data for each plot and class were most likely to represent true abundances. We then compared each version of AMRD to MOA. Best case accuracy was achieved by a version of imagery analysis, which had a mean coverage area error of 2.0%, with a standard deviation of 5.6%. One of the RSRD algorithms was nearly as accurate, achieving a mean error of 3.0%, with a standard deviation of 6.3%, showing the potential of RSRD-based AMRD generation. Application of validated AMRD to specific coarse scale imagery involved three main parts: 1) spatial alignment of coarse and fine scale imagery, 2) aggregation of fine scale abundances to produce coarse scale imagery-specific AMRD, and 3) demonstration of comparisons between coarse scale unmixing abundances and AMRD. Spatial alignment was performed using our scene-wide spectral comparison (SWSC) algorithm, which aligned imagery with accuracy approaching the distance of a single fine scale pixel. We compared simple rectangular aggregation to coarse sensor point spread function (PSF) aggregation, and found that the PSF approach returned lower error, but that rectangular aggregation more accurately estimated true abundances at ground level. We demonstrated various metrics for comparing unmixing results to AMRD, including mean absolute error (MAE) and linear regression (LR). We additionally introduced reference data mean adjusted MAE (MA-MAE), and reference data confidence interval adjusted MAE (CIA-MAE), which account for known error in the reference data itself. MA-MAE analysis indicated that fully constrained linear unmixing of coarse scale imagery across all three scenes returned an error of 10.83% per class and pixel, with regression analysis yielding a slope = 0.85, intercept = 0.04, and R2 = 0.81. Our reference data research has demonstrated a viable methodology to efficiently generate, validate, and apply AMRD to specific examples of airborne remote sensing imagery, thereby enabling direct quantitative assessment of spectral unmixing performance.

Comparing performance of standard and iterative linear unmixing methods for hyperspectral signatures

NASA Astrophysics Data System (ADS)

Gault, Travis R.; Jansen, Melissa E.; DeCoster, Mallory E.; Jansing, E. David; Rodriguez, Benjamin M.

2016-05-01

Linear unmixing is a method of decomposing a mixed signature to determine the component materials that are present in sensor's field of view, along with the abundances at which they occur. Linear unmixing assumes that energy from the materials in the field of view is mixed in a linear fashion across the spectrum of interest. Traditional unmixing methods can take advantage of adjacent pixels in the decomposition algorithm, but is not the case for point sensors. This paper explores several iterative and non-iterative methods for linear unmixing, and examines their effectiveness at identifying the individual signatures that make up simulated single pixel mixed signatures, along with their corresponding abundances. The major hurdle addressed in the proposed method is that no neighboring pixel information is available for the spectral signature of interest. Testing is performed using two collections of spectral signatures from the Johns Hopkins University Applied Physics Laboratory's Signatures Database software (SigDB): a hand-selected small dataset of 25 distinct signatures from a larger dataset of approximately 1600 pure visible/near-infrared/short-wave-infrared (VIS/NIR/SWIR) spectra. Simulated spectra are created with three and four material mixtures randomly drawn from a dataset originating from SigDB, where the abundance of one material is swept in 10% increments from 10% to 90%with the abundances of the other materials equally divided amongst the remainder. For the smaller dataset of 25 signatures, all combinations of three or four materials are used to create simulated spectra, from which the accuracy of materials returned, as well as the correctness of the abundances, is compared to the inputs. The experiment is expanded to include the signatures from the larger dataset of almost 1600 signatures evaluated using a Monte Carlo scheme with 5000 draws of three or four materials to create the simulated mixed signatures. The spectral similarity of the inputs to the output component signatures is calculated using the spectral angle mapper. Results show that iterative methods significantly outperform the traditional methods under the given test conditions.

A randomized, double-blind, placebo-controlled trial of single-dose ciprofloxacin versus erythromycin for the treatment of chancroid in Nairobi, Kenya.

PubMed

Malonza, I M; Tyndall, M W; Ndinya-Achola, J O; Maclean, I; Omar, S; MacDonald, K S; Perriens, J; Orle, K; Plummer, F A; Ronald, A R; Moses, S

1999-12-01

A randomized, double-blind, placebo-controlled clinical trial was conducted in Nairobi, Kenya, to compare single-dose ciprofloxacin with a 7-day course of erythromycin for the treatment of chancroid. In all, 208 men and 37 women presenting with genital ulcers clinically compatible with chancroid were enrolled. Ulcer etiology was determined using culture techniques for chancroid, serology for syphilis, and a multiplex polymerase chain reaction for chancroid, syphilis, and herpes simplex virus (HSV). Ulcer etiology was 31% unmixed chancroid, 23% unmixed syphilis, 16% unmixed HSV, 15% mixed etiology, and 15% unknown. For 111 participants with chancroid, cure rates were 92% with ciprofloxacin and 91% with erythromycin. For all study participants, the treatment failure rate was 15%, mostly related to ulcer etiologies of HSV infection or syphilis, and treatment failure was 3 times more frequent in human immunodeficiency virus-infected subjects than in others, mostly owing to HSV infection. Ciprofloxacin is an effective single-dose treatment for chancroid, but current recommendations for empiric therapy of genital ulcers may result in high treatment failure due to HSV infection.

Mapping tropical rainforest canopies using multi-temporal spaceborne imaging spectroscopy

NASA Astrophysics Data System (ADS)

Somers, Ben; Asner, Gregory P.

2013-10-01

The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among coexisting species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection strategy in MESMA. Instead of using the same spectral subset to unmix each image pixel, our modified approach allowed the spectral subsets to vary on a per pixel basis such that each pixel is evaluated using a spectral subset tuned towards maximal separability of its specific endmember class combination or species mixture. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively demonstrated using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, our approach provided a more accurate tree species map compared to MESMA (Kappa = 0.54). In addition, by the selection of spectral subsets our approach was about 90% faster than MESMA. The flexible or adaptive use of band sets in spectral unmixing as such provides an interesting avenue to address spectral similarities in complex vegetation canopies.

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2004-01-01

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Ion-beam mixed ultra-thin cobalt suicide (CoSi2) films by cobalt sputtering and rapid thermal annealing

NASA Astrophysics Data System (ADS)

Kal, S.; Kasko, I.; Ryssel, H.

1995-10-01

The influence of ion-beam mixing on ultra-thin cobalt silicide (CoSi2) formation was investigated by characterizing the ion-beam mixed and unmixed CoSi2 films. A Ge+ ion-implantation through the Co film prior to silicidation causes an interface mixing of the cobalt film with the silicon substrate and results in improved silicide-to-silicon interface roughness. Rapid thermal annealing was used to form Ge+ ion mixed and unmixed thin CoSi2 layer from 10 nm sputter deposited Co film. The silicide films were characterized by secondary neutral mass spectroscopy, x-ray diffraction, tunneling electron microscopy (TEM), Rutherford backscattering, and sheet resistance measurements. The experi-mental results indicate that the final rapid thermal annealing temperature should not exceed 800°C for thin (<50 nm) CoSi2 preparation. A comparison of the plan-view and cross-section TEM micrographs of the ion-beam mixed and unmixed CoSi2 films reveals that Ge+ ion mixing (45 keV, 1 × 1015 cm-2) produces homogeneous silicide with smooth silicide-to-silicon interface.

Direct comparison of Fe-Cr unmixing characterization by atom probe tomography and small angle scattering

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

Couturier, Laurent, E-mail: laurent.couturier55@ho

The fine microstructure obtained by unmixing of a solid solution either by classical precipitation or spinodal decomposition is often characterized either by small angle scattering or atom probe tomography. This article shows that a common data analysis framework can be used to analyze data obtained from these two techniques. An example of the application of this common analysis is given for characterization of the unmixing of the Fe-Cr matrix of a 15-5 PH stainless steel during long-term ageing at 350 °C and 400 °C. A direct comparison of the Cr composition fluctuations amplitudes and characteristic lengths obtained with both techniquesmore » is made showing a quantitative agreement for the fluctuation amplitudes. The origin of the discrepancy remaining for the characteristic lengths is discussed. - Highlights: •Common analysis framework for atom probe tomography and small angle scattering •Comparison of same microstructural characteristics obtained using both techniques •Good correlation of Cr composition fluctuations amplitudes from both techniques •Good correlation of Cr composition fluctuations amplitudes with classic V parameter.« less

Evaluation of algorithm methods for fluorescence spectra of cancerous and normal human tissues

NASA Astrophysics Data System (ADS)

Pu, Yang; Wang, Wubao; Alfano, Robert R.

2016-03-01

The paper focus on the various algorithms on to unravel the fluorescence spectra by unmixing methods to identify cancerous and normal human tissues from the measured fluorescence spectroscopy. The biochemical or morphologic changes that cause fluorescence spectra variations would appear earlier than the histological approach; therefore, fluorescence spectroscopy holds a great promise as clinical tool for diagnosing early stage of carcinomas and other deceases for in vivo use. The method can further identify tissue biomarkers by decomposing the spectral contributions of different fluorescent molecules of interest. In this work, we investigate the performance of blind source un-mixing methods (backward model) and spectral fitting approaches (forward model) in decomposing the contributions of key fluorescent molecules from the tissue mixture background when certain selected excitation wavelength is applied. Pairs of adenocarcinoma as well as normal tissues confirmed by pathologist were excited by selective wavelength of 340 nm. The emission spectra of resected fresh tissue were used to evaluate the relative changes of collagen, reduced nicotinamide adenine dinucleotide (NADH), and Flavin by various spectral un-mixing methods. Two categories of algorithms: forward methods and Blind Source Separation [such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA), and Nonnegative Matrix Factorization (NMF)] will be introduced and evaluated. The purpose of the spectral analysis is to discard the redundant information which conceals the difference between these two types of tissues, but keep their diagnostically significance. The facts predicted by different methods were compared to the gold standard of histopathology. The results indicate that these key fluorophores within tissue, e.g. tryptophan, collagen, and NADH, and flavin, show differences of relative contents of fluorophores among different types of human cancer and normal tissues. The sensitivity, specificity, and receiver operating characteristic (ROC) are finally employed as the criteria to evaluate the efficacy of these methods in cancer detection. The underlying physical and biological basis for these optical approaches will be discussed with examples. This ex vivo preliminary trial demonstrates that these different criteria from different methods can distinguish carcinoma from normal tissues with good sensitivity and specificity while among them, we found that ICA appears to be the superior method in predication accuracy.

Open-air multispectral fluorescence-guided surgery platform for intraoperative detection of malignant tissue under ambient lighting conditions

NASA Astrophysics Data System (ADS)

Behrooz, Ali; Vasquez, Kristine O.; Waterman, Peter; Meganck, Jeff; Peterson, Jeffrey D.; Miller, Peter; Kempner, Joshua

2017-02-01

Intraoperative resection of tumors currently relies upon the surgeon's ability to visually locate and palpate tumor nodules. Undetected residual malignant tissue often results in the need for additional treatment or surgical intervention. The Solaris platform is a multispectral open-air fluorescence imaging system designed for translational fluorescence-guided surgery. Solaris supports video-rate imaging in four fixed fluorescence channels ranging from visible to near infrared, and a multispectral channel equipped with a liquid crystal tunable filter (LCTF) for multispectral image acquisition (520-620 nm). Identification of tumor margins using reagents emitting in the visible spectrum (400-650 nm), such as fluorescein isothiocyanate (FITC), present challenges considering the presence of auto-fluorescence from tissue and food in the gastrointestinal (GI) tract. To overcome this, Solaris acquires LCTF-based multispectral images, and by applying an automated spectral unmixing algorithm to the data, separates reagent fluorescence from tissue and food auto-fluorescence. The unmixing algorithm uses vertex component analysis to automatically extract the primary pure spectra, and resolves the reagent fluorescent signal using non-negative least squares. For validation, intraoperative in vivo studies were carried out in tumor-bearing rodents injected with FITC-dextran reagent that is primarily residing in malignant tissue 24 hours post injection. In the absence of unmixing, fluorescence from tumors is not distinguishable from that of surrounding tissue. Upon spectral unmixing, the FITC-labeled malignant regions become well defined and detectable. The results of these studies substantiate the multispectral power of Solaris in resolving FITC-based agent signal in deep tumor masses, under ambient and surgical light, and enhancing the ability to surgically resect them.

Subpixel target detection and enhancement in hyperspectral images

NASA Astrophysics Data System (ADS)

Tiwari, K. C.; Arora, M.; Singh, D.

2011-06-01

Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

Non-invasive monitoring of cytokine-based regenerative treatment of cartilage by hyperspectral unmixing (Conference Presentation)

NASA Astrophysics Data System (ADS)

Mahbub, Saabah B.; Succer, Peter; Gosnell, Martin E.; Anwaer, Ayad G.; Herbert, Benjamin; Vesey, Graham; Goldys, Ewa M.

2016-03-01

Extracting biochemical information from tissue autofluorescence is a promising approach to non-invasively monitor disease treatments at a cellular level, without using any external biomarkers. Our recently developed unsupervised hyperspectral unmixing by Dependent Component Analysis (DECA) provides robust and detailed metabolic information with proper account of intrinsic cellular heterogeneity. Moreover this method is compatible with established methods of fluorescent biomarker labelling. Recently adipose-derived stem cell (ADSC) - based therapies have been introduced for treating different diseases in animals and humans. ADSC have been shown promise in regenerative treatments for osteoarthritis and other bone and joint disorders. One of the mechanism of their action is their anti-inflammatory effects within osteoarthritic joints which aid the regeneration of cartilage. These therapeutic effects are known to be driven by secretions of different cytokines from the ADSCs. We have been using the hyperspectral unmixing techniques to study in-vitro the effects of ADSC-derived cytokine-rich secretions with the cartilage chip in both human and bovine samples. The study of metabolic effects of different cytokine treatment on different cartilage layers makes it possible to compare the merits of those treatments for repairing cartilage.

GPU implementation of the simplex identification via split augmented Lagrangian

NASA Astrophysics Data System (ADS)

Sevilla, Jorge; Nascimento, José M. P.

2015-10-01

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

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

Altmann, Yoann; Maccarone, Aurora; McCarthy, Aongus

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the mainmore » materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).« less

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

The Lightning Nitrogen Oxides Model (LNOM): Status and Recent Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Khan, Maudood; Peterson, Harold

2011-01-01

Improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) are discussed. Recent results from an August 2006 run of the Community Multiscale Air Quality (CMAQ) modeling system that employs LNOM lightning NOx (= NO + NO2) estimates are provided. The LNOM analyzes Lightning Mapping Array (LMA) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NOx. The latest LNOM estimates of (a) lightning channel length distributions, (b) lightning 1-m segment altitude distributions, and (c) the vertical profile of NOx are presented. The impact of including LNOM-estimates of lightning NOx on CMAQ output is discussed.

Enthalpy of Mixing in Al–Tb Liquid

DOE PAGES

Zhou, Shihuai; Tackes, Carl; Napolitano, Ralph

2017-06-21

The liquid-phase enthalpy of mixing for Al$-$Tb alloys is measured for 3, 5, 8, 10, and 20 at% Tb at selected temperatures in the range from 1364 to 1439 K. Methods include isothermal solution calorimetry and isoperibolic electromagnetic levitation drop calorimetry. Mixing enthalpy is determined relative to the unmixed pure (Al and Tb) components. The required formation enthalpy for the Al3Tb phase is computed from first-principles calculations. Finally, based on our measurements, three different semi-empirical solution models are offered for the excess free energy of the liquid, including regular, subregular, and associate model formulations. These models are also compared withmore » the Miedema model prediction of mixing enthalpy.« less

Report of the Workshop on Unmixing the SNCs: Chemical, Isotopic, and Petrologic Components of Martian Meteorites

NASA Technical Reports Server (NTRS)

Treiman, Allan H. (Editor); Herd, Christopher D. K. (Editor)

2002-01-01

Geochemical and petrologic studies of the Martian meteorites (nicknamed the SNCs) have proliferated in the past few years, from a wealth of new samples and the perfection of new analytical methods. An intriguing result from these studies is that the chemical and isotopic compositions of the Martian meteorites, all basalts or derived from basaltic magma, can be modeled as mixtures of a limited number of components. These mixing components were the focus of the workshop.

Source apportionments of PM2.5 organic carbon using molecular marker Positive Matrix Factorization and comparison of results from different receptor models

NASA Astrophysics Data System (ADS)

Heo, Jongbae; Dulger, Muaz; Olson, Michael R.; McGinnis, Jerome E.; Shelton, Brandon R.; Matsunaga, Aiko; Sioutas, Constantinos; Schauer, James J.

2013-07-01

Four hundred fine particulate matter (PM2.5) samples collected over a 1-year period at two sites in the Los Angeles Basin were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and organic molecular markers. The results were used in a Positive Matrix Factorization (PMF) receptor model to obtain daily, monthly and annual average source contributions to PM2.5 OC. Results of the PMF model showed similar source categories with comparable year-long contributions to PM2.5 OC across the sites. Five source categories providing reasonably stable profiles were identified: mobile, wood smoke, primary biogenic, and two types of secondary organic carbon (SOC) (i.e., anthropogenic and biogenic emissions). Total primary emission factors and total SOC factors contributed approximately 60% and 40%, respectively, to the annual-average OC concentrations. Primary sources showed strong seasonal patterns with high winter peaks and low summer peaks, while SOC showed a reverse pattern with highs in the spring and summer in the region. Interestingly, smoke from forest fires which occurred episodically in California during the summer and fall of 2009 was identified and combined with the primary biogenic source as one distinct factor to the OC budget. The PMF resolved factors were further investigated and compared to a chemical mass balance (CMB) model and a second multi-variant receptor model (UNMIX) using molecular markers considered in the PMF. Good agreement between the source contribution from mobile sources and biomass burning for three models were obtained, providing additional weight of evidence that these source apportionment techniques are sufficiently accurate for policy development. However, the CMB model did not quantify primary biogenic emissions, which were included in other sources with the SOC. Both multivariate receptor models, the PMF and the UNMIX, were unable to separate source contributions from diesel and gasoline engines.

Molecular dynamics studies of CaAl 2Si 2O 8 liquid. Part II: Equation of state and a thermodynamic model

NASA Astrophysics Data System (ADS)

Ghiorso, Mark S.; Nevins, Dean; Cutler, Ian; Spera, Frank J.

2009-11-01

A thermodynamic model and equation of state (EOS) is developed from the molecular dynamics simulation experiments of Spera et al. (2009) for CaAl 2Si 2O 8 liquid over the temperature range 3500-6000 K and pressure interval 0-125 GPa. The model is constructed utilizing the isothermal Universal EOS of Vinet et al. (1986) combined with an expression for the temperature-dependence of the internal energy derived from density functional theory ( Rosenfeld and Tarazona, 1998). It is demonstrated that this model is more successful at reproducing the data than the temperature-dependent Universal EOS ( Vinet et al., 1987) or the volume-explicit EOS of Ghiorso (2004a). Distinct parameterizations are required to model low (<20 GPa) and high (>20 GPa) pressure regimes. This result is ascribed to the affect of liquid structure on macroscopic thermodynamic properties, specifically the interdependence of average cation-oxygen coordination number on the bulk modulus. The thermodynamic transition between the high- and low-pressure parameterizations is modeled as second order, although the nature of the transition is open to question and may well be first order or lambda-like in character. Analysis of the thermodynamic model reveals a predicted region of liquid-liquid un-mixing at low-temperatures (<1624 K) and pressures (<1.257 GPa). These pressure-temperature conditions are above the glass transition temperature but within the metastable liquid region. They represent the highest temperatures yet suggested for liquid-liquid un-mixing in a silicate bulk composition. A shock wave Hugoniot curve is calculated for comparison with the experimental data of Rigden et al. (1989) and of Asimow and Ahrens (2008). The comparison suggests that the model developed in this paper underestimates the density of the liquid by roughly 10% at pressures greater than ˜20 GPa.

Impact of JPEG2000 compression on endmember extraction and unmixing of remotely sensed hyperspectral data

NASA Astrophysics Data System (ADS)

Martin, Gabriel; Gonzalez-Ruiz, Vicente; Plaza, Antonio; Ortiz, Juan P.; Garcia, Inmaculada

2010-07-01

Lossy hyperspectral image compression has received considerable interest in recent years due to the extremely high dimensionality of the data. However, the impact of lossy compression on spectral unmixing techniques has not been widely studied. These techniques characterize mixed pixels (resulting from insufficient spatial resolution) in terms of a suitable combination of spectrally pure substances (called endmembers) weighted by their estimated fractional abundances. This paper focuses on the impact of JPEG2000-based lossy compression of hyperspectral images on the quality of the endmembers extracted by different algorithms. The three considered algorithms are the orthogonal subspace projection (OSP), which uses only spatial information, and the automatic morphological endmember extraction (AMEE) and spatial spectral endmember extraction (SSEE), which integrate both spatial and spectral information in the search for endmembers. The impact of compression on the resulting abundance estimation based on the endmembers derived by different methods is also substantiated. Experimental results are conducted using a hyperspectral data set collected by NASA Jet Propulsion Laboratory over the Cuprite mining district in Nevada. The experimental results are quantitatively analyzed using reference information available from U.S. Geological Survey, resulting in recommendations to specialists interested in applying endmember extraction and unmixing algorithms to compressed hyperspectral data.

Effects of band selection on endmember extraction for forestry applications

NASA Astrophysics Data System (ADS)

Karathanassi, Vassilia; Andreou, Charoula; Andronis, Vassilis; Kolokoussis, Polychronis

2014-10-01

In spectral unmixing theory, data reduction techniques play an important role as hyperspectral imagery contains an immense amount of data, posing many challenging problems such as data storage, computational efficiency, and the so called "curse of dimensionality". Feature extraction and feature selection are the two main approaches for dimensionality reduction. Feature extraction techniques are used for reducing the dimensionality of the hyperspectral data by applying transforms on hyperspectral data. Feature selection techniques retain the physical meaning of the data by selecting a set of bands from the input hyperspectral dataset, which mainly contain the information needed for spectral unmixing. Although feature selection techniques are well-known for their dimensionality reduction potentials they are rarely used in the unmixing process. The majority of the existing state-of-the-art dimensionality reduction methods set criteria to the spectral information, which is derived by the whole wavelength, in order to define the optimum spectral subspace. These criteria are not associated with any particular application but with the data statistics, such as correlation and entropy values. However, each application is associated with specific land c over materials, whose spectral characteristics present variations in specific wavelengths. In forestry for example, many applications focus on tree leaves, in which specific pigments such as chlorophyll, xanthophyll, etc. determine the wavelengths where tree species, diseases, etc., can be detected. For such applications, when the unmixing process is applied, the tree species, diseases, etc., are considered as the endmembers of interest. This paper focuses on investigating the effects of band selection on the endmember extraction by exploiting the information of the vegetation absorbance spectral zones. More precisely, it is explored whether endmember extraction can be optimized when specific sets of initial bands related to leaf spectral characteristics are selected. Experiments comprise application of well-known signal subspace estimation and endmember extraction methods on a hyperspectral imagery that presents a forest area. Evaluation of the extracted endmembers showed that more forest species can be extracted as endmembers using selected bands.

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.

Emission spectra profiling of fluorescent proteins in living plant cells

PubMed Central

2013-01-01

Background Fluorescence imaging at high spectral resolution allows the simultaneous recording of multiple fluorophores without switching optical filters, which is especially useful for time-lapse analysis of living cells. The collected emission spectra can be used to distinguish fluorophores by a computation analysis called linear unmixing. The availability of accurate reference spectra for different fluorophores is crucial for this type of analysis. The reference spectra used by plant cell biologists are in most cases derived from the analysis of fluorescent proteins in solution or produced in animal cells, although these spectra are influenced by both the cellular environment and the components of the optical system. For instance, plant cells contain various autofluorescent compounds, such as cell wall polymers and chlorophyll, that affect the spectral detection of some fluorophores. Therefore, it is important to acquire both reference and experimental spectra under the same biological conditions and through the same imaging systems. Results Entry clones (pENTR) of fluorescent proteins (FPs) were constructed in order to create C- or N-terminal protein fusions with the MultiSite Gateway recombination technology. The emission spectra for eight FPs, fused C-terminally to the A- or B-type cyclin dependent kinases (CDKA;1 and CDKB1;1) and transiently expressed in epidermal cells of tobacco (Nicotiana benthamiana), were determined by using the Olympus FluoView™ FV1000 Confocal Laser Scanning Microscope. These experimental spectra were then used in unmixing experiments in order to separate the emission of fluorophores with overlapping spectral properties in living plant cells. Conclusions Spectral imaging and linear unmixing have a great potential for efficient multicolor detection in living plant cells. The emission spectra for eight of the most commonly used FPs were obtained in epidermal cells of tobacco leaves and used in unmixing experiments. The generated set of FP Gateway entry vectors represents a valuable resource for plant cell biologists. PMID:23552272

Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery

NASA Astrophysics Data System (ADS)

Stagakis, Stavros; Vanikiotis, Theofilos; Sykioti, Olga

2016-09-01

The advancing technology of hyperspectral remote sensing offers the opportunity of accurate land cover characterization of complex natural environments. In this study, a linear spectral unmixing algorithm that incorporates a novel hierarchical Bayesian approach (BI-ICE) was applied on two spatially and temporally adjacent CHRIS/PROBA images over a forest in North Pindos National Park (Epirus, Greece). The scope is to investigate the potential of this algorithm to discriminate two different forest species (i.e. beech - Fagus sylvatica, pine - Pinus nigra) and produce accurate species-specific abundance maps. The unmixing results were evaluated in uniformly distributed plots across the test site using measured fractions of each species derived by very high resolution aerial orthophotos. Landsat-8 images were also used to produce a conventional discrete-type classification map of the test site. This map was used to define the exact borders of the test site and compare the thematic information of the two mapping approaches (discrete vs abundance mapping). The required ground truth information, regarding training and validation of the applied mapping methodologies, was collected during a field campaign across the study site. Abundance estimates reached very good overall accuracy (R2 = 0.98, RMSE = 0.06). The most significant source of error in our results was due to the shadowing effects that were very intense in some areas of the test site due to the low solar elevation during CHRIS acquisitions. It is also demonstrated that the two mapping approaches are in accordance across pure and dense forest areas, but the conventional classification map fails to describe the natural spatial gradients of each species and the actual species mixture across the test site. Overall, the BI-ICE algorithm presented increased potential to unmix challenging objects with high spectral similarity, such as different vegetation species, under real and not optimum acquisition conditions. Its full potential remains to be investigated in further and more complex study sites in view of the upcoming satellite hyperspectral missions.

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.

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

NASA Technical Reports Server (NTRS)

Kumar, Uttam; Nemani, Ramakrishna R.; Ganguly, Sangram; Kalia, Subodh; Michaelis, Andrew

2017-01-01

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

NASA Astrophysics Data System (ADS)

Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.

2017-12-01

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Evaluating the Effectiveness of Flood Control Strategies in Contrasting Urban Watersheds and Implications for Houston's Future Flood Vulnerability

NASA Astrophysics Data System (ADS)

Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.

2016-12-01

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

The ferroan-anorthositic suite and the extent of primordial lunar melting

NASA Technical Reports Server (NTRS)

Warren, Paul H.; Kallemeyn, Gregory W.

1992-01-01

The Apollo highlands rock collection includes more than 100 'pristine' fragments that survived the intense meteoritic bombardment of the ancient lunar crust with unmixed, endogenously igneous compositions. The geochemical anomaly manifested by the 'ferroan-anorthositic suite' (FAS) appears to reflect a geochemical, and probably also a genetic, bimodality among the ancient lunar cumulates. Early models that purported to account for this bimodality as a product of a single magma have been discredited. The model of the present paper implies that the Mg-suite rocks formed by a comparatively normal variety of basaltic fractional crystallization (FC) shortly after the era of magma ocean (MO) crystallization and FAS genesis.

Turbulent unmixing: how marine turbulence drives patchy distributions of motile phytoplankton

NASA Astrophysics Data System (ADS)

Durham, William; Climent, Eric; Barry, Michael; de Lillo, Filippo; Boffetta, Guido; Cencini, Massimo; Stocker, Roman

2013-11-01

Centimeter-scale patchiness in the distribution of phytoplankton increases the efficacy of many important ecological interactions in the marine food web. We show that turbulent fluid motion, usually synonymous with mixing, instead triggers intense small-scale patchiness in the distribution of motile phytoplankton. We use a suite of experiments, direct numerical simulations of turbulence, and analytical tools to show that turbulent shear and acceleration directs the motility of cells towards well-defined regions of flow, increasing local cell concentrations more than ten fold. This motility-driven `unmixing' offers an explanation for why motile cells are often more patchily distributed than non-motile cells and provides a mechanistic framework to understand how turbulence, whose strength varies profoundly in marine environments, impacts ocean productivity.

Comparisons of a Constrained Least Squares Model versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Abercromby, Kira J.; Rapp, Jason; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2013-01-01

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University (Cal Poly) in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a reddening of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object s suspected material component will be discussed herein.

Comparisons of a Constrained Least Squares Model Versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

NASA Technical Reports Server (NTRS)

Rapp, Jason; Abercromby, Kira J.; Bedard, Donald; Seitzer, Patrick; Cardona, Tommaso; Cowardin, Heather; Barker, Ed; Lederer, Susan

2012-01-01

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a "reddening" of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object's suspected material component will be discussed herein.

Improving alpine-region spectral unmixing with optimal-fit snow endmembers

NASA Technical Reports Server (NTRS)

Painter, Thomas H.; Roberts, Dar A.; Green, Robert O.; Dozier, Jeff

1995-01-01

Surface albedo and snow-covered-area (SCA) are crucial inputs to the hydrologic and climatologic modeling of alpine and seasonally snow-covered areas. Because the spectral albedo and thermal regime of pure snow depend on grain size, areal distribution of snow grain size is required. Remote sensing has been shown to be an effective (and necessary) means of deriving maps of grain size distribution and snow-covered-area. Developed here is a technique whereby maps of grain size distribution improve estimates of SCA from spectral mixture analysis with AVIRIS data.

Dictionary-Based Tensor Canonical Polyadic Decomposition

NASA Astrophysics Data System (ADS)

Cohen, Jeremy Emile; Gillis, Nicolas

2018-04-01

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.

Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

Detailed emission profiles for on-road vehicles derived from ambient measurements during a windless traffic episode in Baltimore using a multi-model approach

NASA Astrophysics Data System (ADS)

Ke, Haohao; Ondov, John M.; Rogge, Wolfgang F.

2013-12-01

Composite chemical profiles of motor vehicle emissions were extracted from ambient measurements at a near-road site in Baltimore during a windless traffic episode in November, 2002, using four independent approaches, i.e., simple peak analysis, windless model-based linear regression, PMF, and UNMIX. Although the profiles are in general agreement, the windless-model-based profile treatment more effectively removes interference from non-traffic sources and is deemed to be more accurate for many species. In addition to abundances of routine pollutants (e.g., NOx, CO, PM2.5, EC, OC, sulfate, and nitrate), 11 particle-bound metals and 51 individual traffic-related organic compounds (including n-alkanes, PAHs, oxy-PAHs, hopanes, alkylcyclohexanes, and others) were included in the modeling.

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods

NASA Astrophysics Data System (ADS)

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-01

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification.

The nature of the fluids associated with the Monte Rosa gold district, NW Alps, Italy

NASA Astrophysics Data System (ADS)

Lattanzi, P.

1990-12-01

Recent O-isotope and fluid inclusion studies have provided evidence on the nature of the fluids associated with the late-Alpine quartz-gold deposits of the Monte Rosa district. The most abundant inclusions in quartz from these deposits contain a low salinity aqueous fluid (about 2% to 10% wt. NaCl eq.), and a CO2 phase (usually less than 20% mol), in places with minor methane. CO2 densities and total homogenization temperatures vary widely throughout the district, reflecting diverse conditions of trapping (P = 1 to 3 kb, T = 300° to 450°C). At Miniera dei Cani, unmixing between CO2-rich and H2O-rich fluids possibly occurred. A second type of inclusion contains an aqueous brine without recognizable CO2, and is especially abundant at Val Toppa. O-isotope studies suggest that fluids were largely equilibrated in a metamorphic environment. It is concluded that the gold-related fluids in the district were mainly of a metamorphic nature; at Val Toppa, both isotopic and fluid inclusion data point to contributions of unexchanged meteoric waters. Mechanisms of gold transport and precipitation are less contrained. A possible model involves transport of gold as bisulfide complexes, and precipitation due to one or more of the following processes: decrease of sulfur activity due to precipitation of sulfides, wall-rock reaction, cooling/dilution, and/or fluid unmixing.

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods.

PubMed

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-15

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification. Copyright © 2017 Elsevier B.V. All rights reserved.

Unmixing techniques for better segmentation of urban zones, roads, and open pit mines

NASA Astrophysics Data System (ADS)

Nikolov, Hristo; Borisova, Denitsa; Petkov, Doyno

2010-10-01

In this paper the linear unmixing method has been applied in classification of manmade objects, namely urbanized zones, roads etc. The idea is to exploit to larger extent the possibilities offered by multispectral imagers having mid spatial resolution in this case TM/ETM+ instruments. In this research unmixing is used to find consistent regression dependencies between multispectral data and those gathered in-situ and airborne-based sensors. The correct identification of the mixed pixels is key element for the subsequent segmentation forming the shape of the artificial feature is determined much more reliable. This especially holds true for objects with relatively narrow structure for example two-lane roads for which the spatial resolution is larger that the object itself. We have combined ground spectrometry of asphalt, Landsat images of RoI, and in-situ measured asphalt in order to determine the narrow roads. The reflectance of paving stones made from granite is highest compared to another ones which is true for open and stone pits. The potential for mapping is not limited to the mid-spatial Landsat data, but also may be used if the data has higher spatial resolution (as fine as 0.5 m). In this research the spectral and directional reflection properties of asphalt and concrete surfaces compared to those of paving stone made from different rocks have been measured. The in-situ measurements, which plays key role have been obtained using the Thematically Oriented Multichannel Spectrometer (TOMS) - designed in STIL-BAS.

(LMRG): Microscope Resolution, Objective Quality, Spectral Accuracy and Spectral Un-mixing

PubMed Central

Bayles, Carol J.; Cole, Richard W.; Eason, Brady; Girard, Anne-Marie; Jinadasa, Tushare; Martin, Karen; McNamara, George; Opansky, Cynthia; Schulz, Katherine; Thibault, Marc; Brown, Claire M.

2012-01-01

The second study by the LMRG focuses on measuring confocal laser scanning microscope (CLSM) resolution, objective lens quality, spectral imaging accuracy and spectral un-mixing. Affordable test samples for each aspect of the study were designed, prepared and sent to 116 labs from 23 countries across the globe. Detailed protocols were designed for the three tests and customized for most of the major confocal instruments being used by the study participants. One protocol developed for measuring resolution and objective quality was recently published in Nature Protocols (Cole, R. W., T. Jinadasa, et al. (2011). Nature Protocols 6(12): 1929–1941). The first study involved 3D imaging of sub-resolution fluorescent microspheres to determine the microscope point spread function. Results of the resolution studies as well as point spread function quality (i.e. objective lens quality) from 140 different objective lenses will be presented. The second study of spectral accuracy looked at the reflection of the laser excitation lines into the spectral detection in order to determine the accuracy of these systems to report back the accurate laser emission wavelengths. Results will be presented from 42 different spectral confocal systems. Finally, samples with double orange beads (orange core and orange coating) were imaged spectrally and the imaging software was used to un-mix fluorescence signals from the two orange dyes. Results from 26 different confocal systems will be summarized. Time will be left to discuss possibilities for the next LMRG study.

Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

The NASA Lightning Nitrogen Oxides Model (LNOM): Recent Updates and Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Peterson, Harold; Biazar, Arastoo; Khan, Maudood; Wang, Lihua; Park, Yee-Hun

2011-01-01

Improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) and its application to the Community Multiscale Air Quality (CMAQ) modeling system are presented. The LNOM analyzes Lightning Mapping Array (LMA) and National Lightning Detection Network(tm) (NLDN) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NOx (= NO + NO2). Lightning channel length distributions and lightning 10-m segment altitude distributions are also provided. In addition to NOx production from lightning return strokes, the LNOM now includes non-return stroke lightning NOx production due to: hot core stepped and dart leaders, stepped leader corona sheath, K-changes, continuing currents, and M-components. The impact of including LNOM-estimates of lightning NOx for an August 2006 run of CMAQ is discussed.

Ignition and structure of a laminar diffusion flame in the field of a vortex

NASA Technical Reports Server (NTRS)

Macaraeg, Michele G.; Jackson, T. L.; Hussaini, M. Y.

1991-01-01

The distortion of flames in flows with vortical motion is examined via asymptotic analysis and numerical simulation. The model consists of a constant density, one step, irreversible Arrhenius reaction between initially unmixed species occupying adjacent half-planes which are then allowed to mix and react in the presence of a vortex. The evolution in time of the temperature and mass fraction fields is followed. Emphasis is placed on the ignition time and location as a function of vortex Reynolds number and initial temperature differences of the reacting species. The study brings out the influence of the vortex on the chemical reaction. In all phases, good agreement is observed between asymptotic analysis and the full numerical solution of the model equations.

Radiative absorption enhancement of dust mixed with anthropogenic pollution over East Asia

NASA Astrophysics Data System (ADS)

Tian, Pengfei; Zhang, Lei; Ma, Jianmin; Tang, Kai; Xu, Lili; Wang, Yuan; Cao, Xianjie; Liang, Jiening; Ji, Yuemeng; Jiang, Jonathan H.; Yung, Yuk L.; Zhang, Renyi

2018-06-01

The particle mixing state plays a significant yet poorly quantified role in aerosol radiative forcing, especially for the mixing of dust (mineral absorbing) and anthropogenic pollution (black carbon absorbing) over East Asia. We have investigated the absorption enhancement of mixed-type aerosols over East Asia by using the Aerosol Robotic Network observations and radiative transfer model calculations. The mixed-type aerosols exhibit significantly enhanced absorbing ability than the corresponding unmixed dust and anthropogenic aerosols, as revealed in the spectral behavior of absorbing aerosol optical depth, single scattering albedo, and imaginary refractive index. The aerosol radiative efficiencies for the dust, mixed-type, and anthropogenic aerosols are -101.0, -112.9, and -98.3 Wm-2 τ-1 at the bottom of the atmosphere (BOA); -42.3, -22.5, and -39.8 Wm-2 τ-1 at the top of the atmosphere (TOA); and 58.7, 90.3, and 58.5 Wm-2 τ-1 in the atmosphere (ATM), respectively. The BOA cooling and ATM heating efficiencies of the mixed-type aerosols are significantly higher than those of the unmixed aerosol types over the East Asia region, resulting in atmospheric stabilization. In addition, the mixed-type aerosols correspond to a lower TOA cooling efficiency, indicating that the cooling effect by the corresponding individual aerosol components is partially counteracted. We conclude that the interaction between dust and anthropogenic pollution not only represents a viable aerosol formation pathway but also results in unfavorable dispersion conditions, both exacerbating the regional air pollution in East Asia. Our results highlight the necessity to accurately account for the mixing state of aerosols in atmospheric models over East Asia in order to better understand the formation mechanism for regional air pollution and to assess its impacts on human health, weather, and climate.

Quantifying the Components of Impervious Surfaces

USGS Publications Warehouse

Tilley, Janet S.; Slonecker, E. Terrence

2006-01-01

This study's objectives were to (1) determine the relative contribution of impervious surface individual components by collecting digital information from high-resolution imagery, 1-meter or better; and to (2) determine which of the more advanced techniques, such as spectral unmixing or the application of coefficients to land use or land cover data, was the most suitable method that could be used by State and local governments as well as Federal agencies to efficiently measure the imperviousness in any given watershed or area of interest. The components of impervious surfaces, combined from all the watersheds and time periods from objective one were the following: buildings 29.2-percent, roads 28.3-percent, parking lots 24.6-percent; with the remaining three totaling 14-percent - driveways, sidewalks, and other, where other were any other features that were not contained within the first five. Results from objective two were spectral unmixing techniques will ultimately be the most efficient method of determining imperviousness, but are not yet accurate enough as it is critical to achieve accuracy better than 10-percent of the truth, of which the method is not consistently accomplishing as observed in this study. Of the three techniques in coefficient application tested, land use coefficient application was not practical, while if the last two methods, coefficients applied to land cover data, were merged, their end results could be to within 5-percent or better, of the truth. Until the spectral unmixing technique has been further refined, land cover coefficients should be used, which offer quick results, but not current as they were developed for the 1992 National Land Characteristics Data.

[Orthogonal Vector Projection Algorithm for Spectral Unmixing].

PubMed

Song, Mei-ping; Xu, Xing-wei; Chang, Chein-I; An, Ju-bai; Yao, Li

2015-12-01

Spectrum unmixing is an important part of hyperspectral technologies, which is essential for material quantity analysis in hyperspectral imagery. Most linear unmixing algorithms require computations of matrix multiplication and matrix inversion or matrix determination. These are difficult for programming, especially hard for realization on hardware. At the same time, the computation costs of the algorithms increase significantly as the number of endmembers grows. Here, based on the traditional algorithm Orthogonal Subspace Projection, a new method called. Orthogonal Vector Projection is prompted using orthogonal principle. It simplifies this process by avoiding matrix multiplication and inversion. It firstly computes the final orthogonal vector via Gram-Schmidt process for each endmember spectrum. And then, these orthogonal vectors are used as projection vector for the pixel signature. The unconstrained abundance can be obtained directly by projecting the signature to the projection vectors, and computing the ratio of projected vector length and orthogonal vector length. Compared to the Orthogonal Subspace Projection and Least Squares Error algorithms, this method does not need matrix inversion, which is much computation costing and hard to implement on hardware. It just completes the orthogonalization process by repeated vector operations, easy for application on both parallel computation and hardware. The reasonability of the algorithm is proved by its relationship with Orthogonal Sub-space Projection and Least Squares Error algorithms. And its computational complexity is also compared with the other two algorithms', which is the lowest one. At last, the experimental results on synthetic image and real image are also provided, giving another evidence for effectiveness of the method.

Estimating photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions using Landsat and MODIS data: Effects of site heterogeneity, soil properties and land cover

NASA Astrophysics Data System (ADS)

Guerschman, J. P.; Scarth, P.; McVicar, T.; Malthus, T. J.; Stewart, J.; Rickards, J.; Trevithick, R.; Renzullo, L. J.

2013-12-01

Vegetation fractional cover is a key indicator for land management monitoring, both in pastoral and agricultural settings. Maintaining adequate vegetation cover protects the soil from the effects of water and wind erosion and also ensures that carbon is returned to soil through decomposition. Monitoring vegetation fractional cover across large areas and continuously in time needs good remote sensing techniques underpinned by high quality ground data to calibrate and validate algorithms. In this study we used Landsat and MODIS reflectance data together with field measurements from 1476 observations across Australia to produce estimates of vegetation fractional cover using a linear unmixing technique. Specifically, we aimed at separating fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (B). We used Landsat reflectance averaged over a 3x3 pixel window representing the area actually measured on the ground and also a 'degraded' Landsat reflectance 40x40 pixel window to simulate the effect of a coarser sensor. Using these two Landsat reflectances we quantified the heterogeneity of each site. We used data from two MODIS-derived reflectance products: the Nadir BRDF-Adjusted surface Reflectance product (MCD43A4) and the MODIS 8-day surface reflectance (MOD09A1). We derived endmembers from the data and estimated fractional cover using a linear unmixing technique. Log transforms and band interaction terms were added to account for non-linearities in the spectral mixing. For each reflectance source we investigated if the residuals were correlated with site heterogeneity, soil colour, soil moisture and land cover type. As expected, the best model was obtained when Landsat data for a small region around each site was used. We obtained root mean square error (RMSE) values of 0.134, 0.175 and 0.153 for PV, NPV and B respectively. When we degraded the Landsat data to an area of ~1 km2 around each site the model performance decreased to RMSE of 0.142, 0.181 and 0.166 for PV, NPV and B. Using MODIS reflectance data (from the MCD43A4 and MOD09A1 products) we obtained similar results as when using the 'degraded' Landsat reflectance, with no significant differences between them. Model performance decreased (i.e. RMSE increased) with site heterogeneity when coarse resolution reflectance data was used. We did not find any evidence of soil colour or moisture influence on model performance. We speculate that the unmixing models may be insensitive to soil colour and/or that the soil moisture in the top few millimetres of soil, which influence reflectance in optical sensors, is decoupled from the soil moisture in the top layer (i.e. a few cm) as measured by passive microwave sensors or estimated by models. The models tended to overestimate PV in cropping areas, possibly due to a strong red/ near infrared signal in homogeneous crops which do not have a high green cover. This study sets the basis for an operational Landsat/ MODIS combined product which would benefit users with varying requirements of spatial, temporal resolution and latency and could potentially be applied to other regions in the world.

Remote sensing of particle dynamics: a two-component unmixing model in a western UK shelf sea.

NASA Astrophysics Data System (ADS)

Mitchell, Catherine; Cunningham, Alex

2014-05-01

The relationship between the backscattering and absorption coefficients, in particular the backscattering to absorption ratio, is mediated by the type of particles present in the water column. By considering the optical signals to be driven by phytoplankton and suspended minerals, with a relatively constant influence from CDOM, radiative transfer modelling is used to propose a method for retrieving the optical contribution of phytoplankton and suspended minerals to the total absorption coefficient with mean percentage errors of below 5% for both components. These contributions can be converted to constituent concentrations if the appropriate specific inherent optical properties are known or can be determined from the maximum and minimum backscattering to absorption ratios of the data. Remotely sensed absorption and backscattering coefficients from eight years of MODIS data for the Irish Sea reveal maximum backscattering to absorption coefficient ratios over the winter (with an average for the region of 0.27), which then decrease to a minimum over the summer months (with an average of 0.06) before increasing again through to winter, indicating a change in the particles present in the water column. Application of the two-component unmixing model to this data showed seasonal cycles of both phytoplankton and suspended mineral concentrations which vary in both amplitude and periodicity depending on their location. For example, in the Bristol Channel the amplitude of the suspended mineral concentration throughout one cycle is approximately 75% greater than a yearly cycle in the eastern Irish Sea. These seasonal cycles give an insight into the complex dynamics of particles in the water column, indicating the suspension of sediment throughout the winter months and the loss of sediments from the surface layer over the summer during stratification. The relationship between the timing of the phytoplankton spring bloom and changes in the availability of light in the water column can be studied to gain an understanding into the phytoplankton phenology across the region.

Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

NASA Astrophysics Data System (ADS)

Nguyen, L. H.; Henebry, G. M.

2017-12-01

The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

Source Characterization of Heavy Gas Dispersion Models for Reactive Chemicals. Volume 1

DTIC Science & Technology

1987-12-21

Temperatura TC10263,3 K (K) f Liquid aerosol TAIRw30 0 K mass fraction in fl " 75% MO unmixed sulfur dioxide cloud 1nil 0.1 it 100 1o0 Mass Air / Mass Sulfur...Modified Sigma Theta Method for Determining Atmospheric Stability a.* Daytime Wind speed Nighttime** ( de ;6ees) stability (m s" at 10 m) stability -U>22.5 A...rate of air mass entrainment into the cloud can be represented by the equations: dE dMT d- PaUE 2 WR H and -- PaUT ’ R2 (5.2.7)dt dt where uE and u are

Oxide dispersion strengthened ferritic steels: a basic research joint program in France

NASA Astrophysics Data System (ADS)

Boutard, J.-L.; Badjeck, V.; Barguet, L.; Barouh, C.; Bhattacharya, A.; Colignon, Y.; Hatzoglou, C.; Loyer-Prost, M.; Rouffié, A. L.; Sallez, N.; Salmon-Legagneur, H.; Schuler, T.

2014-12-01

AREVA, CEA, CNRS, EDF and Mécachrome are funding a joint program of basic research on Oxide Dispersion Strengthened Steels (ODISSEE), in support to the development of oxide dispersion strengthened 9-14% Cr ferritic-martensitic steels for the fuel element cladding of future Sodium-cooled fast neutron reactors. The selected objectives and the results obtained so far will be presented concerning (i) physical-chemical characterisation of the nano-clusters as a function of ball-milling process, metallurgical conditions and irradiation, (ii) meso-scale understanding of failure mechanisms under dynamic loading and creep, and, (iii) kinetic modelling of nano-clusters nucleation and α/α‧ unmixing.

The NASA Lightning Nitrogen Oxides Model (LNOM): Application to Air Quality Modeling

NASA Technical Reports Server (NTRS)

Koshak, William; Peterson, Harold; Khan, Maudood; Biazar, Arastoo; Wang, Lihua

2011-01-01

Recent improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) and its application to the Community Multiscale Air Quality (CMAQ) modeling system are discussed. The LNOM analyzes Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark)(NLDN) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NO(x) (= NO + NO2). The latest LNOM estimates of lightning channel length distributions, lightning 1-m segment altitude distributions, and the vertical profile of lightning NO(x) are presented. The primary improvement to the LNOM is the inclusion of non-return stroke lightning NOx production due to: (1) hot core stepped and dart leaders, (2) stepped leader corona sheath, K-changes, continuing currents, and M-components. The impact of including LNOM-estimates of lightning NO(x) for an August 2006 run of CMAQ is discussed.

Linear mixing model applied to AVHRR LAC data

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.

A Novel Approach to Model the Air-Side Heat Transfer in Microchannel Condensers

NASA Astrophysics Data System (ADS)

Martínez-Ballester, S.; Corberán, José-M.; Gonzálvez-Maciá, J.

2012-11-01

The work presents a model (Fin1D×3) for microchannel condensers and gas coolers. The paper focusses on the description of the novel approach employed to model the air-side heat transfer. The model applies a segment-by-segment discretization to the heat exchanger adding, in each segment, a specific bi-dimensional grid to the air flow and fin wall. Given this discretization, the fin theory is applied by using a continuous piecewise function for the fin wall temperature. It allows taking into account implicitly the heat conduction between tubes along the fin, and the unmixed air influence on the heat capacity. The model has been validated against experimental data resulting in predicted capacity errors within ± 5%. Differences on prediction results and computational cost were studied and compared with the previous authors' model (Fin2D) and with other simplified model. Simulation time of the proposed model was reduced one order of magnitude respect the Fin2D's time retaining its same accuracy.

46 CFR 164.006-5 - Procedure for approval.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the deck covering. (2) The range of thicknesses in which it is proposed to lay the deck covering... (c). (2) Sufficient bulk material (unmixed) to lay a sample one inch thick on an area of 12″×27″. If...

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.

Monitoring intracellular oxidative events using dynamic spectral unmixing microscopy

EPA Science Inventory

There is increasing interest in using live-cell imaging to monitor not just individual intracellular endpoints, but to investigate the interplay between multiple molecular events as they unfold in real time within the cell. A major impediment to simultaneous acquisition of multip...

Exsolution as an Example of Complex-System Behavior

NASA Astrophysics Data System (ADS)

Mogk, D. W.; Dutrow, B. L.

2010-12-01

Exsolution in minerals is an important process that occurs in a wide range of mineral groups (e.g. alkali feldspars, pyroxenes, amphiboles, carbonates, oxides, sulfides) in response to changing physical conditions. Exsolution describes a physical process in which a mineral with an initially homogeneous solid solution separates into at least two distinct derivative minerals of disparate composition and is typically interpreted as the product of unmixing in response to lattice strain during slow cooling. Such a process is typically taught in introductory mineralogy and petrology courses, in part because exsolution textures can be readily observed in hand sample or thin section. Exsolution is typically represented on equilibrium binary phase diagrams (T-X), and compositions of the unmixed products can be used in geothermobarometry to calculate temperatures and pressures of initial equilibration or compositions of the unmixed products. Although central to course content, traditional approaches to teaching exsolution are largely descriptive, and do not address the underlying principles that drive this phenomenon: that is, dissipation of energy results in segregating and self-organizing behavior of the system. This process exemplifies complex-system behavior. We use perthite formation (i.e. exsolution in the alkali feldspar system) in a series of scaffolded exercises to teach and more completely demonstrate complex-system behavior. These exercises include the use of: 1) hand samples and a series of optical and TEM photomicrographs to display the scale invariance of perthite textures; 2) a puzzle activity in which a chessboard is used as an analog model of atomic positions and nickels and pennies are used to represent individual atoms (Na and K respectively); sequential moves to optimize contacts with similar coins approximates minimization of lattice energies and reveals a power-law relationship as the system becomes increasingly segregated as a function of time to create exsolution textures; 3) the NetLogo computer modeling program to demonstrate segregating behavior; 4) visualizations based on the binary alkali feldspar phase diagram to demonstrate changes to the state of the system over a range of temperatures, and 5) a series of follow-on thought questions. An interesting apparent paradox that our students should consider concerns the flow of mass and energy in natural systems. Commonly, we simply note that mass and energy typically flow down natural gradients (thermal, chemical potential) to attain a homogeneous equilibrium state; however, exsolution produces a segregated state of the system in the lowest energy configuration. Why? Complex-system behavior can be discovered in a wide range of geological phenomena such as exsolution, and could be explicitly identified throughout the geoscience curriculum as a mechanism to teach about interacting systems.

Using hyperspectral imagery to assist federal forest monitoring and restoration projects in the Southern Rocky Mountains, Colorado

NASA Astrophysics Data System (ADS)

Wamser, Kyle

Hyperspectral imagery and the corresponding ability to conduct analysis below the pixel level have tremendous potential to aid in landcover monitoring. During large ecosystem restoration projects, being able to monitor specific aspects of the recovery over large and often inaccessible areas under constrained finances are major challenges. The Civil Air Patrol's Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) can provide hyperspectral data in most parts of the United States at relatively low cost. Although designed specifically for use in locating downed aircraft, the imagery holds the potential to identify specific aspects of landcover at far greater fidelity than traditional multispectral means. The goals of this research were to improve the use of ARCHER hyperspectral imagery to classify sub-canopy and open-area vegetation in coniferous forests located in the Southern Rockies and to determine how much fidelity might be lost from a baseline of 1 meter spatial resolution resampled to 2 and 5 meter pixel size to simulate higher altitude collection. Based on analysis comparing linear spectral unmixing with a traditional supervised classification, the linear spectral unmixing proved to be statistically superior. More importantly, however, linear spectral unmixing provided additional sub-pixel information that was unavailable using other techniques. The second goal of determining fidelity loss based on spatial resolution was more difficult to determine due to how the data are represented. Furthermore, the 2 and 5 meter imagery were obtained by resampling the 1 meter imagery and therefore may not be representative of the quality of actual 2 or 5 meter imagery. Ultimately, the information derived from this research may be useful in better utilizing hyperspectral imagery to conduct forest monitoring and assessment.

Determination of sediment provenance by unmixing the mineralogy of source-area sediments: The "SedUnMix" program

USGS Publications Warehouse

Andrews, John T.; Eberl, D.D.

2012-01-01

Along the margins of areas such as Greenland and Baffin Bay, sediment composition reflects a complex mixture of sources associated with the transport of sediment in sea ice, icebergs, melt-water and turbidite plumes. Similar situations arise in many contexts associated with sediment transport and with the mixing of sediments from different source areas. The question is: can contributions from discrete sediment (bedrock) sources be distinguished in a mixed sediment by using mineralogy, and, if so, how accurately? To solve this problem, four end-member source sediments were mixed in various proportions to form eleven artificial mixtures. Two of the end-member sediments are felsic, and the other two have more mafic compositions. End member and mixed sediment mineralogies were measured for the < 2. mm sediment fractions by quantitative X-ray diffraction (qXRD). The proportions of source sediments in the mixtures then were calculated using an Excel macro program named SedUnMix, and the results were evaluated to determine the robustness of the algorithm. The program permits the unmixing of up to six end members, each of which can be represented by up to 5 alternative compositions, so as to better simulate variability within each source region. The results indicate that we can track the relative percentages of the four end members in the mixtures. We recommend, prior to applying the technique to down-core or to other provenance problems, that a suite of known, artificial mixtures of sediments from probable source areas be prepared, scanned, analyzed for quantitative mineralogy, and then analyzed by SedUnMix to check the sensitivity of the method for each specific unmixing problem. ?? 2011 Elsevier B.V..

Hyperspectral fluorescence imaging with multi wavelength LED excitation

NASA Astrophysics Data System (ADS)

Luthman, A. Siri; Dumitru, Sebastian; Quirós-Gonzalez, Isabel; Bohndiek, Sarah E.

2016-04-01

Hyperspectral imaging (HSI) can combine morphological and molecular information, yielding potential for real-time and high throughput multiplexed fluorescent contrast agent imaging. Multiplexed readout from targets, such as cell surface receptors overexpressed in cancer cells, could improve both sensitivity and specificity of tumor identification. There remains, however, a need for compact and cost effective implementations of the technology. We have implemented a low-cost wide-field multiplexed fluorescence imaging system, which combines LED excitation at 590, 655 and 740 nm with a compact commercial solid state HSI system operating in the range 600 - 1000 nm. A key challenge for using reflectance-based HSI is the separation of contrast agent fluorescence from the reflectance of the excitation light. Here, we illustrate how it is possible to address this challenge in software, using two offline reflectance removal methods, prior to least-squares spectral unmixing. We made a quantitative comparison of the methods using data acquired from dilutions of contrast agents prepared in well-plates. We then established the capability of our HSI system for non-invasive in vivo fluorescence imaging in small animals using the optimal reflectance removal method. The HSI presented here enables quantitative unmixing of at least four fluorescent contrast agents (Alexa Fluor 610, 647, 700 and 750) simultaneously in living mice. A successful unmixing of the four fluorescent contrast agents was possible both using the pure contrast agents and with mixtures. The system could in principle also be applied to imaging of ex vivo tissue or intraoperative imaging in a clinical setting. These data suggest a promising approach for developing clinical applications of HSI based on multiplexed fluorescence contrast agent imaging.

18 CFR 292.202 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Definitions. For purposes of this subpart: (a) Biomass means any organic material not derived from fossil.... (c) Cogeneration facility means equipment used to produce electric energy and forms of useful thermal... all forms supplied from external sources; (k) Natural gas means either natural gas unmixed, or any...

18 CFR 292.202 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Definitions. For purposes of this subpart: (a) Biomass means any organic material not derived from fossil.... (c) Cogeneration facility means equipment used to produce electric energy and forms of useful thermal... all forms supplied from external sources; (k) Natural gas means either natural gas unmixed, or any...

18 CFR 292.202 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Definitions. For purposes of this subpart: (a) Biomass means any organic material not derived from fossil.... (c) Cogeneration facility means equipment used to produce electric energy and forms of useful thermal... all forms supplied from external sources; (k) Natural gas means either natural gas unmixed, or any...

18 CFR 292.202 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Definitions. For purposes of this subpart: (a) Biomass means any organic material not derived from fossil.... (c) Cogeneration facility means equipment used to produce electric energy and forms of useful thermal... all forms supplied from external sources; (k) Natural gas means either natural gas unmixed, or any...

18 CFR 292.202 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Definitions. For purposes of this subpart: (a) Biomass means any organic material not derived from fossil.... (c) Cogeneration facility means equipment used to produce electric energy and forms of useful thermal... all forms supplied from external sources; (k) Natural gas means either natural gas unmixed, or any...

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique.

PubMed

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-03-15

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system's lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system's ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection.

Linear mixing model applied to coarse resolution satellite data

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1992-01-01

A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

Model-free data analysis for source separation based on Non-Negative Matrix Factorization and k-means clustering (NMFk)

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Alexandrov, B.

2014-12-01

The identification of the physical sources causing spatial and temporal fluctuations of state variables such as river stage levels and aquifer hydraulic heads is challenging. The fluctuations can be caused by variations in natural and anthropogenic sources such as precipitation events, infiltration, groundwater pumping, barometric pressures, etc. The source identification and separation can be crucial for conceptualization of the hydrological conditions and characterization of system properties. If the original signals that cause the observed state-variable transients can be successfully "unmixed", decoupled physics models may then be applied to analyze the propagation of each signal independently. We propose a new model-free inverse analysis of transient data based on Non-negative Matrix Factorization (NMF) method for Blind Source Separation (BSS) coupled with k-means clustering algorithm, which we call NMFk. NMFk is capable of identifying a set of unique sources from a set of experimentally measured mixed signals, without any information about the sources, their transients, and the physical mechanisms and properties controlling the signal propagation through the system. A classical BSS conundrum is the so-called "cocktail-party" problem where several microphones are recording the sounds in a ballroom (music, conversations, noise, etc.). Each of the microphones is recording a mixture of the sounds. The goal of BSS is to "unmix'" and reconstruct the original sounds from the microphone records. Similarly to the "cocktail-party" problem, our model-freee analysis only requires information about state-variable transients at a number of observation points, m, where m > r, and r is the number of unknown unique sources causing the observed fluctuations. We apply the analysis on a dataset from the Los Alamos National Laboratory (LANL) site. We identify and estimate the impact and sources are barometric pressure and water-supply pumping effects. We also estimate the location of the water-supply pumping wells based on the available data. The possible applications of the NMFk algorithm are not limited to hydrology problems; NMFk can be applied to any problem where temporal system behavior is observed at multiple locations and an unknown number of physical sources are causing these fluctuations.

Hyperspectral remote sensing of coral reefs: Deriving bathymetry, aquatic optical properties and a benthic spectral unmixing classification using AVIRIS data in the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Goodman, James Ansell

My research focuses on the development and application of hyperspectral remote sensing as a valuable component in the assessment and management of coral ecosystems. Remote sensing provides an important quantitative ability to investigate the spatial dynamics of coral health and evaluate the impacts of local, regional and global change on this important natural resource. Furthermore, advances in detector capabilities and analysis methods, particularly with respect to hyperspectral remote sensing, are also increasing the accuracy and level of effectiveness of the resulting data products. Using imagery of Kaneohe Bay and French Frigate Shoals in the Hawaiian Islands, acquired in 2000 by NASA's Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), I developed, applied and evaluated algorithms for analyzing coral reefs using hyperspectral remote sensing data. Research included developing methods for acquiring in situ underwater reflectance, collecting spectral measurements of the dominant bottom components in Kaneohe Bay, applying atmospheric correction and sunglint removal algorithms, employing a semianalytical optimization model to derive bathymetry and aquatic optical properties, and developing a linear unmixing approach for deriving bottom composition. Additionally, algorithm development focused on using fundamental scientific principles to facilitate the portability of methods to diverse geographic locations and across variable environmental conditions. Assessments of this methodology compared favorably with available field measurements and habitat information, and the overall analysis demonstrated the capacity to derive information on water properties, bathymetry and habitat composition. Thus, results illustrated a successful approach for extracting environmental information and habitat composition from a coral reef environment using hyperspectral remote sensing.

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

Cowan, Nicolas B.; Strait, Talia E., E-mail: n-cowan@northwestern.edu

Planned missions will spatially resolve temperate terrestrial planets from their host star. Although reflected light from such a planet encodes information about its surface, it has not been shown how to establish surface characteristics of a planet without assuming known surfaces to begin with. We present a reanalysis of disk-integrated, time-resolved, multiband photometry of Earth obtained by the Deep Impact spacecraft as part of the EPOXI Mission of Opportunity. We extract reflectance spectra of clouds, ocean, and land without a priori knowledge of the numbers or colors of these surfaces. We show that the inverse problem of extracting surface spectramore » from such data is a novel and extreme instance of spectral unmixing, a well-studied problem in remote sensing. Principal component analysis is used to determine an appropriate number of model surfaces with which to interpret the data. Shrink-wrapping a simplex to the color excursions of the planet yields a conservative estimate of the planet's endmember spectra. The resulting surface maps are unphysical, however, requiring negative or larger-than-unity surface coverage at certain locations. Our ''rotational unmixing'' supersedes the endmember analysis by simultaneously solving for the surface spectra and their geographical distributions on the planet, under the assumption of diffuse reflection and known viewing geometry. We use a Markov Chain Monte Carlo to determine best-fit parameters and their uncertainties. The resulting albedo spectra are similar to clouds, ocean, and land seen through a Rayleigh-scattering atmosphere. This study suggests that future direct-imaging efforts could identify and map unknown surfaces and clouds on exoplanets.« less

Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

NASA Astrophysics Data System (ADS)

Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

2016-09-01

Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

Determining Reflectance Spectra of Surfaces and Clouds on Exoplanets

NASA Astrophysics Data System (ADS)

Cowan, Nicolas B.; Strait, Talia E.

2013-03-01

Planned missions will spatially resolve temperate terrestrial planets from their host star. Although reflected light from such a planet encodes information about its surface, it has not been shown how to establish surface characteristics of a planet without assuming known surfaces to begin with. We present a reanalysis of disk-integrated, time-resolved, multiband photometry of Earth obtained by the Deep Impact spacecraft as part of the EPOXI Mission of Opportunity. We extract reflectance spectra of clouds, ocean, and land without a priori knowledge of the numbers or colors of these surfaces. We show that the inverse problem of extracting surface spectra from such data is a novel and extreme instance of spectral unmixing, a well-studied problem in remote sensing. Principal component analysis is used to determine an appropriate number of model surfaces with which to interpret the data. Shrink-wrapping a simplex to the color excursions of the planet yields a conservative estimate of the planet's endmember spectra. The resulting surface maps are unphysical, however, requiring negative or larger-than-unity surface coverage at certain locations. Our "rotational unmixing" supersedes the endmember analysis by simultaneously solving for the surface spectra and their geographical distributions on the planet, under the assumption of diffuse reflection and known viewing geometry. We use a Markov Chain Monte Carlo to determine best-fit parameters and their uncertainties. The resulting albedo spectra are similar to clouds, ocean, and land seen through a Rayleigh-scattering atmosphere. This study suggests that future direct-imaging efforts could identify and map unknown surfaces and clouds on exoplanets.

Overhead longwave infrared hyperspectral material identification using radiometric models

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

Zelinski, M. E.

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimalmore » atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.« less

Band selection using forward feature selection algorithm for citrus Huanglongbing disease detection

USDA-ARS?s Scientific Manuscript database

This study attempted to classify spectrally similar data – obtained from aerial images of healthy citrus plants and the citrus greening disease (Huanglongbing) infected plants - using small differences without un-mixing the endmember components and therefore without the need for endmember library. H...

Machine Learning Approach to Deconvolution of Thermal Infrared (TIR) Spectrum of Mercury Supporting MERTIS Onboard ESA/JAXA BepiColombo

NASA Astrophysics Data System (ADS)

Varatharajan, I.; D'Amore, M.; Maturilli, A.; Helbert, J.; Hiesinger, H.

2018-04-01

Machine learning approach to spectral unmixing of emissivity spectra of Mercury is carried out using endmember spectral library measured at simulated daytime surface conditions of Mercury. Study supports MERTIS payload onboard ESA/JAXA BepiColombo.

Revisiting the "Unmixing Experiment" through Argumentation

ERIC Educational Resources Information Center

Çoban, Gul Ünal; Büber, Ayse; Saglam, Merve Kocagül

2017-01-01

This paper focuses on a series of activities for students at middle school to college level, designed to instill a sound understanding of fluids and the properties of fluids. The first activities investigate diffusion and molecular size and these are followed by tasks exploring viscosity and the factors effecting viscosity. Following this, there…

Context Dependent Spectral Unmixing

DTIC Science & Technology

2014-08-01

the tar- get sizes). The targets were made of 100% cotton fabric and were emplaced so that there would be representatives of each color type completely...method for simplex-based endmember extraction algorithm,” IEEE Transactions on Geoscience and Re- mote Sensing, vol. 44, no. 10, pp. 2804–2819, 2006. [68

Assessment of spruce (Picea obovata) abundance by spectral unmixing algorithm for sustainable forest management in highland Natural Reserve (case study of Zigalga Range, South-Ural State Natural Reserve, Russia).

NASA Astrophysics Data System (ADS)

Mikheeva, Anna; Moiseev, Pavel

2017-04-01

In mountain territories climate change affects forest productivity and growth, which results in the tree line advancing and increasing of the forest density. These changes pose new challenges for forest managers whose responsibilities include forest resources inventory, monitoring and protection of ecosystems, and assessment of forest vulnerability. These activities require a range of sources of information, including exact squares of forested areas, forest densities and species abundances. Picea obovata, dominant tree species in South-Ural State Natural Reserve, Russia has regenerated, propagated and increased its relative cover during the recent 70 years. A remarkable shift of the upper limit of Picea obovata up to 60-80 m upslope was registered by repeating photography, especially on gentle slopes. The stands of Picea obovata are monitored by Reserve inspectors on the test plots to ensure that forests maintain or improve their productivity, these studies also include projective cover measurements. However, it is impossible to cover the entire territory of the Reserve by detailed field observations. Remote sensing data from Terra ASTER imagery provides valuable information for large territories (scene covers an area of 60 x 60 km) and can be used for quantitative mapping of forest and non-forest vegetation at regional scale (spatial resolution is 15-30 m for visible and infrared bands). A case study of estimating Picea obovata abundance was conducted for forest and forest-tundra sites of Zigalga Range, using 9-band ASTER multispectral imagery of 23.08.2007, field data and spectral unmixing algorithm. This type of algorithms intends to derive object and its abundance from a mixed pixel of multispectral imagery which can be further converted to object's projective cover. Atmospheric correction was applied to the imagery prior to spectral unmixing, and then pure spectra of Picea obovata were extracted from the image in 10 points and averaged. These points located in Zigalga Range and were visited in summer 2016. We used Mixture-tuned Match Filtering (MTMF) algorithm, a non-linear subpixel classification technique which allows to separate the spectral mixture containing unknown objects, and to derive only known ones. The results of spectral unmixing classification were abundance maps of Picea obovata. The values were statistically determined (there was only selected abundances with high probabilities of presence and low probabilities of absence) and then constrained to the interval [0; 1]. Verification of maps was made at the sites of Iremel Mountains on the same ASTER image, where projective cover of Picea obovata was measured in the field in 147 points. The correlation coefficient between the spectral unmixing abundances and field-measured abundances was 0.7; not a very high value is due to the low sensitivity of the algorithm to detect abundances less than 0.25. The proposed method provides a tool for defining the Picea obovata boundaries more accurately than per-pixel automatic classification and locating new spruce islands in the mixing tree line environment. The abundances can be obtained for large areas with minimum field work which makes this approach cost-effective in providing timely information to nature reserve managers for adapting forest management actions to climate change.

Large-scale compositional heterogeneity in the Earth's mantle

NASA Astrophysics Data System (ADS)

Ballmer, M.

2017-12-01

Seismic imaging of subducted Farallon and Tethys lithosphere in the lower mantle has been taken as evidence for whole-mantle convection, and efficient mantle mixing. However, cosmochemical constraints point to a lower-mantle composition that has a lower Mg/Si compared to upper-mantle pyrolite. Moreover, geochemical signatures of magmatic rocks indicate the long-term persistence of primordial reservoirs somewhere in the mantle. In this presentation, I establish geodynamic mechanisms for sustaining large-scale (primordial) heterogeneity in the Earth's mantle using numerical models. Mantle flow is controlled by rock density and viscosity. Variations in intrinsic rock density, such as due to heterogeneity in basalt or iron content, can induce layering or partial layering in the mantle. Layering can be sustained in the presence of persistent whole mantle convection due to active "unmixing" of heterogeneity in low-viscosity domains, e.g. in the transition zone or near the core-mantle boundary [1]. On the other hand, lateral variations in intrinsic rock viscosity, such as due to heterogeneity in Mg/Si, can strongly affect the mixing timescales of the mantle. In the extreme case, intrinsically strong rocks may remain unmixed through the age of the Earth, and persist as large-scale domains in the mid-mantle due to focusing of deformation along weak conveyor belts [2]. That large-scale lateral heterogeneity and/or layering can persist in the presence of whole-mantle convection can explain the stagnation of some slabs, as well as the deflection of some plumes, in the mid-mantle. These findings indeed motivate new seismic studies for rigorous testing of model predictions. [1] Ballmer, M. D., N. C. Schmerr, T. Nakagawa, and J. Ritsema (2015), Science Advances, doi:10.1126/sciadv.1500815. [2] Ballmer, M. D., C. Houser, J. W. Hernlund, R. Wentzcovitch, and K. Hirose (2017), Nature Geoscience, doi:10.1038/ngeo2898.

Mixing and unmixedness in plasma jets 1: Near-field analysis

NASA Technical Reports Server (NTRS)

Ilegbusi, Olusegun J.

1993-01-01

The flow characteristics in the near-field of a plasma jet are simulated with a two-fluid model. This model accounts for both gradient-diffusion mixing and uni-directional sifting motion resulting from pressure-gradient-body-force imbalance. This latter mechanism is believed to be responsible for the umixedness observed in plasma jets. The unmixedness is considered to be essentially a Rayleigh-Taylor kind instability. Transport equations are solved for the individual plasma and ambient gas velocities, temperatures and volume fractions. Empirical relations are employed for the interface transfers of mass, momentum and heat. The empirical coefficients are first established by comparison of predictions with available experimental data for shear flows. The model is then applied to an Argon plasma jet ejecting into stagnant air. The predicted results show the significant build-up of unmixed air within the plasma gas, even relatively far downstream of the torch. By adjusting the inlet condition, the model adequately reproduces the experimental data.

Pile mixing increases greenhouse gas emissions during composting of dairy manure

USDA-ARS?s Scientific Manuscript database

The effect of pile mixing on greenhouse gas (GHG) emissions from stored dairy manure was determined using large flux chambers designed to completely cover pilot-scale manure piles. GHG emissions from piles that were mixed four times during the 80 day trial were about 20% higher than unmixed piles. ...

Testing the Nonce Borrowing Hypothesis: Counter-Evidence from English-Origin Verbs in Welsh

ERIC Educational Resources Information Center

Stammers, Jonathan R.; Deuchar, Margaret

2012-01-01

According to the nonce borrowing hypothesis (NBH), "[n]once borrowings pattern exactly like their native counterparts in the (unmixed) recipient language" (Poplack & Meechan, 1998a, p. 137). Nonce borrowings (Sankoff, Poplack & Vanniarajan, 1990, p. 74) are "lone other-language items" which differ from established borrowings in terms of frequency…

Postfire soil burn severity mapping with hyperspectral image unmixing

Treesearch

Peter R. Robichaud; Sarah A. Lewis; Denise Y. M. Laes; Andrew T. Hudak; Raymond F. Kokaly; Joseph A. Zamudio

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after...

Method for hyperspectral imagery exploitation and pixel spectral unmixing

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang (Inventor)

2003-01-01

An efficiently hybrid approach to exploit hyperspectral imagery and unmix spectral pixels. This hybrid approach uses a genetic algorithm to solve the abundance vector for the first pixel of a hyperspectral image cube. This abundance vector is used as initial state in a robust filter to derive the abundance estimate for the next pixel. By using Kalman filter, the abundance estimate for a pixel can be obtained in one iteration procedure which is much fast than genetic algorithm. The output of the robust filter is fed to genetic algorithm again to derive accurate abundance estimate for the current pixel. The using of robust filter solution as starting point of the genetic algorithm speeds up the evolution of the genetic algorithm. After obtaining the accurate abundance estimate, the procedure goes to next pixel, and uses the output of genetic algorithm as the previous state estimate to derive abundance estimate for this pixel using robust filter. And again use the genetic algorithm to derive accurate abundance estimate efficiently based on the robust filter solution. This iteration continues until pixels in a hyperspectral image cube end.

Endmember extraction from hyperspectral image based on discrete firefly algorithm (EE-DFA)

NASA Astrophysics Data System (ADS)

Zhang, Chengye; Qin, Qiming; Zhang, Tianyuan; Sun, Yuanheng; Chen, Chao

2017-04-01

This study proposed a novel method to extract endmembers from hyperspectral image based on discrete firefly algorithm (EE-DFA). Endmembers are the input of many spectral unmixing algorithms. Hence, in this paper, endmember extraction from hyperspectral image is regarded as a combinational optimization problem to get best spectral unmixing results, which can be solved by the discrete firefly algorithm. Two series of experiments were conducted on the synthetic hyperspectral datasets with different SNR and the AVIRIS Cuprite dataset, respectively. The experimental results were compared with the endmembers extracted by four popular methods: the sequential maximum angle convex cone (SMACC), N-FINDR, Vertex Component Analysis (VCA), and Minimum Volume Constrained Nonnegative Matrix Factorization (MVC-NMF). What's more, the effect of the parameters in the proposed method was tested on both synthetic hyperspectral datasets and AVIRIS Cuprite dataset, and the recommended parameters setting was proposed. The results in this study demonstrated that the proposed EE-DFA method showed better performance than the existing popular methods. Moreover, EE-DFA is robust under different SNR conditions.

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique

PubMed Central

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-01-01

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system’s lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system’s ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection. PMID:29543733

Shallow sea-floor reflectance and water depth derived by unmixing multispectral imagery

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

Bierwirth, P.N.; Lee, T.J.; Burne, R.V.

1993-03-01

A major problem for mapping shallow water zones by the analysis of remotely sensed data is that contrast effects due to water depth obscure and distort the special nature of the substrate. This paper outlines a new method which unmixes the exponential influence of depth in each pixel by employing a mathematical constraint. This leaves a multispectral residual which represents relative substrate reflectance. Input to the process are the raw multispectral data and water attenuation coefficients derived by the co-analysis of known bathymetry and remotely sensed data. Outputs are substrate-reflectance images corresponding to the input bands and a greyscale depthmore » image. The method has been applied in the analysis of Landsat TM data at Hamelin Pool in Shark Bay, Western Australia. Algorithm derived substrate reflectance images for Landsat TM bands 1, 2, and 3 combined in color represent the optimum enhancement for mapping or classifying substrate types. As a result, this color image successfully delineated features, which were obscured in the raw data, such as the distributions of sea-grasses, microbial mats, and sandy area. 19 refs.« less

High efficiency organic photovoltaic cells employing hybridized mixed-planar heterojunctions

DOEpatents

Xue, Jiangeng; Uchida, Soichi; Rand, Barry P.; Forrest, Stephen

2015-08-18

A device is provided, having a first electrode, a second electrode, and a photoactive region disposed between the first electrode and the second electrode. The photoactive region includes a first photoactive organic layer that is a mixture of an organic acceptor material and an organic donor material, wherein the first photoactive organic layer has a thickness not greater than 0.8 characteristic charge transport lengths; a second photoactive organic layer in direct contact with the first organic layer, wherein the second photoactive organic layer is an unmixed layer of the organic acceptor material of the first photoactive organic layer, and the second photoactive organic layer has a thickness not less than about 0.1 optical absorption lengths; and a third photoactive organic layer disposed between the first electrode and the second electrode and in direct contact with the first photoactive organic layer. The third photoactive organic layer is an unmixed layer of the organic donor layer of the first photoactive organic layer and has a thickness not less than about 0.1 optical absorption lengths.

Validation of Spectral Unmixing Results from Informed Non-Negative Matrix Factorization (INMF) of Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Wright, L.; Coddington, O.; Pilewskie, P.

2017-12-01

Hyperspectral instruments are a growing class of Earth observing sensors designed to improve remote sensing capabilities beyond discrete multi-band sensors by providing tens to hundreds of continuous spectral channels. Improved spectral resolution, range and radiometric accuracy allow the collection of large amounts of spectral data, facilitating thorough characterization of both atmospheric and surface properties. We describe the development of an Informed Non-Negative Matrix Factorization (INMF) spectral unmixing method to exploit this spectral information and separate atmospheric and surface signals based on their physical sources. INMF offers marked benefits over other commonly employed techniques including non-negativity, which avoids physically impossible results; and adaptability, which tailors the method to hyperspectral source separation. The INMF algorithm is adapted to separate contributions from physically distinct sources using constraints on spectral and spatial variability, and library spectra to improve the initial guess. Using this INMF algorithm we decompose hyperspectral imagery from the NASA Hyperspectral Imager for the Coastal Ocean (HICO), with a focus on separating surface and atmospheric signal contributions. HICO's coastal ocean focus provides a dataset with a wide range of atmospheric and surface conditions. These include atmospheres with varying aerosol optical thicknesses and cloud cover. HICO images also provide a range of surface conditions including deep ocean regions, with only minor contributions from the ocean surfaces; and more complex shallow coastal regions with contributions from the seafloor or suspended sediments. We provide extensive comparison of INMF decomposition results against independent measurements of physical properties. These include comparison against traditional model-based retrievals of water-leaving, aerosol, and molecular scattering radiances and other satellite products, such as aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS).

Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data

NASA Astrophysics Data System (ADS)

Lu, Yuhao; Coops, Nicholas C.; Hermosilla, Txomin

2017-04-01

Urbanization globally is consistently reshaping the natural landscape to accommodate the growing human population. Urban vegetation plays a key role in moderating environmental impacts caused by urbanization and is critically important for local economic, social and cultural development. The differing patterns of human population growth, varying urban structures and development stages, results in highly varied spatial and temporal vegetation patterns particularly in the pan-Pacific region which has some of the fastest urbanization rates globally. Yet spatially-explicit temporal information on the amount and change of urban vegetation is rarely documented particularly in less developed nations. Remote sensing offers an exceptional data source and a unique perspective to map urban vegetation and change due to its consistency and ubiquitous nature. In this research, we assess the vegetation fractions of 25 cities across 12 pan-Pacific countries using annual gap-free Landsat surface reflectance products acquired from 1984 to 2012, using sub-pixel, spectral unmixing approaches. Vegetation change trends were then analyzed using Mann-Kendall statistics and Theil-Sen slope estimators. Unmixing results successfully mapped urban vegetation for pixels located in urban parks, forested mountainous regions, as well as agricultural land (correlation coefficient ranging from 0.66 to 0.77). The greatest vegetation loss from 1984 to 2012 was found in Shanghai, Tianjin, and Dalian in China. In contrast, cities including Vancouver (Canada) and Seattle (USA) showed stable vegetation trends through time. Using temporal trend analysis, our results suggest that it is possible to reduce noise and outliers caused by phenological changes particularly in cropland using dense new Landsat time series approaches. We conclude that simple yet effective approaches of unmixing Landsat time series data for assessing spatial and temporal changes of urban vegetation at regional scales can provide critical information for urban planners and anthropogenic studies globally.

Is There a Paradox of Aging: When the Negative Aging Stereotype Meets the Positivity Effect in Older Adults.

PubMed

Zhou, Liqing; Lu, Jia; Chen, Guopeng; Dong, Li; Yao, Yujia

2017-01-01

Background/Study Context: Socioemotional selectivity theory (SST) states that the positivity effect is a result of older adults' emotion regulation and that older adults derive more emotional satisfaction from prioritizing positive information processing. The authors explored whether the positivity effect appeared when the negative aging stereotype was activated in older adults and also whether the effect differed between mixed and unmixed valence conditions. Sixty younger (18-23 years of age) and 60 older (60-87 years of age) adults were randomly assigned to a control group and a priming group, in which the negative aging stereotype was activated. All the participants were asked to select 15 words that best described the elderly from a mixed-word list (positive and negative words were mixed together) and from an unmixed-word list (positive and negative words were separated). Older adults in the control group selected more positive words, whereas among younger adults, selection did not differ by valence in either the mixed- or unmixed-word list conditions. There were no differences between the positive and negative word choices of the younger and older adults in the priming group. We calculated the differences between the numbers of positive and negative words, and the differences in the older adults' word choices were larger than those among the younger adults; the differences were also larger in the control group than in the priming group. The positivity effect worked by choosing positive stimuli rather than avoiding negative stimuli. The role of emotion regulation in older adults was limited, and when the positivity effect faced the effect of the negative aging stereotype, the negative stereotype effect was dominant. Future research should explore the changes in the positivity effect in the face of a positive aging stereotype and what roles other factors (e.g., activation level of the stereotype, arousal level of affective words) might play.

Detrital illite crystals identified from crystallite thickness measurements in siliciclastic sediments

USGS Publications Warehouse

Aldega, L.; Eberl, D.D.

2005-01-01

Illite crystals in siliciclastic sediments are heterogeneous assemblages of detrital material coming from various source rocks and, at paleotemperatures >70 ??C, of superimposed diagenetic modification in the parent sediment. We distinguished the relative proportions of 2M1 detrital illite and possible diagenetic 1Md + 1M illite by a combined analysis of crystal-size distribution and illite polytype quantification. We found that the proportions of 1Md + 1M and 2M1 illite could be determined from crystallite thickness measurements (BWA method, using the MudMaster program) by unmixing measured crystallite thickness distributions using theoretical and calculated log-normal and/or asymptotic distributions. The end-member components that we used to unmix the measured distributions were three asymptotic-shaped distributions (assumed to be the diagenetic component of the mixture, the 1Md + 1M polytypes) calculated using the Galoper program (Phase A was simulated using 500 crystals per cycle of nucleation and growth, Phase B = 333/cycle, and Phase C = 250/ cycle), and one theoretical log-normal distribution (Phase D, assumed to approximate the detrital 2M1 component of the mixture). In addition, quantitative polytype analysis was carried out using the RockJock software for comparison. The two techniques gave comparable results (r2 = 0.93), which indicates that the unmixing method permits one to calculate the proportion of illite polytypes and, therefore, the proportion of 2M1 detrital illite, from crystallite thickness measurements. The overall illite crystallite thicknesses in the samples were found to be a function of the relative proportions of thick 2M1 and thin 1Md + 1M illite. The percentage of illite layers in I-S mixed layers correlates with the mean crystallite thickness of the 1Md + 1M polytypes, indicating that these polytypes, rather than the 2M1 polytype, participate in I-S mixed layering.

Physical-biopolymer characterization of polyhydroxybutyrate-co-hydroxyvalerate (PHBV) blended with natural rubber latex

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

Kuntanoo, K., E-mail: thip-kk@hotmail.com; Promkotra, S., E-mail: sarunya@kku.ac.th; Kaewkannetra, P., E-mail: paknar@kku.ac.th

A biopolymer of polyhydroxybutyrate-co-hydroxyvalerate (PHBV) is blended with bio-based materials, natural rubber latex, to improve their microstructures. The various ratios between PHBV and natural rubber latex are examined to develop their mechanical properties. In general, physical properties of PHBV are hard, brittle and low flexible while natural rubber (NR) is presented itself as high elastic materials. Concentrations of the PHBV solution are constituted at 1%, 2% and 3% (w/v). The mixtures of their PHBV solutions to natural rubber latex are produced the blended films in three different ratios of 4:6, 5:5 and 6:4, respectively. They are characterized by appearance analysesmore » which are the scanning electron microscope (SEM), universal testing machine (UTM) and differential scanning calorimetry (DSC). The SEM photomicrographs of the blended films and the controlled PHBV can provide the void distribution in the range of 12-14% and 19-21%, respectively. For mechanical properties of the blended films, the various elastic moduli of 1%, 2% and 3% (w/v) PHBV are the average of 773, 956 and 1,007 kPa, respectively. The tensile strengths of the blends increase with the increased concentrations of PHBV, similarly trend to the elastic modulus. The crystallization and melting behavior of unmixed PHBV and the blends are determined by DSC. Melting transition temperatures (T{sub m}) of the unmixed PHBV are stated two melting peak at 154°C and 173°C. Besides, the melting peaks of the blends alter in the range of 152-156°C and 168-171°C, respectively. According to morphology of the blends, the void distribution decreases twice compared to the unmixed PHBV. The results of mechanical properties and thermal analysis indicate that the blended PHBV can be developed their properties by more resilient and wide range of temperature than usual.« less

Unmixing the Mixing Cost: Contributions from Dimensional Relevance and Stimulus-Response Suppression

ERIC Educational Resources Information Center

Mari-Beffa, Paloma; Cooper, Stephen; Houghton, George

2012-01-01

When participants repeat the same task in a context in which the task may also switch (a mixed block), performance deteriorates compared to when there is only one task repeating (a pure block). Three experiments were designed to assess how perceptual and motor transitions influenced this mixing cost. Experiment 1 provided three pure block…

A cross-comparison of field, spectral, and lidar estimates of forest canopy cover

Treesearch

Alistair M. S. Smith; Michael J. Falkowski; Andrew T. Hudak; Jeffrey S. Evans; Andrew P. Robinson; Caiti M. Steele

2010-01-01

A common challenge when comparing forest canopy cover and similar metrics across different ecosystems is that there are many field- and landscape-level measurement methods. This research conducts a cross-comparison and evaluation of forest canopy cover metrics produced using unmixing of reflective spectral satellite data, light detection and ranging (lidar) data, and...

Biomass and health based forest cover delineation using spectral un-mixing

Treesearch

Mohan Tiruveedhula; Joseph Fan; Ravi R. Sadasivuni; Surya S. Durbha; David L. Evans

2009-01-01

Remote sensing is a well-suited source of information on various forest characteristics such as forest cover type, leaf area, biomass, and health. The use of appropriate layers helps to quantify the variables of interest. For example, normalized difference vegetation index (NDVI) and greenness help explain variability in biomass as well as health of forests....

7 CFR 201.60 - Purity percentages.

Code of Federal Regulations, 2014 CFR

2014-01-01

... (2) mixtures in which the particle-weight ratio is 1:1 to 1.49:1, inclusive. Tolerances for... Component of a Purity Analysis for (1) Unmixed Seed or (2) Mixed Seed in Which the Particle Weight Ratio Is... particle-weight ratio is 1.5:1 to 20:1 and beyond: The symbols used in the formula are as follows: T...

7 CFR 201.60 - Purity percentages.

Code of Federal Regulations, 2011 CFR

2011-01-01

... (2) mixtures in which the particle-weight ratio is 1:1 to 1.49:1, inclusive. Tolerances for... Component of a Purity Analysis for (1) Unmixed Seed or (2) Mixed Seed in Which the Particle Weight Ratio Is... particle-weight ratio is 1.5:1 to 20:1 and beyond: The symbols used in the formula are as follows: T...

7 CFR 201.60 - Purity percentages.

Code of Federal Regulations, 2012 CFR

2012-01-01

... (2) mixtures in which the particle-weight ratio is 1:1 to 1.49:1, inclusive. Tolerances for... Component of a Purity Analysis for (1) Unmixed Seed or (2) Mixed Seed in Which the Particle Weight Ratio Is... particle-weight ratio is 1.5:1 to 20:1 and beyond: The symbols used in the formula are as follows: T...

7 CFR 201.60 - Purity percentages.

Code of Federal Regulations, 2013 CFR

2013-01-01

... (2) mixtures in which the particle-weight ratio is 1:1 to 1.49:1, inclusive. Tolerances for... Component of a Purity Analysis for (1) Unmixed Seed or (2) Mixed Seed in Which the Particle Weight Ratio Is... particle-weight ratio is 1.5:1 to 20:1 and beyond: The symbols used in the formula are as follows: T...

A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI.

PubMed

Pisharady, Pramod Kumar; Sotiropoulos, Stamatios N; Sapiro, Guillermo; Lenglet, Christophe

2017-09-01

We propose a sparse Bayesian learning algorithm for improved estimation of white matter fiber parameters from compressed (under-sampled q-space) multi-shell diffusion MRI data. The multi-shell data is represented in a dictionary form using a non-monoexponential decay model of diffusion, based on continuous gamma distribution of diffusivities. The fiber volume fractions with predefined orientations, which are the unknown parameters, form the dictionary weights. These unknown parameters are estimated with a linear un-mixing framework, using a sparse Bayesian learning algorithm. A localized learning of hyperparameters at each voxel and for each possible fiber orientations improves the parameter estimation. Our experiments using synthetic data from the ISBI 2012 HARDI reconstruction challenge and in-vivo data from the Human Connectome Project demonstrate the improvements.

The Chemistry of Population III Supernova Ejecta. II. The Nucleation of Molecular Clusters as a Diagnostic for Dust in the Early Universe

NASA Astrophysics Data System (ADS)

Cherchneff, Isabelle; Dwek, Eli

2010-04-01

We study the formation of molecular precursors to dust in the ejecta of Population III supernovae (Pop. III SNe) using a chemical kinetic approach to follow the evolution of small dust cluster abundances from day 100 to day 1000 after explosion. Our work focuses on zero-metallicity 20 M sun and 170 M sun progenitors, and we consider fully macroscopically mixed and unmixed ejecta. The dust precursors comprise molecular chains, rings, and small clusters of chemical composition relevant to the initial elemental composition of the ejecta under study. The nucleation stage for small silica, metal oxides and sulfides, pure metal, and carbon clusters is described with a new chemical reaction network highly relevant to the kinetic description of dust formation in hot circumstellar environments. We consider the effect of the pressure dependence of critical nucleation rates and test the impact of microscopically mixed He+ on carbon dust formation. Two cases of metal depletion on silica clusters (full and no depletion) are considered to derive upper limits to the amounts of dust produced in SN ejecta at 1000 days, while the chemical composition of clusters gives a prescription for the type of dust formed in Pop. III SNe. We show that the cluster mass produced in the fully mixed ejecta of a 170 M sun progenitor is ~ 25 M sun whereas its 20 M sun counterpart forms ~ 0.16 M sun of clusters. The unmixed ejecta of a 170 M sun progenitor SN synthesize ~5.6 M sun of small clusters, while its 20 M sun counterpart produces ~0.103 M sun. Our results point to smaller amounts of dust formed in the ejecta of Pop. III SNe by a factor of ~ 5 compared to values derived by previous studies, and to different dust chemical compositions. Such deviations result from some erroneous assumptions made, the inappropriate use of classical nucleation theory to model dust formation, and the omission of the synthesis of molecules in SN ejecta. We also find that the unmixed ejecta of massive Pop. III SNe chiefly form silica and/or silicates, and pure silicon grains whereas their lower mass counterparts form a dust mixture dominated by silica and/or silicates, pure silicon, and iron sulfides. Amorphous carbon can only condense via the nucleation of carbon chains and rings characteristic of the synthesis of fullerenes when the ejecta carbon-rich zone is deprived of He+. The first dust enrichment to the primordial gas in the early universe from Pop. III massive SN comprises primarily pure silicon, silica, and silicates. If carbon dust is present at redshift z > 6, alternative dust sources must be considered.

A clustering algorithm for sample data based on environmental pollution characteristics

NASA Astrophysics Data System (ADS)

Chen, Mei; Wang, Pengfei; Chen, Qiang; Wu, Jiadong; Chen, Xiaoyun

2015-04-01

Environmental pollution has become an issue of serious international concern in recent years. Among the receptor-oriented pollution models, CMB, PMF, UNMIX, and PCA are widely used as source apportionment models. To improve the accuracy of source apportionment and classify the sample data for these models, this study proposes an easy-to-use, high-dimensional EPC algorithm that not only organizes all of the sample data into different groups according to the similarities in pollution characteristics such as pollution sources and concentrations but also simultaneously detects outliers. The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and finally modifying the clusters using a method similar to k-Means. The validity and accuracy of the algorithm are tested using both real and synthetic datasets, which makes the EPC algorithm practical and effective for appropriately classifying sample data for source apportionment models and helpful for better understanding and interpreting the sources of pollution.

Medical tourism-A New Arena.

PubMed

Puri, S; Singh, A; Yashik

2010-01-01

Globalisation has given birth to medical tourism. Health and medical tourism are the fastest growing segments in not only developed nations but in developing countries too. India has become a hot destination, as the Indian medical standards match up to the highly prescribed international standards at a very low cost. However, it is an unmixed blessing; along with advantages, it has many unintended side effects also.

The effect of high intensity mixing on the enzymatic hydrolysis of concentrated cellulose fiber suspensions

Treesearch

Joseph R. Samaniuk; C. Tim Scott; Thatcher W. Root; Daniel J. Klingenberg

2011-01-01

Enzymatic hydrolysis of lignocellulosic biomass in a high shear environment was examined. The conversion of cellulose to glucose in samples mixed in a torque rheometer producing shear flows similar to those found in twin screw extruders was greater than that of unmixed samples. In addition, there is a synergistic effect of mixing and enzymatic hydrolysis; mixing...

High spatial resolution spectral unmixing for mapping ash species across a complex urban environment

Treesearch

Jennifer Pontius; Ryan P. Hanavan; Richard A. Hallett; Bruce D. Cook; Lawrence A. Corp

2017-01-01

Ash (Fraxinus L.) species are currently threatened by the emerald ash borer (EAB; Agrilus planipennis Fairmaire) across a growing area in the eastern US. Accurate mapping of ash species is required to monitor the host resource, predict EAB spread and better understand the short- and long-term effects of EAB on the ash resource...

Anion permselective membrane

NASA Technical Reports Server (NTRS)

Hodgdon, R. B.; Waite, W. A.; Alexander, S. S.

1984-01-01

Two polymer ion exchange membranes were synthesized to fulfill the needs of both electrical resistivity and anolyte/catholyte separation for utility load leveling utilizing the DOE/NASA mixed electrolyte REDOX battery. Both membranes were shown to meet mixed electrolyte utility load leveling criteria. Several modifications of an anion exchange membrane failed to meet utility load leveling REDOX battery criteria using the unmixed electrolyte REDOX cell.

Disaggregating tree and grass phenology in tropical savannas

NASA Astrophysics Data System (ADS)

Zhou, Qiang

Savannas are mixed tree-grass systems and as one of the world's largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation. The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency method was better for extracting the green tree phenology, but the original decomposition method was better for retrieval of understory grass phenology. Both methods, however, were less accurate than in the Cerrado than in Australia due to intermingling and intergrading of grass and small woody components. Since African savanna trees are predominantly deciduous, the frequency method was combined with the linear unmixing of fractional cover to attempt to separate the relatively similar phenology of deciduous trees and seasonal grasses. The results for Africa revealed limitations associated with both methods. There was spatial and seasonal variation in the spectral indices used to unmix fractional cover resulting in poor validation for NPV in particular. The frequency analysis revealed significant phase variation indicative of different phenology, but these could not be clearly ascribed to separate grass and tree components. Overall findings indicate that site-specific variation and vegetation structure and composition, along with MODIS pixel resolution, and the simple vegetation index approach used was not robust across the different savanna biomes. The approach showed generally better performance for estimating PV fraction, and separating green phenology, but there were major inconsistencies, errors and biases in estimation of NPV and BS outside of the Australian savanna environment.

Hydrogeology, Chemical Characteristics, and Transport Processes in the Zone of Contribution of a Public-Supply Well in York, Nebraska

USGS Publications Warehouse

Landon, Matthew K.; Clark, Brian R.; McMahon, Peter B.; McGuire, Virginia L.; Turco, Michael J.

2008-01-01

In 2001, the U.S. Geological Survey, as part of the National Water Quality Assessment (NAWQA) Program, initiated a topical study of Transport of Anthropogenic and Natural Contaminants (TANC) to PSW (public-supply wells). Local-scale and regional-scale TANC study areas were delineated within selected NAWQA study units for intensive study of processes effecting transport of contaminants to PSWs. This report describes results from a local-scale TANC study area at York, Nebraska, within the High Plains aquifer, including the hydrogeology and geochemistry of a 108-square-kilometer study area that contains the zone of contribution to a PSW selected for study (study PSW), and describes factors controlling the transport of selected anthropogenic and natural contaminants to PSWs. Within the local-scale TANC study area, the High Plains aquifer is approximately 75 m (meter) thick, and includes an unconfined aquifer, an upper confining unit, an upper confined aquifer, and a lower confining unit with lower confined sand lenses (units below the upper confining unit are referred to as confined aquifers) in unconsolidated alluvial and glacial deposits overlain by loess and underlain by Cretaceous shale. From northwest to southeast, land use in the local-scale TANC study area changes from predominantly irrigated agricultural land to residential and commercial land in the small community of York (population approximately 8,100). For the purposes of comparing water chemistry, wells were classified by degree of aquifer confinement (unconfined and confined), depth in the unconfined aquifer (shallow and deep), land use (urban and agricultural), and extent of mixing in wells in the confined aquifer with water from the unconfined aquifer (mixed and unmixed). Oxygen (delta 18O) and hydrogen (delta D) stable isotopic values indicated a clear isotopic contrast between shallow wells in the unconfined aquifer (hereinafter, unconfined shallow wells) and most monitoring wells in the confined aquifers (hereinafter, confined unmixed wells). Delta 18O and delta D values for a minority of wells in the confined aquifers were intermediate between those for the unconfined shallow wells and those for the confined unmixed wells. These intermediate values were consistent with mixing of water from unconfined and confined aquifers (hereinafter, confined mixed wells). Oxidation-reduction conditions were primarily oxic in the unconfined aquifer and variably reducing in the confined aquifers. Trace amounts of volatile organic compounds (VOC), particularly tetrachloroethylene (PCE) and trichloroethylene (TCE), were widely detected in unconfined shallow urban wells and indicated the presence of young urban recharge waters in most confined mixed wells. The presence of degradation products of agricultural pesticides (acetochlor and alachlor) in some confined mixed wells suggests that some fraction of the water in these wells also was the result of recharge in agricultural areas. In the unconfined aquifer, age-tracer data (chlorofluorocarbon and sulfur hexafluoride data, and tritium to helium-3 ratios) fit a piston-flow model, with apparent recharge ages ranging from 7 to 48 years and generally increasing with depth. Age-tracer data for the confined aquifers were consistent with mixing of 'old' water, not containing modern tracers recharged in the last 60 years, and exponentially-mixed 'young' water with modern tracers. Confined unmixed wells contained less than (=) 97% of old water. Confined mixed wells contained >30% young water and mean ages ranged from 12 to 14 years. Median concentrations of nitrate (as nitrogen, hereinafter, nitrate-N) were 17.3 and 16.0 mg/L (milligram per liter) in unconfined shallow urban and agricultural wells, respectively, indicating a range of likely nitrate sources. Septic systems are most numerous near the edge of the urban area and appear to be

Medical tourism-A New Arena

PubMed Central

Puri, S; Singh, A; Yashik

2010-01-01

Globalisation has given birth to medical tourism. Health and medical tourism are the fastest growing segments in not only developed nations but in developing countries too. India has become a hot destination, as the Indian medical standards match up to the highly prescribed international standards at a very low cost. However, it is an unmixed blessing; along with advantages, it has many unintended side effects also. PMID:23113017

Evaluation of linear spectral unmixing and deltaNBR for predicting post-fire recovery in a North American ponderosa pine forest

Treesearch

A. M. S. Smith; L. B. Lenilte; A. T. Hudak; P. Morgan

2007-01-01

The Differenced Normalized Burn Ratio (deltaNBR) is widely used to map post-fire effects in North America from multispectral satellite imagery, but has not been rigorously validated across the great diversity in vegetation types. The importance of these maps to fire rehabilitation crews highlights the need for continued assessment of alternative remote sensing...

Unmixing the Materials and Mechanics Contributions in Non-resolved Object Signatures

DTIC Science & Technology

2008-09-01

abundances from hyperspectral or multi-spectral time - resolved signatures. A Fourier analysis of temporal variation of material abundance provides...factorization technique to extract the temporal variation of material abundances from hyperspectral or multi-spectral time - resolved signatures. A Fourier...approximately one hundred wavelengths in the visible spectrum. The frame rate for the instrument was not large enough to collect time resolved data. However

Discrimination of Sedimentary Lithologies Through Unmixing of EO-1 Hyperion Data: Melville Island, Canadian High Arctic

NASA Astrophysics Data System (ADS)

Leverington, D. W.

2008-12-01

The use of remote-sensing techniques in the discrimination of rock and soil classes in northern regions can help support a diverse range of activities including environmental characterization, mineral exploration, and the study of Quaternary paleoenvironments. Images of low spectral resolution can commonly be used in the mapping of lithological classes possessing distinct spectral characteristics, but hyperspectral databases offer greater potential for discrimination of materials distinguished by more subtle reflectance properties. Orbiting sensors offer an especially flexible and cost-effective means for acquisition of data to workers unable to conduct airborne surveys. In an effort to better constrain the utility of hyperspectral datasets in northern research, this study undertook to investigate the effectiveness of EO-1 Hyperion data in the discrimination and mapping of surface classes at a study area on Melville Island, Nunavut. Bedrock units in the immediate study area consist of late-Paleozoic clastic and carbonate sequences of the Sverdrup Basin. Weathered and frost-shattered felsenmeer, predominantly taking the form of boulder- to pebble-sized clasts that have accumulated in place and that mantle parent bedrock units, is the most common surface material in the study area. Hyperion data were converted from at-sensor radiance to reflectance, and were then linearly unmixed on the basis of end-member spectra measured from field samples. Hyperion unmixing results effectively portray the general fractional cover of six end members, although the fraction images of several materials contain background values that in some areas overestimate surface exposure. The best separated end members include the snow, green vegetation, and red-weathering sandstone classes, whereas the classes most negatively affected by elevated fraction values include the mudstone, limestone, and 'other' sandstone classes. Local overestimates of fractional cover are likely related to the shared lithological and weathering characteristics of several clastic and carbonate units, and may also be related to the lower radiometric precision characteristic of Hyperion data. Despite these issues, the databases generated in this study successfully provide useful complementary information to that provided by maps of local bedrock geology.

Precombination Cloud Collapse and Baryonic Dark Matter

NASA Technical Reports Server (NTRS)

Hogan, Craig J.

1993-01-01

A simple spherical model of dense baryon clouds in the hot big bang 'strongly nonlinear primordial isocurvature baryon fluctuations' is reviewed and used to describe the dependence of cloud behavior on the model parameters, baryon mass, and initial over-density. Gravitational collapse of clouds before and during recombination is considered including radiation diffusion and trapping, remnant type and mass, and effects on linear large-scale fluctuation modes. Sufficiently dense clouds collapse early into black holes with a minimum mass of approx. 1 solar mass, which behave dynamically like collisionless cold dark matter. Clouds below a critical over-density, however, delay collapse until recombination, remaining until then dynamically coupled to the radiation like ordinary diffuse baryons, and possibly producing remnants of other kinds and lower mass. The mean density in either type of baryonic remnant is unconstrained by observed element abundances. However, mixed or unmixed spatial variations in abundance may survive in the diffuse baryon and produce observable departures from standard predictions.

A self-trained classification technique for producing 30 m percent-water maps from Landsat data

USGS Publications Warehouse

Rover, Jennifer R.; Wylie, Bruce K.; Ji, Lei

2010-01-01

Small bodies of water can be mapped with moderate-resolution satellite data using methods where water is mapped as subpixel fractions using field measurements or high-resolution images as training datasets. A new method, developed from a regression-tree technique, uses a 30 m Landsat image for training the regression tree that, in turn, is applied to the same image to map subpixel water. The self-trained method was evaluated by comparing the percent-water map with three other maps generated from established percent-water mapping methods: (1) a regression-tree model trained with a 5 m SPOT 5 image, (2) a regression-tree model based on endmembers and (3) a linear unmixing classification technique. The results suggest that subpixel water fractions can be accurately estimated when high-resolution satellite data or intensively interpreted training datasets are not available, which increases our ability to map small water bodies or small changes in lake size at a regional scale.

Ignition dynamics of a laminar diffusion flame in the field of a vortex embedded in a shear flow

NASA Technical Reports Server (NTRS)

Macaraeg, Michele G.; Jackson, T. L.; Hussaini, M. Y.

1994-01-01

The role of streamwise-spanwise vorticity interactions that occur in turbulent shear flows on flame/vortex interactions is examined by means of asymptotic analysis and numerical simulation in the limit of small Mach number. An idealized model is employed to describe the interaction process. The model consists of a one-step, irreversible Arrhenius reaction between initially unmixed species occupying adjacent half-planes which are then allowed to mix and react in the presence of a streamwise vortex embedded in a shear flow. It is found that the interaction of the streamwise vortex with shear gives rise to small-scale velocity oscillations which increase in magnitude with shear strength. These oscillations give rise to regions of strong temperature gradients via viscous heating, which can lead to multiple ignition points and substantially decrease ignition times. The evolution in time of the temperature and mass-fraction fields is followed, and emphasis is placed on the ignition time and structure as a function of vortex and shear strength.

Juventae Chasma and Maja Valles, Mars: Further Evidence for Multiple Flooding Events

NASA Astrophysics Data System (ADS)

Gross, C.; Wendt, L.; Dumke, A.; Neukum, G.

2009-04-01

Introduction: In this study we investigate the age relationship of Juventae Chasma to the adjacent Maja Valles in order to gain a feasible explanation for the formation and evolution of rhythmic light-toned layered deposits (LLD). In this first step, we use impact crater size-frequency distributions for dating the planetary surface in the regions of interest. Juventae Chasma is located at the northern side of the Valles Marineris and stretches for approximately 150 km east-west and 250 km north-south. The basin floor shows a depth of 5 km and more below the surrounding surface. To the north lies the adjacent Maja Valles, a 50 km to 150 km wide channel extending for 1600 km northward and discharging into the Chryse Planitia plains. Various investigations of several authors have been carried out on this subject in the past, but the formation of the LLD in Juventae Chasma is still poorly understood. The formation theories range from a volcanic origin [1], lake deposits, delta deposits [2] to spring deposits [3]. A very different hypothesis for the formation of the sulfates is deposition from airfall. This could happen as dry deposition from the atmosphere or in co-precipitation with icy materials such as snow crystals or dust particles. This phenomenon is observed at the poles of Mars, where rhythmic layerings occur showing high similarities to the sulfate deposits in Juventae Chasma. The light-toned materials in the chasma show a spectral signature indicative of kieserite in the outcrops A, C and D and in the lower part of B, whereas the upper part of B was described as gypsum [4]. Wendt et al. [5] identified different mineral assemblages in the cap rock of mount B, using the CRISM instrument and the Multiple-Endmember Linear Spectral Unmixing Model (MELSUM). HRSC DTM: The Digital Terrain Model (DTM ) mosaic (see Fig. 1) was derived from 11 HRSC orbits at approximately -7° S to 8° N and 295° to 301° E with a ground resolution of 100 m per pixel and an ortho-image mosaic with a ground resolution of 12.5 m per pixel. The main processing tasks for the DTM derivation are first a pre-rectification of image data using the global MOLA- based DTM, then a least-squares area-based matching between nadir and the other channels (stereo and photometry) in a pyramidal approach and finally, DTM raster generation. Improved orientation data are necessary for high-resolution digital terrain models and orthoimage mosaics. For this purpose, new exterior and interior orientation data, based on tie-point matching have been used. The bundle adjustment approach for photogrammetric point determination with a three-line camera is a least squares adjustment based on the well known collinearity equations [6]. The construction of the HRSC-DTM is the basis for further investigation of the masses and volumes, transported from Juventae Chasma through Maja Valles. We use HRSC and OMEGA (Mars Express), as well as HiRise and CRISM (Mars Reconnaissance Orbiter) data for generally mapping the target area. Crater counting is carried out using CTX and HRSC images. Results: The results of the first determinations of the impact crater size-frequency distributions are presented in Fig. 2 and 3 and show an age of 1.22 Ga (+/- 0.16 Ga) for the western part of the Maja Valles channel. The southeastern channel (close to the streamlined island) shows older ages of 3.68 Ga (+0.08/-0.17 Ga) and 2.18 Ga (+/- 0.31 Ga). This clearly indicates, that multiple flooding events took place in the area. The first results for Juventae Chasma age determinations indicate an age of 3.33 Ga. Conclusions: The HRSC-DTM enables us to examine the study area most accurately. We dated the formation of the Juventae Chasma with an age of at least 3.33 Ga. The investigated sites at Maja Valles clearly show evidences for multiple outflow events. Some of these events took place before the formation of the sulfate deposits in Juventae Chasma. Further age determinations and mapping will be carried out in this area to obtain a chronology of events of this highly interesting area in the equatorial regions of Mars. Acknowledgements: This research has been supported by the Helmholtz Association through the research alliance "Planetary Evolution and Life" and by the German Space Agency (DLR) in the context of the Mars Express project. References: [1] Chapman, M. and Gudmundsson, M. (2003), JGR, 108, E10, 2-1. [2] Ori, Komatsu et al. (2006), LPSC XXXVII, 1247. [3] Rossi, A.P. et al. (2008), JGR, 113, E8. [4] Gendrin, A. et al. (2005), Science, 307, 5751, 1587-1591. [5] Wendt, L. et al. (2009), LPSC XXXX, 1531. [6] Dumke, A. et al (2009), LPSC XXXX, Valles Marineris, Mars: Model on the Basis of Mars-Express HRSC Data.

Quantitative interpretation of magnetic properties as a way to characterize biogeophysical signatures of biodegraded contaminated sites

NASA Astrophysics Data System (ADS)

Ustra, A.; Kessouri, P.; Leite, A.; Mendonça, C. A.; Bandeira, N.

2017-12-01

Magnetic minerals in soils and rocks are one way to study biogechemical and paleoenvironmental processes. The ultrafine fraction of these minerals (superparmagnetic (SP) and stable single domain (SSD)) are usually investigated in environmental magnetism studies, since changes in mineralogy, concentration, size and morphology of the magnetic grains can be related to biogeochemical processes. In this study, we use low-field frequency dependent susceptibility (FDS) and isothermal remanent magnetization (IRM) to characterize the magnetic properties of materials in environmental magnetism. Magnetic susceptibility (MS) measurements are frequently used as a proxy of magnetic minerals present in soils and rocks. MS is a complex function of magnetic mineralogy and grain size, as well as magnitude and frequency of the applied field. This work presents a method for inverting low-field FDS data. The inverted parameters can be interpreted in terms of grain size variations of magnetic particles on the SP-SSD transition. This work also presents a method for inverting IRM demagnetization curves, to obtain the saturation magnetization, the individual magnetic moment for an assemblage of ultrafine SP minerals and estimate the concentration of magnetic carriers. IRM magnetization curves can be interpreted as resulting from distinct contributions of different mineral phases, which can be described by Cummulative Log-Gaussian (CLG) distributions. Each acquisition curve provides fundamental parameters that are characteristic of the respective mineral phase. The CLG decomposition is widely used in an interpretation procedure named mineral unmixing. In this work we present an inversion method for mineral unmixing, implementing the genetic algorithm to find the parameters of distinct components. These methodologies have been tested by synthetic models and applied to data from environmental magnetism studies. In this work we apply the proposed methodologies to characterize the magnetic properties of samples from the former Brandywine MD Defense Reutilization and Marketing Office (DRMO). The results from the magnetic properties characterization will provide additional information that may assist the interpretation of the biogeophysical signatures observed at the site.

Comparative analysis of spectral unmixing and neural networks for estimating small diameter tree above-ground biomass in the State of Mississippi

Treesearch

Moham P. Tiruveedhula; Joseph Fan; Ravi R. Sadasivuni; Surya S. Durbha; David L. Evans

2010-01-01

The accumulation of small diameter trees (SDTs) is becoming a nationwide concern. Forest management practices such as fire suppression and selective cutting of high grade timber have contributed to an overabundance of SDTs in many areas. Alternative value-added utilization of SDTs (for composite wood products and biofuels) has prompted the need to estimate their...

Spectral Unmixing Applied to Desert Soils for the Detection of Sub-Pixel Disturbances

DTIC Science & Technology

2012-09-01

and Glazner, 1997). Rocks underlying Panum Crater consist of the granitic and metamorphic batholith associated with the Sierra Nevada. On top of this...of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE September...technology can be used to detect and characterize surface disturbance both literally (visually) and non-literally (analytically). Non-literal approaches

Mineral and Lithology Mapping of Drill Core Pulps Using Visible and Infrared Spectrometry

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

Taylor, G. R., E-mail: G.Taylor@unsw.edu.au

2000-12-15

A novel approach for using field spectrometry for determining both the mineralogy and the lithology of drill core pulps (powders) is developed and evaluated. The methodology is developed using material from a single drillhole through a mineralized sequence of rocks from central New South Wales. Mineral library spectra are used in linear unmixing routines to determine the mineral abundances in drill core pulps that represent between 1 m and 3 m of core. Comparison with X-Ray Diffraction (XRD) analyses shows that for most major constituents, spectrometry provides an estimate of quantitative mineralogy that is as reliable as that provided bymore » XRD. Confusion between the absorption features of calcite and those of chlorite causes the calcite contents determined by spectrometry to be unreliable. Convex geometry is used to recognize the spectra of those samples that are extreme and are representative of unique lithologies. Linear unmixing is used to determine the abundance of these lithologies in each drillhole sample and these abundances are used to interpret the geology of the drillhole. The interpreted geology agrees well with conventional drillhole logs of the visible geology and photographs of the split core. The methods developed provide a quick and cost-effective way of determining the lithology and alteration mineralogy of drill core pulps.« less

The Yearly Variation in Fall-Winter Arctic Winter Vortex Descent

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.; Newman, Paul A.

1999-01-01

Using the change in HALOE methane profiles from early September to late March, we have estimated the minimum amount of diabatic descent within the polar which takes place during Arctic winter. The year to year variations are a result in the year to year variations in stratospheric wave activity which (1) modify the temperature of the vortex and thus the cooling rate; (2) reduce the apparent descent by mixing high amounts of methane into the vortex. The peak descent amounts from HALOE methane vary from l0km -14km near the arrival altitude of 25 km. Using a diabatic trajectory calculation, we compare forward and backward trajectories over the course of the winter using UKMO assimilated stratospheric data. The forward calculation agrees fairly well with the observed descent. The backward calculation appears to be unable to produce the observed amount of descent, but this is only an apparent effect due to the density decrease in parcels with altitude. Finally we show the results for unmixed descent experiments - where the parcels are fixed in latitude and longitude and allowed to descend based on the local cooling rate. Unmixed descent is found to always exceed mixed descent, because when normal parcel motion is included, the path average cooling is always less than the cooling at a fixed polar point.

Spectral unmixing of urban land cover using a generic library approach

NASA Astrophysics Data System (ADS)

Degerickx, Jeroen; Lordache, Marian-Daniel; Okujeni, Akpona; Hermy, Martin; van der Linden, Sebastian; Somers, Ben

2016-10-01

Remote sensing based land cover classification in urban areas generally requires the use of subpixel classification algorithms to take into account the high spatial heterogeneity. These spectral unmixing techniques often rely on spectral libraries, i.e. collections of pure material spectra (endmembers, EM), which ideally cover the large EM variability typically present in urban scenes. Despite the advent of several (semi-) automated EM detection algorithms, the collection of such image-specific libraries remains a tedious and time-consuming task. As an alternative, we suggest the use of a generic urban EM library, containing material spectra under varying conditions, acquired from different locations and sensors. This approach requires an efficient EM selection technique, capable of only selecting those spectra relevant for a specific image. In this paper, we evaluate and compare the potential of different existing library pruning algorithms (Iterative Endmember Selection and MUSIC) using simulated hyperspectral (APEX) data of the Brussels metropolitan area. In addition, we develop a new hybrid EM selection method which is shown to be highly efficient in dealing with both imagespecific and generic libraries, subsequently yielding more robust land cover classification results compared to existing methods. Future research will include further optimization of the proposed algorithm and additional tests on both simulated and real hyperspectral data.

Numerical modeling of temperature and species distributions in hydrocarbon reservoirs

NASA Astrophysics Data System (ADS)

Bolton, Edward W.; Firoozabadi, Abbas

2014-01-01

We examine bulk fluid motion and diffusion of multicomponent hydrocarbon species in porous media in the context of nonequilibrium thermodynamics, with particular focus on the phenomenology induced by horizontal thermal gradients at the upper and lower horizontal boundaries. The problem is formulated with respect to the barycentric (mass-averaged) frame of reference. Thermally induced convection, with fully time-dependent temperature distributions, can lead to nearly constant hydrocarbon composition, with minor unmixing due to thermal gradients near the horizontal boundaries. Alternately, the composition can be vertically segregated due to gravitational effects. Independent and essentially steady solutions have been found to depend on how the compositions are initialized in space and may have implications for reservoir history. We also examine injection (to represent filling) and extraction (to represent leakage) of hydrocarbons at independent points and find a large distortion of the gas-oil contact for low permeability.

S-type granitic magmas—petrogenetic issues, models and evidence

NASA Astrophysics Data System (ADS)

Clemens, J. D.

2003-04-01

Despite a perception that it represents a perverse divergence, it is perfectly possible to believe in the existence of S- and I-type granites (and the implications for the nature of their protoliths), and to disbelieve in the applicability of the restite-unmixing model for chemical variation in granitic magmas. White and Chappell erected the S-I classification with impeccable validity. The isotopic evidence demands contrasting source reservoirs for S- and I-type granitic magmas. However, the major advance was not the classification, but the recognition that highly contrasting parental materials must be involved in the genesis of granitic magmas. The restite-unmixing model is commonly seen as a companion to the S-I classification, but it is really a separate issue. This model implies that the compositions of granites 'image' those of their source rocks in a simple way. However, there are other equally valid models that can explain the data, and none of them represents a unique solution. The most cogent explanation for the high-grade metasedimentary enclaves in most S-type granites is that they represent mid-crustal xenoliths; restitic enclaves are either rare or absent. Inherited zircons in S-type rocks are certainly restitic. However, the occurrence of a substantial restitic zircon population does not imply an equally substantial restitic component in the rest of the rock. Zircon and zirconium behaviours are controlled by disequilibrium and kinetics, and Zr contents of granitic rocks can rarely be used to infer magma temperatures. Since the dominant ages among inherited zircons in Lachlan Fold Belt (LFB) S-type granites are Ordovician and Proterozoic, it seems likely that crust of this age, but geochemically different from the exposed rocks, not only underlies much of the LFB but also forms a component in the granite magma sources. The evidence is overwhelming that the dark, microgranular enclaves that occur in both S- and I-type granites are igneous in origin. They represent globules of quenched, more mafic magma mingled and modified by exchange with the host granitic magma. However, magma mixing does not appear to be a significant process affecting the chemical evolution of the host magmas. Likewise, the multicomponent mixing models erected for some granitic rock suites are mathematically nonunique and, in some cases, violate constraints from isotopic studies. S- and I-type magmas commonly retain their distinct identities. This suggests limited source mixing, limited magma mixing and limited wall-rock assimilation. Though intermediate types certainly exist, they are probably relatively minor in volume. Crystal fractionation probably plays the major role in the differentiation of very many granitic magmas, including most S-types, especially those emplaced at high crustal levels or in the volcanic environment. Minor mechanisms include magma mixing, wall-rock assimilation and restite unmixing. Isotopic variations within plutons and in granite suites could be caused by source heterogeneities, magma mixing, assimilation and even by isotopic disequilibrium. However, source heterogeneity, coupled with the inefficiency of magma mixing is probably the major cause of observed heterogeneity. Normal geothermal gradients are seldom sufficient to provide the necessary heat for partial melting of the crust, and crustal thickening likewise fails to provide sufficient heat. Generally, the mantle must be the major heat source. This might be provided through mantle upwelling and crustal thinning, and possibly through the intra- and underplating of mafic magmas. Upper crustal extension seems to have been common in regions undergoing granitic magmatism. Migmatites probably provide poor analogues of granite source regions because they are mostly formed by fluid-present reactions. Granitic magmas are mostly formed by fluid-absent processes. Where we do see rare evidence for arrested fluid-absent partial melting, the melt fraction is invariably concentrated into small shear zones, veinlets and small dykes. Thus, it seems likely that dyking is important in transporting granitic magma on a variety of scales and at many crustal levels. However, one major missing link in the chain is the mechanism by which melt fractions, in small-scale segregations occurring over a wide area, can be gathered and focused to efficiently feed much wider-spaced major magma conduits. Answers may lie in the geometry of the melting zones and in the tendency of younger propagating fractures to curve toward and merge with older ones. Self-organization almost certainly plays a role.

Multispectral Thermal Imagery and Its Application to the Geologic Mapping of the Koobi Fora Formation, Northwestern Kenya

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

Green, Mary K.

The Koobi Fora Formation in northwestern Kenya has yielded more hominin fossils dated between 2.1 and 1.2 Ma than any other location on Earth. This research was undertaken to discover the spectral signatures of a portion of the Koobi Fora Formation using imagery from the DOE's Multispectral Thermal Imager (MTI) satellite. Creation of a digital geologic map from MTI imagery was a secondary goal of this research. MTI is unique amongst multispectral satellites in that it co-collects data from 15 spectral bands ranging from the visible to the thermal infrared with a ground sample distance of 5 meters per pixelmore » in the visible and 20 meters in the infrared. The map was created in two stages. The first was to correct the base MTI image using spatial accuracy assessment points collected in the field. The second was to mosaic various MTI images together to create the final Koobi Fora map. Absolute spatial accuracy of the final map product is 73 meters. The geologic classification of the Koobi Fora MTI map also took place in two stages. The field work stage involved location of outcrops of different lithologies within the Koobi Fora Formation. Field descriptions of these outcrops were made and their locations recorded. During the second stage, a linear spectral unmixing algorithm was applied to the MTI mosaic. In order to train the linear spectra unmixing algorithm, regions of interest representing four different classes of geologic material (tuff, alluvium, carbonate, and basalt), as well as a vegetation class were defined within the MTI mosaic. The regions of interest were based upon the aforementioned field data as well as overlays of geologic maps from the 1976 Iowa State mapping project. Pure spectra were generated for each class from the regions of interest, and then the unmixing algorithm classified each pixel according to relative percentage of classes found within the pixel based upon the pure spectra values. A total of four unique combinations of geologic classes were analyzed using the algorithm. The tuffs within the Koobi Fora Formation were defined with 100% accuracy using a combination of pure spectra from the basalt, vegetation, and tuff.« less

Receptor model comparisons and wind direction analyses of volatile organic compounds and submicrometer particles in an arid, binational, urban air shed.

PubMed

Mukerjee, Shaibal; Norris, Gary A; Smith, Luther A; Noble, Christopher A; Neas, Lucas M; Ozkaynak, A Halûk; Gonzales, Melissa

2004-04-15

The relationship between continuous measurements of volatile organic compounds sources and particle number was evaluated at a Photochemical Assessment Monitoring Station Network (PAMS) site located near the U.S.-Mexico Border in central El Paso, TX. Sources of volatile organic compounds (VOCs) were investigated using the multivariate receptor model UNMIX and the effective variance least squares receptor model known as Chemical Mass Balance (CMB, Version 8.0). As expected from PAMS measurements, overall findings from data screening as well as both receptor models confirmed that mobile sources were the major source of VOCs. Comparison of hourly source contribution estimates (SCEs) from the two receptor models revealed significant differences in motor vehicle exhaust and evaporative gasoline contributions. However, the motor vehicle exhaust contributions were highly correlated with each other. Motor vehicle exhaust was also correlated with the ultrafine and accumulation mode particle count, which suggests that motor vehicle exhaust is a source of these particles at the measurement site. Wind sector analyses were performed using the SCE and pollutant data to assess source location of VOCs, particle count, and criteria pollutants. Results from this study have application to source apportionment studies and mobile source emission control strategies that are ongoing in this air shed.

Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

NASA Technical Reports Server (NTRS)

Cetin, Haluk

1999-01-01

The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and vegetation in the Land-Between-the Lakes (LBL) using Landsat-TM data. A Landsat-TM scene of the same day was obtained to relate ground measurements to the satellite data. A spectral library has been created for overstory species in LBL. Some of the methods, such as NPDF and IDFD techniques for spectral unmixing and reduction of effects of shadows in classifications- comparison of hyperspectral classification techniques, and spectral nonlinear and linear unmixing techniques, are being tested using the laboratory.

Preliminary Tests of Gloss-Reduction and Coloring Agents for Camouflage of Polyvinyl Acetate Dust-Control Film

DTIC Science & Technology

1976-02-01

extenders Kaolin powder Calcium carbonate dust Paint flatteners Celite h99 Nytal 1+00 Dry pigments Chalk dust (various colors) Liquid...a dispersant or wetting agent for satisfactory mixing. Vor this purpose, one of two agents was used: (a) a commercial 10 per- cent determent...pockets of unmixed powder, and in some cases the powder settled to the bottom of the mold. The dispersants that were tried did not effectively disperse

Electrokinetic instability micromixing.

PubMed

Oddy, M H; Santiago, J G; Mikkelsen, J C

2001-12-15

We have developed an electrokinetic process to rapidly stir micro- and nanoliter volume solutions for microfluidic bioanalytical applications. We rapidly stir microflow streams by initiating a flow instability, which we have observed in sinusoidally oscillating, electroosmotic channel flows. As the effect occurs within an oscillating electroosmotic flow, we refer to it here as an electrokinetic instability (EKI). The rapid stretching and folding of material lines associated with this instability can be used to stir fluid streams with Reynolds numbers of order unity, based on channel depth and rms electroosmotic velocity. This paper presents a preliminary description of the EKI and the design and fabrication of two micromixing devices capable of rapidly stirring two fluid streams using this flow phenomenon. A high-resolution CCD camera is used to record the stirring and diffusion of fluorescein from an initially unmixed configuration. Integration of fluorescence intensity over measurement volumes (voxels) provides a measure of the degree to which two streams are mixed to within the length scales of the voxels. Ensemble-averaged probability density functions and power spectra of the instantaneous spatial intensity profiles are used to quantify the mixing processes. Two-dimensional spectral bandwidths of the mixing images are initially anisotropic for the unmixed configuration, broaden as the stirring associated with the EKI rapidly stretches and folds material lines (adding high spatial frequencies to the concentration field), and then narrow to a relatively isotropic spectrum at the well-mixed conditions.

Estimates of the Lightning NOx Profile in the Vicinity of the North Alabama Lightning Mapping Array

NASA Technical Reports Server (NTRS)

Koshak, William J.; Peterson, Harold

2010-01-01

The NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) is applied to August 2006 North Alabama Lightning Mapping Array (LMA) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning nitrogen oxides, NOx = NO + NO 2 . This is part of a larger effort aimed at building a more realistic lightning NOx emissions inventory for use by the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system. Data from the National Lightning Detection Network TM (NLDN) is also employed. Overall, special attention is given to several important lightning variables including: the frequency and geographical distribution of lightning in the vicinity of the LMA network, lightning type (ground or cloud flash), lightning channel length, channel altitude, channel peak current, and the number of strokes per flash. Laboratory spark chamber results from the literature are used to convert 1-meter channel segments (that are located at a particular known altitude; i.e., air density) to NOx concentration. The resulting raw NOx profiles are discussed.

Estimates of the Lightning NOx Profile in the Vicinity of the North Alabama Lightning Mapping Array

NASA Technical Reports Server (NTRS)

Koshak, William J.; Peterson, Harold S.; McCaul, Eugene W.; Blazar, Arastoo

2010-01-01

The NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) is applied to August 2006 North Alabama Lightning Mapping Array (NALMA) data to estimate the (unmixed and otherwise environmentally unmodified) vertical source profile of lightning nitrogen oxides, NOx = NO + NO2. Data from the National Lightning Detection Network (Trademark) (NLDN) is also employed. This is part of a larger effort aimed at building a more realistic lightning NOx emissions inventory for use by the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system. Overall, special attention is given to several important lightning variables including: the frequency and geographical distribution of lightning in the vicinity of the NALMA network, lightning type (ground or cloud flash), lightning channel length, channel altitude, channel peak current, and the number of strokes per flash. Laboratory spark chamber results from the literature are used to convert 1-meter channel segments (that are located at a particular known altitude; i.e., air density) to NOx concentration. The resulting lightning NOx source profiles are discussed.

Multispectral open-air intraoperative fluorescence imaging.

PubMed

Behrooz, Ali; Waterman, Peter; Vasquez, Kristine O; Meganck, Jeff; Peterson, Jeffrey D; Faqir, Ilias; Kempner, Joshua

2017-08-01

Intraoperative fluorescence imaging informs decisions regarding surgical margins by detecting and localizing signals from fluorescent reporters, labeling targets such as malignant tissues. This guidance reduces the likelihood of undetected malignant tissue remaining after resection, eliminating the need for additional treatment or surgery. The primary challenges in performing open-air intraoperative fluorescence imaging come from the weak intensity of the fluorescence signal in the presence of strong surgical and ambient illumination, and the auto-fluorescence of non-target components, such as tissue, especially in the visible spectral window (400-650 nm). In this work, a multispectral open-air fluorescence imaging system is presented for translational image-guided intraoperative applications, which overcomes these challenges. The system is capable of imaging weak fluorescence signals with nanomolar sensitivity in the presence of surgical illumination. This is done using synchronized fluorescence excitation and image acquisition with real-time background subtraction. Additionally, the system uses a liquid crystal tunable filter for acquisition of multispectral images that are used to spectrally unmix target fluorescence from non-target auto-fluorescence. Results are validated by preclinical studies on murine models and translational canine oncology models.

Quantitative methods and detection techniques in hyperspectral imaging involving medical and other applications

NASA Astrophysics Data System (ADS)

Roy, Ankita

2007-12-01

This research using Hyperspectral imaging involves recognizing targets through spatial and spectral matching and spectral un-mixing of data ranging from remote sensing to medical imaging kernels for clinical studies based on Hyperspectral data-sets generated using the VFTHSI [Visible Fourier Transform Hyperspectral Imager], whose high resolution Si detector makes the analysis achievable. The research may be broadly classified into (I) A Physically Motivated Correlation Formalism (PMCF), which places both spatial and spectral data on an equivalent mathematical footing in the context of a specific Kernel and (II) An application in RF plasma specie detection during carbon nanotube growing process. (III) Hyperspectral analysis for assessing density and distribution of retinopathies like age related macular degeneration (ARMD) and error estimation enabling the early recognition of ARMD, which is treated as an ill-conditioned inverse imaging problem. The broad statistical scopes of this research are two fold-target recognition problems and spectral unmixing problems. All processes involve experimental and computational analysis of Hyperspectral data sets is presented, which is based on the principle of a Sagnac Interferometer, calibrated to obtain high SNR levels. PMCF computes spectral/spatial/cross moments and answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required precisely for a particular target recognition. Spectral analysis of RF plasma radicals, typically Methane plasma and Argon plasma using VFTHSI has enabled better process monitoring during growth of vertically aligned multi-walled carbon nanotubes by instant registration of the chemical composition or density changes temporally, which is key since a significant correlation can be found between plasma state and structural properties. A vital focus of this dissertation is towards medical Hyperspectral imaging applied to retinopathies like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the deoxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while beta-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease.

Hyperspectral imaging for presumptive identification of bacterial colonies on solid chromogenic culture media

NASA Astrophysics Data System (ADS)

Guillemot, Mathilde; Midahuen, Rony; Archeny, Delpine; Fulchiron, Corine; Montvernay, Regis; Perrin, Guillaume; Leroux, Denis F.

2016-04-01

BioMérieux is automating the microbiology laboratory in order to reduce cost (less manpower and consumables), to improve performance (increased sensitivity, machine algorithms) and to gain traceability through optimization of the clinical laboratory workflow. In this study, we evaluate the potential of Hyperspectral imaging (HSI) as a substitute to human visual observation when performing the task of microbiological culture interpretation. Microbial colonies from 19 strains subcategorized in 6 chromogenic classes were analyzed after a 24h-growth on a chromogenic culture medium (chromID® CPS Elite, bioMérieux, France). The HSI analysis was performed in the VNIR region (400-900 nm) using a linescan configuration. Using algorithms relying on Linear Spectral Unmixing, and using exclusively Diffuse Reflectance Spectra (DRS) as input data, we report interclass classification accuracies of 100% using a fully automatable approach and no use of morphological information. In order to eventually simplify the instrument, the performance of degraded DRS was also evaluated using only the most discriminant 14 spectral channels (a model for a multispectral approach) or 3 channels (model of a RGB image). The overall classification performance remains unchanged for our multispectral model but is degraded for the predicted RGB model, hints that a multispectral solution might bring the answer for an improved colony recognition.

Improving Automated Endmember Identification for Linear Unmixing of HyspIRI Spectral Data.

NASA Astrophysics Data System (ADS)

Gader, P.

2016-12-01

The size of data sets produced by imaging spectrometers is increasing rapidly. There is already a processing bottleneck. Part of the reason for this bottleneck is the need for expert input using interactive software tools. This process can be very time consuming and laborious but is currently crucial to ensuring the quality of the analysis. Automated algorithms can mitigate this problem. Although it is unlikely that processing systems can become completely automated, there is an urgent need to increase the level of automation. Spectral unmixing is a key component to processing HyspIRI data. Algorithms such as MESMA have been demonstrated to achieve results but require carefully, expert construction of endmember libraries. Unfortunately, many endmembers found by automated algorithms for finding endmembers are deemed unsuitable by experts because they are not physically reasonable. Unfortunately, endmembers that are not physically reasonable can achieve very low errors between the linear mixing model with those endmembers and the original data. Therefore, this error is not a reasonable way to resolve the problem on "non-physical" endmembers. There are many potential approaches for resolving these issues, including using Bayesian priors, but very little attention has been given to this problem. The study reported on here considers a modification of the Sparsity Promoting Iterated Constrained Endmember (SPICE) algorithm. SPICE finds endmembers and abundances and estimates the number of endmembers. The SPICE algorithm seeks to minimize a quadratic objective function with respect to endmembers E and fractions P. The modified SPICE algorithm, which we refer to as SPICED, is obtained by adding the term D to the objective function. The term D pressures the algorithm to minimize sum of the squared differences between each endmember and a weighted sum of the data. By appropriately modifying the, the endmembers are pushed towards a subset of the data with the potential for becoming exactly equal to the data points. The algorithm has been applied to spectral data and the differences between the endmembers resulting from ecorded. The results so far are that the endmembers found SPICED are approximately 25% closer to the data with indistinguishable reconstruction error compared to those found using SPICE.

FORCinel Version 3.0: An Integrated Environment for Processing, Analysis and Simulation of First-Order Reversal Curve Diagrams

NASA Astrophysics Data System (ADS)

Lascu, I.; Harrison, R. J.

2016-12-01

First-order reversal curve (FORC) diagrams are a powerful method to characterise the hysteresis properties of magnetic grain ensembles. Methods of processing, analysis and simulation of FORC diagrams have developed rapidly over the past few years, dramatically expanding their utility within rock magnetic research. Here we announce the latest release of FORCinel (Version 3.0), which integrates many of these developments into a unified, user-friendly package running within Igor Pro (www.wavemetrics.com). FORCinel v. 3.0 can be downloaded from https://wserv4.esc.cam.ac.uk/nanopaleomag/. The release will be accompanied by a series of video tutorials outlining each of the new features, including: i) improved work flow, with unified smoothing approach; ii) increased processing speed using multiple processors; iii) control of output resolution, enabling large datasets (> 500 FORCs) to be smoothed in a matter of seconds; iv) load, process, analyse and average multiple FORC diagrams; v) load and process non-gridded data and data acquired on non-PMC systems; vi) improved method for exploring optimal smoothing parameters; vii) interactive and un-doable data-pretreatments; viii) automated detection and removal of measurement outliers; ix) improved interactive method for the generation and optimisation of colour scales; x) full integration with FORCem1 - supervised quantitative unmixing of FORC diagrams using principle component analysis (PCA); xi) full integration with FORCulator2 - micromagnetic simulation of FORC diagrams; xiii) simulate TRM acquisition using the kinetic Monte Carlo simulation algorithm of Shcherbakov3. 1. Lascu, I., Harrison, R.J., Li, Y., Muraszko, J.R., Channell, J.E.T., Piotrowski, A.M., Hodell, D.A., 2015. Magnetic unmixing of first-order reversal curve diagrams using principal component analysis. Geochemistry, Geophys. Geosystems 16, 2900-2915. 2. Harrison, R.J., Lascu, I., 2014. FORCulator: A micromagnetic tool for simulating first-order reversal curve diagrams. Geochemistry Geophys. Geosystems 15, 4671-4691. 3. Shcherbakov, V.P., Lamash, B.E., Sycheva, N.K., 1995. Monte-Carlo modelling of thermoremanence acquisition in interacting single-domain grains. Phys. Earth Planet. Inter. 87, 197-211.

Postfire soil burn severity mapping with hyperspectral image unmixing

USGS Publications Warehouse

Robichaud, P.R.; Lewis, S.A.; Laes, D.Y.M.; Hudak, A.T.; Kokaly, R.F.; Zamudio, J.A.

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.

N-Way FRET Microscopy of Multiple Protein-Protein Interactions in Live Cells

PubMed Central

Hoppe, Adam D.; Scott, Brandon L.; Welliver, Timothy P.; Straight, Samuel W.; Swanson, Joel A.

2013-01-01

Fluorescence Resonance Energy Transfer (FRET) microscopy has emerged as a powerful tool to visualize nanoscale protein-protein interactions while capturing their microscale organization and millisecond dynamics. Recently, FRET microscopy was extended to imaging of multiple donor-acceptor pairs, thereby enabling visualization of multiple biochemical events within a single living cell. These methods require numerous equations that must be defined on a case-by-case basis. Here, we present a universal multispectral microscopy method (N-Way FRET) to enable quantitative imaging for any number of interacting and non-interacting FRET pairs. This approach redefines linear unmixing to incorporate the excitation and emission couplings created by FRET, which cannot be accounted for in conventional linear unmixing. Experiments on a three-fluorophore system using blue, yellow and red fluorescent proteins validate the method in living cells. In addition, we propose a simple linear algebra scheme for error propagation from input data to estimate the uncertainty in the computed FRET images. We demonstrate the strength of this approach by monitoring the oligomerization of three FP-tagged HIV Gag proteins whose tight association in the viral capsid is readily observed. Replacement of one FP-Gag molecule with a lipid raft-targeted FP allowed direct observation of Gag oligomerization with no association between FP-Gag and raft-targeted FP. The N-Way FRET method provides a new toolbox for capturing multiple molecular processes with high spatial and temporal resolution in living cells. PMID:23762252

Search at BaBar for D^0--\\overlineD^0 Mixing using Semileptonic Decays.

NASA Astrophysics Data System (ADS)

Flood, Kevin

2004-05-01

Based on a 87 fb-1 dataset acquired by the Babar experiment running on and near the Υ(4S) from 1999-2002, a new upper limit is set on the rate of D^0--\\overlineD^0 mixing using the decay modes D^*+ arrow π^+ D^0, D^0 arrow [K / K^*]eν (+c.c.). These modes offer unambiguous initial and final-state charm flavor tags, and allow the combined use of the D^0 lifetime and D^*+--D^0 mass difference (Δ M) in a global likelihood fit. The high-statistics sample of reconstructed unmixed semileptonic D^0 decays is used to model Δ M and the time-dependence of mixed events directly from the data. Neural networks are used both to select events and to fully reconstruct the D^0. The current world-best published limit on semileptonic charm mixing is 5x10-3 (90% C.L.) (E791).

Simulated altitude exposure assessment by hyperspectral imaging

NASA Astrophysics Data System (ADS)

Calin, Mihaela Antonina; Macovei, Adrian; Miclos, Sorin; Parasca, Sorin Viorel; Savastru, Roxana; Hristea, Razvan

2017-05-01

Testing the human body's reaction to hypoxia (including the one generated by high altitude) is important in aeronautic medicine. This paper presents a method of monitoring blood oxygenation during experimental hypoxia using hyperspectral imaging (HSI) and a spectral unmixing model based on a modified Beer-Lambert law. A total of 20 healthy volunteers (males) aged 25 to 60 years were included in this study. A line-scan HSI system was used to acquire images of the faces of the subjects. The method generated oxyhemoglobin and deoxyhemoglobin distribution maps from the foreheads of the subjects at 5 and 10 min of hypoxia and after recovery in a high oxygen breathing mixture. The method also generated oxygen saturation maps that were validated using pulse oximetry. An interesting pattern of desaturation on the forehead was discovered during the study, showing one of the advantages of using HSI for skin oxygenation monitoring in hypoxic conditions. This could bring new insight into the physiological response to high altitude and may become a step forward in air crew testing.

Nonlinear scalar forcing based on a reaction analogy

NASA Astrophysics Data System (ADS)

Daniel, Don; Livescu, Daniel

2017-11-01

We present a novel reaction analogy (RA) based forcing method for generating stationary passive scalar fields in incompressible turbulence. The new method can produce more general scalar PDFs (e.g. double-delta) than current methods, while ensuring that scalar fields remain bounded, unlike existent forcing methodologies that can potentially violate naturally existing bounds. Such features are useful for generating initial fields in non-premixed combustion or for studying non-Gaussian scalar turbulence. The RA method mathematically models hypothetical chemical reactions that convert reactants in a mixed state back into its pure unmixed components. Various types of chemical reactions are formulated and the corresponding mathematical expressions derived. For large values of the scalar dissipation rate, the method produces statistically steady double-delta scalar PDFs. Gaussian scalar statistics are recovered for small values of the scalar dissipation rate. In contrast, classical forcing methods consistently produce unimodal Gaussian scalar fields. The ability of the new method to produce fully developed scalar fields is discussed using 2563, 5123, and 10243 periodic box simulations.

Simulated altitude exposure assessment by hyperspectral imaging.

PubMed

Calin, Mihaela Antonina; Macovei, Adrian; Miclos, Sorin; Parasca, Sorin Viorel; Savastru, Roxana; Hristea, Razvan

2017-05-01

Testing the human body’s reaction to hypoxia (including the one generated by high altitude) is important in aeronautic medicine. This paper presents a method of monitoring blood oxygenation during experimental hypoxia using hyperspectral imaging (HSI) and a spectral unmixing model based on a modified Beer–Lambert law. A total of 20 healthy volunteers (males) aged 25 to 60 years were included in this study. A line-scan HSI system was used to acquire images of the faces of the subjects. The method generated oxyhemoglobin and deoxyhemoglobin distribution maps from the foreheads of the subjects at 5 and 10 min of hypoxia and after recovery in a high oxygen breathing mixture. The method also generated oxygen saturation maps that were validated using pulse oximetry. An interesting pattern of desaturation on the forehead was discovered during the study, showing one of the advantages of using HSI for skin oxygenation monitoring in hypoxic conditions. This could bring new insight into the physiological response to high altitude and may become a step forward in air crew testing.

Study on the Spectral Mixing Model for Mineral Pigments Based on Derivative of Ratio Spectroscopy-Take Vermilion and Stone Yellow for Example

NASA Astrophysics Data System (ADS)

Zhao, H.; Hao, Y.; Liu, X.; Hou, M.; Zhao, X.

2018-04-01

Hyperspectral remote sensing is a completely non-invasive technology for measurement of cultural relics, and has been successfully applied in identification and analysis of pigments of Chinese historical paintings. Although the phenomenon of mixing pigments is very usual in Chinese historical paintings, the quantitative analysis of the mixing pigments in the ancient paintings is still unsolved. In this research, we took two typical mineral pigments, vermilion and stone yellow as example, made precisely mixed samples using these two kinds of pigments, and measured their spectra in the laboratory. For the mixing spectra, both fully constrained least square (FCLS) method and derivative of ratio spectroscopy (DRS) were performed. Experimental results showed that the mixing spectra of vermilion and stone yellow had strong nonlinear mixing characteristics, but at some bands linear unmixing could also achieve satisfactory results. DRS using strong linear bands can reach much higher accuracy than that of FCLS using full bands.

Parametric Study of a Mixer/Ejector Nozzle with Mixing Enhancement Devices

NASA Technical Reports Server (NTRS)

DalBello, T.; Steffen, C. J., Jr.

2001-01-01

A numerical study employing a simplified model of the High Speed Civil Transport mixer/ejector nozzle has been conducted to investigate the effect of tabs (vortex generators) on the mixing process. More complete mixing of the primary and secondary flows within the confined ejector lowers peak exit velocity resulting in reduced jet noise. Tabs were modeled as vortex pairs and inserted into the computational model. The location, size, and number of tabs were varied and its effect on the mixing process is presented here both quantitatively and qualitatively. A baseline case (no tabs) along with six other cases involving two different vortex strengths at three different orientations have been computed and analyzed. The case with the highest vorticity (six vortices representing large tabs) gives the best mixing. It is shown that the influence of the vorticity acts primarily in the forward or middle portions of the duct, significantly alters the flow structure, and promotes some mixing in the lateral direction. Unmixed pockets were found at the top and bottom of the lobe, and more clever placement of tabs improved mixing in the vertical direction. The technique of replacing tabs with vortices shows promise as an efficient tool for quickly optimizing tab placement in lobed mixers.

Characterization of VOC sources in an urban area based on PTR-MS measurements and receptor modelling.

PubMed

Stojić, A; Stojić, S Stanišić; Šoštarić, A; Ilić, L; Mijić, Z; Rajšić, S

2015-09-01

In this study, the concentrations of volatile organic compounds were measured by the use of proton transfer reaction mass spectrometry, together with NO x , NO, NO2, SO2, CO and PM10 and meteorological parameters in an urban area of Belgrade during winter 2014. The multivariate receptor model US EPA Unmix was applied to the obtained dataset resolving six source profiles, which can be attributed to traffic-related emissions, gasoline evaporation/oil refineries, petrochemical industry/biogenic emissions, aged plumes, solid-fuel burning and local laboratories. Besides the vehicle exhaust, accounting for 27.6 % of the total mixing ratios, industrial emissions, which are present in three out of six resolved profiles, exert a significant impact on air quality in the urban area. The major contribution of regional and long-range transport was determined for source profiles associated with petrochemical industry/biogenic emissions (40 %) and gasoline evaporation/oil refineries (29 %) using trajectory sector analysis. The concentration-weighted trajectory model was applied with the aim of resolving the spatial distribution of potential distant sources, and the results indicated that emission sources from neighbouring countries, as well as from Slovakia, Greece, Poland and Scandinavian countries, significantly contribute to the observed concentrations.

Identification and quantification of the hydrological impacts of imperviousness in urban catchments: a review.

PubMed

Jacobson, Carol R

2011-06-01

Urbanisation produces numerous changes in the natural environments it replaces. The impacts include habitat fragmentation and changes to both the quality and quantity of the stormwater runoff, and result in changes to hydrological systems. This review integrates research in relatively diverse areas to examine how the impacts of urban imperviousness on hydrological systems can be quantified and modelled. It examines the nature of reported impacts of urbanisation on hydrological systems over four decades, including the effects of changes in imperviousness within catchments, and some inconsistencies in studies of the impacts of urbanisation. The distribution of imperviousness within urban areas is important in understanding the impacts of urbanisation and quantification requires detailed characterisation of urban areas. As a result most mapping of urban areas uses remote sensing techniques and this review examines a range of techniques using medium and high resolution imagery, including spectral unmixing. The third section examines the ways in which scientists and hydrological and environmental engineers model and quantify water flows in urban areas, the nature of hydrological models and methods for their calibration. The final section examines additional factors which influence the impact of impervious surfaces and some uncertainties that exist in current knowledge. Copyright © 2011 Elsevier Ltd. All rights reserved.

Estimation of Subpixel Snow-Covered Area by Nonparametric Regression Splines

NASA Astrophysics Data System (ADS)

Kuter, S.; Akyürek, Z.; Weber, G.-W.

2016-10-01

Measurement of the areal extent of snow cover with high accuracy plays an important role in hydrological and climate modeling. Remotely-sensed data acquired by earth-observing satellites offer great advantages for timely monitoring of snow cover. However, the main obstacle is the tradeoff between temporal and spatial resolution of satellite imageries. Soft or subpixel classification of low or moderate resolution satellite images is a preferred technique to overcome this problem. The most frequently employed snow cover fraction methods applied on Moderate Resolution Imaging Spectroradiometer (MODIS) data have evolved from spectral unmixing and empirical Normalized Difference Snow Index (NDSI) methods to latest machine learning-based artificial neural networks (ANNs). This study demonstrates the implementation of subpixel snow-covered area estimation based on the state-of-the-art nonparametric spline regression method, namely, Multivariate Adaptive Regression Splines (MARS). MARS models were trained by using MODIS top of atmospheric reflectance values of bands 1-7 as predictor variables. Reference percentage snow cover maps were generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also employed to estimate the percentage snow-covered area on the same data set. The results indicated that the developed MARS model performed better than th

Near-infrared fluorescent proteins for multicolor in vivo imaging

PubMed Central

Shcherbakova, Daria M.; Verkhusha, Vladislav V.

2013-01-01

Near-infrared fluorescent proteins are in high demand for in vivo imaging. We developed four spectrally distinct fluorescent proteins, iRFP670, iRFP682, iRFP702, and iRFP720, from bacterial phytochromes. iRFPs exhibit high brightness in mammalian cells and tissues and are suitable for long-term studies. iRFP670 and iRFP720 enable two-color imaging in living cells and mice using standard approaches. Five iRFPs including previously engineered iRFP713 allow multicolor imaging in living mice with spectral unmixing. PMID:23770755

Developing a Control Strategy for Jets in Crossflow Using Direct Numerical Simulation

DTIC Science & Technology

2010-03-29

the total volume of scalar–containing fluid ( Vsc ) for stroke ratios equal to 2 and 6. Vsc is computed as the sum of all volume elements which have...concentration allows the difference between the scalar containing fluid and unmixed ambient fluid to be represented. Vsc can be considered as a measure of the...spread of the scalar in the flow–field. Figure 2.10(a) shows that Vsc increases nearly linearly (at a rate of 1.7) until t∗ ∼ 2. In general, Vsc

Automatic building detection based on Purposive FastICA (PFICA) algorithm using monocular high resolution Google Earth images

NASA Astrophysics Data System (ADS)

Ghaffarian, Saman; Ghaffarian, Salar

2014-11-01

This paper proposes an improved FastICA model named as Purposive FastICA (PFICA) with initializing by a simple color space transformation and a novel masking approach to automatically detect buildings from high resolution Google Earth imagery. ICA and FastICA algorithms are defined as Blind Source Separation (BSS) techniques for unmixing source signals using the reference data sets. In order to overcome the limitations of the ICA and FastICA algorithms and make them purposeful, we developed a novel method involving three main steps: 1-Improving the FastICA algorithm using Moore-Penrose pseudo inverse matrix model, 2-Automated seeding of the PFICA algorithm based on LUV color space and proposed simple rules to split image into three regions; shadow + vegetation, baresoil + roads and buildings, respectively, 3-Masking out the final building detection results from PFICA outputs utilizing the K-means clustering algorithm with two number of clusters and conducting simple morphological operations to remove noises. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.6% and 85.5% overall pixel-based and object-based precision performances, respectively.

More on the Possible Composition of the Meridiani Hematite-Rich Concretions

NASA Technical Reports Server (NTRS)

Jolliff, B. L.; Gellert, R.; Mittlefehldt, D. W.

2007-01-01

Elsewhere in these proceedings, Schneider et al. discuss compositional constraints on hematite-rich spherule (blueberry) formation at Meridiani Planum. Schneider et al. provide the background for work done to date to understand the composition and mineralogy of the spherules and devise a test of possible concretion growth processes. They also report the results of area analyses of spherules in targets analyzed with the Alpha Particle X-ray Spectrometer (APXS) and test several possible models for included components other than hematite. In this abstract, we use the compositional trends for spherule-rich targets to compute possible elemental compositions of the spherules. This approach differs from that of, which also used a determination of the area of spherules in APXS targets, coupled with a correction for the radial acceptance function, to try to un-mix the compositions directly, using 2 and 3-component models and mass balance. That approach contained a fair amount of uncertainty owing to problems associated with irregular and heterogeneous target geometry, unknown composition of non-spherule lithic components, and variable dust coatings on spherules. Since then, Opportunity has analyzed additional spherule-rich targets, and the compositional trends so obtained permit a more direct assessment of the data.

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Automatic sub-pixel coastline extraction based on spectral mixture analysis using EO-1 Hyperion data

NASA Astrophysics Data System (ADS)

Hong, Zhonghua; Li, Xuesu; Han, Yanling; Zhang, Yun; Wang, Jing; Zhou, Ruyan; Hu, Kening

2018-06-01

Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between coastal land and a water surface and features seawater edge movements as tides rise and fall. Remote sensing techniques have increasingly been used for coastline extraction; however, traditional hard classification methods are performed only at the pixel-level and extracting subpixel accuracy using soft classification methods is both challenging and time consuming due to the complex features in coastal regions. This paper presents an automatic sub-pixel coastline extraction method (ASPCE) from high-spectral satellite imaging that performs coastline extraction based on spectral mixture analysis and, thus, achieves higher accuracy. The ASPCE method consists of three main components: 1) A Water- Vegetation-Impervious-Soil (W-V-I-S) model is first presented to detect mixed W-V-I-S pixels and determine the endmember spectra in coastal regions; 2) The linear spectral mixture unmixing technique based on Fully Constrained Least Squares (FCLS) is applied to the mixed W-V-I-S pixels to estimate seawater abundance; and 3) The spatial attraction model is used to extract the coastline. We tested this new method using EO-1 images from three coastal regions in China: the South China Sea, the East China Sea, and the Bohai Sea. The results showed that the method is accurate and robust. Root mean square error (RMSE) was utilized to evaluate the accuracy by calculating the distance differences between the extracted coastline and the digitized coastline. The classifier's performance was compared with that of the Multiple Endmember Spectral Mixture Analysis (MESMA), Mixture Tuned Matched Filtering (MTMF), Sequential Maximum Angle Convex Cone (SMACC), Constrained Energy Minimization (CEM), and one classical Normalized Difference Water Index (NDWI). The results from the three test sites indicated that the proposed ASPCE method extracted coastlines more efficiently than did the compared methods, and its coastline extraction accuracy corresponded closely to the digitized coastline, with 0.39 pixels, 0.40 pixels, and 0.35 pixels in the three test regions, showing that the ASPCE method achieves an accuracy below 12.0 m (0.40 pixels). Moreover, in the quantitative accuracy assessment for the three test sites, the ASPCE method shows the best performance in coastline extraction, achieving a 0.35 pixel-level at the Bohai Sea, China test site. Therefore, the proposed ASPCE method can extract coastline more accurately than can the hard classification methods or other spectral unmixing methods.

Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

NASA Technical Reports Server (NTRS)

Swayze, Gregg A.; Clark, Roger N.

1995-01-01

The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines.

Vizualization Challenges of a Subduction Simulation Using One Billion Markers

NASA Astrophysics Data System (ADS)

Rudolph, M. L.; Gerya, T. V.; Yuen, D. A.

2004-12-01

Recent advances in supercomputing technology have permitted us to study the multiscale, multicomponent fluid dynamics of subduction zones at unprecedented resolutions down to about the length of a football field. We have performed numerical simulations using one billion tracers over a grid of about 80 thousand points in two dimensions. These runs have been performed using a thermal-chemical simulation that accounts for hydration and partial melting in the thermal, mechanical, petrological, and rheological domains. From these runs, we have observed several geophysically interesting phenomena including the development of plumes with unmixed mantle composition as well as plumes with mixed mantle/crust components. Unmixed plumes form at depths greater than 100km (5-10 km above the upper interface of subducting slab) and consist of partially molten wet peridotite. Mixed plumes form at lesser depth directly from the subducting slab and contain partially molten hydrated oceanic crust and sediments. These high resolution simulations have also spurred the development of new visualization methods. We have created a new web-based interface to data from our subduction simulation and other high-resolution 2D data that uses an hierarchical data format to achieve response times of less than one second when accessing data files on the order of 3GB. This interface, WEB-IS4, uses a Javascript and HTML frontend coupled with a C and PHP backend and allows the user to perform region of interest zooming, real-time colormap selection, and can return relevant statistics relating to the data in the region of interest.

GEMAS: Unmixing magnetic properties of European agricultural soil

NASA Astrophysics Data System (ADS)

Fabian, Karl; Reimann, Clemens; Kuzina, Dilyara; Kosareva, Lina; Fattakhova, Leysan; Nurgaliev, Danis

2016-04-01

High resolution magnetic measurements provide new methods for world-wide characterization and monitoring of agricultural soil which is essential for quantifying geologic and human impact on the critical zone environment and consequences of climatic change, for planning economic and ecological land use, and for forensic applications. Hysteresis measurements of all Ap samples from the GEMAS survey yield a comprehensive overview of mineral magnetic properties in European agricultural soil on a continental scale. Low (460 Hz), and high frequency (4600 Hz) magnetic susceptibility k were measured using a Bartington MS2B sensor. Hysteresis properties were determined by a J-coercivity spectrometer, built at the paleomagnetic laboratory of Kazan University, providing for each sample a modified hysteresis loop, backfield curve, acquisition curve of isothermal remanent magnetization, and a viscous IRM decay spectrum. Each measurement set is obtained in a single run from zero field up to 1.5 T and back to -1.5 T. The resulting data are used to create the first continental-scale maps of magnetic soil parameters. Because the GEMAS geochemical atlas contains a comprehensive set of geochemical data for the same soil samples, the new data can be used to map magnetic parameters in relation to chemical and geological parameters. The data set also provides a unique opportunity to analyze the magnetic mineral fraction of the soil samples by unmixing their IRM acquisition curves. The endmember coefficients are interpreted by linear inversion for other magnetic, physical and chemical properties which results in an unprecedented and detailed view of the mineral magnetic composition of European agricultural soils.

The effect of food bolus location on jaw movement smoothness and masticatory efficiency.

PubMed

Molenaar, W N B; Gezelle Meerburg, P J; Luraschi, J; Whittle, T; Schimmel, M; Lobbezoo, F; Peck, C C; Murray, G M; Minami, I

2012-09-01

Masticatory efficiency in individuals with extensive tooth loss has been widely discussed. However, little is known about jaw movement smoothness during chewing and the effect of differences in food bolus location on movement smoothness and masticatory efficiency. The aim of this study was to determine whether experimental differences in food bolus location (anterior versus posterior) had an effect on masticatory efficiency and jaw movement smoothness. Jaw movement smoothness was evaluated by measuring jerk-cost (calculated from acceleration) with an accelerometer that was attached to the skin of the mentum of 10 asymptomatic subjects, and acceleration was recorded during chewing on two-colour chewing gum, which was used to assessed masticatory efficiency. Chewing was performed under two conditions: posterior chewing (chewing on molars and premolars only) and anterior chewing (chewing on canine and first premolar teeth only). Jerk-cost and masticatory efficiency (calculated as the ratio of unmixed azure colour to the total area of gum, the unmixed fraction) were compared between anterior and posterior chewing with the Wilcoxon signed rank test (two-tailed). Subjects chewed significantly less efficiently during anterior chewing than during posterior chewing (P = 0·0051). There was no significant difference in jerk-cost between anterior and posterior conditions in the opening phase (P = 0·25), or closing phase (P = 0·42). This is the first characterisation of the effect of food bolus location on jaw movement smoothness at the same time as recording masticatory efficiency. The data suggest that anterior chewing decreases masticatory efficiency, but does not influence jerk-cost. © 2012 Blackwell Publishing Ltd.

Unmixing of fluorescence spectra to resolve quantitative time-series measurements of gene expression in plate readers.

PubMed

Lichten, Catherine A; White, Rachel; Clark, Ivan B N; Swain, Peter S

2014-02-03

To connect gene expression with cellular physiology, we need to follow levels of proteins over time. Experiments typically use variants of Green Fluorescent Protein (GFP), and time-series measurements require specialist expertise if single cells are to be followed. Fluorescence plate readers, however, a standard in many laboratories, can in principle provide similar data, albeit at a mean, population level. Nevertheless, extracting the average fluorescence per cell is challenging because autofluorescence can be substantial. Here we propose a general method for correcting plate reader measurements of fluorescent proteins that uses spectral unmixing and determines both the fluorescence per cell and the errors on that fluorescence. Combined with strain collections, such as the GFP fusion collection for budding yeast, our methodology allows quantitative measurements of protein levels of up to hundreds of genes and therefore provides complementary data to high throughput studies of transcription. We illustrate the method by following the induction of the GAL genes in Saccharomyces cerevisiae for over 20 hours in different sugars and argue that the order of appearance of the Leloir enzymes may be to reduce build-up of the toxic intermediate galactose-1-phosphate. Further, we quantify protein levels of over 40 genes, again over 20 hours, after cells experience a change in carbon source (from glycerol to glucose). Our methodology is sensitive, scalable, and should be applicable to other organisms. By allowing quantitative measurements on a per cell basis over tens of hours and over hundreds of genes, it should increase our understanding of the dynamic changes that drive cellular behaviour.

Introducing causality violation for improved DPOAE component unmixing

NASA Astrophysics Data System (ADS)

Moleti, Arturo; Sisto, Renata; Shera, Christopher A.

2018-05-01

The DPOAE response consists of the linear superposition of two components, a nonlinear distortion component generated in the overlap region, and a reflection component generated by roughness in the DP resonant region. Due to approximate scaling symmetry, the DPOAE distortion component has approximately constant phase. As the reflection component may be considered as a SFOAE generated by the forward DP traveling wave, it has rapidly rotating phase, relative to that of its source, which is also equal to the phase of the DPOAE distortion component. This different phase behavior permits effective separation of the DPOAE components (unmixing), using time-domain or time-frequency domain filtering. Departures from scaling symmetry imply fluctuations around zero delay of the distortion component, which may seriously jeopardize the accuracy of these filtering techniques. The differential phase-gradient delay of the reflection component obeys causality requirements, i.e., the delay is positive only, and the fine-structure oscillations of amplitude and phase are correlated to each other, as happens for TEOAEs and SFOAEs relative to their stimulus phase. Performing the inverse Fourier (or wavelet) transform of a modified DPOAE complex spectrum, in which a constant phase function is substituted for the measured one, the time (or time-frequency) distribution shows a peak at (exactly) zero delay and long-latency specular symmetric components, with a modified (positive and negative) delay, which is that relative to that of the distortion component in the original response. Component separation, applied to this symmetrized distribution, becomes insensitive to systematic errors associated with violation of the scaling symmetry in specific frequency ranges.

Applicability of the "Emotiv EEG Neuroheadset" as a user-friendly input interface.

PubMed

Boutani, Hidenori; Ohsuga, Mieko

2013-01-01

We aimed to develop an input interface by using the P3 component of visual event-related potentials (ERPs). When using electroencephalography (EEG) in daily applications, coping with ocular-motor artifacts and ensuring that the equipment is user-friendly are both important. To address the first issue, we applied a previously proposed method that applies an unmixing matrix to acquire independent components (ICs) obtained from another dataset. For the second issue, we introduced a 14-channel EEG commercial headset called the "Emotiv EEG Neuroheadset". An advantage of the Emotiv headset is that users can put it on by themselves within 1 min without any specific skills. However, only a few studies have investigated whether EEG and ERP signals are accurately measured by Emotiv. Additionally, no electrodes of the Emotiv headset are located over the centroparietal area of the head where P3 components are reported to show large amplitudes. Therefore, we first demonstrated that the P3 components obtained by the headset and by commercial plate electrodes and a multipurpose bioelectric amplifier during an oddball task were comparable. Next, we confirmed that eye-blink and ocular movement components could be decomposed by independent component analysis (ICA) using the 14-channel signals measured by the headset. We also demonstrated that artifacts could be removed with an unmixing matrix, as long as the matrix was obtained from the same person, even if they were measured on different days. Finally, we confirmed that the fluctuation of the sampling frequency of the Emotiv headset was not a major problem.

A review of the contrasting behavior of two magmatic volatiles: Chlorine and carbon dioxide

USGS Publications Warehouse

Lowenstern, J. B.

2000-01-01

Chlorine (Cl) and carbon dioxide (CO2) are common magmatic volatiles with contrasting behaviors. CO2 solubility increases with pressure whereas Cl solubility shows relatively little pressure or temperature effect. CO2 speciation changes with silicate melt composition, dissolving as carbonate in basaltic magmas and molecular CO2 in more silicic compositions. In H2O-bearing systems, the strongly non-ideal behavior of alkali chlorides causes unmixing of the volatile phase to form a H2O-rich vapor and a hydrosaline phase with important implications for the maximum concentration of Cl in magmas. Addition of CO2 to magma hastens immiscibility at crustal pressures (<500 MPa), inducing the formation of CO2-rich vapors and Cl-rich hydrosaline melts. (C) 2000 Elsevier Science B.V. All rights reserved.Chlorine (Cl) and carbon dioxide (CO2) are common magmatic volatiles with contrasting behaviors. CO2 solubility increases with pressure whereas Cl solubility shows relatively little pressure or temperature effect. CO2 speciation changes with silicate melt composition, dissolving as carbonate in basaltic magmas and molecular CO2 in more silicic compositions. In H2O-bearing systems, the strongly non-ideal behavior of alkali chlorides causes unmixing of the volatile phase to form a H2O-rich vapor and a hydrosaline phase with important implications for the maximum concentration of Cl in magmas. Addition of CO2 to magma hastens immiscibility at crustal pressures (<500 MPa), inducing the formation of CO2-rich vapors and Cl-rich hydrosaline melts.

Unmixing of fluorescence spectra to resolve quantitative time-series measurements of gene expression in plate readers

PubMed Central

2014-01-01

Background To connect gene expression with cellular physiology, we need to follow levels of proteins over time. Experiments typically use variants of Green Fluorescent Protein (GFP), and time-series measurements require specialist expertise if single cells are to be followed. Fluorescence plate readers, however, a standard in many laboratories, can in principle provide similar data, albeit at a mean, population level. Nevertheless, extracting the average fluorescence per cell is challenging because autofluorescence can be substantial. Results Here we propose a general method for correcting plate reader measurements of fluorescent proteins that uses spectral unmixing and determines both the fluorescence per cell and the errors on that fluorescence. Combined with strain collections, such as the GFP fusion collection for budding yeast, our methodology allows quantitative measurements of protein levels of up to hundreds of genes and therefore provides complementary data to high throughput studies of transcription. We illustrate the method by following the induction of the GAL genes in Saccharomyces cerevisiae for over 20 hours in different sugars and argue that the order of appearance of the Leloir enzymes may be to reduce build-up of the toxic intermediate galactose-1-phosphate. Further, we quantify protein levels of over 40 genes, again over 20 hours, after cells experience a change in carbon source (from glycerol to glucose). Conclusions Our methodology is sensitive, scalable, and should be applicable to other organisms. By allowing quantitative measurements on a per cell basis over tens of hours and over hundreds of genes, it should increase our understanding of the dynamic changes that drive cellular behaviour. PMID:24495318

Parallel-multiplexed excitation light-sheet microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Laser scanning light-sheet imaging allows fast 3D image of live samples with minimal bleach and photo-toxicity. Existing light-sheet techniques have very limited capability in multi-label imaging. Hyper-spectral imaging is needed to unmix commonly used fluorescent proteins with large spectral overlaps. However, the challenge is how to perform hyper-spectral imaging without sacrificing the image speed, so that dynamic and complex events can be captured live. We report wavelength-encoded structured illumination light sheet imaging (λ-SIM light-sheet), a novel light-sheet technique that is capable of parallel multiplexing in multiple excitation-emission spectral channels. λ-SIM light-sheet captures images of all possible excitation-emission channels in true parallel. It does not require compromising the imaging speed and is capable of distinguish labels by both excitation and emission spectral properties, which facilitates unmixing fluorescent labels with overlapping spectral peaks and will allow more labels being used together. We build a hyper-spectral light-sheet microscope that combined λ-SIM with an extended field of view through Bessel beam illumination. The system has a 250-micron-wide field of view and confocal level resolution. The microscope, equipped with multiple laser lines and an unlimited number of spectral channels, can potentially image up to 6 commonly used fluorescent proteins from blue to red. Results from in vivo imaging of live zebrafish embryos expressing various genetic markers and sensors will be shown. Hyper-spectral images from λ-SIM light-sheet will allow multiplexed and dynamic functional imaging in live tissue and animals.

Grain size dependent magnetic discrimination of Iceland and South Greenland terrestrial sediments in the northern North Atlantic sediment record

NASA Astrophysics Data System (ADS)

Hatfield, Robert G.; Stoner, Joseph S.; Reilly, Brendan T.; Tepley, Frank J.; Wheeler, Benjamin H.; Housen, Bernard A.

2017-09-01

We use isothermal and temperature dependent in-field and magnetic remanence methods together with electron microscopy to characterize different sieved size fractions from terrestrial sediments collected in Iceland and southern Greenland. The magnetic fraction of Greenland silts (3-63 μm) and sands (>63 μm) is primarily composed of near-stoichiometric magnetite that may be oxidized in the finer clay (<3 μm) fractions. In contrast, all Icelandic fractions dominantly contain titanomagnetite of a range of compositions. Ferrimagnetic minerals preferentially reside in the silt-size fraction and exist as fine single-domain (SD) and pseudo-single-domain (PSD) size inclusions in Iceland samples, in contrast to coarser PSD and multi-domain (MD) discrete magnetites from southern Greenland. We demonstrate the potential of using magnetic properties of the silt fraction for source unmixing by creating known endmember mixtures and by using naturally mixed marine sediments from the Eirik Ridge south of Greenland. We develop a novel approach to ferrimagnetic source unmixing by using low temperature magnetic susceptibility curves that are sensitive to the different crystallinity and cation substitution characteristics of the different source regions. Covariation of these properties with hysteresis parameters suggests sediment source changes have driven the magnetic mineral variations observed in Eirik Ridge sediments since the last glacial maximum. These observations assist the development of a routine method and interpretative framework to quantitatively determine provenance in a geologically realistic and meaningful way and assess how different processes combine to drive magnetic variation in the North Atlantic sediment record.

Cubesat-Derived Detection of Seagrasses Using Planet Imagery Following Unmixing-Based Denoising: is Small the Next Big?

NASA Astrophysics Data System (ADS)

Traganos, D.; Cerra, D.; Reinartz, P.

2017-05-01

Seagrasses are one of the most productive and widespread yet threatened coastal ecosystems on Earth. Despite their importance, they are declining due to various threats, which are mainly anthropogenic. Lack of data on their distribution hinders any effort to rectify this decline through effective detection, mapping and monitoring. Remote sensing can mitigate this data gap by allowing retrospective quantitative assessment of seagrass beds over large and remote areas. In this paper, we evaluate the quantitative application of Planet high resolution imagery for the detection of seagrasses in the Thermaikos Gulf, NW Aegean Sea, Greece. The low Signal-to-noise Ratio (SNR), which characterizes spectral bands at shorter wavelengths, prompts the application of the Unmixing-based denoising (UBD) as a pre-processing step for seagrass detection. A total of 15 spectral-temporal patterns is extracted from a Planet image time series to restore the corrupted blue and green band in the processed Planet image. Subsequently, we implement Lyzenga's empirical water column correction and Support Vector Machines (SVM) to evaluate quantitative benefits of denoising. Denoising aids detection of Posidonia oceanica seagrass species by increasing its producer and user accuracy by 31.7 % and 10.4 %, correspondingly, with a respective increase in its Kappa value from 0.3 to 0.48. In the near future, our objective is to improve accuracies in seagrass detection by applying more sophisticated, analytical water column correction algorithms to Planet imagery, developing time- and cost-effective monitoring of seagrass distribution that will enable in turn the effective management and conservation of these highly valuable and productive ecosystems.

A FPGA implementation for linearly unmixing a hyperspectral image using OpenCL

NASA Astrophysics Data System (ADS)

Guerra, Raúl; López, Sebastián.; Sarmiento, Roberto

2017-10-01

Hyperspectral imaging systems provide images in which single pixels have information from across the electromagnetic spectrum of the scene under analysis. These systems divide the spectrum into many contiguos channels, which may be even out of the visible part of the spectra. The main advantage of the hyperspectral imaging technology is that certain objects leave unique fingerprints in the electromagnetic spectrum, known as spectral signatures, which allow to distinguish between different materials that may look like the same in a traditional RGB image. Accordingly, the most important hyperspectral imaging applications are related with distinguishing or identifying materials in a particular scene. In hyperspectral imaging applications under real-time constraints, the huge amount of information provided by the hyperspectral sensors has to be rapidly processed and analysed. For such purpose, parallel hardware devices, such as Field Programmable Gate Arrays (FPGAs) are typically used. However, developing hardware applications typically requires expertise in the specific targeted device, as well as in the tools and methodologies which can be used to perform the implementation of the desired algorithms in the specific device. In this scenario, the Open Computing Language (OpenCL) emerges as a very interesting solution in which a single high-level synthesis design language can be used to efficiently develop applications in multiple and different hardware devices. In this work, the Fast Algorithm for Linearly Unmixing Hyperspectral Images (FUN) has been implemented into a Bitware Stratix V Altera FPGA using OpenCL. The obtained results demonstrate the suitability of OpenCL as a viable design methodology for quickly creating efficient FPGAs designs for real-time hyperspectral imaging applications.

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Pixel decomposition for tracking in low resolution videos

NASA Astrophysics Data System (ADS)

Govinda, Vivekanand; Ralph, Jason F.; Spencer, Joseph W.; Goulermas, John Y.; Yang, Lihua; Abbas, Alaa M.

2008-04-01

This paper describes a novel set of algorithms that allows indoor activity to be monitored using data from very low resolution imagers and other non-intrusive sensors. The objects are not resolved but activity may still be determined. This allows the use of such technology in sensitive environments where privacy must be maintained. Spectral un-mixing algorithms from remote sensing were adapted for this environment. These algorithms allow the fractional contributions from different colours within each pixel to be estimated and this is used to assist in the detection and monitoring of small objects or sub-pixel motion.

For geological investigations with airborne thermal infrared multispectral images: Transfer of calibration from laboratory spectrometer to TIMS as alternative for removing atmospheric effects

NASA Technical Reports Server (NTRS)

Edgett, Kenneth S.; Anderson, Donald L.

1995-01-01

This paper describes an empirical method to correct TIMS (Thermal Infrared Multispectral Scanner) data for atmospheric effects by transferring calibration from a laboratory thermal emission spectrometer to the TIMS multispectral image. The method does so by comparing the laboratory spectra of samples gathered in the field with TIMS 6-point spectra for pixels at the location of field sampling sites. The transference of calibration also makes it possible to use spectra from the laboratory as endmembers in unmixing studies of TIMS data.

Constraints on the explosion mechanism and progenitors of Type Ia supernovae

NASA Astrophysics Data System (ADS)

Dessart, Luc; Blondin, Stéphane; Hillier, D. John; Khokhlov, Alexei

2014-06-01

Observations of SN 2011fe at early times reveal an evolution analogous to a fireball model of constant colour. In contrast, our unmixed delayed detonations of Chandrasekhar-mass white dwarfs (DDC series) exhibit a faster brightening concomitant with a shift in colour to the blue. In this paper, we study the origin of these discrepancies. We find that strong chemical mixing largely resolves the photometric mismatch at early times, but it leads to an enhanced line broadening that contrasts, for example, with the markedly narrow Si II 6355 Å line of SN 2011fe. We also explore an alternative configuration with pulsational-delayed detonations (PDDEL model series). Because of the pulsation, PDDEL models retain more unburnt carbon, have little mass at high velocity, and have a much hotter outer ejecta after the explosion. The pulsation does not influence the inner ejecta, so PDDEL and DDC models exhibit similar radiative properties beyond maximum. However, at early times, PDDEL models show bluer optical colours and a higher luminosity, even for weak mixing. Their early-time radiation is derived primarily from the initial shock-deposited energy in the outer ejecta rather than radioactive-decay heating. Furthermore, PDDEL models show short-lived C II lines, reminiscent of SN 2013dy. They typically exhibit lines that are weaker, narrower, and of near-constant width, reminiscent of SN 2011fe. In addition to multidimensional effects, varying configurations for such `pulsations' offer a source of spectral diversity amongst Type Ia supernovae (SNe Ia). PDDEL and DDC models also provide one explanation for low- and high-velocity-gradient SNe Ia.

Analysis of simulated advanced spaceborne thermal emission and reflection (ASTER) radiometer data of the Iron Hill, Colorado, study area for mapping lithologies

USGS Publications Warehouse

Rowan, L.C.

1998-01-01

The advanced spaceborne thermal emission and reflection (ASTER) radiometer was designed to record reflected energy in nine channels with 15 or 30 m resolution, including stereoscopic images, and emitted energy in five channels with 90 m resolution from the NASA Earth Observing System AM1 platform. A simulated ASTER data set was produced for the Iron Hill, Colorado, study area by resampling calibrated, registered airborne visible/infrared imaging spectrometer (AVIRIS) data, and thermal infrared multispectral scanner (TIMS) data to the appropriate spatial and spectral parameters. A digital elevation model was obtained to simulate ASTER-derived topographic data. The main lithologic units in the area are granitic rocks and felsite into which a carbonatite stock and associated alkalic igneous rocks were intruded; these rocks are locally covered by Jurassic sandstone, Tertiary rhyolitic tuff, and colluvial deposits. Several methods were evaluated for mapping the main lithologic units, including the unsupervised classification and spectral curve-matching techniques. In the five thermal-infrared (TIR) channels, comparison of the results of linear spectral unmixing and unsupervised classification with published geologic maps showed that the main lithologic units were mapped, but large areas with moderate to dense tree cover were not mapped in the TIR data. Compared to TIMS data, simulated ASTER data permitted slightly less discrimination in the mafic alkalic rock series, and carbonatite was not mapped in the TIMS nor in the simulated ASTER TIR data. In the nine visible and near-infrared channels, unsupervised classification did not yield useful results, but both the spectral linear unmixing and the matched filter techniques produced useful results, including mapping calcitic and dolomitic carbonatite exposures, travertine in hot spring deposits, kaolinite in argillized sandstone and tuff, and muscovite in sericitized granite and felsite, as well as commonly occurring illite/muscovite. However, the distinction made in AVIRIS data between calcite and dolomite was not consistently feasible in the simulated ASTER data. Comparison of the lithologic information produced by spectral analysis of the simulated ASTER data to a photogeologic interpretation of a simulated ASTER color image illustrates the high potential of spectral analysis of ASTER data to geologic interpretation. This paper is not subject to U.S. copyright. Published in 1998 by the American Geophysical Union.

Temporal evolution of main ambient PM2. 5 sources in Santiago, Chile, from 1998 to 2012

NASA Astrophysics Data System (ADS)

Barraza, Francisco; Lambert, Fabrice; Jorquera, Héctor; María Villalobos, Ana; Gallardo, Laura

2017-08-01

The inhabitants of Santiago, Chile have been exposed to harmful levels of air pollutants for decades. The city's poor air quality is a result of steady economic growth, and stable atmospheric conditions adverse to mixing and ventilation that favor the formation of oxidants and secondary aerosols. Identifying and quantifying the sources that contribute to the ambient levels of pollutants is key for designing adequate mitigation measures. Estimating the evolution of source contributions to ambient pollution levels is also paramount to evaluating the effectiveness of pollution reduction measures that have been implemented in recent decades. Here, we quantify the main sources that have contributed to fine particulate matter (PM2. 5) between April 1998 and August 2012 in downtown Santiago by using two different source-receptor models (PMF 5.0 and UNMIX 6.0) that were applied to elemental measurements of 1243 24 h filter samples of ambient PM2.5. PMF resolved six sources that contributed to ambient PM2. 5, with UNMIX producing similar results: motor vehicles (37.3 ± 1.1 %), industrial sources (18.5 ± 1.3 %), copper smelters (14.4 ± 0.8 %), wood burning (12.3 ± 1.0 %), coastal sources (9.5 ± 0.7 %) and urban dust (3.0 ± 1.2 %). Our results show that over the 15 years analyzed here, four of the resolved sources significantly decreased [95 % confidence interval]: motor vehicles 21.3 % [2.6, 36.5], industrial sources 39.3 % [28.6, 48.4], copper smelters 81.5 % [75.5, 85.9], and coastal sources 58.9 % [38.5, 72.5], while wood burning did not significantly change and urban dust increased by 72 % [48.9, 99.9]. These changes are consistent with emission reduction measures, such as improved vehicle emission standards, cleaner smelting technology, introduction of low-sulfur diesel for vehicles and natural gas for industrial processes, public transport improvements, etc. However, it is also apparent that the mitigation expected from the above regulations has been partially offset by the increasing amount of private vehicle use in the city, with motor vehicles becoming the dominant source of ambient PM2. 5 in recent years. Consequently, Santiago still experiences ambient PM2. 5 levels above the annual and 24 h Chilean and World Health Organization standards, and further regulations are required to reach ambient air quality standards.

Automated deconvolution of structured mixtures from heterogeneous tumor genomic data

PubMed Central

Roman, Theodore; Xie, Lu

2017-01-01

With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly improving, they remain too noisy and costly at present for population-level studies. Bulk sequencing remains the standard for population-scale tumor genomics, creating a need for computational tools to separate contributions of multiple tumor clones and assorted stromal and infiltrating cell populations to pooled genomic data. All such methods are limited to coarse approximations of only a few cell subpopulations, however. In prior work, we demonstrated the feasibility of improving cell type deconvolution by taking advantage of substructure in genomic mixtures via a strategy called simplicial complex unmixing. We improve on past work by introducing enhancements to automate learning of substructured genomic mixtures, with specific emphasis on genome-wide copy number variation (CNV) data, as well as the ability to process quantitative RNA expression data, and heterogeneous combinations of RNA and CNV data. We introduce methods for dimensionality estimation to better decompose mixture model substructure; fuzzy clustering to better identify substructure in sparse, noisy data; and automated model inference methods for other key model parameters. We further demonstrate their effectiveness in identifying mixture substructure in true breast cancer CNV data from the Cancer Genome Atlas (TCGA). Source code is available at https://github.com/tedroman/WSCUnmix PMID:29059177

Odor detection of mixtures of homologous carboxylic acids and coffee aroma compounds by humans.

PubMed

Miyazawa, Toshio; Gallagher, Michele; Preti, George; Wise, Paul M

2009-11-11

Mixture summation among homologous carboxylic acids, that is, the relationship between detection probabilities for mixtures and detection probabilities for their unmixed components, varies with similarity in carbon-chain length. The current study examined detection of acetic, butyric, hexanoic, and octanoic acids mixed with three other model odorants that differ greatly from the acids in both structure and odor character, namely, 2-hydroxy-3-methylcyclopent-2-en-1-one, furan-2-ylmethanethiol, and (3-methyl-3-sulfanylbutyl) acetate. Psychometric functions were measured for both single compounds and binary mixtures (2 of 5, forced-choice method). An air dilution olfactometer delivered stimuli, with vapor-phase calibration using gas chromatography-mass spectrometry. Across the three odorants that differed from the acids, acetic and butyric acid showed approximately additive (or perhaps even supra-additive) summation at low perithreshold concentrations, but subadditive interactions at high perithreshold concentrations. In contrast, the medium-chain acids showed subadditive interactions across a wide range of concentrations. Thus, carbon-chain length appears to influence not only summation with other carboxylic acids but also summation with at least some unrelated compounds.

Spatial Heterogeneity and Imperfect Mixing in Chemical Reactions: Visualization of Density-Driven Pattern Formation

DOE PAGES

Sobel, Sabrina G.; Hastings, Harold M.; Testa, Matthew

2009-01-01

Imore » mperfect mixing is a concern in industrial processes, everyday processes (mixing paint, bread machines), and in understanding salt water-fresh water mixing in ecosystems. The effects of imperfect mixing become evident in the unstirred ferroin-catalyzed Belousov-Zhabotinsky reaction, the prototype for chemical pattern formation. Over time, waves of oxidation (high ferriin concentration, blue) propagate into a background of low ferriin concentration (red); their structure reflects in part the history of mixing in the reaction vessel. However, it may be difficult to separate mixing effects from reaction effects. We describe a simpler model system for visualizing density-driven pattern formation in an essentially unmixed chemical system: the reaction of pale yellow Fe 3 + with colorless SCN − to form the blood-red Fe ( SCN ) 2 + complex ion in aqueous solution. Careful addition of one drop of Fe ( NO 3 ) 3 to KSCN yields striped patterns after several minutes. The patterns appear reminiscent of Rayleigh-Taylor instabilities and convection rolls, arguing that pattern formation is caused by density-driven mixing.« less

Spatial Heterogeneity and Imperfect Mixing in Chemical Reactions: Visualization of Density-Driven Pattern Formation

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

Sobel, Sabrina G.; Hastings, Harold M.; Testa, Matthew

Imore » mperfect mixing is a concern in industrial processes, everyday processes (mixing paint, bread machines), and in understanding salt water-fresh water mixing in ecosystems. The effects of imperfect mixing become evident in the unstirred ferroin-catalyzed Belousov-Zhabotinsky reaction, the prototype for chemical pattern formation. Over time, waves of oxidation (high ferriin concentration, blue) propagate into a background of low ferriin concentration (red); their structure reflects in part the history of mixing in the reaction vessel. However, it may be difficult to separate mixing effects from reaction effects. We describe a simpler model system for visualizing density-driven pattern formation in an essentially unmixed chemical system: the reaction of pale yellow Fe 3 + with colorless SCN − to form the blood-red Fe ( SCN ) 2 + complex ion in aqueous solution. Careful addition of one drop of Fe ( NO 3 ) 3 to KSCN yields striped patterns after several minutes. The patterns appear reminiscent of Rayleigh-Taylor instabilities and convection rolls, arguing that pattern formation is caused by density-driven mixing.« less

Fuel-Flexible Gasification-Combustion Technology for Production of H2 and Sequestration-Ready CO2

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

George Rizeq; Janice West; Raul Subia

GE Global Research is developing an innovative energy technology for coal gasification with high efficiency and near-zero pollution. This Unmixed Fuel Processor (UFP) technology simultaneously converts coal, steam and air into three separate streams of hydrogen-rich gas, sequestration-ready CO{sub 2}, and high-temperature, high-pressure vitiated air to produce electricity in gas turbines. This is the draft final report for the first stage of the DOE-funded Vision 21 program. The UFP technology development program encompassed lab-, bench- and pilot-scale studies to demonstrate the UFP concept. Modeling and economic assessments were also key parts of this program. The chemical and mechanical feasibility weremore » established via lab and bench-scale testing, and a pilot plant was designed, constructed and operated, demonstrating the major UFP features. Experimental and preliminary modeling results showed that 80% H{sub 2} purity could be achieved, and that a UFP-based energy plant is projected to meet DOE efficiency targets. Future work will include additional pilot plant testing to optimize performance and reduce environmental, operability and combined cycle integration risks. Results obtained to date have confirmed that this technology has the potential to economically meet future efficiency and environmental performance goals.« less

Fluorescent marker-based and marker-free discrimination between healthy and cancerous human tissues using hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2015-06-01

Two problems are addressed in this paper (i) the fluorescent marker-based and the (ii) marker-free discrimination between healthy and cancerous human tissues. For both applications the performance of hyper-spectral methods are quantified. Fluorescent marker-based tissue classification uses a number of fluorescent markers to dye specific parts of a human cell. The challenge is that the emission spectra of the fluorescent dyes overlap considerably. They are, furthermore disturbed by the inherent auto-fluorescence of human tissue. This results in ambiguities and decreased image contrast causing difficulties for the treatment decision. The higher spectral resolution introduced by tunable-filter-based spectral imaging in combination with spectral unmixing techniques results in an improvement of the image contrast and therefore more reliable information for the physician to choose the treatment decision. Marker-free tissue classification is based solely on the subtle spectral features of human tissue without the use of artificial markers. The challenge in this case is that the spectral differences between healthy and cancerous tissues are subtle and embedded in intra- and inter-patient variations of these features. The contributions of this paper are (i) the evaluation of hyper-spectral imaging in combination with spectral unmixing techniques for fluorescence marker-based tissue classification, (ii) the evaluation of spectral imaging for marker-free intra surgery tissue classification. Within this paper, we consider real hyper-spectral fluorescence and endoscopy data sets to emphasize the practical capability of the proposed methods. It is shown that the combination of spectral imaging with multivariate statistical methods can improve the sensitivity and specificity of the detection and the staging of cancerous tissues compared to standard procedures.

Carbonate-silicate liquid immiscibility in the mantle propels kimberlite magma ascent

NASA Astrophysics Data System (ADS)

Kamenetsky, Vadim S.; Yaxley, Gregory M.

2015-06-01

Kimberlite is a rare volcanic rock renowned as the major host of diamonds and originated at the base of the subcontinental lithospheric mantle. Although kimberlite magmas are dense in crystals and deeply-derived rock fragments, they ascend to the surface extremely rapidly, enabling diamonds to survive. The unique physical properties of kimberlite magmas depend on the specific compositions of their parental melts that, in absence of historical eruptions and due to pervasive alteration of kimberlite rocks, remain highly debatable. We explain exceptionally rapid ascent of kimberlite magma from mantle depths by combining empirical data on the essentially carbonatite composition of the kimberlite primary melts and experimental evidence on interaction of the carbonate liquids with mantle minerals. Our experimental study shows that orthopyroxene is completely dissolved in a Na2CO3 melt at 2.0-5.0 GPa and 1000-1200 °C. The dissolution of orthopyroxene results in homogeneous silicate-carbonate melt at 5.0 GPa and 1200 °C, and is followed by unmixing of carbonate and carbonated silicate melts and formation of stable magmatic emulsion at lower pressures and temperatures. The dispersed silicate melt has a significant capacity for storing a carbonate component in the deep mantle (13 wt% CO2 at 2.0 GPa). We envisage that this component reaches saturation and is gradually released as CO2 bubbles, as the silicate melt globules are transported upwards through the lithosphere by the carbonatite magma. The globules of unmixed, CO2-rich silicate melt are continuously produced upon further reaction between the natrocarbonatite melt and mantle peridotite. On decompression the dispersed silicate melt phase ensures a continuous supply of CO2 bubbles that decrease density and increase buoyancy and promote rapid ascent of the magmatic emulsion.

Quantitative Analysis of Immunohistochemistry in Melanoma Tumors

PubMed Central

Lilyquist, Jenna; White, Kirsten Anne Meyer; Lee, Rebecca J.; Philips, Genevieve K.; Hughes, Christopher R.; Torres, Salina M.

2017-01-01

Abstract Identification of positive staining is often qualitative and subjective. This is particularly troublesome in pigmented melanoma lesions, because melanin is difficult to distinguish from the brown stain resulting from immunohistochemistry (IHC) using horse radish peroxidase developed with 3,3′-Diaminobenzidine (HRP-DAB). We sought to identify and quantify positive staining, particularly in melanoma lesions. We visualized G-protein coupled estrogen receptor (GPER) expression developed with HRP-DAB and counterstained with Azure B (stains melanin) in melanoma tissue sections (n = 3). Matched sections (n = 3), along with 22 unmatched sections, were stained only with Azure B as a control. Breast tissue (n = 1) was used as a positive HRP-DAB control. Images of the stained tissues were generated using a Nuance Spectral Imaging Camera. Analysis of the images was performed using the Nuance Spectral Imaging software and SlideBook. Data was analyzed using a Kruskal–Wallis one way analysis of variance (ANOVA). We showed that a pigmented melanoma tissue doubly stained with anti-GPER HRP-DAB and Azure B can be unmixed using spectra derived from a matched, Azure B-only section, and an anti-GPER HRP-DAB control. We unmixed each of the melanoma lesions using each of the Azure B spectra, evaluated the mean intensity of positive staining, and examined the distribution of the mean intensities (P = .73; Kruskal–Wallis). These results suggest that this method does not require a matched Azure B-only stained control tissue for every melanoma lesion, allowing precious tissues to be conserved for other studies. Importantly, this quantification method reduces the subjectivity of protein expression analysis, and provides a valuable tool for accurate evaluation, particularly for pigmented tissues. PMID:28403073

Unmixing-Based Denoising as a Pre-Processing Step for Coral Reef Analysis

NASA Astrophysics Data System (ADS)

Cerra, D.; Traganos, D.; Gege, P.; Reinartz, P.

2017-05-01

Coral reefs, among the world's most biodiverse and productive submerged habitats, have faced several mass bleaching events due to climate change during the past 35 years. In the course of this century, global warming and ocean acidification are expected to cause corals to become increasingly rare on reef systems. This will result in a sharp decrease in the biodiversity of reef communities and carbonate reef structures. Coral reefs may be mapped, characterized and monitored through remote sensing. Hyperspectral images in particular excel in being used in coral monitoring, being characterized by very rich spectral information, which results in a strong discrimination power to characterize a target of interest, and separate healthy corals from bleached ones. Being submerged habitats, coral reef systems are difficult to analyse in airborne or satellite images, as relevant information is conveyed in bands in the blue range which exhibit lower signal-to-noise ratio (SNR) with respect to other spectral ranges; furthermore, water is absorbing most of the incident solar radiation, further decreasing the SNR. Derivative features, which are important in coral analysis, result greatly affected by the resulting noise present in relevant spectral bands, justifying the need of new denoising techniques able to keep local spatial and spectral features. In this paper, Unmixing-based Denoising (UBD) is used to enable analysis of a hyperspectral image acquired over a coral reef system in the Red Sea based on derivative features. UBD reconstructs pixelwise a dataset with reduced noise effects, by forcing each spectrum to a linear combination of other reference spectra, exploiting the high dimensionality of hyperspectral datasets. Results show clear enhancements with respect to traditional denoising methods based on spatial and spectral smoothing, facilitating the coral detection task.

Spectral imaging perspective on cytomics.

PubMed

Levenson, Richard M

2006-07-01

Cytomics involves the analysis of cellular morphology and molecular phenotypes, with reference to tissue architecture and to additional metadata. To this end, a variety of imaging and nonimaging technologies need to be integrated. Spectral imaging is proposed as a tool that can simplify and enrich the extraction of morphological and molecular information. Simple-to-use instrumentation is available that mounts on standard microscopes and can generate spectral image datasets with excellent spatial and spectral resolution; these can be exploited by sophisticated analysis tools. This report focuses on brightfield microscopy-based approaches. Cytological and histological samples were stained using nonspecific standard stains (Giemsa; hematoxylin and eosin (H&E)) or immunohistochemical (IHC) techniques employing three chromogens plus a hematoxylin counterstain. The samples were imaged using the Nuance system, a commercially available, liquid-crystal tunable-filter-based multispectral imaging platform. The resulting data sets were analyzed using spectral unmixing algorithms and/or learn-by-example classification tools. Spectral unmixing of Giemsa-stained guinea-pig blood films readily classified the major blood elements. Machine-learning classifiers were also successful at the same task, as well in distinguishing normal from malignant regions in a colon-cancer example, and in delineating regions of inflammation in an H&E-stained kidney sample. In an example of a multiplexed ICH sample, brown, red, and blue chromogens were isolated into separate images without crosstalk or interference from the (also blue) hematoxylin counterstain. Cytomics requires both accurate architectural segmentation as well as multiplexed molecular imaging to associate molecular phenotypes with relevant cellular and tissue compartments. Multispectral imaging can assist in both these tasks, and conveys new utility to brightfield-based microscopy approaches. Copyright 2006 International Society for Analytical Cytology.

Geology and geochemistry of the Clear Creek intrusion-related gold occurrences, Tintina Gold Province, Yukon, Canada

USGS Publications Warehouse

Marsh, E.E.; Goldfarb, R.J.; Hart, C.J.R.; Johnson, C.A.

2003-01-01

The Clear Creek gold occurrences lie within deformed lower greenschist-facies rocks of the western Selwyn basin. They consist of auriferous, sheeted quartz veins that cut six Cretaceous stocks and their hornfels. The veins contain 1-2% combined pyrite and arsenopyrite, with lesser pyrrhotite, bismuthinite, and scheelite, as well as 2-5 g/t Au. New 40Ar/39Ar geochronology of hydrothermal micas indicates that the veins formed within 1-2 million years of granitoid emplacement. Fluid inclusion microthermometry defines a parent ore fluid of -81 mol.% H2O, 14 mol.% CO2, 4 mol.% NaCl ?? KCl, and 1 mol.% CH4, which unmixed into a low- and high-salinity immiscible pair. This suggests a more saline parent fluid and a greater degree of fluid unmixing relative to the other occurrences in the eastern Tintina Gold Province. Inclusions trapped in As- and Bi-rich, high-gold grade veins have homogenization temperatures of 300-350??C, whereas inclusions found in more Ag- and Pb-rich veins are characterized by temperatures of 250-300??C. Fluid inclusion geobarometry suggests hydro-fracturing and gold deposition at 5-7 km depth. The ??18O values of quartz samples range from 13-16??? (per mil) and ??34S for sulfides are also consistent between -3.0???, 0???, with the exception of some outliers from the Contact Zone of the Pukelman stock that indicate a lower temperature second phase of mineralization. It remains uncertain as to whether the Clear Creek ore fluids were exsolved from magmas at depth or from devolatilization reactions within the contact metamorphic aureoles of the intrusions.

Variation in photosynthetic and nonphotosynthetic vegetation along edaphic and compositional gradients in northwestern Amazonia

NASA Astrophysics Data System (ADS)

Higgins, M. A.; Asner, G. P.; Perez, E.; Elespuru, N.; Alonso, A.

2014-03-01

Tropical forests vary substantially in aboveground properties such as canopy height, canopy structure, and plant species composition, corresponding to underlying variations in soils and geology. Forest properties are often difficult to detect and map in the field, however, due to the remoteness and inaccessibility of these forests. Spectral mixture analysis of Landsat imagery allows mapping of photosynthetic and nonphotosynthetic vegetation quantities (PV and NPV), corresponding to biophysical properties such as canopy openness, forest productivity, and disturbance. Spectral unmixing has been used for applications ranging from deforestation monitoring to identifying burn scars from past fires, but little is known about variations in PV and NPV in intact rainforest. Here we use spectral unmixing of Landsat imagery to map PV and NPV in northern Amazonia, and to test their relationship to soils and plant species composition. To do this we sampled 117 sites crossing a geological boundary in northwestern Amazonia for soil cation concentrations and plant species composition. We then used the Carnegie Landsat Analysis System to map PV and NPV for these sites from multiple dates of Landsat imagery. We found that soil cation concentrations and plant species composition consistently explain a majority of the variation in remotely sensed PV and NPV values. After combining PV and NPV into a single variable (PV-NPV), we determined that the influence of soil properties on canopy properties was inseparable from the influence of plant species composition. In all cases, patterns in PV and NPV corresponded to underlying geological patterns. Our findings suggest that geology and soils regulate canopy PV and NPV values in intact tropical forest, possibly through changes in plant species composition.

Variation in photosynthetic and nonphotosynthetic vegetation along edaphic and compositional gradients in northwestern Amazonia

NASA Astrophysics Data System (ADS)

Higgins, M. A.; Asner, G. P.; Perez, E.; Elespuru, N.; Alonso, A.

2014-07-01

Tropical forests vary substantially in aboveground properties such as canopy height, canopy structure, and plant species composition, corresponding to underlying variations in soils and geology. Forest properties are often difficult to detect and map in the field, however, due to the remoteness and inaccessibility of these forests. Spectral mixture analysis of Landsat imagery allows mapping of photosynthetic and nonphotosynthetic vegetation quantities (PV and NPV), corresponding to biophysical properties such as canopy openness, forest productivity, and disturbance. Spectral unmixing has been used for applications ranging from deforestation monitoring to identifying burn scars from past fires, but little is known about variations in PV and NPV in intact rainforests. Here we use spectral unmixing of Landsat imagery to map PV and NPV in northern Amazonia, and to test their relationship to soils and plant species composition. To do this we sampled 117 sites crossing a geological boundary in northwestern Amazonia for soil cation concentrations and plant species composition. We then used the Carnegie Landsat Analysis System to map PV and NPV for these sites from multiple dates of Landsat imagery. We found that soil cation concentrations and plant species composition consistently explain a majority of the variation in remotely sensed PV and NPV values. After combining PV and NPV into a single variable (PV-NPV), we determined that the influence of soil properties on canopy properties was inseparable from the influence of plant species composition. In all cases, patterns in PV and NPV corresponded to underlying geological patterns. Our findings suggest that geology and soils regulate canopy PV and NPV values in intact tropical forests, possibly through changes in plant species composition.

Old and new physics interpretations of the NuTeV anomaly

NASA Astrophysics Data System (ADS)

Davidson, Sacha; Forte, Stefano; Gambino, Paolo; Rius, Nuria; Strumia, Alessandro

2002-02-01

We discuss whether the NuTeV anomaly can be explained, compatibly with all other data, by QCD effects (maybe, if the strange sea is asymmetric, or there is a tiny violation of isospin), new physics in propagators or couplings of the vector bosons (not really), loops of supersymmetric particles (no), dimension six operators (yes, for one specific SU(2)L-invariant operator), leptoquarks (not in a minimal way), extra U(1) gauge bosons (maybe: an unmixed Z' coupled to B-3Lμ also increases the muon g-2 by about 10-9 and gives a `burst' to cosmic rays above the GZK cutoff).

Depth profiles of Mn-53 in lunar rocks and soils

NASA Technical Reports Server (NTRS)

Imamura, M.; Nishiizumi, K.; Honda, M.; Finkel, R. C.; Arnold, J. R.; Kohl, C. P.

1974-01-01

Results of measurements of cosmic-ray-produced Mn-53 taken down the length of the Apollo 16 deep drill core are presented. They indicate that the lunar regolith has been unmixed, on a meter scale, for the past 5 million years at the location of this core. The data are in agreement with earlier Mn-53 measurements on the Apollo 15 drill core. Mn-53 activity profiles in 14310, 12002, and 14321 are compared to each other; all three rocks have probably been on the lunar surface long enough to saturate their solar cosmic-ray-produced Mn-53 (half-life = 3.7 m.y.) activity.

Fractal reaction kinetics.

PubMed

Kopelman, R

1988-09-23

Classical reaction kinetics has been found to be unsatisfactory when the reactants are spatially constrained on the microscopic level by either walls, phase boundaries, or force fields. Recently discovered theories of heterogeneous reaction kinetics have dramatic consequences, such as fractal orders for elementary reactions, self-ordering and self-unmixing of reactants, and rate coefficients with temporal "memories." The new theories were needed to explain the results of experiments and supercomputer simulations of reactions that were confined to low dimensions or fractal dimensions or both. Among the practical examples of "fractal-like kinetics" are chemical reactions in pores of membranes, excitation trapping in molecular aggregates, exciton fusion in composite materials, and charge recombination in colloids and clouds.

Lattice Independent Component Analysis for Mobile Robot Localization

NASA Astrophysics Data System (ADS)

Villaverde, Ivan; Fernandez-Gauna, Borja; Zulueta, Ekaitz

This paper introduces an approach to appearance based mobile robot localization using Lattice Independent Component Analysis (LICA). The Endmember Induction Heuristic Algorithm (EIHA) is used to select a set of Strong Lattice Independent (SLI) vectors, which can be assumed to be Affine Independent, and therefore candidates to be the endmembers of the data. Selected endmembers are used to compute the linear unmixing of the robot's acquired images. The resulting mixing coefficients are used as feature vectors for view recognition through classification. We show on a sample path experiment that our approach can recognise the localization of the robot and we compare the results with the Independent Component Analysis (ICA).

Acoustic response of a rectangular levitator with orifices

NASA Technical Reports Server (NTRS)

El-Raheb, Michael; Wagner, Paul

1990-01-01

The acoustic response of a rectangular cavity to speaker-generated excitation through waveguides terminating at orifices in the cavity walls is analyzed. To find the effects of orifices, acoustic pressure is expressed by eigenfunctions satisfying Neumann boundary conditions as well as by those satisfying Dirichlet ones. Some of the excess unknowns can be eliminated by point constraints set over the boundary, by appeal to Lagrange undetermined multipliers. The resulting transfer matrix must be further reduced by partial condensation to the order of a matrix describing unmixed boundary conditions. If the cavity is subjected to an axial temperature dependence, the transfer matrix is determined numerically.

Evaluation of a metering, mixing, and dispensing system for mixing polysulfide adhesive

NASA Technical Reports Server (NTRS)

Evans, Kurt B.

1989-01-01

Tests were performed to evaluate whether a metered mixing system can mix PR-1221 polysulfide adhesive as well as or better than batch-mixed adhesive; also, to evaluate the quality of meter-mixed PR-1860 and PS-875 polysulfide adhesives. These adhesives are candidate replacements for PR-1221 which will not be manufactured in the future. The following material properties were evaluated: peel strength, specific gravity and adhesive components of mixed adhesives, Shore A hardness, tensile adhesion strength, and flow rate. Finally, a visual test called the butterfly test was performed to observe for bubbles and unmixed adhesive. The results of these tests are reported and discussed.

Development of a phase-sensitive Fourier domain optical coherence tomography system to measure mouse organ of Corti vibrations in two cochlear turns

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

Ramamoorthy, Sripriya; Zhang, Yuan; Jacques, Steven

In this study, we have developed a phase-sensitive Fourier-domain optical coherence tomography system to simultaneously measure the in vivo inner ear vibrations in the hook area and second turn of the mouse cochlea. This technical development will enable measurement of intra-cochlear distortion products at ideal locations such as the distortion product generation site and reflection site. This information is necessary to un-mix the complex mixture of intra-cochlear waves comprising the DPOAE and thus leads to the non-invasive identification of the local region of cochlear damage.

Screening prostate cancer using a portable near infrared scanning imaging unit with an optical fiber-based rectal probe

NASA Astrophysics Data System (ADS)

Pu, Yang; Wang, Wubao; Tang, Guichen; Budansky, Yury; Sharonov, Mikhail; Xu, Min; Achilefu, Samuel; Eastham, James A.; Alfano, Robert R.

2012-01-01

A portable near infrared scanning polarization imaging unit with an optical fiber-based rectal probe, namely Photonic Finger, was designed and developed o locate the 3D position of abnormal prostate site inside normal prostate tissue. An inverse algorithm, Optical Tomography using Independent Component Analysis (OPTICA) was improved particularly to unmix the signal from targets (cancerous tissue) embedded in a turbid medium (normal tissue) in the backscattering imaging geometry. Photonic Finger combined with OPTICA was tested to characterize different target(s) inside different tissue medium, including cancerous prostate tissue embedded by large piece of normal tissue.

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

NASA Astrophysics Data System (ADS)

Meusburger, K.; Konz, N.; Schaub, M.; Alewell, C.

2010-06-01

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km 2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed "hotspots" of high erosion of up to 16 t ha -1 a -1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.

Influence of fracture anisotropy on ground water ages and chemistry, Valley and Ridge province, Pennsylvania

USGS Publications Warehouse

Burton, W.C.; Plummer, Niel; Busenberg, E.; Lindsey, B.D.; Gburek, W.J.

2002-01-01

Model ground water ages based on chlorofluorocarbons (CFCs) and tritium/helium-3 (3H/3He) data were obtained from two arrays of nested piezometers located on the north limb of an anticline in fractured sedimentary rocks in the Valley and Ridge geologic province of Pennsylvania. The fracture geometry of the gently east plunging fold is very regular and consists predominately of south dipping to subhorizontal to north dipping bedding-plane parting and east striking, steeply dipping axial-plane spaced cleavage. In the area of the piezometer arrays, which trend north-south on the north limb of the fold, north dipping bedding-plane parting is a more dominant fracture set than is steeply south dipping axial-plane cleavage. The dating of ground water from the piezometer arrays reveals that ground water traveling along paths parallel to the dip direction of bedding-plane parting has younger 3H/3He and CFC model ages, or a greater component of young water, than does ground water traveling along paths opposite to the dip direction. In predominantly unmixed samples there is a strong positive correlation between age of the young fraction of water and dissolved sodium concentration. The travel times inferred from the model ages are significantly longer than those previously calculated by a ground water flow model, which assumed isotropically fractured layers parallel to topography. A revised model factors in the directional anisotropy to produce longer travel times. Ground water travel times in the watershed therefore appear to be more influenced by anisotropic fracture geometry than previously realized. This could have significant implications for ground water models in other areas underlain by similarly tilted or folded sedimentary rock, such as elsewhere in the Valley and Ridge or the early Mesozoic basins.

Using dark current data to estimate AVIRIS noise covariance and improve spectral analyses

NASA Technical Reports Server (NTRS)

Boardman, Joseph W.

1995-01-01

Starting in 1994, all AVIRIS data distributions include a new product useful for quantification and modeling of the noise in the reported radiance data. The 'postcal' file contains approximately 100 lines of dark current data collected at the end of each data acquisition run. In essence this is a regular spectral-image cube, with 614 samples, 100 lines and 224 channels, collected with a closed shutter. Since there is no incident radiance signal, the recorded DN measure only the DC signal level and the noise in the system. Similar dark current measurements, made at the end of each line are used, with a 100 line moving average, to remove the DC signal offset. Therefore, the pixel-by-pixel fluctuations about the mean of this dark current image provide an excellent model for the additive noise that is present in AVIRIS reported radiance data. The 61,400 dark current spectra can be used to calculate the noise levels in each channel and the noise covariance matrix. Both of these noise parameters should be used to improve spectral processing techniques. Some processing techniques, such as spectral curve fitting, will benefit from a robust estimate of the channel-dependent noise levels. Other techniques, such as automated unmixing and classification, will be improved by the stable and scene-independence noise covariance estimate. Future imaging spectrometry systems should have a similar ability to record dark current data, permitting this noise characterization and modeling.

Long-term responses of rainforest erosional systems at different spatial scales to selective logging and climatic change.

PubMed

Walsh, R P D; Bidin, K; Blake, W H; Chappell, N A; Clarke, M A; Douglas, I; Ghazali, R; Sayer, A M; Suhaimi, J; Tych, W; Annammala, K V

2011-11-27

Long-term (21-30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km(2) Baru catchment, slope erosion measurements over 1990-2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994-1996 landslides. Analysis and modelling of 5-15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km(-2) a(-1) 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout (210)Pb and (137)Cs values from a lateral bench core indicate that sedimentation rates in the 721 km(2) Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7-13 times when steep terrain was logged in 1992-1993 and 1999-2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale.

Mapping invasive species and spectral mixture relationships with neotropical woody formations in southeastern Brazil

NASA Astrophysics Data System (ADS)

Amaral, Cibele H.; Roberts, Dar A.; Almeida, Teodoro I. R.; Souza Filho, Carlos R.

2015-10-01

Biological invasion substantially contributes to the increasing extinction rates of native vegetative species. The remote detection and mapping of invasive species is critical for environmental monitoring. This study aims to assess the performance of a Multiple Endmember Spectral Mixture Analysis (MESMA) applied to imaging spectroscopy data for mapping Dendrocalamus sp. (bamboo) and Pinus elliottii L. (slash pine), which are invasive plant species, in a Brazilian neotropical landscape within the tropical Brazilian savanna biome. The work also investigates the spectral mixture between these exotic species and the native woody formations, including woodland savanna, submontane and alluvial seasonal semideciduous forests (SSF). Visible to Shortwave Infrared (VSWIR) imaging spectroscopy data at one-meter spatial resolution were atmospherically corrected and subset into the different spectral ranges (VIS-NIR1: 530-919 nm; and NIR2-SWIR: 1141-2352 nm). The data were further normalized via continuum removal (CR). Multiple endmember selection methods, including Interactive Endmember Selection (IES), Endmember average root mean square error (EAR), Minimum average spectral angle (MASA) and Count-based (CoB) (collectively called EMC), were employed to create endmember libraries for the targeted vegetation classes. The performance of the MESMA was assessed at the pixel and crown scales. Statistically significant differences (α = 0.05) were observed between overall accuracies that were obtained at various spectral ranges. The infrared region (IR) was critical for detecting the vegetation classes using spectral data. The invasive species endmembers exhibited spectral patterns in the IR that were not observed in the native formations. Bamboo was characterized as having a high green vegetation (GV) fraction, lower non-photosynthetic vegetation (NPV) and a low shade fraction, while pine exhibited higher NPV and shade fractions. The invasive species showed a statistically significant larger number of spectra erroneously assigned to the woodland savanna class versus the alluvial and submontane SSF classes. Consequently, the invasive species tended to be overestimated, especially in the woodland savanna. Bamboo was best classified using the VSWIR(CR) data with the EMC endmember selection method (User's accuracy and Producer's accuracy = 98.11% and 72.22%, respectively). Pine was best classified using NIR2-SWIR(CR) data with the IES selected endmembers (97.06% and 62.26%, respectively). The results obtained during the two-endmember modeling were fully translated into the three-endmember unmixed images. The sub-pixel invasive species abundance analysis showed that MESMA performs well when unmixing at the pixel scale and for mapping invasive species fractions in a complex neotropical environment, at pixel and crown scales with 1-m spatial resolution data.

Quantitative comparison between full-spectrum and filter-based imaging in hyperspectral fluorescence microscopy

PubMed Central

GAO, L.; HAGEN, N.; TKACZYK, T.S.

2012-01-01

Summary We implement a filterless illumination scheme on a hyperspectral fluorescence microscope to achieve full-range spectral imaging. The microscope employs polarisation filtering, spatial filtering and spectral unmixing filtering to replace the role of traditional filters. Quantitative comparisons between full-spectrum and filter-based microscopy are provided in the context of signal dynamic range and accuracy of measured fluorophores’ emission spectra. To show potential applications, a five-colour cell immunofluorescence imaging experiment is theoretically simulated. Simulation results indicate that the use of proposed full-spectrum imaging technique may result in three times improvement in signal dynamic range compared to that can be achieved in the filter-based imaging. PMID:22356127

Edge Diffusion Flame Propagation and Stabilization Studied

NASA Technical Reports Server (NTRS)

Takahashi, Fumiaki; Katta, Viswanath R.

2004-01-01

In most practical combustion systems or fires, fuel and air are initially unmixed, thus forming diffusion flames. As a result of flame-surface interactions, the diffusion flame often forms an edge, which may attach to burner walls, spread over condensed fuel surfaces, jump to another location through the fuel-air mixture formed, or extinguish by destabilization (blowoff). Flame holding in combustors is necessary to achieve design performance and safe operation of the system. Fires aboard spacecraft behave differently from those on Earth because of the absence of buoyancy in microgravity. This ongoing in-house flame-stability research at the NASA Glenn Research Center is important in spacecraft fire safety and Earth-bound combustion systems.

Hyperspectral light sheet microscopy

NASA Astrophysics Data System (ADS)

Jahr, Wiebke; Schmid, Benjamin; Schmied, Christopher; Fahrbach, Florian O.; Huisken, Jan

2015-09-01

To study the development and interactions of cells and tissues, multiple fluorescent markers need to be imaged efficiently in a single living organism. Instead of acquiring individual colours sequentially with filters, we created a platform based on line-scanning light sheet microscopy to record the entire spectrum for each pixel in a three-dimensional volume. We evaluated data sets with varying spectral sampling and determined the optimal channel width to be around 5 nm. With the help of these data sets, we show that our setup outperforms filter-based approaches with regard to image quality and discrimination of fluorophores. By spectral unmixing we resolved overlapping fluorophores with up to nanometre resolution and removed autofluorescence in zebrafish and fruit fly embryos.

Hyperspectral light sheet microscopy.

PubMed

Jahr, Wiebke; Schmid, Benjamin; Schmied, Christopher; Fahrbach, Florian O; Huisken, Jan

2015-09-02

To study the development and interactions of cells and tissues, multiple fluorescent markers need to be imaged efficiently in a single living organism. Instead of acquiring individual colours sequentially with filters, we created a platform based on line-scanning light sheet microscopy to record the entire spectrum for each pixel in a three-dimensional volume. We evaluated data sets with varying spectral sampling and determined the optimal channel width to be around 5 nm. With the help of these data sets, we show that our setup outperforms filter-based approaches with regard to image quality and discrimination of fluorophores. By spectral unmixing we resolved overlapping fluorophores with up to nanometre resolution and removed autofluorescence in zebrafish and fruit fly embryos.

Local coexistence of VO 2 phases revealed by deep data analysis

DOE PAGES

Strelcov, Evgheni; Ievlev, Anton; Tselev, Alexander; ...

2016-07-07

We report a synergistic approach of micro-Raman spectroscopic mapping and deep data analysis to study the distribution of crystallographic phases and ferroelastic domains in a defected Al-doped VO 2 microcrystal. Bayesian linear unmixing revealed an uneven distribution of the T phase, which is stabilized by the surface defects and uneven local doping that went undetectable by other classical analysis techniques such as PCA and SIMPLISMA. This work demonstrates the impact of information recovery via statistical analysis and full mapping in spectroscopic studies of vanadium dioxide systems, which is commonly substituted by averaging or single point-probing approaches, both of which suffermore » from information misinterpretation due to low resolving power.« less

They Came from the Deep in the Supernova: The Origin of TiC and Metal Subgrains in Presolar Graphite Grains

NASA Astrophysics Data System (ADS)

Lodders, Katharina

2006-08-01

A new formation scenario for TiC and Fe-Ni metal inclusions in presolar graphite grains of supernova origin is described. The mineralogy and chemistry require condensation of Fe-Ni titanides from Fe-, Ni-, and Ti-rich gaseous ejecta, subsequent carburization to make TiC and metal, and encapsulation into graphite. Titanides only condense if Si is depleted relative to heavier elements, which requires α-rich freeze-out and a deep mass cut for the supernova ejecta. This Si-poor core material must remain unmixed with other supernova zones until the titanides condense. This can be accomplished by transport of core ejecta in bipolar jets through the major expanding supernova zone ejecta. If the jets stall in regions dominated by C-rich ejecta such as the C-He zone, where graphite condenses, thermochemically favored in situ carburization of the titanides-either before or during encapsulation into condensing graphite-leads to a TiC-and-metal composite. This scenario agrees with theoretical models and observations of asymmetric core collapse in supernovae that are associated with bipolar jets loaded with iron-peak elements.

In situ measurement of magnesium carbonate formation from CO2 using static high-pressure and -temperature 13C NMR.

PubMed

Surface, J Andrew; Skemer, Philip; Hayes, Sophia E; Conradi, Mark S

2013-01-02

We explore a new in situ NMR spectroscopy method that possesses the ability to monitor the chemical evolution of supercritical CO(2) in relevant conditions for geological CO(2) sequestration. As a model, we use the fast reaction of the mineral brucite, Mg(OH)(2), with supercritical CO(2) (88 bar) in aqueous conditions at 80 °C. The in situ conversion of CO(2) into metastable and stable carbonates is observed throughout the reaction. After more than 58 h of reaction, the sample was depressurized and analyzed using in situ Raman spectroscopy, where the laser was focused on the undisturbed products through the glass reaction tube. Postreaction, ex situ analysis was performed on the extracted and dried products using Raman spectroscopy, powder X-ray diffraction, and magic-angle spinning (1)H-decoupled (13)C NMR. These separate methods of analysis confirmed a spatial dependence of products, possibly caused by a gradient of reactant availability, pH, and/or a reaction mechanism that involves first forming hydroxy-hydrated (basic, hydrated) carbonates that convert to the end-product, anhydrous magnesite. This carbonation reaction illustrates the importance of static (unmixed) reaction systems at sequestration-like conditions.

Unmixing the Galactic halo with RR Lyrae tagging

NASA Astrophysics Data System (ADS)

Belokurov, V.; Deason, A. J.; Koposov, S. E.; Catelan, M.; Erkal, D.; Drake, A. J.; Evans, N. W.

2018-06-01

We show that tagging RR Lyrae stars according to their location in the period-amplitude diagram can be used to shed light on the genesis of the Galactic stellar halo. The mixture of RR Lyrae of ab type, separated into classes along the lines suggested by Oosterhoff, displays a strong and coherent evolution with Galactocentric radius. The change in the RR Lyrae composition appears to coincide with the break in the halo's radial density profile at ˜25 kpc. Using simple models of the stellar halo, we establish that at least three different types of accretion events are necessary to explain the observed RRab behaviour. Given that there exists a correlation between the RRab class fraction and the total stellar content of a dwarf satellite, we hypothesize that the field halo RRab composition is controlled by the mass of the progenitor contributing the bulk of the stellar debris at the given radius. This idea is tested against a suite of cosmological zoom-in simulations of Milky Way-like stellar halo formation. Finally, we study some of the most prominent stellar streams in the Milky Way halo and demonstrate that their RRab class fractions follow the trends established previously.

Aeolian sand as a tool for understanding Mars: Thermal infrared remote sensing of volcaniclastic Mars-analog sand dunes in Christmas Lake Valley, Oregon, U.S.A.

NASA Astrophysics Data System (ADS)

Edgett, Kenneth S.

1996-10-01

INTRODUCTION: On Earth, aeolian sand dunes are used as tools of scientific inquiry. Holocene and Pleistocene dunes preserve clues about Quaternary climate variations and human activities ranging from Ice Age hunting practices to Twentieth Century warfare. Modern dunes contain the sedimentary textures and structures necessary for interpreting ancient sandstones, and they provide natural laboratories for investigation of aeolian physics and desertification processes. The dunes of Mars can likewise be used as scientific tools. Dunes provide relatively dust-free surfaces. From a remote sensing perspective, martian dunes have much potential for providing clues about surface mineralogy and the interaction between the surface and atmosphere. Such information can in turn provide insights regarding crust composition, volcanic evolution, present and past climate events, and perhaps weathering rates. The Mars Global Surveyor Thermal Emission Spectrometer (TES) is expected to reach the planet in September 1997. TES will provide 6 to 50 micrometer spectra of the martian surface at ground resolutions of 3 to 9 km. Sandy aeolian environments on Mars might provide key information about bedrock composition. To prepare for the TES investigation, I have been examining a thermal infrared image of a Mars-composition analog dune field in Christmas Lake Valley, Oregon. COMPOSITION AND GEOLOGIC SETTING: The "Shifting Sand Dunes" dune field is located at the eastern end of Christmas Lake Valley, in what was once the Pleistocene Fort Rock Lake [1]. Much of the sand that makes up the Shifting Sand Dunes dune field is reworked Mt. Mazama airfall from its terminal eruption 6,800 years ago, plus material deflated from the lake bed [1, 2]. The main constituents of the dunes are volcanic glass and devitrified glass fragments, plagioclase crystals, basalt lithic fragments, aggregates of silt and clay-size volcanic ash, pyroxenes, opaque oxide minerals (mostly magnetite), and trace occurrences of fossil fragments and other minerals [3]. THERMAL INFRARED IMAGE: The thermal infrared images used in this study was obtained by the NASA Ames Research Center C-130 Earth Resources airborne Thermal Infrared Multispectral Scanner (TIMS) on 21 September 1991. The image has 6 spectral bands between 8 and 12 micrometers and a ground resolution of 9 m/pixel. The raw image was converted to calibrated radiance, from which normalized emittance was computed for each of the six bands, following the method of Realmutto [4]. Atmospheric effects were corrected using an empirical method described by Edgett and Anderson [5]. The resulting 6-band image provides quantitative determination of the surface emissivity. Dune spectra in the image match spectra obtained in our laboratory using samples collected from the field area [3, 5]. ACTIVE DUNES, INACTIVE DUNES, AND INTERDUNE AREAS FROM EMISSIVITY VARIATION: This study shows that in a modern dune field, the location of active dunes, interdune surfaces, and inactive dunes can be mapped using emissivity in the thermal infrared band that shows the most spectral variation [6]. In this case, TIMS band 3 (9.2 micrometers) had the most variation, although the entire emissivity range was only from 0.89 to 1.0. Active dunes had the lowest emissivities (0.89 to 0.91), inactive dunes were distinguished by higher emissivities (.094 to 1.0), and interdune surfaces had intermediate values (0.90 to 0.95). These emissivity variations result from differences in particle size, as inactive dunes tend to have finer-grained silt and dust on them. LINEAR UNMIXING USING IMAGE ENDMEMBERS: Quantitative estimates of thermal infrared spectral emissivity are ideally suited to unmixing analysis. For grains larger than the wavelength (e.g., dune sand), a linear unmixing approach provides geologically useful results [7]. In the present study, image endmembers were selected for a preliminary unmixing study: (1) "regular sand," which contains nearly 50% plagioclase and nearly 20% volcanic glass; (2) "dark sand, which consists mainly of basalt clasts (> 25%) and glass (> 30%); (3) "mud chips," which are volcanic ash aggregates broken into sand-sized pieces, (4) sagebrush and grass; and (5) thick vegetation, such as an alfalfa farm near the dunes. The most important result of this preliminary unmixing work is an image that shows the distribution of ash aggregates and "dark sand," both of which vary throughout the dune field as a function of proximity to the source. The volcanic ash aggregates, in particular, are locally eroded from a layer that caps the Pleistocene lake beds that underlie the dunes [3]. SUMMARY: This study highlights the use of thermal infrared spectra to map local contributions of sand to a dune field, and to distinguish active versus inactive dune fields. Mapping of local contributions to active dune fields on Mars using TES or other multispectral images has potential to provide indications of local bedrock composition. REFERENCES: [1] Allison, I. S. (1979) Oregon Dept. Geol. Minl. Res. Spec. Pap. 7. [2] Dole, H. M. (1942) M.S. Thesis, Oregon State, Corvallis, Or. [3] Edgett, K. S. (1994) in Ph.D. Diss., pp. 145-201, Arizona State, Tempe, AZ. [4] Realmutto, V. J. (1990) in JPL Publ. 90-55, pp. 31-35. [5] Edgett, K. S., and D. L. Anderson (1995) in JPL Publ. 95-1, v. 2, pp. 9-12. [6] Edgett, K. S. et al. (1995) in JPL Publ. 95-1, v. 2, pp. 13-16. [7] Ramsey, M. S. (1996) Ph.D. Diss, Arizona State, Tempe, AZ.

Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China.

PubMed

Ji, Cuicui; Jia, Yonghong; Gao, Zhihai; Wei, Huaidong; Li, Xiaosong

2017-01-01

Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement.

Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China

PubMed Central

Jia, Yonghong; Gao, Zhihai; Wei, Huaidong

2017-01-01

Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement. PMID:29240777

Measurement and modeling of diffusion time dependence of apparent diffusion coefficient and fractional anisotropy in prostate tissue ex vivo.

PubMed

Bourne, Roger; Liang, Sisi; Panagiotaki, Eleftheria; Bongers, Andre; Sved, Paul; Watson, Geoffrey

2017-10-01

The purpose of this study was to measure and model the diffusion time dependence of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) derived from conventional prostate diffusion-weighted imaging methods as used in recommended multiparametric MRI protocols. Diffusion tensor imaging (DTI) was performed at 9.4 T with three radical prostatectomy specimens, with diffusion times in the range 10-120 ms and b-values 0-3000 s/mm 2 . ADC and FA were calculated from DTI measurements at b-values of 800 and 1600 s/mm 2 . Independently, a two-component model (restricted isotropic plus Gaussian anisotropic) was used to synthesize DTI data, from which ADC and FA were predicted and compared with the measured values. Measured ADC and FA exhibited a diffusion time dependence, which was closely predicted by the two-component model. ADC decreased by about 0.10-0.15 μm 2 /ms as diffusion time increased from 10 to 120 ms. FA increased with diffusion time at b-values of 800 and 1600 s/mm 2 but was predicted to be independent of diffusion time at b = 3000 s/mm 2 . Both ADC and FA exhibited diffusion time dependence that could be modeled as two unmixed water pools - one having isotropic restricted dynamics, and the other unrestricted anisotropic dynamics. These results highlight the importance of considering and reporting diffusion times in conventional ADC and FA calculations and protocol recommendations, and inform the development of improved diffusion methods for prostate cancer imaging. Copyright © 2017 John Wiley & Sons, Ltd.

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.

Sensitive dual color in vivo bioluminescence imaging using a new red codon optimized firefly luciferase and a green click beetle luciferase.

PubMed

Mezzanotte, Laura; Que, Ivo; Kaijzel, Eric; Branchini, Bruce; Roda, Aldo; Löwik, Clemens

2011-04-22

Despite a plethora of bioluminescent reporter genes being cloned and used for cell assays and molecular imaging purposes, the simultaneous monitoring of multiple events in small animals is still challenging. This is partly attributable to the lack of optimization of cell reporter gene expression as well as too much spectral overlap of the color-coupled reporter genes. A new red emitting codon-optimized luciferase reporter gene mutant of Photinus pyralis, Ppy RE8, has been developed and used in combination with the green click beetle luciferase, CBG99. Human embryonic kidney cells (HEK293) were transfected with vectors that expressed red Ppy RE8 and green CBG99 luciferases. Populations of red and green emitting cells were mixed in different ratios. After addition of the shared single substrate, D-luciferin, bioluminescent (BL) signals were imaged with an ultrasensitive cooled CCD camera using a series of band pass filters (20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that expressed the two luciferases were injected at different depth in the animals. Spectrally-separate images and quantification of the dual BL signals in a mixed population of cells was achieved when cells were either injected subcutaneously or directly into the prostate. We report here the re-engineering of different luciferase genes for in vitro and in vivo dual color imaging applications to address the technical issues of using dual luciferases for imaging. In respect to previously used dual assays, our study demonstrated enhanced sensitivity combined with spatially separate BL spectral emissions using a suitable spectral unmixing algorithm. This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future for more accurate quantitative gene expression studies in vivo by simultaneously monitoring two events in real time.

Nutrient Losses during Winter and Summer Storage of Separated and Unseparated Digested Cattle Slurry.

PubMed

Perazzolo, Francesca; Mattachini, Gabriele; Riva, Elisabetta; Provolo, Giorgio

2017-07-01

Management factors affect nutrient loss during animal manure slurry storage in different ways. We conducted a pilot-scale study to evaluate carbon (C) and nitrogen (N) losses from unseparated and digested dairy slurry during winter and summer storage. In addition to season, treatments included mechanical separation of digestate into liquid and solid fractions and bimonthly mixing. Chemical analyses were performed every 2 wk for the mixed materials and at the start and end of storage for unmixed materials. The parameters examined allowed us to estimate C and N losses and examine the factors that determine these losses as well as emission patterns. Gas measurements were done every 2 wk to determine the main forms in which gaseous losses occurred. To evaluate the effect of separation, measured losses and emissions of separated liquid and solid fractions were mathematically combined using the mass separation efficiency of the mechanical separator. Nutrient losses were mainly affected by climatic conditions. Losses of C (up to 23%) from unseparated, unmixed digestate and of N (38% from combined separated fractions and from unseparated digestate) were much greater in summer than in winter, when C and N losses were <7%. Mixing tended to significantly increase N losses ( < 0.1) only in winter. Mechanical separation resulted in lower GHG emissions from combined separated fractions than from unseparated digestate. Results indicate that to maximize the fertilizer value of digested slurry, dairy farmers must carefully choose management practices, especially in summer. For separated digestates, practices should focus on storage of the liquid fraction, the major contributor of C and N losses (up to 64 and 90% of total losses, respectively) in summer. Moreover, management practices should limit NH, the main form of N losses (up to 99.5%). Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Sensitive Dual Color In Vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase

PubMed Central

Mezzanotte, Laura; Que, Ivo; Kaijzel, Eric; Branchini, Bruce; Roda, Aldo; Löwik, Clemens

2011-01-01

Background Despite a plethora of bioluminescent reporter genes being cloned and used for cell assays and molecular imaging purposes, the simultaneous monitoring of multiple events in small animals is still challenging. This is partly attributable to the lack of optimization of cell reporter gene expression as well as too much spectral overlap of the color-coupled reporter genes. A new red emitting codon-optimized luciferase reporter gene mutant of Photinus pyralis, Ppy RE8, has been developed and used in combination with the green click beetle luciferase, CBG99. Principal Findings Human embryonic kidney cells (HEK293) were transfected with vectors that expressed red Ppy RE8 and green CBG99 luciferases. Populations of red and green emitting cells were mixed in different ratios. After addition of the shared single substrate, D-luciferin, bioluminescent (BL) signals were imaged with an ultrasensitive cooled CCD camera using a series of band pass filters (20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that expressed the two luciferases were injected at different depth in the animals. Spectrally-separate images and quantification of the dual BL signals in a mixed population of cells was achieved when cells were either injected subcutaneously or directly into the prostate. Significance We report here the re-engineering of different luciferase genes for in vitro and in vivo dual color imaging applications to address the technical issues of using dual luciferases for imaging. In respect to previously used dual assays, our study demonstrated enhanced sensitivity combined with spatially separate BL spectral emissions using a suitable spectral unmixing algorithm. This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future for more accurate quantitative gene expression studies in vivo by simultaneously monitoring two events in real time. PMID:21544210

Ferrobasalt-rhyolite immiscibility in tholeiitic volcanic and plutonic series (Invited)

NASA Astrophysics Data System (ADS)

Charlier, B.; Namur, O.; Kamenetsky, V. S.; Grove, T. L.

2013-12-01

One atmosphere experiments show that silicate liquid immiscibility develops between Fe-rich and Si-rich melts below 1000-1020°C in compositionally diverse lavas that represent classical tholeiitic trends, such as Mull, Iceland, Snake River Plain and Sept Iles. Extreme iron enrichment along the evolution trend is not necessary; immiscibility also develops during iron depletion and silica enrichment after Fe-Ti oxide saturation. Natural liquid lines of descent for major tholeiitic series also approach or intersect the experimentally-defined compositional space of immiscibility. The importance of ferrobasalt-rhyolite unmixing in both volcanic and plutonic environments is supported by worldwide occurrence of immiscible globules in the mesostasis of erupted basalts, and by unmixed melt inclusions in cumulus phases of major layered intrusions such as Sept Iles, Skaergaard and Sudbury. A clear case of liquid immiscibility is also recorded in intrusive tholeiitic gabbros from the Siberian Large Igneous Province and is evidenced by textures and compositions of millimeter-sized silicate melt pools trapped in native iron. An important implication of immiscibility in natural ferrobasaltic provinces is the development of a compositional gap characterized by the absence of intermediate compositions, a major feature observed in many tholeiitic provinces and referred to as the Daly gap. The compositions of experimental silica-rich immiscible melts coincide with those of natural rhyolites with high FeOtot and low Al2O3, which suggests a potential role for large-scale immiscibility in the petrogenesis of late-stage ferroan silicic melts. No evidence for the paired ferrobasaltic melt is observed in volcanic provinces, probably because of its uneruptable characteristics. Instead, Fe-Ti×P-rich gabbros crystallized at depth and are the cumulate products of immiscible Fe-rich melts in plutonic settings, a feature clearly evidenced in the Sept Iles intrusion. The production of immiscible Fe-Ti-Ca-P liquids has also important implications for the formation of some iron deposits associated with alkaline lavas.

Detection and Identification of potentially toxic elements in urban soil using in situ spectroscopy

NASA Astrophysics Data System (ADS)

Brook, Anna; Kopel, Daniella; Wittenberg, Lea

2017-04-01

Anthropogenic urban soils are the foundation of the urban green infrastructure, the green net quality is as good as each of its patches. In early days of pedology urban soil has been recognized with respect to contamination and the risks for human health but in study performed since the 70s, the importance of urban soil for the urban ecology became increasingly significant. Urban soils are highly disturbed land that was created by the process of urbanization. The dominant agent in the creation of urban soils is human activity which modifies the natural soil through mixing, filling or by contamination of land surfaces so as to create a layer of urban soil which can be more than 50 cm thick. The objective of this study is to determine the extent to which field spectroscopy methods can be used to extend the knowledge of toxic elements in urban soils. The majority of the studies on urban soils concentrate on identifying and mapping of known pollution mostly certain heavy metals, we are focusing on almost non disturbed soils where no direct disturbance occurred but the urban matrix inflicted on it. The elements in those soils where an-knowns features. In this study a top-down analysis is applied for detecting the presence of minerals, organic matter and pollutants in mixed soil samples. Results of the proposed top-down unmixing method suggest that the analysis is made very fast due to the simplified hierarchy which avoids the high-learning curve associated with unmixing algorithms showed that the most abundant components were coarse organic matter 12% followed by concrete dust, plastic crumbs, other man made materials, clay and other minerals. The results of the soils pH, measured electrometrically and the particle size distribution, measured by Laser diffraction, indicate there is no big different between the samples particle size distribution and the pH values of the samples but they are not significantly different from the expected, except for the OM percentage which is significantly higher in most samples. The suggested method was very effective for tracing the man-made substances, we could find concrete and asphalt, plastic and synthetic polymers after they were assimilated, broken down and decomposed into soil particles. By the top-down un-mixing method we did not limit the substances we characterize and so we could detect unexpected materials and contaminants. In five location we have traces of cyanide cadmium Cd(CN)2 probably residues of old television scenes, traces of schwertmannite Fe8O8(OH)6(SO4)·nH2O or Fe3+16O16(OH,SO4)12-13·10-12H2O acid drainage were found in four sites and the most alarmingly the detecting of actinolite Ca2(Mg4.5-2.5Fe2+0.5-2.5)Si8O22(OH)2 and tremolite Ca2(Mg5.0-4.5Fe2+0.0-0.5)Si8O22(OH), asbestos minerals, originate from the construction debris in almost all of the sites.

Analyses of atmospheric pollutants in Hong Kong and the Pearl River Delta by observation-based methods

NASA Astrophysics Data System (ADS)

Yuan, Zibing

Despite continuous efforts paid on pollution control by the Hong Kong (HK) environmental authorities in the past decade, the air pollution in HK has been deteriorating in recent years. In this thesis work a variety of observation-based approaches were applied to analyze the air pollutant monitoring data in HK and the Pearl River Delta (PRD) area. The two major pollutants of interest are ozone and respirable suspended particulate (RSP, or PM10), which exceed the Air Quality Objective more frequently. Receptor models serve as powerful tools for source identification, estimation of source contributions, and source localization when incorporated with wind profiles. This thesis work presents the first-ever application of two advanced receptor-models, positive matrix factorization (PMT) and Unmix, on the PM10 and VOCs speciation data in HK. Speciated PM10 data were collected from a monitoring network in HK between July-1998 and Dec-2005. Seven and nine sources were identified by Unmix and PMF10, respectively. Overall, secondary sulfate and vehicle emissions gave the largest contribution to PM10 (27% each), followed by biomass burning/waste incineration (13%) and secondary nitrate (11%). Sources were classified as local and regional based on its seasonal and spatial variations as well as source directional analysis. Regional sources accounted for about 56% of the ambient PM10 mass on an annual basis, and even higher (67%) during winter. Regional contributions also showed an increasing trend, with their annual averaged fraction rising from 53% in 1999 to 64% in 2005. The particulate pollution in HK is therefore sensitive to the regional influence and regional air quality management strategies are crucial in reducing PM level in HK. On the other hand, many species with significant adverse health impacts were produced locally. Local control measures should be strengthened for better protection of public health. Secondary organic carbon (SOC) could be a significant portion of OC in particles. SOC was examined by using PMF-derived source apportionment results and estimated to be sum of OC present in the secondary sources. The annual average SOC in HK was estimated to be 4.1 mugC/m3 while summertime average was 1.8 RgC/m3 and wintertime average was 6.9 ggC/m 3. In comparison with the SOC estimates by the PMF method, the method that uses elemental carbon (EC) as the tracer for primary OC to derive at SOC overestimates by 78-210% for the summer samples and by 9-49% for the winter samples. The overestimation by the EC tracer method was a result of incapability of obtaining a single OC/EC ratio that represented a mixture of primary sources varying in time and space. It was found that SOC and secondary sulfate had their seasonal variation in sync, suggesting common factors that control their formation. The close tracking of SOC and sulfate appears to suggest that in-cloud pathway is also important for SOC formation. Speciated VOCs were obtained in four air quality monitoring stations (AQMSs) in HK from August-2002 to August-2003. Both Unmix and PMF identified five stable sources. Mixed solvents gave the largest contributions ranging from 34% at rural Tap Mun to 52% at urban Central/Western. The wind directional analysis indicates the main source location at the central PRD area. Regional transport accounts for about 19% of the total VOC, while the two local and vehicle-related sources are responsible for 27%. By weighing the abundance and reactivity of each VOC species, mixed solvent use is estimated to be the largest contributor of local ozone, with the contributions ranging from 42% at Tung Chung to 57% at Tap Mun. The next largest is the vehicle exhaust, accounting for about 28% in Yuen Long. Biogenic emission is responsible for nearly 20% of the ozone generation at Tap Mun but this figure is likely underestimated. Distinct secondary inorganic aerosol (SIA) responses are expected to the reduction of different precursors as a result of non-linear chemical reactions involved in its formation. The last part of this thesis work concerns developing a chemical box model to determine the sensitivity of SIA to changes to the emissions of their precursors. The model is composed of three parts. The first part is a time-dependent module to estimate the temporal variation of all species, before and after the emission has been disturbed. The second part is a gas-particle conversion module that partitions the semi-volatile species into the two phases. The last module would then calculate the aerosol forming potential for the entire simulation period. It is estimated that SIA shows the largest response to the reduction of SO2 emission in YL, followed by NH3 and NOx. Significant regional transport of SIA is discovered in YL, limiting the indication of relative effectiveness for controlling different precursors. At the end, future research directions are proposed to better refine and validate the OBM performance for SIA simulation.

A probabilistic approach to remote compositional analysis of planetary surfaces

USGS Publications Warehouse

Lapotre, Mathieu G.A.; Ehlmann, Bethany L.; Minson, Sarah E.

2017-01-01

Reflected light from planetary surfaces provides information, including mineral/ice compositions and grain sizes, by study of albedo and absorption features as a function of wavelength. However, deconvolving the compositional signal in spectra is complicated by the nonuniqueness of the inverse problem. Trade-offs between mineral abundances and grain sizes in setting reflectance, instrument noise, and systematic errors in the forward model are potential sources of uncertainty, which are often unquantified. Here we adopt a Bayesian implementation of the Hapke model to determine sets of acceptable-fit mineral assemblages, as opposed to single best fit solutions. We quantify errors and uncertainties in mineral abundances and grain sizes that arise from instrument noise, compositional end members, optical constants, and systematic forward model errors for two suites of ternary mixtures (olivine-enstatite-anorthite and olivine-nontronite-basaltic glass) in a series of six experiments in the visible-shortwave infrared (VSWIR) wavelength range. We show that grain sizes are generally poorly constrained from VSWIR spectroscopy. Abundance and grain size trade-offs lead to typical abundance errors of ≤1 wt % (occasionally up to ~5 wt %), while ~3% noise in the data increases errors by up to ~2 wt %. Systematic errors further increase inaccuracies by a factor of 4. Finally, phases with low spectral contrast or inaccurate optical constants can further increase errors. Overall, typical errors in abundance are <10%, but sometimes significantly increase for specific mixtures, prone to abundance/grain-size trade-offs that lead to high unmixing uncertainties. These results highlight the need for probabilistic approaches to remote determination of planetary surface composition.

Use of sediment source fingerprinting to assess the role of subsurface erosion in the supply of fine sediment in a degraded catchment in the Eastern Cape, South Africa.

PubMed

Manjoro, Munyaradzi; Rowntree, Kate; Kakembo, Vincent; Foster, Ian; Collins, Adrian L

2017-06-01

Sediment source fingerprinting has been successfully deployed to provide information on the surface and subsurface sources of sediment in many catchments around the world. However, there is still scope to re-examine some of the major assumptions of the technique with reference to the number of fingerprint properties used in the model, the number of model iterations and the potential uncertainties of using more than one sediment core collected from the same floodplain sink. We investigated the role of subsurface erosion in the supply of fine sediment to two sediment cores collected from a floodplain in a small degraded catchment in the Eastern Cape, South Africa. The results showed that increasing the number of individual fingerprint properties in the composite signature did not improve the model goodness-of-fit. This is still a much debated issue in sediment source fingerprinting. To test the goodness-of-fit further, the number of model repeat iterations was increased from 5000 to 30,000. However, this did not reduce uncertainty ranges in modelled source proportions nor improve the model goodness-of-fit. The estimated sediment source contributions were not consistent with the available published data on erosion processes in the study catchment. The temporal pattern of sediment source contributions predicted for the two sediment cores was very different despite the cores being collected in close proximity from the same floodplain. This highlights some of the potential limitations associated with using floodplain cores to reconstruct catchment erosion processes and associated sediment source contributions. For the source tracing approach in general, the findings here suggest the need for further investigations into uncertainties related to the number of fingerprint properties included in un-mixing models. The findings support the current widespread use of ≤5000 model repeat iterations for estimating the key sources of sediment samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exsolution in clinoamphiboles

USGS Publications Warehouse

Ross, M.; Papike, J.J.; Weiblen, P.W.

1968-01-01

Ten amphibole specimens from a variety of metamorphic rocks such as talc schists, eclogites, and metamorphosed iron formations contain lamellae of a second amphibole oriented parallel to (101) or (100), or both, of the host. Tremolites, actinolites, and hornblendes commonly have lamellae of a calcium-poor clinoamphibole with P21/m space-group symmetry, or lamellae of citmmingtonite with C2/m space-group symmetry. Likewise ciimmingtonites and P21/m clinoamphiboles commonly contain lamellae of calcium-rich C2/m amphiboles such as tremolite. Results of x-ray diffraction, electron-probe, and microscope studies indicate that most lamellae result from unmixing of a homogeneous amphibole. The P21/m clinoampliibole is analogous to the clinopyroxene pigeonite in agreement with the results of M. G. Bown.

Validating SWE reconstruction using Airborne Snow Observatory measurements in the Sierra Nevada

NASA Astrophysics Data System (ADS)

Bair, N.; Rittger, K.; Davis, R. E.; Dozier, J.

2015-12-01

The Airborne Snow Observatory (ASO) program offers high resolution estimates of snow water equivalent (SWE) in several small basins across California during the melt season. Primarily, water managers use this information to model snowmelt runoff into reservoirs. Another, and potentially more impactful, use of ASO SWE measurements is in validating and improving satellite-based SWE estimates which can be used in austere regions with no ground-based snow or water measurements, such as Afghanistan's Hindu Kush. Using the entire ASO dataset to date (2013-2015) which is mostly from the Upper Tuolumne basin, but also includes measurements from 2015 in the Kings, Rush Creek, Merced, and Mammoth Lakes basins, we compare ASO measurements to those from a SWE reconstruction method. Briefly, SWE reconstruction involves downscaling energy balance forcings to compute potential melt energy, then using satellite-derived estimates of fractional snow covered area (fSCA) to estimate snow melt from potential melt. The snowpack can then be built in reverse, given a remotely-sensed date of snow disappearance (fSCA=0). Our model has improvements over previous iterations in that it: uses the full energy balance (compared to a modified degree-day) approach, models bulk and surface snow temperatures, accounts for ephemeral snow, and uses a remotely-sensed snow albedo adjusted for impurities. To check that ASO provides accurate snow measurements, we compare fSCA derived from ASO snow depth at 3 m resolution with fSCA from a spectral unmixing algorithm for LandSAT at 30 m, and from binary SCA estimates from Geoeye at 0.5 m from supervised classification. To conclude, we document how our reconstruction model has evolved over the years and provide specific examples where improvements have been made using ASO and other verification sources.

Long-term responses of rainforest erosional systems at different spatial scales to selective logging and climatic change

PubMed Central

Walsh, R. P. D.; Bidin, K.; Blake, W. H.; Chappell, N. A.; Clarke, M. A.; Douglas, I.; Ghazali, R.; Sayer, A. M.; Suhaimi, J.; Tych, W.; Annammala, K. V.

2011-01-01

Long-term (21–30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km2 Baru catchment, slope erosion measurements over 1990–2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994–1996 landslides. Analysis and modelling of 5–15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km−2 a−1 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout 210Pb and 137Cs values from a lateral bench core indicate that sedimentation rates in the 721 km2 Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7–13 times when steep terrain was logged in 1992–1993 and 1999–2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale. PMID:22006973

A spectroscopic analysis of Martian crater central peaks: Formation of the ancient crust

NASA Astrophysics Data System (ADS)

Skok, J. R.; Mustard, J. F.; Tornabene, L. L.; Pan, C.; Rogers, D.; Murchie, S. L.

2012-11-01

The earliest formed crust on a single plate planet such as Mars should be preserved, deeply buried under subsequent surface materials. Mars' extensive cratering history would have fractured and disrupted the upper layers of this ancient crust. Large impacts occurring late in Martian geologic history would have excavated and exposed this deeply buried material. We report the compositional analysis of unaltered mafic Martian crater central peaks with high-resolution spectral data that was used to characterize the presence, distribution and composition of mafic mineralogy. Reflectance spectra of mafic outcrops are modeled with the Modified Gaussian Model (MGM) to determine cation composition of olivine and pyroxene mineral deposits. Observations show that central peaks with unaltered mafic units are only observed in four general regions of Mars. Each mafic unit exhibits spectrally unmixed outcrops of olivine or pyroxene, indicating dunite and pyroxenite dominated compositions instead of basaltic composition common throughout much of the planet. Compositional analysis shows a wide range of olivine Fo# ranging from Fo60 to Fo5. This variation is best explained by a high degree of fractionation in a slowly cooling, differentiating magma body. Pyroxene analysis shows that all the sites in the Southern Highlands are consistent with moderately Fe-rich, low-Ca pyroxene. Mineral segregation in the ancient crust could be caused by cumulate crystallization and settling in a large, potentially global, lava lake or near surface plutons driven by a hypothesized early Martian mantle overturn.

Conditions for super-adiabatic droplet growth after entrainment mixing

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

Yang, Fan; Shaw, Raymond; Xue, Huiwen

Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixedmore » parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. Lastly, these findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.« less

Probability of Elevated Volatile Organic Compound (VOC) Concentrations in Groundwater in the Eagle River Watershed Valley-Fill Aquifer, Eagle County, North-Central Colorado, 2006-2007

USGS Publications Warehouse

Rupert, Michael G.; Plummer, Niel

2009-01-01

This raster data set delineates the predicted probability of elevated volatile organic compound (VOC) concentrations in groundwater in the Eagle River watershed valley-fill aquifer, Eagle County, North-Central Colorado, 2006-2007. This data set was developed by a cooperative project between the U.S. Geological Survey, Eagle County, the Eagle River Water and Sanitation District, the Town of Eagle, the Town of Gypsum, and the Upper Eagle Regional Water Authority. This project was designed to evaluate potential land-development effects on groundwater and surface-water resources so that informed land-use and water management decisions can be made. This groundwater probability map and its associated probability maps was developed as follows: (1) A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic (related to human activities) and hydrogeologic data by using a geographic information system to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Statistical models predicting the probability of elevated nitrate concentrations, the probability of unmixed young water (using chlorofluorocarbon-11 concentrations and tritium activities), and the probability of elevated volatile organic compound concentrations were developed using logistic regression techniques. (3) The statistical models were entered into a GIS and the probability map was constructed.

Probability of Elevated Nitrate Concentrations in Groundwater in the Eagle River Watershed Valley-Fill Aquifer, Eagle County, North-Central Colorado, 2006-2007

USGS Publications Warehouse

Rupert, Michael G.; Plummer, Niel

2009-01-01

This raster data set delineates the predicted probability of elevated nitrate concentrations in groundwater in the Eagle River watershed valley-fill aquifer, Eagle County, North-Central Colorado, 2006-2007. This data set was developed by a cooperative project between the U.S. Geological Survey, Eagle County, the Eagle River Water and Sanitation District, the Town of Eagle, the Town of Gypsum, and the Upper Eagle Regional Water Authority. This project was designed to evaluate potential land-development effects on groundwater and surface-water resources so that informed land-use and water management decisions can be made. This groundwater probability map and its associated probability maps was developed as follows: (1) A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic (related to human activities) and hydrogeologic data by using a geographic information system to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Statistical models predicting the probability of elevated nitrate concentrations, the probability of unmixed young water (using chlorofluorocarbon-11 concentrations and tritium activities), and the probability of elevated volatile organic compound concentrations were developed using logistic regression techniques. (3) The statistical models were entered into a GIS and the probability map was constructed.

Conditions for super-adiabatic droplet growth after entrainment mixing

DOE PAGES

Yang, Fan; Shaw, Raymond; Xue, Huiwen

2016-07-29

Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixedmore » parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. Lastly, these findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.« less

Fingerprinting of bed sediment in the Tay Estuary, Scotland: an environmental magnetism approach

NASA Astrophysics Data System (ADS)

Jenkins, Pierre A.; Duck, Rob W.; Rowan, John S.; Walden, John

Sediment fingerprinting is commonly used for sediment provenance studies in lakes, rivers and reservoirs and on hillslopes and floodplains. This investigation explores the mixing of terrestrial and marine-derived sediment in the Tay Estuary, Scotland, using mineral magnetic attributes for fingerprinting. Samples representative of the estuary sediments and of four sources (end-members) were subjected to a suite of magnetic susceptibility and remanence measurements. Sediment samples from the beds of the Rivers Tay and Earn represented fluvial inputs while samples from the Angus and Fife coasts represented marine input. Multivariate discriminant and factor analysis showed that the sources could be separated on the basis of six magnetic parameters in a simple multivariate unmixing model to identify source contributions to estuarine bed sediments. Multi-domain magnetite signatures, characteristic of unweathered bedrock, dominate the magnetic measurements. Overall contributions of 3% from the River Earn, 17% from the River Tay, 29% from the Angus coast and 51% from the Fife coast source end-members, demonstrated the present-day regime of marine sediment derivation in the Tay Estuary. However, this conceals considerable spatial variability both along-estuary and in terms of sub-environments, with small-scale variations in sediment provenance reflecting local morphology, particularly areas of channel convergence.

Source apportionment of PM10 by positive matrix factorization in urban area of Mumbai, India.

PubMed

Gupta, Indrani; Salunkhe, Abhaysinh; Kumar, Rakesh

2012-01-01

Particulate Matter (PM(10)) has been one of the main air pollutants exceeding the ambient standards in most of the major cities in India. During last few years, receptor models such as Chemical Mass Balance, Positive Matrix Factorization (PMF), PCA-APCS and UNMIX have been used to provide solutions to the source identification and contributions which are accepted for developing effective and efficient air quality management plans. Each site poses different complexities while resolving PM(10) contributions. This paper reports the variability of four sites within Mumbai city using PMF. Industrial area of Mahul showed sources such as residual oil combustion and paved road dust (27%), traffic (20%), coal fired boiler (17%), nitrate (15%). Residential area of Khar showed sources such as residual oil combustion and construction (25%), motor vehicles (23%), marine aerosol and nitrate (19%), paved road dust (18%) compared to construction and natural dust (27%), motor vehicles and smelting work (25%), nitrate (16%) and biomass burning and paved road dust (15%) in Dharavi, a low income slum residential area. The major contributors of PM(10) at Colaba were marine aerosol, wood burning and ammonium sulphate (24%), motor vehicles and smelting work (22%), Natural soil (19%), nitrate and oil burning (18%).

Isograde mapping and mineral identification on the island of Naxos, Greece, using DAIS 7915 hyperspectral data

NASA Astrophysics Data System (ADS)

Echtler, Helmut; Segl, Karl; Dickerhof, Corinna; Chabrillat, Sabine; Kaufmann, Hermann J.

2003-03-01

The ESF-LSF 1997 flight campaign conducted by the German Aerospace Center (DLR) recorded several transects across the island of Naxos using the airborne hyperspectral scanner DAIS. The geological targets cover all major litho-tectonic units of a metamorphic dome with the transition of metamorphic zonations from the outer meta-sedimentary greenschist envelope to the gneissic amphibolite facies and migmatitic core. Mineral identification of alternating marble-dolomite sequences and interlayered schists bearing muscovite and biotite has been accomplished using the airborne hyperspectral DAIS 7915 sensor. Data have been noise filtered based on maximum noise fraction (MNF) and fast Fourier transform (FFT) and converted from radiance to reflectance. For mineral identification, constrained linear spectral unmixing and spectral angle mapper (SAM) algorithms were tested. Due to their unsatisfying results a new approach was developed which consists of a linear mixture modeling and spectral feature fitting. This approach provides more detailed and accurate information. Results are discussed in comparison with detailed geological mapping and additional information. Calcites are clearly separated from dolomites as well as the mica-schist sequences by a good resolution of the mineral muscovite. Thereon an outstanding result represents the very good resolution of the chlorite/mica (muscovite, biotite)-transition defining a metamorphic isograde.

Mapping Environmental Contaminants at Ray Mine, AZ

NASA Technical Reports Server (NTRS)

McCubbin, Ian; Lang, Harold

2000-01-01

Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Protection Agency (EPA) through the Advanced Measurement Initiative (AMI). The overall goal of AMI is to accelerate adoption and application of advanced measurement technologies for cost effective environmental monitoring. The site was selected to demonstrate the benefit to EPA in using advanced remote sensing technologies for the detection of environmental contaminants due to the mineral extraction industry. The role of the Jet Propulsion Laboratory in this pilot study is to provide data as well as performing calibration, data analysis, and validation of the AVIRIS results. EPA is also interested in developing protocols that use commercial software to perform such work on other high priority EPA sites. Reflectance retrieval was performed using outputs generated by the MODTRAN radiative transfer model and field spectra collected for the purpose of calibration. We are presenting advanced applications of the ENVI software package using n-Dimensional Partial Unmixing to identify image-derived endmembers that best match target materials reference spectra from multiple spectral libraries. Upon identification of the image endmembers the Mixture Tuned Match Filter algorithm was applied to map the endmembers within each scene. Using this technique it was possible to map four different mineral classes that are associated with mine generated acid waste.

Spectroscopic identification of individual fluorophores using photoluminescence excitation spectra.

PubMed

Czerski, J; Colomb, W; Cannataro, F; Sarkar, S K

2018-01-25

The identity of a fluorophore can be ambiguous if other fluorophores or nonspecific fluorescent impurities have overlapping emission spectra. The presence of overlapping spectra makes it difficult to differentiate fluorescent species using discrete detection channels and unmixing of spectra. The unique absorption and emission signatures of fluorophores provide an opportunity for spectroscopic identification. However, absorption spectroscopy may be affected by scattering, whereas fluorescence emission spectroscopy suffers from signal loss by gratings or other dispersive optics. Photoluminescence excitation spectra, where excitation is varied and emission is detected at a fixed wavelength, allows hyperspectral imaging with a single emission filter for high signal-to-background ratio without any moving optics on the emission side. We report a high throughput method for measuring the photoluminescence excitation spectra of individual fluorophores using a tunable supercontinuum laser and prism-type total internal reflection fluorescence microscope. We used the system to measure and sort the photoluminescence excitation spectra of individual Alexa dyes, fluorescent nanodiamonds (FNDs), and fluorescent polystyrene beads. We used a Gaussian mixture model with maximum likelihood estimation to objectively separate the spectra. Finally, we spectroscopically identified different species of fluorescent nanodiamonds with overlapping spectra and characterized the heterogeneity of fluorescent nanodiamonds of varying size. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

Numerical Study on Crossflow Printed Circuit Heat Exchanger for Advanced Small Modular Reactors

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

Yoon, Su-Jong; Sabharwall, Piyush; Kim, Eung-Soo

2014-03-01

Various fluids such as water, gases (helium), molten salts (FLiNaK, FLiBe) and liquid metal (sodium) are used as a coolant of advanced small modular reactors (SMRs). The printed circuit heat exchanger (PCHE) has been adopted as the intermediate and/or secondary heat exchanger of SMR systems because this heat exchanger is compact and effective. The size and cost of PCHE can be changed by the coolant type of each SMR. In this study, the crossflow PCHE analysis code for advanced small modular reactor has been developed for the thermal design and cost estimation of the heat exchanger. The analytical solution ofmore » single pass, both unmixed fluids crossflow heat exchanger model was employed to calculate a two dimensional temperature profile of a crossflow PCHE. The analytical solution of crossflow heat exchanger was simply implemented by using built in function of the MATLAB program. The effect of fluid property uncertainty on the calculation results was evaluated. In addition, the effect of heat transfer correlations on the calculated temperature profile was analyzed by taking into account possible combinations of primary and secondary coolants in the SMR systems. Size and cost of heat exchanger were evaluated for the given temperature requirement of each SMR.« less

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Bateson, C. Ann; Curtiss, Brian; Benning, Tracy L.

1993-01-01

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

Constraints on the Geometries and Compositions of Subvolcanic Conduits from Intrusions of the San Rafael Swell, Utah

NASA Astrophysics Data System (ADS)

Wetmore, P. H.; Connor, C.; Wilson, J.

2010-12-01

Conduit models incorporate varying degrees of complexity (or parsimony) and account for the transport properties of magmas, steady-state or transient behavior, and conduit geometry (e.g., 1- to 1.5 D, variable width and erodable conduit walls). Improvement of these models is important if we are to work toward deployment of eruption models at active volcanoes, link these models to geophysical observations (seismic, deformation, gravity) and eventually forecast eruption magnitude. One conclusion of a recent comparison of many conduit models (Sahagian, 2005 JVGR) is that next generation models need to better account for interaction of the erupting mixture with surrounding wall rocks (accounting for melting, solidification, and erosion) and better account for the effects of conduit shape on flows. In an effort to address these issues our research group has completed mapping of a suite of subvolcanic intrusions (dikes, sills, and conduits) from the west-central San Rafael Swell of central Utah. The results of this study demonstrate that vertical flow of melt through crust in this system of intrusion was dominated by dikes. Conduits form, in nearly all cases, as a result of localized flow along dikes. The conduits are commonly comprised of three distinct lithologic units: brecciated host rock (without any intrusive material), brecciated host rock mixed with brecciated and mechanically contaminated intrusive, and relatively clean (i.e. containing less than ~10% accidental material) intrusive. Contacts between all three of these units are typically discreet and traceable for several tens of meters. In some examples clasts within the unmixed breccia unit exhibit a strong alignment of clasts dipping into the core of the conduit. These observations suggests an evolutionary history that involves an early phase of brecciation and mixing, followed by confined flow with a fluidized mixed unit and an essentially uninvolved outer zone (i.e. the breccia). The final phase likely involves the inward collapse as fluid pressures reduce.

Coexpression of CdSe and CdSe/CdS quantum dots in live cells using molecular hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Li, Qingli; Peng, Hui; Wang, Jing; Wang, Yiting; Guo, Fangmin

2015-11-01

A direct spatial and spectral observation of CdSe and CdSe/CdS quantum dots (QDs) as probes in live cells is performed by using a custom molecular hyperspectral imaging (MHI) system. Water-soluble CdSe and CdSe/CdS QDs are synthesized in aqueous solution under the assistance of high-intensity ultrasonic irradiation and incubated with colon cancer cells for bioimaging. Unlike the traditional fluorescence microscopy methods, MHI technology can identify QD probes according to their spectral signatures and generate coexpression and stain titer maps by a clustering method. The experimental results show that the MHI method has potential to unmix biomarkers by their spectral information, which opens up a pathway of optical multiplexing with many different QD probes.

Geology of the Andover Granite and surrounding rocks, Massachusetts

USGS Publications Warehouse

Castle, Robert O.

1964-01-01

Field and petrographic studies of the Andover Granite and surrounding rocks have afforded an opportunity for an explanation of its emplacement and crystallization. The investigation has contributed secondarily to an understanding of the geologic history of southeastern New England, particularly as it is revealed in the Lawrence, Wilmington, South Groveland, and Reading quadrangles of Massachusetts. The Andover Granite and Sharpners Pond Tonalite together comprise up to 90 percent of the Acadian(?) subalkaline intrusive series cropping out within the area of study. The subalkaline series locally invades a sequence of early to middle Paleozoic and possibly Precambrian metasedimentary and metavolcanic rocks. Much of the subalkaline series and most of the Andover Granite is confined between two prominent east-northeast trending faults or fault systems. The northern fault separates the mildly metamorphosed Middle Silurian(?) Merrimack Group on the north from a highly metamorphosed and thoroughly intruded Ordovician(?) sequence on the south. The southern 'boundary '' fault is a major structural discontinuity characterized by penetrative, diffuse shearing over a zone one-half mile or more in width. The magmatic nature of the Andover Granite is demonstrated by: (1) sharply crosscutting relationships with surrounding rocks; (2) the occurrence of tabular-shaped xenoliths whose long directions parallel the foliation within the granite and whose internal foliation trends at a high angle to that of the granite; (3) continuity with the clearly intrusive Sharpners Pond Tonalite; (4) the compositional uniformity of the granite as contrasted with the compositional diversity of the rocks it invades; (5) its modal and normative correspondence with (a) calculated norms of salic extrusives and (b) that of the ternary (granite) minimum for the system NaAlSi3O8-KAlSi3O8-SiO2. Orogenic granites, as represented by the Andover, contrast with post-orogenic granites, represented locally by the Peabody Granite, in their phase composition and texture. Unlike the Peabody, the Andover Granite is thought to have been thoroughly recrystallized through the unmixing of initially homogeneous phases with the concomitant development of extremely intricate, allotriomorphic textures. Textural relationships between potassium and plagioclase feldspars and among quartz and the two feldspars, suggest that the Andover Granite has evolved through exsolution of a single hypersolvus feldspar (or two coexisting subsolvus feldspars of only slightly disparate compositions) into discrete grains of plagioclase and potassium feldspar, much along the lines proposed by Tuttle (1952). A hypothesis is proposed for the origin of myrmekite whereby it is evolved indirectly through exsolution of a homogeneous, hypersolvus, calcalkali feldspar in the presence of a silica reservoir. Where the An 'molecule' is contained in the primary mix crystal, exsolution into potassium and plagioclase feldspar phases normally requires a paired exchange between Ca-Al and K-Si. Should the silicon requirements of the developing potassium feldspar be met by the matrix silica reservoir, the concomitantly evolving plagioclase may become stoichiometrically enriched in silicon and ultimately develop into myrmekite. Discrete unmixing of pure alkali feldspar proceeds through simple alkali ion exchange; ternary compostions high in An are more apt to fall initially in the two-feldspar field, thereby reducing the unmixing potential. General restriction of myrmekite to plagioclase of calcic albite to oligoclase composition is explained accordingly.

Sediment transport processes in the Pearl River Estuary as revealed by grain-size end-member modeling and sediment trend analysis

NASA Astrophysics Data System (ADS)

Li, Tao; Li, Tuan-Jie

2018-04-01

The analysis of grain-size distribution enables us to decipher sediment transport processes and understand the causal relations between dynamic processes and grain-size distributions. In the present study, grain sizes were measured from surface sediments collected in the Pearl River Estuary and its adjacent coastal areas. End-member modeling analysis attempts to unmix the grain sizes into geologically meaningful populations. Six grain-size end-members were identified. Their dominant modes are 0 Φ, 1.5 Φ, 2.75 Φ, 4.5 Φ, 7 Φ, and 8 Φ, corresponding to coarse sand, medium sand, fine sand, very coarse silt, silt, and clay, respectively. The spatial distributions of the six end-members are influenced by sediment transport and depositional processes. The two coarsest end-members (coarse sand and medium sand) may reflect relict sediments deposited during the last glacial period. The fine sand end-member would be difficult to transport under fair weather conditions, and likely indicates storm deposits. The three remaining fine-grained end-members (very coarse silt, silt, and clay) are recognized as suspended particles transported by saltwater intrusion via the flood tidal current, the Guangdong Coastal Current, and riverine outflow. The grain-size trend analysis shows distinct transport patterns for the three fine-grained end-members. The landward transport of the very coarse silt end-member occurs in the eastern part of the estuary, the seaward transport of the silt end-member occurs in the western part, and the east-west transport of the clay end-member occurs in the coastal areas. The results show that grain-size end-member modeling analysis in combination with sediment trend analysis help to better understand sediment transport patterns and the associated transport mechanisms.

Mapping and modeling the urban landscape in Bangkok, Thailand: Physical-spectral-spatial relations of population-environmental interactions

NASA Astrophysics Data System (ADS)

Shao, Yang

This research focuses on the application of remote sensing, geographic information systems, statistical modeling, and spatial analysis to examine the dynamics of urban land cover, urban structure, and population-environment interactions in Bangkok, Thailand, with an emphasis on rural-to-urban migration from rural Nang Rong District, Northeast Thailand to the primate city of Bangkok. The dissertation consists of four main sections: (1) development of remote sensing image classification and change-detection methods for characterizing imperviousness for Bangkok, Thailand from 1993-2002; (2) development of 3-D urban mapping methods, using high spatial resolution IKONOS satellite images, to assess high-rises and other urban structures; (3) assessment of urban spatial structure from 2-D and 3-D perspectives; and (4) an analysis of the spatial clustering of migrants from Nang Rong District in Bangkok and the neighborhood environments of migrants' locations. Techniques are developed to improve the accuracy of the neural network classification approach for the analysis of remote sensing data, with an emphasis on the spectral unmixing problem. The 3-D building heights are derived using the shadow information on the high-resolution IKONOS image. The results from the 2-D and 3-D mapping are further examined to assess urban structure and urban feature identification. This research contributes to image processing of remotely-sensed images and urban studies. The rural-urban migration process and migrants' settlement patterns are examined using spatial statistics, GIS, and remote sensing perspectives. The results show that migrants' spatial clustering in urban space is associated with the source village and a number of socio-demographic variables. In addition, the migrants' neighborhood environments in urban setting are modeled using a set of geographic and socio-demographic variables, and the results are scale-dependent.

Pairwise mixture model for unmixing partial volume effect in multi-voxel MR spectroscopy of brain tumour patients

NASA Astrophysics Data System (ADS)

Olliverre, Nathan; Asad, Muhammad; Yang, Guang; Howe, Franklyn; Slabaugh, Gregory

2017-03-01

Multi-Voxel Magnetic Resonance Spectroscopy (MV-MRS) provides an important and insightful technique for the examination of the chemical composition of brain tissue, making it an attractive medical imaging modality for the examination of brain tumours. MRS, however, is affected by the issue of the Partial Volume Effect (PVE), where the signals of multiple tissue types can be found within a single voxel and provides an obstacle to the interpretation of the data. The PVE results from the low resolution achieved in MV-MRS images relating to the signal to noise ratio (SNR). To counteract PVE, this paper proposes a novel Pairwise Mixture Model (PMM), that extends a recently reported Signal Mixture Model (SMM) for representing the MV-MRS signal as normal, low or high grade tissue types. Inspired by Conditional Random Field (CRF) and its continuous variant the PMM incorporates the surrounding voxel neighbourhood into an optimisation problem, the solution of which provides an estimation to a set of coefficients. The values of the estimated coefficients represents the amount of each tissue type (normal, low or high) found within a voxel. These coefficients can then be visualised as a nosological rendering using a coloured grid representing the MV-MRS image overlaid on top of a structural image, such as a Magnetic Resonance Image (MRI). Experimental results show an accuracy of 92.69% in classifying patient tumours as either low or high grade compared against the histopathology for each patient. Compared to 91.96% achieved by the SMM, the proposed PMM method demonstrates the importance of incorporating spatial coherence into the estimation as well as its potential clinical usage.

Multi-Fluid Interpenetration Mixing in X-ray and Directly Laser driven ICF Capsule Implosions

NASA Astrophysics Data System (ADS)

Wilson, Douglas

2003-10-01

Mix between a surrounding shell and the fuel leads to degradation in ICF capsule performance. Both indirectly (X-ray) and directly laser driven implosions provide a wealth of data to test mix models. One model, the multi-fluid interpenetration mix model of Scannapieco and Cheng (Phys. Lett. A., 299, 49, 2002), was implemented in an ICF code and applied to a wide variety of experiments (e.g. J. D. Kilkenny et al., Proc. Conf Plasm. Phys. Contr. Nuc. Fus. Res. 3, 29(1988), P. Amendt, R. E. Turner, O. L. Landen, Phy. Rev. Lett., 89, 165001 (2002), or Li et al., Phy. Rev. Lett, 89, 165002 (2002)). With its single adjustable parameter fixed, it replicates well the yield degradation with increasing convergence ratio for both directly and indirectly driven capsules. Often, but not always the ion temperatures with mixing are calculated to be higher than in an unmixed implosion, agreeing with observations. Comparison with measured directly driven implosion yield rates ( from the neutron temporal diagnostic or NTD) shows mixing increases rapidly during the burn. The model also reproduces the decrease of the fuel "rho-r" with fill gas pressure, measured by observing escaping deuterons or secondary neutrons. The mix model assumes fully atomically mixed constituents, but when experiments with deuterated plastic layers and 3He fuel are modeled, less that full atomic mix is appropriate. Applying the mix model to the ablator - solid DT interface in indirectly driven ignition capsules for the NIF or LMJ suggests that the capsules will ignite, but that burn after ignition may be somewhat degraded. Situations in which the Scannapieco and Cheng model fails to agree with experiments can guide us to improvements or the development of other models. Some directly driven symmetric implosions suggest that in highly mixed situations, a higher value of the mix parameter may needed. Others show the model underestimating the fuel burn temperature. This work was performed by the Los Alamos National Laboratory under DOE contract number W-7405-Eng-36.

Mass Dependency of Isotope Fractionation of Gases Under Thermal Gradient and Its Possible Implications for Planetary Atmosphere Escaping Process

NASA Technical Reports Server (NTRS)

Sun, Tao; Niles, Paul; Bao, Huiming; Socki, Richard

2014-01-01

Physical processes that unmix elements/isotopes of gas molecules involve phase changes, diffusion (chemical or thermal), effusion and gravitational settling. Some of those play significant roles for the evolution of chemical and isotopic compositions of gases in planetary bodies which lead to better understanding of surface paleoclimatic conditions, e.g. gas bubbles in Antarctic ice, and planetary evolution, e.g. the solar-wind erosion induced gas escaping from exosphere on terrestrial planets.. A mass dependent relationship is always expected for the kinetic isotope fractionations during these simple physical processes, according to the kinetic theory of gases by Chapman, Enskog and others [3-5]. For O-bearing (O16, -O17, -O18) molecules the alpha O-17/ alpha O-18 is expected at 0.5 to 0.515, and for S-bearing (S32,-S33. -S34, -S36) molecules, the alpha S-33/ alpha S-34 is expected at 0.5 to 0.508, where alpha is the isotope fractionation factor associated with unmixing processes. Thus, one isotope pair is generally proxied to yield all the information for the physical history of the gases. However, we recently] reported the violation of mass law for isotope fractionation among isotope pairs of multiple isotope system during gas diffusion or convection under thermal gradient (Thermal Gradient Induced Non-Mass Dependent effect, TGI-NMD). The mechanism(s) that is responsible to such striking observation remains unanswered. In our past studies, we investigated polyatomic molecules, O2 and SF6, and we suggested that nuclear spin effect could be responsible to the observed NMD effect in a way of changing diffusion coefficients of certain molecules, owing to the fact of negligible delta S-36 anomaly for SF6.. On the other hand, our results also showed that for both diffusion and convection under thermal gradient, this NMD effect is increased by lower gas pressure, bigger temperature gradient and lower average temperature, which indicate that the nuclear spin effect may not be the significant contributor as the energies involved in the hyperfine effect are much smaller than those with molecular collisions, especially under convective conditions.

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

NASA Technical Reports Server (NTRS)

Huemmrich, Karl Fred; Gamon, John A.; Tweedie, Craig E.; Campbell, Petya K. Entcheva; Landis, David R.; Middleton, Elizabeth M.

2013-01-01

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes.

Mineralogic variability of the Kelso Dunes, Mojave Desert, California derived from Thermal Infrared Multispectral Scanner (TIMS) data

NASA Technical Reports Server (NTRS)

Ramsey, Michael S.; Howard, Douglas A.; Christensen, Philip R.; Lancaster, Nicholas

1993-01-01

Mineral identification and mapping of alluvial material using thermal infrared (TIR) remote sensing is extremely useful for tracking sediment transport, assessing the degree of weathering and locating sediment sources. As a result of the linear relation between a mineral's percentage in a given area (image pixel) and the depth of its diagnostic spectral features, TIR spectra can be deconvolved in order to ascertain mineralogic percentages. Typical complications such as vegetation, particle size and thermal shadowing are minimized upon examination of dunes. Actively saltating dunes contain little to no vegetation, are very well sorted and lack the thermal shadows that arise from rocky terrain. The primary focus of this work was to use the Kelso Dunes as a test location for an accuracy analysis of temperature/emissivity separation and linear unmixing algorithms. Accurate determination of ground temperature and component discrimination will become key products of future ASTER data. A decorrelation stretch of the TIMS image showed clear color variations within the active dunes. Samples collected from these color units were analyzed for mineralogy, grain size, and separated into endmembers. This analysis not only revealed that the dunes contained significant mineralogic variation, but were more immature (low quartz percentage) than previously reported. Unmixing of the TIMS data using the primary mineral endmembers produced unique variations within the dunes and may indicate near, rather than far, source locales for the dunes. The Kelso Dunes lie in the eastern Mojave Desert, California, approximately 95 km west of the Colorado River. The primary dune field is contained within a topographic basin bounded by the Providence, Granite Mountains, with the active region marked by three northeast trending linear ridges. Although active, the dunes appear to lie at an opposing regional wind boundary which produces little net movement of the crests. Previous studies have estimated the dunes range from 70% to 90% quartz mainly derived from a source 40 km to the west. The dune field is assumed to have formed in a much more arid climate than present, with the age of the deposit estimated at greater than 100,000 years.

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh-Dokhtar Volcanic Belt, Iran

NASA Astrophysics Data System (ADS)

Pour, Amin Beiranvand; Hashim, Mazlan

2012-02-01

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh-Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.Spectral transform methods enhanced hydrothermally altered rocks associated with the known porphyry copper deposits and new identified prospects using shortwave infrared (SWIR) bands of ASTER. These methods showed the discrimination of quartz rich igneous rocks from the magmatic background and the boundary between igneous and sedimentary rocks using the thermal infrared (TIR) bands of ASTER at regional scale. Spectral mapping methods distinguished the sericitically- and argillically-altered rocks (the phyllic and argillic alteration zones) that surrounded by discontinuous to extensive zones of propylitized rocks (the propylitic alteration zone) using SWIR bands of ASTER at both regional and district scales. Linear spectral unmixing method can be best suited for distinguishing specific high economic-potential hydrothermal alteration zone (the phyllic zone) and mineral assemblages using SWIR bands of ASTER. Results have proven to be effective, and in accordance with the results of field surveying, spectral reflectance measurements and X-ray diffraction (XRD) analysis. In conclusion, the image processing methods used can provide cost-effective information to discover possible locations of porphyry copper and epithermal gold mineralization prior to detailed and costly ground investigations. The extraction of spectral information from ASTER data can produce comprehensive and accurate information for copper and gold resource investigations around the world, including those yet to be discovered.

Regional sub-cratonic mantle heterogeneities under the Kaapvaal craton recorded by sulfide inclusions in diamond.

NASA Astrophysics Data System (ADS)

Thomassot, E.; Lorand, J. P.

2016-12-01

Sulfide inclusions in diamonds (SID) have been trapped by their host at depth greater than 150 km and then protected from alteration or reequilibration processes. Subsequently, depending on their initial composition, there have experienced multiple exsolution events at temperatures between 650°C and 200°C. Mineralogical and isotopic composition of SID thus directly reflects their sources whereas their texture give information on the exhumation history of their diamond host. Our samples originating from Koffiefontein, De Beers Pool and Jwaneng kimberlites, include both peridotitic (P-type, n=6) and eclogitic (E-type, n=151) sulfides. P-type sulfides are monosulfide solid solutions (exsolved from a nickeliferous monosulfide solid solution, mss, stable at T>300°C). Their Ni and Cr content indicate that the sublithospheric mantle under Koffiefontein (Ni=26wt%; Cr=0.36 wt%) is more refractory than De Beers Pool (Ni=24wt%; Cr=0.28wt%) and Jwaneng (Ni=17wt%; Cr=0.22wt%). Sulfides from De Beers Pool have S/Se (3900±100) greater than the chondritic values ( 2540) pointing to a metasomatic overprint predating the formation of diamonds. S-isotopic composition (d34S=-0.9 ± 0.5‰, Δ33S=0‰) are homogeneous, and consistent with the composition of MORB. E-type sulfides are unmixed assemblage of chalcopyrite (crystallized from an intermediate solid solution formed at T 650°C) pentlandite (T° from 260 to >200°C) and pyrrhotite. Comparing the chemical composition of the unmixed phases with experimental data, we determined a blocking T° for E-type assemblages ranging from 540°C at Koffiefontein, to less than 200°C at Jwaneng and DeBeersPool. E-type sulfides thus confirm the chemical heterogeneity from one mine to the other, with d34S extended to fractionated values (-9 to +11‰). Our study indicates that SID are robust probes to explore regional scale mantle heterogeneities likely associated to discrete depletion events and possible recycling of ancient sediment, predating the formation of diamonds. Major, trace element and isotopes data will be presented at the conference in order to support this conclusion.

Origins of fine aerosol mass in the Baltimore-Washington corridor: implications from observation, factor analysis, and ensemble air parcel back trajectories

NASA Astrophysics Data System (ADS)

Antony Chen, L.-W.; Doddridge, Bruce G.; Dickerson, Russell R.; Chow, Judith C.; Henry, Ronald C.

Chemically speciated fine particulate matter (PM 2.5) and trace gases (including NH 3, HNO 3, CO, SO 2, NO y) have been sampled at Fort Meade (FME: 39.10°N, 76.74°W; elevation 46 m MSL), Maryland, since July 1999. FME is suburban, located in the middle of the Baltimore-Washington corridor, and generally downwind of the highly industrialized Midwest. The PM 2.5 at FME is expected to be of both local and regional sources. Measurements over a 2-year period include eight seasonally representative months. The PM 2.5 shows an annual mean of 13 μg m -3 and primarily consists of sulfate, nitrate, ammonium, and carbonaceous material. Day-to-day and seasonal variations in the PM 2.5 chemical composition reflect changes of contribution from various sources. UNMIX, an innovative receptor model, is used to retrieve potential sources of the PM 2.5. A six-factor model, including regional sulfate, local sulfate, wood smoke, copper/iron processing industry, mobile, and secondary nitrate, is constructed and compared with reported source emission profiles. The six factors are studied further using an ensemble back trajectory method to identify possible source locations. Sources of local sulfate, mobile, and secondary nitrate are more localized around the receptor than those of other factors. Regional sulfate and wood smoke are more regional and associated with westerly and southerly transport, respectively. This study suggests that the local contribution to PM 2.5 mass can vary from <30% in summer to >60% in winter.

Interventional multispectral photoacoustic imaging with a clinical linear array ultrasound probe for guiding nerve blocks

NASA Astrophysics Data System (ADS)

Xia, Wenfeng; West, Simeon J.; Nikitichev, Daniil I.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

2016-03-01

Accurate identification of tissue structures such as nerves and blood vessels is critically important for interventional procedures such as nerve blocks. Ultrasound imaging is widely used as a guidance modality to visualize anatomical structures in real-time. However, identification of nerves and small blood vessels can be very challenging, and accidental intra-neural or intra-vascular injections can result in significant complications. Multi-spectral photoacoustic imaging can provide high sensitivity and specificity for discriminating hemoglobin- and lipid-rich tissues. However, conventional surface-illumination-based photoacoustic systems suffer from limited sensitivity at large depths. In this study, for the first time, an interventional multispectral photoacoustic imaging (IMPA) system was used to image nerves in a swine model in vivo. Pulsed excitation light with wavelengths in the ranges of 750 - 900 nm and 1150 - 1300 nm was delivered inside the body through an optical fiber positioned within the cannula of an injection needle. Ultrasound waves were received at the tissue surface using a clinical linear array imaging probe. Co-registered B-mode ultrasound images were acquired using the same imaging probe. Nerve identification was performed using a combination of B-mode ultrasound imaging and electrical stimulation. Using a linear model, spectral-unmixing of the photoacoustic data was performed to provide image contrast for oxygenated and de-oxygenated hemoglobin, water and lipids. Good correspondence between a known nerve location and a lipid-rich region in the photoacoustic images was observed. The results indicate that IMPA is a promising modality for guiding nerve blocks and other interventional procedures. Challenges involved with clinical translation are discussed.

Computational parametric study of a Richtmyer-Meshkov instability for an inclined interface.

PubMed

McFarland, Jacob A; Greenough, Jeffrey A; Ranjan, Devesh

2011-08-01

A computational study of the Richtmyer-Meshkov instability for an inclined interface is presented. The study covers experiments to be performed in the Texas A&M University inclined shock tube facility. Incident shock wave Mach numbers from 1.2 to 2.5, inclination angles from 30° to 60°, and gas pair Atwood numbers of ∼0.67 and ∼0.95 are used in this parametric study containing 15 unique combinations of these parameters. Qualitative results are examined through a time series of density plots for multiple combinations of these parameters, and the qualitative effects of each of the parameters are discussed. Pressure, density, and vorticity fields are presented in animations available online to supplement the discussion of the qualitative results. These density plots show the evolution of two main regions in the flow field: a mixing region containing driver and test gas that is dominated by large vortical structures, and a more homogeneous region of unmixed fluid which can separate away from the mixing region in some cases. The interface mixing width is determined for various combinations of the parameters listed at the beginning of the Abstract. A scaling method for the mixing width is proposed using the interface geometry and wave velocities calculated using one-dimensional gas dynamic equations. This model uses the transmitted wave velocity for the characteristic velocity and an initial offset time based on the travel time of strong reflected waves. It is compared to an adapted Richtmyer impulsive model scaling and shown to scale the initial mixing width growth rate more effectively for fixed Atwood number.

Tunable thin-film optical filters for hyperspectral microscopy

NASA Astrophysics Data System (ADS)

Favreau, Peter F.; Rich, Thomas C.; Prabhat, Prashant; Leavesley, Silas J.

2013-02-01

Hyperspectral imaging was originally developed for use in remote sensing applications. More recently, it has been applied to biological imaging systems, such as fluorescence microscopes. The ability to distinguish molecules based on spectral differences has been especially advantageous for identifying fluorophores in highly autofluorescent tissues. A key component of hyperspectral imaging systems is wavelength filtering. Each filtering technology used for hyperspectral imaging has corresponding advantages and disadvantages. Recently, a new optical filtering technology has been developed that uses multi-layered thin-film optical filters that can be rotated, with respect to incident light, to control the center wavelength of the pass-band. Compared to the majority of tunable filter technologies, these filters have superior optical performance including greater than 90% transmission, steep spectral edges and high out-of-band blocking. Hence, tunable thin-film optical filters present optical characteristics that may make them well-suited for many biological spectral imaging applications. An array of tunable thin-film filters was implemented on an inverted fluorescence microscope (TE 2000, Nikon Instruments) to cover the full visible wavelength range. Images of a previously published model, GFP-expressing endothelial cells in the lung, were acquired using a charge-coupled device camera (Rolera EM-C2, Q-Imaging). This model sample presents fluorescently-labeled cells in a highly autofluorescent environment. Linear unmixing of hyperspectral images indicates that thin-film tunable filters provide equivalent spectral discrimination to our previous acousto-optic tunable filter-based approach, with increased signal-to-noise characteristics. Hence, tunable multi-layered thin film optical filters may provide greatly improved spectral filtering characteristics and therefore enable wider acceptance of hyperspectral widefield microscopy.

Hyperspectral processing in graphical processing units

NASA Astrophysics Data System (ADS)

Winter, Michael E.; Winter, Edwin M.

2011-06-01

With the advent of the commercial 3D video card in the mid 1990s, we have seen an order of magnitude performance increase with each generation of new video cards. While these cards were designed primarily for visualization and video games, it became apparent after a short while that they could be used for scientific purposes. These Graphical Processing Units (GPUs) are rapidly being incorporated into data processing tasks usually reserved for general purpose computers. It has been found that many image processing problems scale well to modern GPU systems. We have implemented four popular hyperspectral processing algorithms (N-FINDR, linear unmixing, Principal Components, and the RX anomaly detection algorithm). These algorithms show an across the board speedup of at least a factor of 10, with some special cases showing extreme speedups of a hundred times or more.

Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

NASA Astrophysics Data System (ADS)

Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing

2016-10-01

Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.

Spectrally Resolved Fiber Photometry for Multi-component Analysis of Brain Circuits.

PubMed

Meng, Chengbo; Zhou, Jingheng; Papaneri, Amy; Peddada, Teja; Xu, Karen; Cui, Guohong

2018-04-25

To achieve simultaneous measurement of multiple cellular events in molecularly defined groups of neurons in vivo, we designed a spectrometer-based fiber photometry system that allows for spectral unmixing of multiple fluorescence signals recorded from deep brain structures in behaving animals. Using green and red Ca 2+ indicators differentially expressed in striatal direct- and indirect-pathway neurons, we were able to simultaneously monitor the neural activity in these two pathways in freely moving animals. We found that the activities were highly synchronized between the direct and indirect pathways within one hemisphere and were desynchronized between the two hemispheres. We further analyzed the relationship between the movement patterns and the magnitude of activation in direct- and indirect-pathway neurons and found that the striatal direct and indirect pathways coordinately control the dynamics and fate of movement. Published by Elsevier Inc.

Quantitative analysis of the local phase transitions induced by the laser heating

DOE PAGES

Levlev, Anton V.; Susner, Michael A.; McGuire, Michael A.; ...

2015-11-04

Functional imaging enabled by scanning probe microscopy (SPM) allows investigations of nanoscale material properties under a wide range of external conditions, including temperature. However, a number of shortcomings preclude the use of the most common material heating techniques, thereby limiting precise temperature measurements. Here we discuss an approach to local laser heating on the micron scale and its applicability for SPM. We applied local heating coupled with piezoresponse force microscopy and confocal Raman spectroscopy for nanoscale investigations of a ferroelectric-paraelectric phase transition in the copper indium thiophosphate layered ferroelectric. Bayesian linear unmixing applied to experimental results allowed extraction of themore » Raman spectra of different material phases and enabled temperature calibration in the heated region. Lastly, the obtained results enable a systematic approach for studying temperature-dependent material functionalities in heretofore unavailable temperature regimes.« less

Evaluating the effect of spatial subsetting on subpixel unmixing methodology applied to ASTER over a hydrothermally altered terrain

NASA Astrophysics Data System (ADS)

Ayoobi, Iman; Tangestani, Majid H.

2017-10-01

This study investigates the effect of spatial subsets of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) L1B visible-near infrared and short wave-infrared (VNIR-SWIR) data on matched filtering results at the central part of Kerman magmatic arc, where abundant porphyry copper deposits exist. The matched filtering (MF) procedure was run separately at sites containing hydrothermal minerals such as sericite, kaolinite, chlorite, and jarosite to map the abundances of these minerals on spatial subsets containing 100, 75, 50, and 25 percent of the original scene. Results were evaluated by comparing the matched filtering scores with the mineral abundances obtained by semi-quantitative XRD analysis of corresponding field samples. It was concluded that MF method should be applied to the whole scene prior to any data subsetting.

Demonstration of FRET in solutions

NASA Astrophysics Data System (ADS)

Shah, Sunil; Gryczynski, Zygmunt; Chib, Rahul; Fudala, Rafal; Baxi, Aatmun; Borejdo, Julian; Synak, Anna; Gryczynski, Ignacy

2016-03-01

We measured the Förster resonance energy transfer (FRET) from Uranin (U) donor to Rhodamine 101 (R101) acceptor in propylene glycol. Steady-state fluorescence measurements show a significant difference between mixed and unmixed fluorophore solutions. In the solution with mixed fluorophores, fluorescence intensity of the U donor decreases and intensity of R101 fluorescence increases. This is visualized as a color change from green to orange. Fluorescence anisotropy of the mixture solution increases in the donor emission wavelength region and decreases in the acceptor emission wavelengths; which is consistent with FRET occurrence. Time-resolved (lifetime) measurements show a decrease of the U lifetime in the presence of R101 acceptor. In the intensity decay of R101 acceptor appears a negative component indicating excited state process. All these measurements prove the presence of FRET in U/R101 mixture fluorescence.

Search for neutral D meson mixing using semileptonic decays

NASA Astrophysics Data System (ADS)

Flood, Kevin T.

Based on a 87 fb-1 dataset, a search for D0-D¯0 mixing is made using the semileptonic decay modes D*+ → pi +D0, D0 → [K/K*]enu (+c.c.) at the B-Factory facility at the Stanford Linear Accelerator Center. These modes offer unambiguous initial and final-state charm flavor tags, and allow the combined use of the D0 lifetime and D*+- D0 mass difference (DeltaM) in a global likelihood fit. The high-statistics sample of reconstructed unmixed semileptonic D0 decays is used to model both the DeltaM distribution and the time-dependence of mixed events directly from the data. Neural networks are used both to select events and to fully reconstruct the D0. A result consistent with no charm mixing has been obtained, Rmix = 0.0023 +/- 0.0012(stat) +/- 0.0004(sys ). This corresponds to an upper limit of Rmix < 0.0047 (95% C.L.) and Rmix < 0.0043 (90% C.L.). The lowest current published limit on semileptonic charm mixing is 0.005 (90% C.L.) (E791, E.M. Aitala et al., Phys.Rev.Lett. 77 2384 (1996)). The current best published limit using any analysis technique on the total rate of charm mixing is 0.0016 (95% C.L.) (Babar Kpi mixing, B. Aubert et al., Phys.Rev.Lett. 91 171801 (2003)).

Excitation-scanning hyperspectral imaging as a means to discriminate various tissues types

NASA Astrophysics Data System (ADS)

Deal, Joshua; Favreau, Peter F.; Lopez, Carmen; Lall, Malvika; Weber, David S.; Rich, Thomas C.; Leavesley, Silas J.

2017-02-01

Little is currently known about the fluorescence excitation spectra of disparate tissues and how these spectra change with pathological state. Current imaging diagnostic techniques have limited capacity to investigate fluorescence excitation spectral characteristics. This study utilized excitation-scanning hyperspectral imaging to perform a comprehensive assessment of fluorescence spectral signatures of various tissues. Immediately following tissue harvest, a custom inverted microscope (TE-2000, Nikon Instruments) with Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) were used to acquire hyperspectral image data from each sample. Scans utilized excitation wavelengths from 340 nm to 550 nm in 5 nm increments. Hyperspectral images were analyzed with custom Matlab scripts including linear spectral unmixing (LSU), principal component analysis (PCA), and Gaussian mixture modeling (GMM). Spectra were examined for potential characteristic features such as consistent intensity peaks at specific wavelengths or intensity ratios among significant wavelengths. The resultant spectral features were conserved among tissues of similar molecular composition. Additionally, excitation spectra appear to be a mixture of pure endmembers with commonalities across tissues of varied molecular composition, potentially identifiable through GMM. These results suggest the presence of common autofluorescent molecules in most tissues and that excitationscanning hyperspectral imaging may serve as an approach for characterizing tissue composition as well as pathologic state. Future work will test the feasibility of excitation-scanning hyperspectral imaging as a contrast mode for discriminating normal and pathological tissues.

Evolution of Dust in Primordial Supernova Remnants and Its Influence on the Elemental Composition of Hyper-Metal-Poor Stars

NASA Astrophysics Data System (ADS)

Nozawa, Takaya; Kozasa, Takashi; Habe, Asao; Dwek, Eli; Umeda, Hideyuki; Tominaga, Nozomu; Maeda, Keiichi; Nomoto, Ken'ichi

2008-05-01

The calculations for the evolution of dust within Population III supernova remnants (SNRs) are presented, based on the models of dust formed in the unmixed ejecta of Type II SNe. We show that once dust grains collide with the reverse shock penetrating into the ejecta, their fates strongly depend on the initial radius aini. For SNRs expanding into the interstellar medium (ISM) with nH,0 = 1 cm-3, grains of aini<0.05 μm are trapped in the hot gas to be completely destroyed; grains of aini = 0.05-0.2 μm are piled up in the dense shell formed behind the forward shock; grains of aini>0.2 μm are injected into the ISM without being eroded significantly. The total mass of surviving dust is 0.01 to 0.8 Msolar for nH,0 = 10 to 0.1 cm-3. We also investigate the influence of the piled-up dust on the elemental abundances of the second-generation stars formed in the dense shell of Population III SNRs. The comparison of the calculated elemental abundances with those observed in hyper-metal-poor (HMP) and ultra-metal-poor (UMP) stars indicates that the transport of dust separated from metal-rich gas can be an important process in determining the abundance patterns of Mg and Si in HMP and UMP stars.

Remote Sensing of Climate-Driven Range Shifts of Vegetation across North American Mountain Ranges

NASA Astrophysics Data System (ADS)

Kendrick, J. A.; Sax, D. F.; Kellner, J. R.

2015-12-01

Global climate change is driving shifts in local environmental conditions, and many organisms are projected to become poorly adapted to their current ranges. Some species may respond by gradually shifting their range limits to track environmental change. This adaptation strategy is expected to be most feasible in regions with sharp climatic gradients, such as mountain ranges. However, the extent to which this process is taking place is poorly understood, and some evidence suggests that shifts upwards in elevation might be more difficult than expected. Direct empirical evidence of range shifts in response to recent climate change could inform models and conservation strategies. Here we used Monte Carlo spectral unmixing of Landsat surface reflectance data to characterize changes in vegetation cover across major North American mountain ranges over the past 30 years. This approach allows us to observe changes in photosynthetic and nonphotosynthetic vegetation as well as absolute change in vegetation cover. We found evidence of a gradual increase in total vegetation cover at increasing elevations, but this pattern varied in its strength both within and among mountain ranges. We also observed more dramatic changes in vegetation type which differed strongly between regions with different climates. Our analysis shows that upslope range shift is a possible climate response in many cases, but that this process does not occur uniformly.

Assessment of tissue oxygenation of periodontal inflammation in smokers using optical spectroscopy.

PubMed

Liu, Kan-Zhi; Duarte, Poliana Mendes; Santos, Vanessa Renata; Xiang, Xiaoming; Xu, Minqi; Miranda, Tamires Szeremeske; Fermiano, Daiane; Gonçalves, Tiago Eduardo Dias; Sowa, Micheal G

2014-04-01

We have recently developed a periodontal diagnostic tool that was validated in non-smokers with periodontitis. Tobacco smoking is a recognized risk factor for periodontal diseases that can mask gingival bleeding and lead to a false negative diagnosis. Therefore, the purpose of current study is to further validate this instrument in smokers with periodontal diseases. Using a portable optical near-infrared spectrometer, optical spectra were obtained, processed and evaluated from healthy (n = 108), gingivitis (n = 100), and periodontitis (n = 79) sites of 54 systemically healthy smokers. A modified Beer-Lambert unmixing model that incorporates a non-parametric scattering loss function was used to determine the relative contribution of deoxygenated haemoglobin (Hb) and oxygenated haemoglobin (HbO2 ) to the overall spectrum. The balance between tissue oxygen delivery and utilization in periodontal tissues was then assessed. Tissue oxygen saturation was significantly decreased in the gingivitis (p = 0.016) and periodontitis (p = 0.007) sites, compared to the healthy sites. There was a trend towards increased concentration of Hb and decreased concentration of HbO2 from healthy to diseased sites, without statistical significance (p > 0.05). Optical spectroscopy can determine tissue oxygenation profiles of healthy and diseased sites in smokers. The spectral profile of periodontal sites in smokers generally resembles those from non-smoking patients. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Design and operation of an anaerobic digester for waste management and fuel generation during long term lunar mission

NASA Astrophysics Data System (ADS)

Dhoble, Abhishek S.; Pullammanappallil, Pratap C.

2014-10-01

Waste treatment and management for manned long term exploratory missions to moon will be a challenge due to longer mission duration. The present study investigated appropriate digester technologies that could be used on the base. The effect of stirring, operation temperature, organic loading rate and reactor design on the methane production rate and methane yield was studied. For the same duration of digestion, the unmixed digester produced 20-50% more methane than mixed system. Two-stage design which separated the soluble components from the solids and treated them separately had more rapid kinetics than one stage system, producing the target methane potential in one-half the retention time than the one stage system. The two stage system degraded 6% more solids than the single stage system. The two stage design formed the basis of a prototype digester sized for a four-person crew during one year exploratory lunar mission.

Nanohole-array-based device for 2D snapshot multispectral imaging

PubMed Central

Najiminaini, Mohamadreza; Vasefi, Fartash; Kaminska, Bozena; Carson, Jeffrey J. L.

2013-01-01

We present a two-dimensional (2D) snapshot multispectral imager that utilizes the optical transmission characteristics of nanohole arrays (NHAs) in a gold film to resolve a mixture of input colors into multiple spectral bands. The multispectral device consists of blocks of NHAs, wherein each NHA has a unique periodicity that results in transmission resonances and minima in the visible and near-infrared regions. The multispectral device was illuminated over a wide spectral range, and the transmission was spectrally unmixed using a least-squares estimation algorithm. A NHA-based multispectral imaging system was built and tested in both reflection and transmission modes. The NHA-based multispectral imager was capable of extracting 2D multispectral images representative of four independent bands within the spectral range of 662 nm to 832 nm for a variety of targets. The multispectral device can potentially be integrated into a variety of imaging sensor systems. PMID:24005065

A Framework of Hyperspectral Image Compression using Neural Networks

DOE PAGES

Masalmah, Yahya M.; Martínez Nieves, Christian; Rivera Soto, Rafael; ...

2015-01-01

Hyperspectral image analysis has gained great attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows usmore » to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. Lastly, this paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.« less

Multispectral Live-Cell Imaging.

PubMed

Cohen, Sarah; Valm, Alex M; Lippincott-Schwartz, Jennifer

2018-06-01

Fluorescent proteins and vital dyes are invaluable tools for studying dynamic processes within living cells. However, the ability to distinguish more than a few different fluorescent reporters in a single sample is limited by the spectral overlap of available fluorophores. Here, we present a protocol for imaging live cells labeled with six fluorophores simultaneously. A confocal microscope with a spectral detector is used to acquire images, and linear unmixing algorithms are applied to identify the fluorophores present in each pixel of the image. We describe the application of this method to visualize the dynamics of six different organelles, and to quantify the contacts between organelles. However, this method can be used to image any molecule amenable to tagging with a fluorescent probe. Thus, multispectral live-cell imaging is a powerful tool for systems-level analysis of cellular organization and dynamics. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

NASA Redox Project status summary

NASA Technical Reports Server (NTRS)

Hagedorn, N. H.

1983-01-01

This report is a summary of the results of the Redox Project effort during Cy 1982. It was presented at the Fifth U.S. Department of Energy Battery and Electrochemical Contractors Conference, Arlington, Va., Dec. 7-9, 1982. The major development during 1982 was the shift from Redox system operation at 25 C with unmixed reactants to operation at 65 C with mixed reactants. This change has made possible a two- or three-fold increase in operating current density, to about 65 mA/sq cm, and an increase in reactant utilization from 40% to about 90%. Both of these improvements will lead to significant system cost reductions. Contract studies have indicated that Redox reactant costs also will be moderate. A new catalyst for the chromuim electrode offers all the advantages of the conventional gold-lead catalyst while being easier to apply and more forgiving in use.

Co-design in synthetic biology: a system-level analysis of the development of an environmental sensing device.

PubMed

Ball, David A; Lux, Matthew W; Graef, Russell R; Peterson, Matthew W; Valenti, Jane D; Dileo, John; Peccoud, Jean

2010-01-01

The concept of co-design is common in engineering, where it is necessary, for example, to determine the optimal partitioning between hardware and software of the implementation of a system features. Here we propose to adapt co-design methodologies for synthetic biology. As a test case, we have designed an environmental sensing device that detects the presence of three chemicals, and returns an output only if at least two of the three chemicals are present. We show that the logical operations can be implemented in three different design domains: (1) the transcriptional domain using synthetically designed hybrid promoters, (2) the protein domain using bi-molecular fluorescence complementation, and (3) the fluorescence domain using spectral unmixing and relying on electronic processing. We discuss how these heterogeneous design strategies could be formalized to develop co-design algorithms capable of identifying optimal designs meeting user specifications.

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.

Spectrally resolved visualization of fluorescent dyes permeating into skin

NASA Astrophysics Data System (ADS)

Maeder, Ulf; Bergmann, Thorsten; Beer, Sebastian; Burg, Jan Michael; Schmidts, Thomas; Runkel, Frank; Fiebich, Martin

2012-03-01

We present a spectrally resolved confocal imaging approach to qualitatively asses the overall uptake and the penetration depth of fluorescent dyes into biological tissue. We use a confocal microscope with a spectral resolution of 5 nm to measure porcine skin tissue after performing a Franz-Diffusion experiment with a submicron emulsion enriched with the fluorescent dye Nile Red. The evaluation uses linear unmixing of the dye and the tissue autofluorescence spectra. The results are combined with a manual segmentation of the skin's epidermis and dermis layers to assess the penetration behavior additionally to the overall uptake. The diffusion experiments, performed for 3h and 24h, show a 3-fold increased dye uptake in the epidermis and dermis for the 24h samples. As the method is based on spectral information it does not face the problem of superimposed dye and tissue spectra and therefore is more precise compared to intensity based evaluation methods.

Resolving Mixed Algal Species in Hyperspectral Images

PubMed Central

Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

2014-01-01

We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

Non-invasive detection of superimposed latent fingerprints and inter-ridge trace evidence by infrared spectroscopic imaging.

PubMed

Bhargava, Rohit; Perlman, Rebecca Schwartz; Fernandez, Daniel C; Levin, Ira W; Bartick, Edward G

2009-08-01

Current latent print and trace evidence collecting technologies are usually invasive and can be destructive to the original deposits. We describe a non-invasive vibrational spectroscopic approach that yields latent fingerprints that are overlaid on top of one another or that may contain trace evidence that needs to be distinguished from the print. Because of the variation in the chemical composition distribution within the fingerprint, we demonstrate that linear unmixing applied to the spectral content of the data can be used to provide images that reveal superimposed fingerprints. In addition, we demonstrate that the chemical composition of the trace evidence located in the region of the print can potentially be identified by its infrared spectrum. Thus, trace evidence found at a crime scene that previously could not be directly related to an individual, now has the potential to be directly related by its presence in the individual-identifying fingerprints.

LRRTM1 underlies synaptic convergence in visual thalamus

PubMed Central

Monavarfeshani, Aboozar; Stanton, Gail; Van Name, Jonathan; Su, Kaiwen; Mills, William A; Swilling, Kenya; Kerr, Alicia; Huebschman, Natalie A; Su, Jianmin

2018-01-01

It has long been thought that the mammalian visual system is organized into parallel pathways, with incoming visual signals being parsed in the retina based on feature (e.g. color, contrast and motion) and then transmitted to the brain in unmixed, feature-specific channels. To faithfully convey feature-specific information from retina to cortex, thalamic relay cells must receive inputs from only a small number of functionally similar retinal ganglion cells. However, recent studies challenged this by revealing substantial levels of retinal convergence onto relay cells. Here, we sought to identify mechanisms responsible for the assembly of such convergence. Using an unbiased transcriptomics approach and targeted mutant mice, we discovered a critical role for the synaptic adhesion molecule Leucine Rich Repeat Transmembrane Neuronal 1 (LRRTM1) in the emergence of retinothalamic convergence. Importantly, LRRTM1 mutant mice display impairment in visual behaviors, suggesting a functional role of retinothalamic convergence in vision. PMID:29424692

[Study of Cervical Exfoliated Cell's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology].

PubMed

Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui

2016-02-01

The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.

Mix or un-mix? Trace element segregation from a heterogeneous mantle, simulated.

NASA Astrophysics Data System (ADS)

Katz, R. F.; Keller, T.; Warren, J. M.; Manley, G.

2016-12-01

Incompatible trace-element concentrations vary in mid-ocean ridge lavas and melt inclusions by an order of magnitude or more, even in samples from the same location. This variability has been attributed to channelised melt flow [Spiegelman & Kelemen, 2003], which brings enriched, low-degree melts to the surface in relative isolation from depleted inter-channel melts. We re-examine this hypothesis using a new melting-column model that incorporates mantle volatiles [Keller & Katz 2016]. Volatiles cause a deeper onset of channelisation: their corrosivity is maximum at the base of the silicate melting regime. We consider how source heterogeneity and melt transport shape trace-element concentrations in basaltic lavas. We use both equilibrium and non-equilibrium formulations [Spiegelman 1996]. In particular, we evaluate the effect of melt transport on probability distributions of trace element concentration, comparing the inflow distribution in the mantle with the outflow distribution in the magma. Which features of melt transport preserve, erase or overprint input correlations between elements? To address this we consider various hypotheses about mantle heterogeneity, allowing for spatial structure in major components, volatiles and trace elements. Of interest are the roles of wavelength, amplitude, and correlation of heterogeneity fields. To investigate how different modes of melt transport affect input distributions, we compare melting models that produce either shallow or deep channelisation, or none at all.References:Keller & Katz (2016). The Role of Volatiles in Reactive Melt Transport in the Asthenosphere. Journal of Petrology, http://doi.org/10.1093/petrology/egw030. Spiegelman (1996). Geochemical consequences of melt transport in 2-D: The sensitivity of trace elements to mantle dynamics. Earth and Planetary Science Letters, 139, 115-132. Spiegelman & Kelemen (2003). Extreme chemical variability as a consequence of channelized melt transport. Geochemistry Geophysics Geosystems, http://doi.org/10.1029/2002GC000336

Confined combustion of TNT explosion products in air

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

Chandler, J; Ferguson, R E; Forbes, J

1998-08-31

Effects of turbulent combustion induced by explosion of a 0.8 kg cylindrical charge of TNT in a 17 m 3 chamber filled with air, are investigated. The detonation wave in the charge transforms the solid explosive (C 7H 5N 3O 6) to gaseous products, rich (~20% each) in carbon dust and carbon monoxide. The detonation pressure (~210 kb) thereby engendered causes the products to expand rapidly, driving a blast wave into the surrounding air. The interface between the products and air, being essentially unstable as a consequence of strong acceleration to which it is subjected within the blast wave, evolvesmore » into a turbulent mixing layer-a process enhanced by shock reflections from the walls. Under such circumstances rapid combustion takes place where the expanded detonation products play the role of fuel. Its dynamic effect is manifested by the experimental measurement of ~3 bar pressure increase in the chamber, in contrast to ~1bar attained by a corresponding TNT explosion in nitrogen. The experiments were modeled as a turbulent combustion in an unmixed system at infinite Reynolds, Peclet and DamkGhler numbers. The CFD solution was obtained by a high-order Godunov scheme using an AMR (Adaptive Mesh Refinement) to trace the turbulent mixing on the computational grid in as much detail as possible. The evolution of the mass fraction of fuel consumed by combustion thus determined exhibited the properties of an exponential decay following a sharp initiation. The results reveal all the dynamic features of the exothermic process of combustion controlled by fluid mechanic transport in a highly turbulent field, in contrast to those elucidated by the conventional reaction-diffusion model.« less

Behavior of the main sources that contribute to ambient PM2.5 in Santiago since 1998

NASA Astrophysics Data System (ADS)

Barraza, F.; Lambert, F.; Jorquera, H.; Villalobos, A. M.; Gallardo, L.

2016-12-01

Santiago's inhabitants have been exposed to high concentrations of fine particle matter (PM2.5) for decades. To contribute to a solution for this long-standing problem it is necessary to clearly identify and quantify the agents that contribute to ambient levels of PM2.5. We present an analysis of a long historical elemental concentrations database measured in air filter particles taken in central Santiago from April 1998 to August 2012 (1243 daily samples). We identify and quantify the main sources that contribute to PM2.5 levels using the source-receptor models PMF 5.0 and UNMIX 6.0. . The 6 main sources that contribute to outdoor PM2.5 levels were: vehicles (13.26±0.42 µg/m3), industrial sulfates (6.60±0.0.47 µg/m3), copper smelters (5.12±0.29 µg/m3), residential wood burning (4.38±0.36 µg/m3), marine aerosols (3.39±0.24 µg/m3), and urban dust (1.07±0.42 µg/m3). The unexplained fraction amounts to 1.76±0.90 µg/m3). The similar results obtained with both receptor models suggest a robust estimation of the main Santiago PM2.5 source apportionment. The analysis of the time series of these sources shows that their absolute contribution to PM2.5 levels has been decreasing during the last decade (except for urban dust which is increasing), and shows the effectiveness of government emission reduction policies. However, these improvements have not been sufficient to reduce PM2.5 concentrations to daily levels below the Chilean standard of 50 µg/m3, let alone the WHO standard of 25 µg/m3.

Time-averaged fluxes of lead and fallout radionuclides to sediments in Florida Bay

USGS Publications Warehouse

Robbins, J.A.; Holmes, C.; Halley, R.; Bothner, Michael H.; Shinn, E.; Graney, J.; Keeler, G.; TenBrink, M.; Orlandini, K.A.; Rudnick, D.

2000-01-01

Recent, unmixed sediments from mud banks of central Florida Bay were dated using 210Pb/226Ra, and chronologies were verified by comparing sediment lead temporal records with Pb/Ca ratios in annual layers of coral (Montastrea annularis) located on the ocean side of the Florida Keys. Dates of sediment lead peaks (1978±2) accord with prior observations of a 6 year lag between the occurrence of maximum atmospheric lead in 1972 and peak coral lead in 1978. Smaller lags of 1–2 years occur between the maximum atmospheric radionuclide fallout and peaks in sediment temporal records of 137Cs and Pu. Such lags are consequences of system time averaging (STA) in which atmospherically delivered particle-associated constituents accumulate and mix in a (sedimentary?) reservoir before transferring to permanent sediments and coral. STA model calculations, using time-dependent atmospheric inputs, produced optimized profiles in excellent accord with measured sediment 137Cs, Pu, lead, and coral lead distributions. Derived residence times of these particle tracers (16±1, 15.7±0.7, 19±3, and 16±2 years, respectively) are comparable despite differences in sampling locations, in accumulating media, and in element loading histories and geochemical properties. For a 16 year weighted mean residence time, STA generates the observed 6 year lead peak lag. Evidently, significant levels of nondegradable, particle-associated contaminants can persist in Florida Bay for many decades following elimination of external inputs. Present results, in combination with STA model analysis of previously reported radionuclide profiles, suggest that decade-scale time averaging may occur widely in recent coastal marine sedimentary environments.

Comparative analysis of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and Hyperspectral Thermal Emission Spectrometer (HyTES) longwave infrared (LWIR) hyperspectral data for geologic mapping

NASA Astrophysics Data System (ADS)

Kruse, Fred A.

2015-05-01

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and spatially coincident Hyperspectral Thermal Emission Spectrometer (HyTES) data were used to map geology and alteration for a site in northern Death Valley, California and Nevada, USA. AVIRIS, with 224 bands at 10 nm spectral resolution over the range 0.4 - 2.5 μm at 3-meter spatial resolution were converted to reflectance using an atmospheric model. HyTES data with 256 bands at approximately 17 nm spectral resolution covering the 8 - 12 μm range at 4-meter spatial resolution were converted to emissivity using a longwave infrared (LWIR) radiative transfer atmospheric compensation model and a normalized temperature-emissivity separation approach. Key spectral endmembers were separately extracted for each wavelength region and identified, and the predominant material at each pixel was mapped for each range using Mixture-Tuned-Matched Filtering (MTMF), a partial unmixing approach. AVIRIS mapped iron oxides, clays, mica, and silicification (hydrothermal alteration); and the difference between calcite and dolomite. HyTES separated and mapped several igneous phases (not possible using AVIRIS), silicification, and validated separation of calcite from dolomite. Comparison of the material maps from the different modes, however, reveals complex overlap, indicating that multiple materials/processes exist in many areas. Combined and integrated analyses were performed to compare individual results and more completely characterize occurrences of multiple materials. Three approaches were used 1) integrated full-range analysis, 2) combined multimode classification, and 3) directed combined analysis in geologic context. Results illustrate that together, these two datasets provide an improved picture of the distribution of geologic units and subsequent alteration.

Using lidar and effective LAI data to evaluate IKONOS and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest

USGS Publications Warehouse

Chen, X.; Vierling, Lee; Rowell, E.; DeFelice, Tom

2004-01-01

Structural and functional analyses of ecosystems benefit when high accuracy vegetation coverages can be derived over large areas. In this study, we utilize IKONOS, Landsat 7 ETM+, and airborne scanning light detection and ranging (lidar) to quantify coniferous forest and understory grass coverages in a ponderosa pine (Pinus ponderosa) dominated ecosystem in the Black Hills of South Dakota. Linear spectral mixture analyses of IKONOS and ETM+ data were used to isolate spectral endmembers (bare soil, understory grass, and tree/shade) and calculate their subpixel fractional coverages. We then compared these endmember cover estimates to similar cover estimates derived from lidar data and field measures. The IKONOS-derived tree/shade fraction was significantly correlated with the field-measured canopy effective leaf area index (LAIe) (r2=0.55, p<0.001) and with the lidar-derived estimate of tree occurrence (r2=0.79, p<0.001). The enhanced vegetation index (EVI) calculated from IKONOS imagery showed a negative correlation with the field measured tree canopy effective LAI and lidar tree cover response (r2=0.30, r=−0.55 and r2=0.41, r=−0.64, respectively; p<0.001) and further analyses indicate a strong linear relationship between EVI and the IKONOS-derived grass fraction (r2=0.99, p<0.001). We also found that using EVI resulted in better agreement with the subpixel vegetation fractions in this ecosystem than using normalized difference of vegetation index (NDVI). Coarsening the IKONOS data to 30 m resolution imagery revealed a stronger relationship with lidar tree measures (r2=0.77, p<0.001) than at 4 m resolution (r2=0.58, p<0.001). Unmixed tree/shade fractions derived from 30 m resolution ETM+ imagery also showed a significant correlation with the lidar data (r2=0.66, p<0.001). These results demonstrate the power of using high resolution lidar data to validate spectral unmixing results of satellite imagery, and indicate that IKONOS data and Landsat 7 ETM+ data both can serve to make the important distinction between tree/shade coverage and exposed understory grass coverage during peak summertime greenness in a ponderosa pine forest ecosystem.

Effect of animal mixing as a stressor on biomarkers of autophagy and oxidative stress during pig muscle maturation.

PubMed

Rubio-González, A; Potes, Y; Illán-Rodríguez, D; Vega-Naredo, I; Sierra, V; Caballero, B; Fàbrega, E; Velarde, A; Dalmau, A; Oliván, M; Coto-Montes, A

2015-07-01

The objective of this work was to study the postmortem evolution of potential biomarkers of autophagy (Beclin 1, LC3-II/LC3-I ratio) and oxidative stress (total antioxidant activity, TAA; superoxide dismutase activity, SOD and catalase activity, CAT) in the Longissimus dorsi muscle of entire male ((Large White×Landrace)×Duroc) pigs subjected to different management treatments that may promote stress, such as mixing unfamiliar animals at the farm and/or during transport and lairage before slaughter. During the rearing period at the farm, five animals were never mixed after the initial formation of the experimental groups (unmixed group at the farm, UF), whereas 10 animals were subjected to a common routine of being mixed with unfamiliar animals (mixed group at the farm, MF). Furthermore, two different treatments were used during the transport and lairage before slaughter: 10 pigs were not mixed (unmixed group during transport and lairage, UTL), whereas five pigs were mixed with unfamiliar animals on the lorry and during lairage (mixed group during transport and lairage, MTL). These mixing treatments were then combined into three pre-slaughter treatments - namely, UF-UTL, MF-UTL and MF-MTL. The results show that MF-UTL and MF-MTL increased significantly the muscle antioxidant defense (TAA, SOD and CAT) at short postmortem times (4 and 8 h; P<0.001), followed by an earlier depletion of the antioxidant activity at 24 h postmortem (P<0.05). We also found that mixing unfamiliar animals, both at the farm and during transport and lairage, triggers postmortem muscle autophagy, which showed an earlier activation (higher expression of Beclin 1 and LC3-II/LC3-I ratio at 4 h postmortem followed by a decreasing pattern of this ratio along first 24 h postmortem) in the muscle tissues of animals from the MF-UTL and MF-MTL groups, as an adaptive strategy of the muscle cells for counteracting induced stress. From these results, we propose that monitoring the evolution of the main biomarkers of autophagy (Beclin 1, LC3-II/LC3-I ratio) and muscle antioxidant defense (TAA, SOD, CAT) in the muscle tissue within the first 24 h postmortem may help the detection of animal stress and its potential effect on the postmortem muscle metabolism.

Fast sparse Raman spectral unmixing for chemical fingerprinting and quantification

NASA Astrophysics Data System (ADS)

Yaghoobi, Mehrdad; Wu, Di; Clewes, Rhea J.; Davies, Mike E.

2016-10-01

Raman spectroscopy is a well-established spectroscopic method for the detection of condensed phase chemicals. It is based on scattered light from exposure of a target material to a narrowband laser beam. The information generated enables presumptive identification from measuring correlation with library spectra. Whilst this approach is successful in identification of chemical information of samples with one component, it is more difficult to apply to spectral mixtures. The capability of handling spectral mixtures is crucial for defence and security applications as hazardous materials may be present as mixtures due to the presence of degradation, interferents or precursors. A novel method for spectral unmixing is proposed here. Most modern decomposition techniques are based on the sparse decomposition of mixture and the application of extra constraints to preserve the sum of concentrations. These methods have often been proposed for passive spectroscopy, where spectral baseline correction is not required. Most successful methods are computationally expensive, e.g. convex optimisation and Bayesian approaches. We present a novel low complexity sparsity based method to decompose the spectra using a reference library of spectra. It can be implemented on a hand-held spectrometer in near to real-time. The algorithm is based on iteratively subtracting the contribution of selected spectra and updating the contribution of each spectrum. The core algorithm is called fast non-negative orthogonal matching pursuit, which has been proposed by the authors in the context of nonnegative sparse representations. The iteration terminates when the maximum number of expected chemicals has been found or the residual spectrum has a negligible energy, i.e. in the order of the noise level. A backtracking step removes the least contributing spectrum from the list of detected chemicals and reports it as an alternative component. This feature is particularly useful in detection of chemicals with small contributions, which are normally not detected. The proposed algorithm is easily reconfigurable to include new library entries and optional preferential threat searches in the presence of predetermined threat indicators. Under Ministry of Defence funding, we have demonstrated the algorithm for fingerprinting and rough quantification of the concentration of chemical mixtures using a set of reference spectral mixtures. In our experiments, the algorithm successfully managed to detect the chemicals with concentrations below 10 percent. The running time of the algorithm is in the order of one second, using a single core of a desktop computer.

Comparison of lithological mapping results from airborne hyperspectral VNIR-SWIR, LWIR and combined data

NASA Astrophysics Data System (ADS)

Feng, Jilu; Rogge, Derek; Rivard, Benoit

2018-02-01

This study investigates using the Airborne Hyperspectral Imaging Systems (AISA) visible and short-wave infrared (SWIR) and Spatially Enhanced Broadband Array Spectrograph System (SEBASS) longwave infrared (LWIR) (2 and 4 m spatial resolution, respectively) imagery independently and in combination to produce detailed lithologic maps in a subarctic region (Cape Smith Belt, Nunavik, Canada) where regionally metamorphosed lower greenschist mafic, ultramafic and sedimentary rocks are exposed in the presence of lichen coatings. We make use of continuous wavelet analysis (CWA) to improve the radiometric quality of the imagery through the minimization of random noise and the enhancement of spectral features, the minimization of residual errors in the ISAC radiometric correction and target temperature estimation in the case of the LWIR data, the minimization of line to line residual calibration effects that lead to inconsistencies in data mosaics, and the reduction in variability of the spectral continuum introduced by variable illumination and topography. The use of CWA also provides a platform to directly combine the wavelet scale spectral profiles of the SWIR and LWIR after applying a scalar correction factor to the LWIR such that the dynamic range of two data sets have equal weight. This is possible using CWA as the datasets are normalized to a zero mean allowing spectra from different spectral regions to be adjoined. Lithologic maps are generated using an iterative spectral unmixing approach with image spectral endmembers extracted from the SWIR and LWIR imagery based on locations defined from previous work of the study area and field mapping information. Unmixing results of the independent SWIR and LWIR data, and the combined data show clear benefits to using the CWA combined imagery. The analysis showed SWIR and LWIR imagery highlight similar regions and spatial distributions for the three ultramafic units (dunite, peridotite, pyroxenite). However, significant differences are observed for quartz-rich sediments, with the SWIR overestimating the distribution of these rocks whereas the LWIR provided more consistent results compared with existing maps. Both SWIR and LWIR imagery were impacted by the pervasive lichen coatings on the mafic rocks (basalts and gabbros), although the SWIR provided better results than the LWIR. Limitations observed for the independent data sets were removed using the combined spectral data resulting in all geologically meaningful units mapped correctly in comparison with existing geological maps.

Do Chemistry-Climate Models Project the Same Greenhouse Gas Chemistry if Initialized with Observations of the Trace Gases: A Pre-ATom Test

NASA Astrophysics Data System (ADS)

Flynn, C. M.; Prather, M. J.; Zhu, X.; Strode, S. A.; Steenrod, S. D.; Strahan, S. E.; Lamarque, J. F.; Fiore, A. M.; Horowitz, L. W.; Mao, J.; Murray, L. T.; Shindell, D. T.

2016-12-01

Experience with climate and chemistry model intercomparison projects (MIPs) has demonstrated a diversity in model projections for the chemical greenhouse gases CH4 and O3, even when forced by the same emissions. In general, the MIPs show that models diverge in the distribution of the many key trace species that control the reactivity of the troposphere (defined here as the loss of CH4 and the production and loss of O3). Two possible sources of model differences are the chemistry-transport coupling that creates the pattern of the essential precursor species, and the calculation of reactivity. Suppose that observations, such as those planned by NASA's Atmospheric Tomography (ATom) mission, provide us with enough of a chemical climatology to constrain the modeled distribution of the essential chemical species for the current epoch. Would the models calculate the same reactivity? ATom uses the DC-8 to make in situ measurements slicing through the middle of the Pacific and Atlantic Ocean basins each season and measuring the essential trace species. Unfortunately, ATom measurements will not be available until mid-2017. Here we take the baseline chemistry from one model version (as pseudo-observations) and use it to initialize 6 other global chemistry models. In this pre-ATom MIP, we take the full chemical composition for meridional slices centered on the Dateline (UC Irvine Chemistry-Transport Model, 0.6 deg resolution, 30 layers in the troposphere). We use grid cells between 0.5 and 12 km from 60 S to 60 N to initialize grid cells in the other six models (GEOS-Chem, GFDL-AM3, GISS ModelE2, GSFC GMI, NCAR, UCI CTM). The models are then integrated for 1 day and the key chemical rates (CH4, O3) are saved. These simulations assume that the initialized parcels remain unmixed over the 24 hours, and, hence, model-to-model variations will be due to differences in photochemistry, including clouds. In addition, we assess the relative importance of the precursor species by running sensitivity tests in which each of the major precursors (e.g., NOx, HOOH, HCHO, CO) is perturbed by 10%. Such sensitivity tests can help determine the causes of model differences. Overall, this new approach allows us to characterize each model's chemistry package for a wide range of designated chemical composition. The real test will be with ATom data next year.

Recent Changes in Tree Species Abundance: Patterns, Trends, and Drivers Across Northeastern US Forests

NASA Astrophysics Data System (ADS)

Gudex-Cross, D.; Pontius, J.; Adams, A.

2017-12-01

Monitoring trends in the abundance and distribution of tree species is essential to understanding potential impacts of climate change on forested ecosystems. Related studies to date have largely focused on modeling distributional shifts according to future climate scenarios or used field inventory data to examine compositional changes across broader landscapes. Here, we leverage a novel remote sensing technique that utilizes field data, multitemporal Landsat imagery, and spectral unmixing to model regional changes in the abundance (percent basal area) of key northeastern US species over a 30-year period (1985-2015). We examine patterns in how species abundance has changed, as well as their relationship with climate, landscape, and soil characteristics using spatial regression models. Results show significant declines in overall abundance for sugar maple ( 8.6% 30-yr loss), eastern hemlock ( 7.8% 30-yr loss), balsam fir ( 5.0% 30-yr loss), and red spruce ( 3.8% total 30-yr loss). Species that saw significant increasing abundance include American beech ( 7.0% 30-yr gain) and red maple ( 2.5% 30-yr gain). However, these changes were not consistent across the landscape. For example, red spruce is increasing at upper elevations with concurrent losses in balsam fir and birch species. Similarly, sugar maple decreases are concentrated at lower elevations, likely due to increases in American beech. Various abiotic factors were significantly associated with changes in species composition including landscape position (e.g. longitude, elevation, and heat load index) and ecologically-relevant climate variables (e.g. growing season precipitation and annual temperature range). Interestingly, there was a stronger relationship in abundance changes across longitudes, rather than latitudes or elevations as predicted in modeled species migration scenarios.These results indicate that the dominant composition of northeastern forests is changing in ways that run counter to accepted successional patterns and land use history effects. We hypothesize that climate change and other anthropogenic stress agents (e.g. acid deposition legacy) are likely altering the competitive relationships among co-occurring species, with potential implications for forest management and ecosystem modeling efforts.

Novel MixSIAR fingerprint model implementation in a Mediterranean mountain catchment

NASA Astrophysics Data System (ADS)

Lizaga, Ivan; Gaspar, Leticia; Blake, William; Palazón, Leticia; Quijano, Laura; Navas, Ana

2017-04-01

Increased sediment erosion levels can lead to degraded water and food quality, reduced aquatic biodiversity, decrease reservoir capacity and restrict recreational usage but determining soil redistribution and sediment budgets in watersheds is often challenging. One of the methods for making such determinations applies sediment fingerprinting methods by using sediment properties. The fingerprinting procedure tests a range of source material tracer properties to select a subset that can discriminate between the different potential sediment sources. The present study aims to test the feasibility of geochemical and radioisotopic fingerprint properties to apportion sediment sources within the Barués catchment. For this purpose, the new MixSIAR unmixing model was implemented as statistical tool. A total of 98 soil samples from different land cover sources (Mediterranean forest, pine forest scrubland, agricultural and subsoil) were collected in the Barués catchment (23 km2). This new approach divides the catchment into six different sub-catchments to evaluate how the sediment provenance varies along the river and the percentage of its sources and not only the contribution at the end. For this purpose, target sediments were collected at the end of each sub-catchment to introduce the variation along the entire catchment. Geochemistry and radioisotopic activity were analyzed for each sample and introduced as input parameters in the model. Percentage values from the five sources were different along the different subcatchments and the variations of all of them are summarized at the final target sample located at the end of the catchment. This work represents a good approximation to the fine sediment provenance in Mediterranean agricultural catchments and has the potential to be used for water resource control and future soil management. Identifying sediment contribution from different land uses offers considerable potential to prevent environmental degradation and the decrease in food production and quality.

Characterization and quantification of suspended sediment sources to the Manawatu River, New Zealand.

PubMed

Vale, S S; Fuller, I C; Procter, J N; Basher, L R; Smith, I E

2016-02-01

Knowledge of sediment movement throughout a catchment environment is essential due to its influence on the character and form of our landscape relating to agricultural productivity and ecological health. Sediment fingerprinting is a well-used tool for evaluating sediment sources within a fluvial catchment but still faces areas of uncertainty for applications to large catchments that have a complex arrangement of sources. Sediment fingerprinting was applied to the Manawatu River Catchment to differentiate 8 geological and geomorphological sources. The source categories were Mudstone, Hill Subsurface, Hill Surface, Channel Bank, Mountain Range, Gravel Terrace, Loess and Limestone. Geochemical analysis was conducted using XRF and LA-ICP-MS. Geochemical concentrations were analysed using Discriminant Function Analysis and sediment un-mixing models. Two mixing models were used in conjunction with GRG non-linear and Evolutionary optimization methods for comparison. Discriminant Function Analysis required 16 variables to correctly classify 92.6% of sediment sources. Geological explanations were achieved for some of the variables selected, although there is a need for mineralogical information to confirm causes for the geochemical signatures. Consistent source estimates were achieved between models with optimization techniques providing globally optimal solutions for sediment quantification. Sediment sources was attributed primarily to Mudstone, ≈38-46%; followed by the Mountain Range, ≈15-18%; Hill Surface, ≈12-16%; Hill Subsurface, ≈9-11%; Loess, ≈9-15%; Gravel Terrace, ≈0-4%; Channel Bank, ≈0-5%; and Limestone, ≈0%. Sediment source apportionment fits with the conceptual understanding of the catchment which has recognized soft sedimentary mudstone to be highly susceptible to erosion. Inference of the processes responsible for sediment generation can be made for processes where there is a clear relationship with the geomorphology, but is problematic for processes which occur within multiple terrains. Copyright © 2015 Elsevier B.V. All rights reserved.

Testing coherent reflection in chinchilla: Auditory-nerve responses predict stimulus-frequency emissions

PubMed Central

Shera, Christopher A.; Tubis, Arnold; Talmadge, Carrick L.

2008-01-01

Coherent-reflection theory explains the generation of stimulus-frequency and transient-evoked otoacoustic emissions by showing how they emerge from the coherent “backscattering” of forward-traveling waves by mechanical irregularities in the cochlear partition. Recent published measurements of stimulus-frequency otoacoustic emissions (SFOAEs) and estimates of near-threshold basilar-membrane (BM) responses derived from Wiener-kernel analysis of auditory-nerve responses allow for comprehensive tests of the theory in chinchilla. Model predictions are based on (1) an approximate analytic expression for the SFOAE signal in terms of the BM traveling wave and its complex wave number, (2) an inversion procedure that derives the wave number from BM traveling waves, and (3) estimates of BM traveling waves obtained from the Wiener-kernel data and local scaling assumptions. At frequencies above 4 kHz, predicted median SFOAE phase-gradient delays and the general shapes of SFOAE magnitude-versus-frequency curves are in excellent agreement with the measurements. At frequencies below 4 kHz, both the magnitude and the phase of chinchilla SFOAEs show strong evidence of interference between short- and long-latency components. Approximate unmixing of these components, and association of the long-latency component with the predicted SFOAE, yields close agreement throughout the cochlea. Possible candidates for the short-latency SFOAE component, including wave-fixed distortion, are considered. Both empirical and predicted delay ratios (long-latency SFOAE delay∕BM delay) are significantly less than 2 but greater than 1. Although these delay ratios contradict models in which SFOAE generators couple primarily into cochlear compression waves, they are consistent with the notion that forward and reverse energy propagation in the cochlea occurs predominantly by means of traveling pressure-difference waves. The compelling overall agreement between measured and predicted delays suggests that the coherent-reflection model captures the dominant mechanisms responsible for the generation of reflection-source otoacoustic emissions. PMID:18646984

Demystifying autofluorescence with excitation scanning hyperspectral imaging

NASA Astrophysics Data System (ADS)

Deal, Joshua; Harris, Bradley; Martin, Will; Lall, Malvika; Lopez, Carmen; Rider, Paul; Boudreaux, Carole; Rich, Thomas; Leavesley, Silas J.

2018-02-01

Autofluorescence has historically been considered a nuisance in medical imaging. Many endogenous fluorophores, specifically, collagen, elastin, NADH, and FAD, are found throughout the human body. Diagnostically, these signals can be prohibitive since they can outcompete signals introduced for diagnostic purposes. Recent advances in hyperspectral imaging have allowed the acquisition of significantly more data in a shorter time period by scanning the excitation spectra of fluorophores. The reduced acquisition time and increased signal-to-noise ratio allow for separation of significantly more fluorophores than previously possible. Here, we propose to utilize excitation-scanning of autofluorescence to examine tissues and diagnose pathologies. Spectra of autofluorescent molecules were obtained using a custom inverted microscope (TE-2000, Nikon Instruments) with a Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) Scans utilized excitation wavelengths from 360 nm to 550 nm in 5 nm increments. The resultant spectra were used to examine hyperspectral image stacks from various collaborative studies, including an atherosclerotic rat model and a colon cancer study. Hyperspectral images were analyzed with ENVI and custom Matlab scripts including linear spectral unmixing (LSU) and principal component analysis (PCA). Initial results suggest the ability to separate the signals of endogenous fluorophores and measure the relative concentrations of fluorophores among healthy and diseased states of similar tissues. These results suggest pathology-specific changes to endogenous fluorophores can be detected using excitationscanning hyperspectral imaging. Future work will expand the library of pure molecules and will examine more defined disease states.

Depth of Ultra High Energy Cosmic Ray Induced Air Shower Maxima Measured by the Telescope Array Black Rock and Long Ridge FADC Fluorescence Detectors and Surface Array in Hybrid Mode

NASA Astrophysics Data System (ADS)

Abbasi, R. U.; Abe, M.; Abu-Zayyad, T.; Allen, M.; Azuma, R.; Barcikowski, E.; Belz, J. W.; Bergman, D. R.; Blake, S. A.; Cady, R.; Cheon, B. G.; Chiba, J.; Chikawa, M.; di Matteo, A.; Fujii, T.; Fujita, K.; Fukushima, M.; Furlich, G.; Goto, T.; Hanlon, W.; Hayashi, M.; Hayashi, Y.; Hayashida, N.; Hibino, K.; Honda, K.; Ikeda, D.; Inoue, N.; Ishii, T.; Ishimori, R.; Ito, H.; Ivanov, D.; Jeong, H. M.; Jeong, S. M.; Jui, C. C. H.; Kadota, K.; Kakimoto, F.; Kalashev, O.; Kasahara, K.; Kawai, H.; Kawakami, S.; Kawana, S.; Kawata, K.; Kido, E.; Kim, H. B.; Kim, J. H.; Kim, J. H.; Kishigami, S.; Kitamura, S.; Kitamura, Y.; Kuzmin, V.; Kuznetsov, M.; Kwon, Y. J.; Lee, K. H.; Lubsandorzhiev, B.; Lundquist, J. P.; Machida, K.; Martens, K.; Matsuyama, T.; Matthews, J. N.; Mayta, R.; Minamino, M.; Mukai, K.; Myers, I.; Nagasawa, K.; Nagataki, S.; Nakamura, R.; Nakamura, T.; Nonaka, T.; Oda, H.; Ogio, S.; Ogura, J.; Ohnishi, M.; Ohoka, H.; Okuda, T.; Omura, Y.; Ono, M.; Onogi, R.; Oshima, A.; Ozawa, S.; Park, I. H.; Pshirkov, M. S.; Rodriguez, D. C.; Rubtsov, G.; Ryu, D.; Sagawa, H.; Sahara, R.; Saito, K.; Saito, Y.; Sakaki, N.; Sakurai, N.; Scott, L. M.; Seki, T.; Sekino, K.; Shah, P. D.; Shibata, F.; Shibata, T.; Shimodaira, H.; Shin, B. K.; Shin, H. S.; Smith, J. D.; Sokolsky, P.; Stokes, B. T.; Stratton, S. R.; Stroman, T. A.; Suzawa, T.; Takagi, Y.; Takahashi, Y.; Takamura, M.; Takeda, M.; Takeishi, R.; Taketa, A.; Takita, M.; Tameda, Y.; Tanaka, H.; Tanaka, K.; Tanaka, M.; Thomas, S. B.; Thomson, G. B.; Tinyakov, P.; Tkachev, I.; Tokuno, H.; Tomida, T.; Troitsky, S.; Tsunesada, Y.; Tsutsumi, K.; Uchihori, Y.; Udo, S.; Urban, F.; Wong, T.; Yamamoto, M.; Yamane, R.; Yamaoka, H.; Yamazaki, K.; Yang, J.; Yashiro, K.; Yoneda, Y.; Yoshida, S.; Yoshii, H.; Zhezher, Y.; Zundel, Z.; Telescope Array Collaboration

2018-05-01

The Telescope Array (TA) observatory utilizes fluorescence detectors and surface detectors (SDs) to observe air showers produced by ultra high energy cosmic rays in Earth’s atmosphere. Cosmic-ray events observed in this way are termed hybrid data. The depth of air shower maximum is related to the mass of the primary particle that generates the shower. This paper reports on shower maxima data collected over 8.5 yr using the Black Rock Mesa and Long Ridge fluorescence detectors in conjunction with the array of SDs. We compare the means and standard deviations of the observed {X}\\max distributions with Monte Carlo {X}\\max distributions of unmixed protons, helium, nitrogen, and iron, all generated using the QGSJet II-04 hadronic model. We also perform an unbinned maximum likelihood test of the observed data, which is subjected to variable systematic shifting of the data {X}\\max distributions to allow us to test the full distributions, and compare them to the Monte Carlo to see which elements are not compatible with the observed data. For all energy bins, QGSJet II-04 protons are found to be compatible with TA hybrid data at the 95% confidence level after some systematic {X}\\max shifting of the data. Three other QGSJet II-04 elements are found to be compatible using the same test procedure in an energy range limited to the highest energies where data statistics are sparse.

A study of the trace sulfide mineral assemblages in the Stillwater Complex, Montana, USA

NASA Astrophysics Data System (ADS)

Aird, Hannah M.; Ferguson, Katherine M.; Lehrer, Malia L.; Boudreau, Alan E.

2017-03-01

The sulfide assemblages of the Stillwater Complex away from the well-studied ore zones are composed mainly of variable proportions of pyrrhotite, chalcopyrite, pentlandite, and ±pyrite. Excluding vein assemblages and those affected by greenschist and lower temperature alteration, the majority can be classified into two broad assemblages, defined here as pristine (multiphase, often globular in shape) or volatile-bearing (multiphase, high-temperature, volatile-rich minerals such as biotite, hornblende, or an unmixed calcite-dolomite assemblage). The volatile-bearing assemblages are mainly found within and below the J-M reef, where native copper and sphalerite are also locally present. Pristine sulfides are found throughout the stratigraphy. Both groups can be affected by apparent S loss in the form of pyrite being converted to magnetite and chalcopyrite to a Cu-Fe-oxide (delafossite), with little to no silicate alteration. An upward trend from pentlandite-rich to pyrrhotite-rich to pyrite-rich assemblages is observed in the footwall rocks in upper GN-I, and the same trend repeats from just below the reef and continues into the overlying N-II and GN-II. Modeling suggests that the sulfide Ni in the Peridotite Zone is largely controlled by silicate Ni. When taken together, observations are most readily explained by the remobilization of selected elements by a high-temperature fluid with the apparent loss of S > Cu > Ni. This could concentrate ore metals by vapor refining, eventually producing a platinum group element-enriched sulfide ore zone, such as the J-M reef.

Linear spectral unmixing to monitor crop growth in typical organic and inorganic amended arid soil

NASA Astrophysics Data System (ADS)

El Battay, A.; Mahmoudi, H.

2016-06-01

The soils of the GCC countries are dominantly sandy which is typical of arid regions such as the Arabian Peninsula. Such soils are low in nutrients and have a poor water holding capacity associated with a high infiltration rate. Soil amendments may rehabilitate these soils by restoring essential soil properties and hence enable site revegetation and revitalization for crop production, especially in a region where food security is a priority. In this study, two inorganic amendments; AustraHort and Zeoplant pellet, and one organic locally produced compost were tested as soil amendments at the experimental field of the International Center for Biosaline Agriculture in Dubai, UAE. The main objective is to assess the remote sensing ability to monitor crop growth, for instance Okra (Abelmoschus esculentus), having these amendments, as background with the soil. Three biomass spectral vegetation indices were used namely; NDVI, TDVI and SAVI. Pure spectral signatures of the soil and the three amendments were collected, using a field spectroradiometer, in addition to the spectral signatures of Okra in two growing stages (vegetative and flowering) in the field with a mixed F.O.V of the plant and amended soil during March and May 2015. The spectral signatures were all collected using the FieldSpec® HandHeld 2 (HH2) in the spectral range 325 nm - 1075 nm over 12 plots. A set of 4 plots were assigned for each of the three amendments as follow: three replicates of a 1.5 by 1.5 meter plot with 3kg/m2 of each amendment and 54 plants, one plot as control and all plots were given irrigation treatments at 100% based on ETc. Spectra collected over the plots were inversed in the range of 400-900 nm via a Linear Mixture Model using pure soil and amendments spectral signatures as reference. Field pictures were used to determine the vegetation fraction (in term of area of the F.O.V). Hence, the Okra spectral signatures were isolated for all plots with the three types of amendments. The three vegetation indices were then calculated and compared in the vegetation fraction of the entire F.O.V. The key outcome of this analysis was that a considerable bias was induced when using a mixed F.O.V. In fact, the compost as an organic soil amendment containing dead vegetation affects similarly the sensitivity of the three vegetation indices in the vegetative stage of Okra compared to AustraHort and Zeoplant pellet amended plots. However, the TDVI is very sensitive to vegetation presence even with unmixed crop spectra. AustraHort amendment led to better status of Okra both in March and May with values of 0.19 and 0.28 respectively. Bias induced by some soil amendments can be misleading when upscaling spectral information to satellite imagery with low spectral and spatial resolutions. The results obtained are encouraging for further use of spectral information for crop monitoring in soil containing amendments.

Advanced receptor models for exploiting highly time-resolved data acquired in the EPA supersite preject

NASA Astrophysics Data System (ADS)

Ke, Haohao

Receptor models have been widely used in air quality studies to identify pollution sources and estimate their contributions. A common problem for most current receptor models is insufficient consideration of realistic constraints such as can be obtained from emission inventories, chemical composition profiles of the sources, and the physics of plume dispersion. In addition, poor resolving of collinear sources was often found. With the high quality time-, composition-, and size-resolved measurements during the EPA Supersite project, efforts towards resolving nearby industrial sources were made by combinative use of Positive Matrix Factorization (PMF) and the Pseudo-Deterministic Receptor Model (PDRM). The PMF modeling of Baltimore data in September 2001 revealed coal-fired and oil-fired power plants (CFPP and OFPP, respectively) with significant cross contamination, as indicated by the high Se/Ni ratio in the OFPP profile. Nevertheless, the PMF results provided a good estimate of background and the PMF-constrained emission rates well seeded the trajectory-driven PDRM modeling. Using NOx as the tracer gas for chi/Q tuning, ultimately resolved emissions from individual stacks exhibited acceptable tracer ratios and the emission rates of metals generally agreed with the TRI estimates. This approach was later applied to two metal pollution episodes in St. Louis during in November 2001 and March 2002 and met a similar success. As NOx measurements were unavailable at those metal-production facilities, highly-specific tracer metals (i.e., Cd, Zn, and Cu) for the corresponding units were used to tune chi/Qs and their contributions were well resolved with the PMF-seeded PDRM. Opportunistically a PM2.5 excursion during a windless morning in November 2002 allowed the extraction of an in-situ profile of vehicular emissions in Baltimore. The profiles obtained by direct peak observation, windless model linear regression (WMA), PMF, and UNMIX were comparable and the WMA profile showed the best predictions for non-traffic tracers. Besides, an approach to evaluate vehicular emission factors was developed by receptor measurements under windless conditions. Using SVOC tracers, seasonal variations of traffic and other sources including coal burning, heating, biomass burning, and vegetation were investigated by PMF and in particular the November traffic profile was consistent with the WMA profile obtained earlier.

Changing Pattern of Crop Fraction in Late Blight Induced Potato Crops in Potato Bowl of West Bengal by using Multi-temporal Time Series AWiFs Data

NASA Astrophysics Data System (ADS)

Chakrabarty, Abhisek

2016-07-01

Crop fraction is the ratio of crop occupying a unit area in ground pixel, is very important for monitoring crop growth. One of the most important variables in crop growth monitoring is the fraction of available solar radiation intercepted by foliage. Late blight of potato (Solanum tuberosum), caused by the oomycete pathogen Phytophthora infestans, is considered to be the most destructive crop diseases of potato worldwide. Under favourable climatic conditions, and without intervention (i.e. fungicide sprays), the disease can destroy potato crop within few weeks. Therefore it is important to evaluate the crop fraction for monitoring the healthy and late blight affected potato crops. This study was conducted in potato bowl of West Bengal, which consists of districts of Hooghly, Howrah, Burdwan, Bankuara, and Paschim Medinipur. In this study different crop fraction estimation method like linear spectral un-mixing, Normalized difference vegetation index (NDVI) based DPM model (Zhang et al. 2013), Ratio vegetation index based DPM model, improved Pixel Dichotomy Model (Li et al. 2014) ware evaluated using multi-temporal IRS AWiFs data in two successive potato growing season of 2012-13 and 2013-14 over the study area and compared with measured crop fraction. The comparative study based on measured healthy and late blight affected potato crop fraction showed that improved Pixel Dichotomy Model maintain the high coefficient of determination (R2= 0.835) with low root mean square error (RMSE=0.21) whereas the correlation values of NDVI based DPM model and RVI based DPM model is 0.763 and 0.694 respectively. The changing pattern of crop fraction profile of late blight affected potato crop was studied in respect of healthy potato crop fraction which was extracted from the 269 GPS points of potato field. It showed that the healthy potato crop fraction profile maintained the normal phenological trend whereas the late blight affected potato crop fraction profile suddenly fallen after late blight disease affected in potato crops. Therefore, it can be concluded that based on the result of this study the improved Pixel Dichotomy Model is the most convenient method for crop fraction estimation for this region with satisfactory accuracy.

Soil Biogeochemical Properties and Erosion Source Prediction Model Summary for the Buffalo Bayou Watershed, Houston, Texas

NASA Astrophysics Data System (ADS)

Ahmed, I.

2015-12-01

We draw conclusions on the research output and findings from a 4-year multidisciplinary USDA-CBG collaborative program in sustainable integrated monitoring of soil organic carbon (SOC) loss prediction via erosion. The underlying method uses the state-of-the-art stable isotope science of sediment tracing under uncertain hydrologic influences. The research finds are rooted in the (i) application of Bayesian Markov Chain Monte Carlo statistical models to assess the relationship between rainfall-runoff and soil erosion in space and time, (ii) capture of the episodic nature of rainfall events and its role in the spatial distribution of SOC loss from water erosion, (iii) stable isotope composition guided fingerprinting (source and quantity) of eroded soil, and (iv) the creation of an integrated watershed scale statistical soil loss monitoring model driven by spatial and temporal correlation of flow and stable isotope composition. The research theme was successfully applied on the urbanized Buffalo Bayou Watershed in Houston, Texas. The application brought to light novel future research conceptual outlines which will also be discussed in this deliverable to the AGU meeting. These include but not limited to: regional rainfall cluster research, physics of muddy river-bank soil and suspended sediment interaction, and friction & mobility that together make up the plasticity of soil aggregates that control erosion processes and landscape changes in a riparian corridor. References: Ahmed, I., Karim, A., Boutton, T.W., and Strom, K.B. (2013a). "Monitoring Soil Organic Carbon Loss from Erosion Using Stable Isotopes." Proc., Soil Carbon Sequestration, International Conference, May 26-29, Reykjavik, Iceland. Ahmed, I, Bouttom, T.W., Strom, K. B., Karim, A., and Irvin-Smith, N. (2013b). "Soil carbon distribution and loss monitoring in the urbanized Buffalo Bayou watershed, Houston, Texas." Proc., 4th Annual All Investigators Meeting of the North American Carbon Program, February 4-7, Albuquerque, NM. Fox, J.F. and Papanicolaou, A.N. (2008). An un-mixing model to study watershed erosion processes. Advances in Water Resources, 31, 96-108.

Simple on-shell renormalization framework for the Cabibbo-Kobayashi-Maskawa matrix

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

Kniehl, Bernd A.; Sirlin, Alberto

2006-12-01

We present an explicit on-shell framework to renormalize the Cabibbo-Kobayashi-Maskawa (CKM) quark mixing matrix at the one-loop level. It is based on a novel procedure to separate the external-leg mixing corrections into gauge-independent self-mass (sm) and gauge-dependent wave-function renormalization contributions, and to adjust nondiagonal mass counterterm matrices to cancel all the divergent sm contributions, and also their finite parts subject to constraints imposed by the Hermiticity of the mass matrices. It is also shown that the proof of gauge independence and finiteness of the remaining one-loop corrections to W{yields}q{sub i}+q{sub j} reduces to that in the unmixed, single-generation case. Diagonalizationmore » of the complete mass matrices leads then to an explicit expression for the CKM counterterm matrix, which is gauge independent, preserves unitarity, and leads to renormalized amplitudes that are nonsingular in the limit in which any two fermions become mass degenerate.« less

Single cell performance studies on the FE/CR Redox Energy Storage System using mixed reactant solutions at elevated temperature

NASA Technical Reports Server (NTRS)

Gahn, R. F.; Hagedorn, N. H.; Ling, J. S.

1983-01-01

Experimental studies in a 14.5 sq cm single cell system using mixed reactant solutions at 65 C are described. Systems were tested under isothermal conditions, i.e., reactants and the cell were at the same temperature. Charging and discharging performance were evaluated by measuring watt-hour and coulombic efficiencies, voltage-current relationships, hydrogen evolution and membrane resistivity. Watt-hour efficiencies ranged from 86 percent at 43 ma/sq cm to 75 percent at 129 ma/sq cm with corresponding coulombic efficiencies of 92 percent and 97 percent, respectively. Hydrogen evolution was less than 1 percent of the charge coulumbic capacity during charge-discharge cycling. Bismuth amd bismuth-lead catalyzed chromium electrodes maintained reversible performance and low hydrogen evolution under normal and adverse cycling conditions. Reblending of the anode and cathode solutions was successfully demonstrated to compensate for osmotic volume changes. Improved performance was obtained with mixed reactant systems in comparison to the unmixed reactant systems. Previously announced in STAR as N83-25042

Surface (sea floor) and near-surface (box cores) sediment mineralogy in Baffin Bay as a key to sediment provenance and ice sheet variations

USGS Publications Warehouse

Andrews, John T.; Eberl, D.D.

2011-01-01

To better understand the glacial history of the ice sheets surrounding Baffin Bay and to provide information on sediment pathways, samples from 82 seafloor grabs and core tops, and from seven box cores were subjected to quantitative X-ray diffraction weight percent (wt.%) analysis of the 2000 m) all show an abrupt drop in calcite wt.% (post-5 cal ka BP?) following a major peak in detrital carbonate (mainly dolomite). This dolomite-rich detrital carbonate (DC) event in JR175BC06 is possibly coeval with the Younger Dryas cold event. Four possible glacial-sourced end members were employed in a compositional unmixing algorithm to gain insight into down core changes in sediment provenance at the deep central basin. Estimates of the rates of sediment accumulation in the central basin are only in the range of 2 to 4 cm/cal ka, surprisingly low given the glaciated nature of the surrounding land.

Spectral unmixing of agents on surfaces for the Joint Contaminated Surface Detector (JCSD)

NASA Astrophysics Data System (ADS)

Slamani, Mohamed-Adel; Chyba, Thomas H.; LaValley, Howard; Emge, Darren

2007-09-01

ITT Corporation, Advanced Engineering and Sciences Division, is currently developing the Joint Contaminated Surface Detector (JCSD) technology under an Advanced Concept Technology Demonstration (ACTD) managed jointly by the U.S. Army Research, Development, and Engineering Command (RDECOM) and the Joint Project Manager for Nuclear, Biological, and Chemical Contamination Avoidance for incorporation on the Army's future reconnaissance vehicles. This paper describes the design of the chemical agent identification (ID) algorithm associated with JCSD. The algorithm detects target chemicals mixed with surface and interferent signatures. Simulated data sets were generated from real instrument measurements to support a matrix of parameters based on a Design Of Experiments approach (DOE). Decisions based on receiver operating characteristics (ROC) curves and area-under-the-curve (AUC) measures were used to down-select between several ID algorithms. Results from top performing algorithms were then combined via a fusion approach to converge towards optimum rates of detections and false alarms. This paper describes the process associated with the algorithm design and provides an illustrating example.

High efficiency organic photovoltaic cells employing hybridized mixed-planar heterojunctions

DOEpatents

Xue, Jiangeng; Uchida, Soichi; Rand, Barry P; Forrest, Stephen

2013-11-19

A device is provided, having a first electrode, a second electrode, and a photoactive region disposed between the first electrode and the second electrode. The photoactive region includes a first organic layer comprising a mixture of an organic acceptor material and an organic donor material, wherein the first organic layer has a thickness not greater than 0.8 characteristic charge transport lengths, and a second organic layer in direct contact with the first organic layer, wherein: the second organic layer comprises an unmixed layer of the organic acceptor material or the organic donor material of the first organic layer, and the second organic layer has a thickness not less than about 0.1 optical absorption lengths. Preferably, the first organic layer has a thickness not greater than 0.3 characteristic charge transport lengths. Preferably, the second organic layer has a thickness of not less than about 0.2 optical absorption lengths. Embodiments of the invention can be capable of power efficiencies of 2% or greater, and preferably 5% or greater.

Single cell performance studies on the Fe/Cr Redox Energy Storage System using mixed reactant solutions at elevated temperature

NASA Technical Reports Server (NTRS)

Gahn, R. F.; Hagedorn, N. H.; Ling, J. S.

1983-01-01

Experimental studies in a 14.5 sq cm single cell system using mixed reactant solutions at 65 C are described. Systems were tested under isothermal conditions i.e., reactants and the cell were at the same temperature. Charging and discharging performance were evaluted by measuring watt-hour and coulombic efficiencies, voltage-current relationships, hydrogen evolution and membrane resistivity. Watt-hour efficiencies ranged from 86% at 43 ma/sq cm to 75% at 129 ma/sq cm with corresponding coulombic efficiencies of 92% and 97%, respectively. Hydrogen evolution was less than 1% of the charge coulombic capacity during charge-discharge cycling. Bismuth and bismuth-lead catalyzed chromium electrodes maintained reversible performance and low hydrogen evolution under normal and adverse cycling conditions. Reblending of the anode and cathode solutions was successfully demonstrated to compensate for osmotic volume changes. Improved performance was obtained with mixed reactant systems in comparison to the unmixed reactant systems.

Pile mixing increases greenhouse gas emissions during composting of dairy manure.

PubMed

Ahn, H K; Mulbry, W; White, J W; Kondrad, S L

2011-02-01

The effect of pile mixing on greenhouse gas (GHG) emissions during dairy manure composting was determined using large flux chambers designed to completely cover replicate pilot-scale compost piles. GHG emissions from compost piles that were mixed four times during the 80 day trial were approximately 20% higher than emissions from unmixed (static) piles. For both treatments, carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) accounted for 75-80%, 18-21%, and 2-4% of GHG emissions, respectively. Seventy percent of CO(2) emissions and 95% of CH(4) emissions from all piles occurred within first 23 days. By contrast, 80-95% of N(2)O emissions occurred after this period. Mixed and static piles released 2 and 1.6 kg GHG (CO(2)-Eq.) for each kg of degraded volatile solids (VS), respectively. Our results suggest that to minimize GHG emissions, farmers should store manure in undisturbed piles or delay the first mixing of compost piles for approximately 4 weeks. Published by Elsevier Ltd.

Archaeointensity and rock magnetism on Maya locations pottery, Southeast Mexico, from Preclassic to Posclassic

NASA Astrophysics Data System (ADS)

Rodriguez Trejo, A.; Alva-Valdivia, L. M.; Nieto Calleja, R.; Jimenez, S.

2016-12-01

Archeointensity results are presented from 7 archeological sites of the Maya Zone, southeast Mexico: Chiapas, Yucatan and Quintana Roo, distributed geographically over a 500,000 Km2 area over the Yucatan Peninsula. The sites corresponds to over 250 samples from Palenque, Chichén-Itzá, Flor de Mayo, El Mirador, Oxtancah, Busiljá and Mensabak. All the artifact sites correspond from the Preclasic to Posclasic period (1000 b.C. to 1600 a.C.), which represent the most important period in Mesoamerica. The laboratory experiments for rock magnetism includes the suscpetibility vs. temperature curves (KT), hysteresis loop, first order reversal curves analysis (FORC), IRM coercivity unmixing and thermal and AF demagnetization. Archaeointensity were carried out using previously selected samples that accomplish the quality criteria, using the Thellier - Thellier methology and the Coe check modification. These results will be used to construct a secular variation curve for intensity in this region, which eventually could be used for dating many archeological materials of unknown age.

Adaptive and automatic red blood cell counting method based on microscopic hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Liu, Xi; Zhou, Mei; Qiu, Song; Sun, Li; Liu, Hongying; Li, Qingli; Wang, Yiting

2017-12-01

Red blood cell counting, as a routine examination, plays an important role in medical diagnoses. Although automated hematology analyzers are widely used, manual microscopic examination by a hematologist or pathologist is still unavoidable, which is time-consuming and error-prone. This paper proposes a full-automatic red blood cell counting method which is based on microscopic hyperspectral imaging of blood smears and combines spatial and spectral information to achieve high precision. The acquired hyperspectral image data of the blood smear in the visible and near-infrared spectral range are firstly preprocessed, and then a quadratic blind linear unmixing algorithm is used to get endmember abundance images. Based on mathematical morphological operation and an adaptive Otsu’s method, a binaryzation process is performed on the abundance images. Finally, the connected component labeling algorithm with magnification-based parameter setting is applied to automatically select the binary images of red blood cell cytoplasm. Experimental results show that the proposed method can perform well and has potential for clinical applications.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Disturbance Source Separation in Shear Flows Using Blind Source Separation Methods

NASA Astrophysics Data System (ADS)

Gluzman, Igal; Cohen, Jacob; Oshman, Yaakov

2017-11-01

A novel approach is presented for identifying disturbance sources in wall-bounded shear flows. The method can prove useful for active control of boundary layer transition from laminar to turbulent flow. The underlying idea is to consider the flow state, as measured in sensors, to be a mixture of sources, and to use Blind Source Separation (BSS) techniques to recover the separate sources and their unknown mixing process. We present a BSS method based on the Degenerate Unmixing Estimation Technique. This method can be used to identify any (a priori unknown) number of sources by using the data acquired by only two sensors. The power of the new method is demonstrated via numerical and experimental proofs of concept. Wind tunnel experiments involving boundary layer flow over a flat plate were carried out, in which two hot-wire anemometers were used to separate disturbances generated by disturbance generators such as a single dielectric barrier discharge plasma actuator and a loudspeaker.

Near-infrared imaging spectroscopy for counterfeit drug detection

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2011-06-01

Pharmaceutical counterfeiting is a significant issue in the healthcare community as well as for the pharmaceutical industry worldwide. The use of counterfeit medicines can result in treatment failure or even death. A rapid screening technique such as near infrared (NIR) spectroscopy could aid in the search for and identification of counterfeit drugs. This work presents a comparison of two laboratory NIR imaging systems and the chemometric analysis of the acquired spectroscopic image data. The first imaging system utilizes a NIR liquid crystal tuneable filter and is designed for the investigation of stationary objects. The second imaging system utilizes a NIR imaging spectrograph and is designed for the fast analysis of moving objects on a conveyor belt. Several drugs in form of tablets and capsules were analyzed. Spectral unmixing techniques were applied to the mixed reflectance spectra to identify constituent parts of the investigated drugs. The results show that NIR spectroscopic imaging can be used for contact-less detection and identification of a variety of counterfeit drugs.

Mid Term Progress Report: Desertification Assessment and Monitoring in China Based on Remote Sensing

NASA Astrophysics Data System (ADS)

Gao, Zhihai; del Barrio, Gabriel; Li, Xiaosong; Wang, Bengyu; Puigdefabregas, Juan; Sanjuan, Maria E.; Bai, Lina; Wu, Junjun; Sun, Bin; Li, Changlong

2014-11-01

The objective of Dragon 3 Project 10367 is the development of techniques research for desertification assessment and monitoring in China using remote sensing data in combination with climate and environmental-related data. The main achievements acquired since2012could be summarized as follows: (1)Photosynthetic vegetation(PV)and non-photosynthetic vegetation(NPV)fraction were retrieved separately through utilizing Auto Monte Carlo Unmixing technique (AutoMCU), based on BJ-1 data and field measured spectral library. (2) The accuracy of sandy land classification was as high as81.52%when the object-oriented method and Support Vector Machine (SVM) classifiers were used. (3) A new Monthly net primary productivity (NPP)dataset from 2002 to 2010 for the whole China were established with Envisat-MERIS fraction of absorbed photosynthetically active radiation (FPAR) data. (4) The 2dRUE proved to be a good indicator for land degradation, based on which, land degradation status in the general potential extent of desertification in China(PEDC) was assessed preliminarily.

Spectral Unmixing of Vegetation, Soil and Dry Carbon in Arid Regions: Comparing Multispectral and Hyperspectral Observations

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Heidebrecht, Kathleen B.

2001-01-01

Remote sensing of vegetation cover and condition is critically needed to understand the impacts of land use and climate variability in and and semi-arid regions. However, remote sensing of vegetation change in these environments is difficult for several reasons. First, individual plant canopies are typically small and do not reach the spatial scale of typical Landsat-like satellite image pixels. Second, the phenological status and subsequent dry carbon (or non-photosynthetic) fraction of plant canopies varies dramatically in both space and time throughout and and semi-arid regions. Detection of only the 'green' part of the vegetation using a metric such as the normalized difference vegetation index (NDVI) thus yields limited information on the presence and condition of plants in these ecosystems. Monitoring of both photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) is needed to understand a range of ecosystem characteristics including vegetation presence, cover and abundance, physiological and biogeochemical functioning, drought severity, fire fuel load, disturbance events and recovery from disturbance.

Mid Term Progress Report: Desertification Assessment and Monitoring in China Based on Remote Sensing

NASA Astrophysics Data System (ADS)

Gao, Zhihai; del Barrio, Gabriel; Li, Xiaosong; Wang, Wengyu; Puigdefabregas, Juan; Sanjuan, Maria E.; Bai, Lina; Wu, Junjun; Sun, Bin; Li, Changlong

2014-11-01

The objective of Dragon 3 Project 10367 is the development of techniques research for desertification assessment and monitoring in China using remote sensing data in combination with climate and environmental-related data. The main achievements acquired since 2012 could be summarized as follows:(1) Photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) fraction were retrieved separately through utilizing Auto Monte Carlo Unmixing technique (AutoMCU), based on BJ-1 data and field measured spectral library.(2) The accuracy of sandy land classification was as high as 81.52% when the object-oriented method and Support Vector Machine (SVM) classifiers were used.(3) A new Monthly net primary productivity (NPP) dataset from 2002 to 2010 for the whole China were established with Envisat-MERIS fraction of absorbed photosynthetically active radiation (FPAR) data.(4) The 2dRUE proved to be a good indicator for land degradation, based on which, land degradation status in the general potential extent of desertification in China (PEDC) was assessed preliminarily.

Kinetics of T-cell receptor-dependent antigen recognition determined in vivo by multi-spectral normalized epifluorescence laser scanning

NASA Astrophysics Data System (ADS)

Favicchio, Rosy; Zacharakis, Giannis; Oikonomaki, Katerina; Zacharopoulos, Athanasios; Mamalaki, Clio; Ripoll, Jorge

2012-07-01

Detection of multiple fluorophores in conditions of low signal represents a limiting factor for the application of in vivo optical imaging techniques in immunology where fluorescent labels report for different functional characteristics. A noninvasive in vivo Multi-Spectral Normalized Epifluorescence Laser scanning (M-SNELS) method was developed for the simultaneous and quantitative detection of multiple fluorophores in low signal to noise ratios and used to follow T-cell activation and clonal expansion. Colocalized DsRed- and GFP-labeled T cells were followed in tandem during the mounting of an immune response. Spectral unmixing was used to distinguish the overlapping fluorescent emissions representative of the two distinct cell populations and longitudinal data reported the discrete pattern of antigen-driven proliferation. Retrieved values were validated both in vitro and in vivo with flow cytometry and significant correlation between all methodologies was achieved. Noninvasive M-SNELS successfully quantified two colocalized fluorescent populations and provides a valid alternative imaging approach to traditional invasive methods for detecting T cell dynamics.

Mixing and chemical reaction in sheared and nonsheared homogeneous turbulence

NASA Technical Reports Server (NTRS)

Leonard, Andy D.; Hill, James C.

1992-01-01

Direct numerical simulations were made to examine the local structure of the reaction zone for a moderately fast reaction between unmixed species in decaying, homogeneous turbulence and in a homogeneous turbulent shear flow. Pseudospectral techniques were used in domains of 64 exp 3 and higher wavenumbers. A finite-rate, single step reaction between non-premixed reactants was considered, and in one case temperature-dependent Arrhenius kinetics was assumed. Locally intense reaction rates that tend to persist throughout the simulations occur in locations where the reactant concentration gradients are large and are amplified by the local rate of strain. The reaction zones are more organized in the case of a uniform mean shear than in isotropic turbulence, and regions of intense reaction rate appear to be associated with vortex structures such as horseshoe vortices and fingers seen in mixing layers. Concentration gradients tend to align with the direction of the most compressive principal strain rate, more so in the isotropic case.

Estimation of sub-pixel water area on Tibet plateau using multiple endmembers spectral mixture spectral analysis from MODIS data

NASA Astrophysics Data System (ADS)

Cui, Qian; Shi, Jiancheng; Xu, Yuanliu

2011-12-01

Water is the basic needs for human society, and the determining factor of stability of ecosystem as well. There are lots of lakes on Tibet Plateau, which will lead to flood and mudslide when the water expands sharply. At present, water area is extracted from TM or SPOT data for their high spatial resolution; however, their temporal resolution is insufficient. MODIS data have high temporal resolution and broad coverage. So it is valuable resource for detecting the change of water area. Because of its low spatial resolution, mixed-pixels are common. In this paper, four spectral libraries are built using MOD09A1 product, based on that, water body is extracted in sub-pixels utilizing Multiple Endmembers Spectral Mixture Analysis (MESMA) using MODIS daily reflectance data MOD09GA. The unmixed result is comparing with contemporaneous TM data and it is proved that this method has high accuracy.

Genesis of the heaviest elements in the Milky Way Galaxy.

PubMed

Sneden, Christopher; Cowan, John J

2003-01-03

We review the origin and evolution of the heavy elements, those with atomic numbers greater than 30, in the early history of the Milky Way. There is a large star-to-star bulk scatter in the concentrations of heavy elements with respect to the lighter metals, which suggests an early chemically unmixed and inhomogeneous Galaxy. The relative abundance patterns among the heavy elements are often very different from the solar system mix, revealing the characteristics of the first element donors in the Galaxy. Abundance comparisons among several halo stars show that the heaviest neutron-capture elements (including barium and heavier) are consistent with a scaled solar system rapid neutron-capture abundance distribution, whereas the lighter such elements do not conform to the solar pattern. The stellar abundances indicate an increasing contribution from the slow neutron-capture process (s-process) at higher metallicities in the Galaxy. The detection of thorium in halo and globular cluster stars offers a promising, independent age-dating technique that can put lower limits on the age of the Galaxy.

Spectral mixture analyses of hyperspectral data acquired using a tethered balloon

USGS Publications Warehouse

Chen, Xuexia; Vierling, Lee

2006-01-01

Tethered balloon remote sensing platforms can be used to study radiometric issues in terrestrial ecosystems by effectively bridging the spatial gap between measurements made on the ground and those acquired via airplane or satellite. In this study, the Short Wave Aerostat-Mounted Imager (SWAMI) tethered balloon-mounted platform was utilized to evaluate linear and nonlinear spectral mixture analysis (SMA) for a grassland-conifer forest ecotone during the summer of 2003. Hyperspectral measurement of a 74-m diameter ground instantaneous field of view (GIFOV) attained by the SWAMI was studied. Hyperspectral spectra of four common endmembers, bare soil, grass, tree, and shadow, were collected in situ, and images captured via video camera were interpreted into accurate areal ground cover fractions for evaluating the mixture models. The comparison between the SWAMI spectrum and the spectrum derived by combining in situ spectral data with video-derived areal fractions indicated that nonlinear effects occurred in the near infrared (NIR) region, while nonlinear influences were minimal in the visible region. The evaluation of hyperspectral and multispectral mixture models indicated that nonlinear mixture model-derived areal fractions were sensitive to the model input data, while the linear mixture model performed more stably. Areal fractions of bare soil were overestimated in all models due to the increased radiance of bare soil resulting from side scattering of NIR radiation by adjacent grass and trees. Unmixing errors occurred mainly due to multiple scattering as well as close endmember spectral correlation. In addition, though an apparent endmember assemblage could be derived using linear approaches to yield low residual error, the tree and shade endmember fractions calculated using this technique were erroneous and therefore separate treatment of endmembers subject to high amounts of multiple scattering (i.e. shadows and trees) must be done with caution. Including the short wave infrared (SWIR) region in the hyperspectral and multispectral endmember data significantly reduced the Pearson correlation coefficient values among endmember spectra. Therefore, combination of visible, NIR, and SWIR information is likely to further improve the utility of SMA in understanding ecosystem structure and function and may help narrow uncertainties when utilizing remotely sensed data to extrapolate trace glas flux measurements from the canopy scale to the landscape scale.

Unmixing the young fossil record using radiocarbon-calibrated amino-acid racemization (Gulf of Trieste, northern Adriatic Sea)

NASA Astrophysics Data System (ADS)

Tomašových, Adam; Gallmetzer, Ivo; Haselmair, Alex; Kaufman, Darrell S.; Vidović, Jelena; Zuschin, Martin

2017-04-01

Marine coastal habitats globally have been affected by eutrophication, hypoxia, habitat alteration, overfishing, and resource exploitation over recent decades. However, reconstruction of past natural ecosystem states is compromised by short-term archives and biotic surveys limited to the past decades and/or by low stratigraphic resolution of fossil assemblages in sedimentary cores due to slow sedimentation and bioturbation. In the northern Adriatic Sea, which was affected by eutrophication, algal blooms and mucilage blooms, and hypoxia during the second half of the 20th century, the composition of natural baseline states of benthic ecosystems and their responses to natural and anthropogenic disturbances over longer, centennial scales are poorly known. In this study, we evaluate the timing and forcing of past hypoxia events in the northern Adriatic Sea (Gulf of Trieste) based on the production history of the opportunistic, hypoxia-tolerant bivalve Corbula gibba, using 210Pb data, radiocarbon dating, amino acid racemization, and distribution of foraminifers in 1.5-m-thick sediment cores that capture the past 500 yr. Corbula gibba tolerates eutrophied and polluted conditions and survives seasonal hypoxic and mass mortality events affecting most of the benthic macrofauna in the northern Adriatic Sea. In the aftermath of such events, it can achieve density of thousands of individuals/1 m2 and can contribute with more than 80% of individuals to the bivalve assemblage. Unmixing the stratigraphic record of cores on the basis of 311 shells of C. gibba, we show that production of this species underwent major decadal-scale fluctuations since the 18th century, with outbreaks corresponding to density of more than 1000 individuals per square meter. A positive correlation between abundances of hypoxia-tolerant foraminifers and C. gibba, the temporal coincidence between the peak in abundance at 1980 and several hypoxic crises in the Gulf of Trieste in 1974, 1980, and 1983, and the temporal coincidence between the decline in C. gibba abundance and low frequency of hypoxia in the past two decades, suggest that outbreaks of C. gibba do correspond to past hypoxia events. We suggest that the outbreaks of C. gibba represent long-term phenomena in the northern Adriatic ecosystem rather than novel states characteristic of the 20th century eutrophication. These outbreaks correlate significantly positively with maxima in sea-surface temperature, indicating that the hypoxia events were connected with water-column stratification rather than with eutrophication events. The reconstructed fluctuations in production do not correlate with abundances of C. gibba in the raw stratigraphic record due to centennial-scale time averaging of bivalve assemblages.

Hyperspectral remote sensing exploration of carbonatite - an example from Epembe, Kunene region, Namibia

NASA Astrophysics Data System (ADS)

Zimmermann, Robert; Brandmeier, Melanie; Andreani, Louis; Gloaguen, Richard

2015-04-01

Remote sensing data can provide valuable information about ore deposits and their alteration zones at surface level. High spectral and spatial resolution of the data is essential for detailed mapping of mineral abundances and related structures. Carbonatites are well known for hosting economic enrichments in REE, Ta, Nb and P (Jones et al. 2013). These make them a preferential target for exploration for those critical elements. In this study we show how combining geomorphic, textural and spectral data improves classification result. We selected a site with a well-known occurrence in northern Namibia: the Epembe dyke. For analysis LANDSAT 8, SRTM and airborne hyperspectral (HyMap) data were chosen. The overlapping data allows a multi-scale and multi-resolution approach. Results from data analysis were validated during fieldwork in 2014. Data was corrected for atmospherical and geometrical effects. Image classification, mineral mapping and tectonic geomorphology allow a refinement of the geological map by lithological mapping in a second step. Detailed mineral abundance maps were computed using spectral unmixing techniques. These techniques are well suited to map abundances of carbonate minerals, but not to discriminate the carbonatite itself from surrounding rocks with similar spectral signatures. Thus, geometric indices were calculated using tectonic geomorphology and textures. For this purpose the TecDEM-toolbox (SHAHZAD & GLOAGUEN 2011) was applied to the SRTM-data for geomorphic analysis. Textural indices (e.g. uniformity, entropy, angular second moment) were derived from HyMap and SRTM by a grey-level co-occurrence matrix (CLAUSI 2002). The carbonatite in the study area is ridge-forming and shows a narrow linear feature in the textural bands. Spectral and geometric information were combined using kohonen Self-Organizing Maps (SOM) for unsupervised clustering. The resulting class spectra were visually compared and interpreted. Classes with similar signatures were merged according to geological context. The major conclusions are: 1. Carbonate minerals can be mapped using spectral unmixing techniques. 2. Carbonatites are associated with specific geometric pattern 3. The combination of spectral and geometric information improves classification result and reduces misclassification. References Clausi, D. A. (2002): An analysis of co-occurrence texture statistics as a function of grey-level quantization. - Canadian Journal of Remote Sensing, 28 (1), 45-62 Jones, A. P., Genge, M. and Carmody, L (2013): Carbonate Melts and Carbonatites. - Reviews in Mineralogy & Geochemistry, 75, 289-322 Shahzad, F. & Gloaguen, R. (2011): TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 2: Surface dynamics and basin analysis. - Computers and Geosciences, 37 (2), 261-271

Multilevel Effects of Wealth on Women's Contraceptive Use in Mozambique

PubMed Central

Dias, José G.; de Oliveira, Isabel Tiago

2015-01-01

Objective This paper analyzes the impact of wealth on the use of contraception in Mozambique unmixing the contextual effects due to community wealth from the individual effects associated with the women's situation within the community of residence. Methods Data from the 2011 Mozambican Demographic and Health Survey on women who are married or living together are analyzed for the entire country and also for the rural and urban areas separately. We used single level and multilevel probit regression models. Findings A single level probit regression reveals that region, religion, age, previous fertility, education, and wealth impact contraceptive behavior. The multilevel analysis shows that average community wealth and the women’s relative socioeconomic position within the community have significant positive effects on the use of modern contraceptives. The multilevel framework proved to be necessary in rural settings but not relevant in urban areas. Moreover, the contextual effects due to community wealth are greater in rural than in urban areas and this feature is associated with the higher socioeconomic heterogeneity within the richest communities. Conclusion This analysis highlights the need for the studies on contraceptive behavior to specifically address the individual and contextual effects arising from the poverty-wealth dimension in rural and urban areas separately. The inclusion in a particular community of residence is not relevant in urban areas, but it is an important feature in rural areas. Although the women's individual position within the community of residence has a similar effect on contraceptive adoption in rural and urban settings, the impact of community wealth is greater in rural areas and smaller in urban areas. PMID:25786228

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

PubMed

Piqueras, Sara; Bedia, Carmen; Beleites, Claudia; Krafft, Christoph; Popp, Jürgen; Maeder, Marcel; Tauler, Romà; de Juan, Anna

2018-06-05

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

PubMed

Leibig, Christian; Wachtler, Thomas; Zeck, Günther

2016-09-15

Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (ICA) achieves rapid unsupervised sorting, it ignores the convolutive structure of extracellular data, thus limiting the unmixing to a subset of neurons. Here we present a spike sorting algorithm based on convolutive ICA (cICA) to retrieve a larger number of accurately sorted neurons than with instantaneous ICA while accounting for signal overlaps. Spike sorting was applied to datasets with varying signal-to-noise ratios (SNR: 3-12) and 27% spike overlaps, sampled at either 11.5 or 23kHz on 4365 electrodes. We demonstrate how the instantaneity assumption in ICA-based algorithms has to be relaxed in order to improve the spike sorting performance for high-density microelectrode array recordings. Reformulating the convolutive mixture as an instantaneous mixture by modeling several delayed samples jointly is necessary to increase signal-to-noise ratio. Our results emphasize that different cICA algorithms are not equivalent. Spike sorting performance was assessed with ground-truth data generated from experimentally derived templates. The presented spike sorter was able to extract ≈90% of the true spike trains with an error rate below 2%. It was superior to two alternative (c)ICA methods (≈80% accurately sorted neurons) and comparable to a supervised sorting. Our new algorithm represents a fast solution to overcome the current bottleneck in spike sorting of large datasets generated by simultaneous recording with thousands of electrodes. Copyright © 2016 Elsevier B.V. All rights reserved.

In vivo determination of multiple indices of periodontal inflammation by optical spectroscopy

PubMed Central

Liu, KZ; Xiang, XM; Man, A; Sowa, MG; Cholakis, N; Ghiabi, E; Singer, DL; Scott, DA

2008-01-01

Background and Objective Visible – near infrared (optical) spectroscopy can be used to measure regional tissue hemodynamics and edema and, therefore, may represent an ideal tool with which to non-invasively study periodontal inflammation. The study objective was to evaluate the ability of optical spectroscopy to simultaneously determine multiple inflammatory indices (tissue oxygenation, total tissue hemoglobin, deoxyhemoglobin, oxygenated hemoglobin, and tissue edema) in periodontal tissues in vivo. Material and Methods Spectra were obtained, processed, and evaluated from healthy, gingivitis, and periodontitis sites (n = 133) using a portable optical – near infrared spectrometer. A modified Beer-Lambert unmixing model that incorporates a nonparametric scattering loss function was used to determine the relative contribution of each inflammatory component to the overall spectrum. Results Optical spectroscopy was harnessed to successfully generate complex inflammatory profiles in periodontal tissues. Tissue oxygenation at periodontitis sites was significantly decreased (p<0.05) compared to gingivitis and healthy controls. This is largely due to an increase in deoxyhemoglobin in the periodontitis sites compared to healthy (p<0.01) and gingivitis (p=0.05) sites. Tissue water content per se showed no significant difference between the sites but a water index associated with tissue electrolyte levels and temperature differed was significantly between periodontitis sites when compared to both healthy and gingivitis sites (p<0.03). Conclusion This study establishes that optical spectroscopy can simultaneously determine multiple inflammatory indices directly in the periodontal tissues in vivo. Visible - near infrared spectroscopy has the potential to be developed into a simple, reagent-free, user friendly, chair-side, site-specific, diagnostic and prognostic test for periodontitis. PMID:18973538

Curie temperatures of titanomagnetite in ignimbrites: Effects of emplacement temperatures, cooling rates, exsolution, and cation ordering

NASA Astrophysics Data System (ADS)

Jackson, Mike; Bowles, Julie A.

2014-11-01

Pumices, ashes, and tuffs from Mt. St. Helens and from Novarupta contain two principal forms of titanomagnetite: homogeneous grains with Curie temperatures in the range 350-500°C and oxyexsolved grains with similar bulk composition, containing ilmenite lamellae and having Curie temperatures above 500°C. Thermomagnetic analyses and isothermal annealing experiments in combination with stratigraphic settings and thermal models show that emplacement temperatures and cooling history may have affected the relative proportions of homogeneous and exsolved grains and have clearly had a strong influence on the Curie temperature of the homogeneous phase. The exsolved grains are most common where emplacement temperatures exceeded 600°C, and in laboratory experiments, heating to over 600°C in air causes the homogeneous titanomagnetites to oxyexsolve rapidly. Where emplacement temperatures were lower, Curie temperatures of the homogeneous grains are systematically related to overburden thickness and cooling timescales, and thermomagnetic curves are generally irreversible, with lower Curie temperatures measured during cooling, but little or no change is observed in room temperature susceptibility. We interpret this irreversible behavior as reflecting variations in the degree of cation ordering in the titanomagnetites, although we cannot conclusively rule out an alternative interpretation involving fine-scale subsolvus unmixing. Short-range ordering within the octahedral sites may play a key role in the observed phenomena. Changes in the Curie temperature have important implications for the acquisition, stabilization, and retention of natural remanence and may in some cases enable quantification of the emplacement temperatures or cooling rates of volcanic units containing homogeneous titanomagnetites.

Hybrid ICA-Bayesian Network approach reveals distinct effective connectivity differences in schizophrenia

PubMed Central

Kim, D.; Burge, J.; Lane, T.; Pearlson, G. D; Kiehl, K. A; Calhoun, V. D.

2008-01-01

We utilized a discrete dynamic Bayesian network (dDBN) approach (Burge et al., 2007) to determine differences in brain regions between patients with schizophrenia and healthy controls on a measure of effective connectivity, termed the approximate conditional likelihood score (ACL) (Burge and Lane, 2005). The ACL score represents a class-discriminative measure of effective connectivity by measuring the relative likelihood of the correlation between brain regions in one group versus another. The algorithm is capable of finding non-linear relationships between brain regions because it uses discrete rather than continuous values and attempts to model temporal relationships with a first-order Markov and stationary assumption constraint (Papoulis, 1991). Since Bayesian networks are overly sensitive to noisy data, we introduced an independent component analysis (ICA) filtering approach that attempted to reduce the noise found in fMRI data by unmixing the raw datasets into a set of independent spatial component maps. Components that represented noise were removed and the remaining components reconstructed into the dimensions of the original fMRI datasets. We applied the dDBN algorithm to a group of 35 patients with schizophrenia and 35 matched healthy controls using an ICA filtered and unfiltered approach. We determined that filtering the data significantly improved the magnitude of the ACL score. Patients showed the greatest ACL scores in several regions, most markedly the cerebellar vermis and hemispheres. Our findings suggest that schizophrenia patients exhibit weaker connectivity than healthy controls in multiple regions, including bilateral temporal and frontal cortices, plus cerebellum during an auditory paradigm. PMID:18602482

Application of ensemble back trajectory and factor analysis methods to aerosol data from Fort Meade, MD: Implications for sources

NASA Astrophysics Data System (ADS)

Chen, L. A.; Doddridge, B. G.; Dickerson, R. R.

2001-12-01

As the primary field experiment for Maryland Aerosol Research and CHaracterization (MARCH-Atlantic) study, chemically speciated PM2.5 has been sampled at Fort Meade (FME, 39.10° N 76.74° W) since July 1999. FME is suburban, located in the middle of the bustling Baltimore-Washington corridor, which is generally downwind of the highly industrialized Midwest. Due to this unique sampling location, the PM2.5 observed at FME is expected to be of both local and regional sources, with relative contributions varying temporally. This variation, believed to be largely controlled by the meteorology, influences day-to-day or seasonal profiles of PM2.5 mass concentration and chemical composition. Air parcel back trajectories, which describe the path of air parcels traveling backward in time from site (receptor), reflect changes in the synoptic meteorological conditions. In this paper, an ensemble back trajectory method is employed to study the meteorology associated with each high/low PM2.5 episode in different seasons. For every sampling day, the residence time of air parcels within the eastern US at a 1° x 1° x 500 m geographic resolution can be estimated in order to resolve areas likely dominating the production of various PM2.5 components. Local sources are found to be more dominant in winter than in summer. "Factor analysis" is based on mass balance approach, providing useful insights on air pollution data. Here, a newly developed factor analysis model (UNMIX) is used to extract source profiles and contributions from the speciated PM2.5 data. Combing the model results with ensemble back trajectory method improves the understanding of the source regions and helps partition the contributions from local or more distant areas. >http://www.meto.umd.edu/~bruce/MARCH-Atl.html

Insights into Silicate and Oxide Melt Structure from Amorphous, Non-Glass-Forming Materials

NASA Astrophysics Data System (ADS)

Stebbins, J. F.

2015-12-01

Many silicate and oxide liquids of interest in the Earth sciences and in technology cannot readily be quenched to glasses, either because of low silica contents (and hence low viscosity at the melting point and accompanying liquid 'fragility') or because of liquid-liquid unmixing at high temperature. Although in-situ, high temperature structural tools have been in use for decades and are rapidly developing, many methods are still most informative for glass samples quenched to ambient pressure and temperature, e.g. high-resolution solid-state NMR. Amorphous oxides, including alumina and silicate compositions, have widespread technological applications. These are generally deposited by a variety of high-energy sputtering methods, as films of thicknesses of 10's to 100's of nm. Using Al-27, Si-29, and O-17 NMR, we have recently shown that for such films, very similar short-range structure is seen in materials made by very different kinetic pathways, such as sol-gel synthesis vs. ion-beam sputtering. This path-independent structure suggests that these materials pass through transient equilibrium states during their formation, probably that of deeply supercooled liquids just above glass transition temperatures. In the HfO2-SiO2 and ZrO2-SiO2 systems, for example, samples have well-resolved O-17 NMR spectra, allowing quantitation of O sites with only Hf(Zr) neighbors (so-called "free" oxide ions), with mixed Hf(Zr) and Si neighbors, and Si only. The observed oxygen speciation agrees well with a simple thermodynamic model of one of the most fundamental equilibria in silicate systems, namely the reaction of bridging (Si-O-Si) and "free" (e.g. OHf3 and OHf4) oxide ions to produce "non-bridging" oxygens (e.g. Si-OHf2). This new approach to sampling such structural equilibria in compositions far outside the range of normal glass-forming liquids may provide new insights into more geological compositions as well, as well as in more general models of silicate melt chemistry.

Assessing the biophysical naturalness of grassland in eastern North Dakota with hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhou, Qiang

Over the past two decades, non-native species within grassland communities have quickly developed due to human migration and commerce. Invasive species like Smooth Brome grass (Bromus inermis) and Kentucky Blue Grass (Poa pratensis), seriously threaten conservation of native grasslands. This study aims to discriminate between native grasslands and planted hayfields and conservation areas dominated by introduced grasses using hyperspectral imagery. Hyperspectral imageries from the Hyperion sensor on EO-1 were acquired in late spring and late summer on 2009 and 2010. Field spectra for widely distributed species as well as smooth brome grass and Kentucky blue grass were collected from the study sites throughout the growing season. Imagery was processed with an unmixing algorithm to estimate fractional cover of green and dry vegetation and bare soil. As the spectrum is significantly different through growing season, spectral libraries for the most common species are then built for both the early growing season and late growing season. After testing multiple methods, the Adaptive Coherence Estimator (ACE) was used for spectral matching analysis between the imagery and spectral libraries. Due in part to spectral similarity among key species, the results of spectral matching analysis were not definitive. Additional indexes, "Level of Dominance" and "Band variance", were calculated to measure the predominance of spectral signatures in any area. A Texture co-occurrence analysis was also performed on both "Level of Dominance" and "Band variance" indexes to extract spatial characteristics. The results suggest that compared with disturbed area, native prairie tend to have generally lower "Level of Dominance" and "Band variance" as well as lower spatial dissimilarity. A final decision tree model was created to predict presence of native or introduced grassland. The model was more effective for identification of Mixed Native Grassland than for grassland dominated by a single species. The discrimination of native and introduced grassland was limited by the similarity of spectral signatures between forb-dominated native grasslands and brome-grass stands. However, saline native grasslands were distinguishable from brome grass.

Lunar and Planetary Science XXXV: Mars: Remote Sensing and Terrestrial Analogs

NASA Technical Reports Server (NTRS)

2004-01-01

The session "Mars: Remote Sensing and Terrestrial Analogs" included the following:Physical Meaning of the Hapke Parameter for Macroscopic Roughness: Experimental Determination for Planetary Regolith Surface Analogs and Numerical Approach; Near-Infrared Spectra of Martian Pyroxene Separates: First Results from Mars Spectroscopy Consortium; Anomalous Spectra of High-Ca Pyroxenes: Correlation Between Ir and M ssbauer Patterns; THEMIS-IR Emissivity Spectrum of a Large Dark Streak near Olympus Mons; Geomorphologic/Thermophysical Mapping of the Athabasca Region, Mars, Using THEMIS Infrared Imaging; Mars Thermal Inertia from THEMIS Data; Multispectral Analysis Methods for Mapping Aqueous Mineral Depostis in Proposed Paleolake Basins on Mars Using THEMIS Data; Joint Analysis of Mars Odyssey THEMIS Visible and Infrared Images: A Magic Airbrush for Qualitative and Quantitative Morphology; Analysis of Mars Thermal Emission Spectrometer Data Using Large Mineral Reference Libraries ; Negative Abundance : A Problem in Compositional Modeling of Hyperspectral Images; Mars-LAB: First Remote Sensing Data of Mineralogy Exposed at Small Mars-Analog Craters, Nevada Test Site; A Tool for the 2003 Rover Mini-TES: Downwelling Radiance Compensation Using Integrated Line-Sight Sky Measurements; Learning About Mars Geology Using Thermal Infrared Spectral Imaging: Orbiter and Rover Perspectives; Classifying Terrestrial Volcanic Alteration Processes and Defining Alteration Processes they Represent on Mars; Cemented Volcanic Soils, Martian Spectra and Implications for the Martian Climate; Palagonitic Mars: A Basalt Centric View of Surface Composition and Aqueous Alteration; Combining a Non Linear Unmixing Model and the Tetracorder Algorithm: Application to the ISM Dataset; Spectral Reflectance Properties of Some Basaltic Weathering Products; Morphometric LIDAR Analysis of Amboy Crater, California: Application to MOLA Analysis of Analog Features on Mars; Airborne Radar Study of Soil Moisture at a Mars Analog Site: Tohachi Wash/Little Colorado River; and Antarctic Dry Valleys: Modification of Rocks and Soils and Implications for Mars The Arkaroola Mars Analogue Region, South Australia.

How well do we characterize the biophysical effects of vegetation cover change? Benchmarking land surface models against satellite observations.

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Forzieri, Giovanni; Robertson, Eddy; Georgievski, Goran; Li, Wei; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Changes in vegetation cover can affect the climate by altering the carbon, water and energy cycles. The main tools to characterize such land-climate interactions for both the past and future are land surface models (LSMs) that can be embedded in larger Earth System models (ESMs). While such models have long been used to characterize the biogeochemical effects of vegetation cover change, their capacity to model biophysical effects accurately across the globe remains unclear due to the complexity of the phenomena. The result of competing biophysical processes on the surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate (e.g. presence of snow or soil moisture). Here we present a global scale benchmarking exercise of four of the most commonly used LSMs (JULES, ORCHIDEE, JSBACH and CLM) against a dedicated dataset of satellite observations. To facilitate the understanding of the causes that lead to discrepancies between simulated and observed data, we focus on pure transitions amongst major plant functional types (PFTs): from different tree types (evergreen broadleaf trees, deciduous broadleaf trees and needleleaf trees) to either grasslands or crops. From the modelling perspective, this entails generating a separate simulation for each PFT in which all 1° by 1° grid cells are uniformly covered with that PFT, and then analysing the differences amongst them in terms of resulting biophysical variables (e.g net radiation, latent and sensible heat). From the satellite perspective, the effect of pure transitions is obtained by unmixing the signal of different 0.05° spatial resolution MODIS products (albedo, latent heat, upwelling longwave radiation) over a local moving window using PFT maps derived from the ESA Climate Change Initiative land cover map. After aggregating to a common spatial support, the observation and model-driven datasets are confronted and analysed across different climate zones. Results indicate that models tend to catch better radiative than non-radiative energy fluxes. However, for various vegetation transitions, models do not agree amongst themselves on the magnitude nor the sign of the change. In particular, predicting the impact of land cover change on the partitioning of the available energy between latent and sensible heat proves to be a challenging task for vegetation models. We expect that this benchmarking exercise will shed a light on where to prioritize the efforts in model development as well as inform where consensus between model and observations is already met. Improving the robustness and consistency of land-model is essential to develop and inform land-based mitigation and adaptation policies that account for both biogeochemical and biophysical vegetation impacts on climate.

Spectroscopy as a diagnostic tool for urban soil

NASA Astrophysics Data System (ADS)

Brook, Anna; Kopel, Daniella; Wittenberg, Lea

2015-04-01

Anthropogenic urban soil are the foundation of the urban green infrastructure, the green net quality is as good as each of its patches. In early days of pedology urban soil has been recognized with respect to contamination and the risks for human health but in study performed since the 70s, the importance of urban soil for the urban ecology became increasingly significant (Gómez-Baggethun and Barton 2013). Urban soils are highly disturbed land that was created by the process of urbanization. The dominant agent in the creation of urban soils is human activity which modifies the natural soil through mixing, filling or by contamination of land surfaces so as to create a layer of urban soil which can be more than 50 cm thick (Pavao-Zuckerman 2008). The objective of this study is to determine the extent to which field spectroscopy methods can be used to extend the knowledge of urban soils features and components. The majority of the studies on urban soils concentrate on identifying and mapping of pollution mostly heavy metals. In this study a top-down analysis is developed - a simple and intuitive spectral feature for detecting the presence of minerals, organic matter and pollutants in mixed soil samples. The developed method uses spectral activity (SA) detection in a structured hierarchical approach to quickly and, more importantly, correctly identify dominant spectral features. The developed method is adopted by multiple in-production tools including continuum removal normalization, guided by polynomial generalization, and spectral-likelihood algorithms: orthogonal subspace projection (OSP) and iterative spectral mixture analysis (ISMA) were compared to feature likelihood methods (Li et al. 2014). Results of the proposed top-down unmixing method suggest that the analysis is made very fast due to the simplified hierarchy which avoids the high-learning curve associated with unmixing algorithms showed that the most abundant components were coarse organic matter 12% followed by concrete dust, plastic crumbs, other man made materials, clay and other minerals. The major part of the mineralogical composition was dominated by Montmorillonite and Kaolinite as is it expected to be in the Mount Carmel soils. Pyroxene and Olivine are also typical to the mineralogy of the Mount Carmel were there are several known magmatic eruption areas of Scoria and Basalt. There is a high frequency of Actinolite (Ca2(Mg,Fe)5(Si8O22)(OH)2), Amphibole family (2.5%) that is typical to metamorphic rocks that are not to be found in the Mount Carmel region. Some of the mineral found in the analysis is of marine origin like Syngenite (K2Ca(SO4)2(H2O)) and Blodite (Na2Mg(SO4)24(H2O)) as the area was created under the Mediterranean Sea and is still influence by it. None of the endmembers were detected only once, the lowest frequency was 4 times for Cyanide-Cadmium (Cd(CN)2) and Andalusite (Al2SiO5). The results of the soils pH, measured electrometrically and the particle size distribution, measured by Laser diffraction, indicate there is no big different between the samples particle size distribution and the pH values of the samples but they are not significantly different from the expected, except for the OM percentage which is significantly higher in most samples. The suggested method was very effective for tracing the man-made substances, we could find concrete and asphalt, plastic and synthetic polymers after they were assimilated, broken down and decomposed into soil particles. By the top-down unmixing method we did not limit the substances we characterize and so we could detect unexpected materials and contaminants. Gómez-Baggethun, Erik and David N. Barton. 2013. "Classifying and Valuing Ecosystem Services for Urban Planning." Ecological Economics 86: 235-245. Pavao-Zuckerman, M. A. 2008. "The Nature of Urban Soils and their Role in Ecological Restoration in Cities." Restoration Ecology 16 (4): 642-649. Li, Lijun, Peter E. Holm, Helle Marcussen, and Hans Christian Bruun Hansen. 2014. "Release of Cadmium, Copper and Lead from Urban Soils of Copenhagen." Environmental Pollution 187: 90-97.

Development Of Nutrient And Water Recycling Capabilities In Algae Biofuels Production Systems. Final Summary Report

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

Lundquist, Tryg; Spierling, Ruth; Poole, Kyle

The objective of this project was to develop and demonstrate methods of recycling of water and nutrients for algal biofuels production. Recycling was accomplished both internal to the system and, in a broader sense, through import and reuse of municipal wastewater. Such an integrated system with wastewater input had not been demonstrated previously, and the performance was unknown, particularly in terms of influence of recycling on algal productivity and the practical extent of nutrient recovery from biomass residuals. Through long-term laboratory and pilot research, the project resulted in the following: 1. Bench-scale pretreatment of algal biomass did not sufficiently increasemore » methane yield of nutrient solubilization during anaerobic digestion to warrant incorporation of pre-treatment into the pilot plant. The trial pretreatments were high-pressure orifice homogenization, sonication, and two types of heat treatment. 2. Solubilization of biomass particulate nutrients by lab anaerobic digesters ranged from 20% to nearly 60% for N and 40-65% for P. Subsequent aerobic degradation of the anaerobically digested biomass simulated raceways receiving whole digestate and resulted in an additional 20-55% N solubilization and additional 20% P solubilization. 3. Comparisons of laboratory and pilot digesters showed that laboratory units were reasonable proxies for pilot-scale. 4. Pilot-scale anaerobic digesters were designed, installed, and operated to digest algal biomass. Nutrient re-solubilization by the digesters was monitored and whole digestate was successfully used as a fertilizer in pilot algae raceways. 5. Unheated, unmixed digesters achieved greater methane yield and nutrient solubilization than heated, mixed digesters, presumably due to longer the solids residence times in unmixed digesters. The unmixed, unheated pilot digesters yielded 0.16 L CH4/g volatile solids (VS) introduced with 0.15 g VS/L-d organic loading and 16oC average temperature. A conventional heated mixed lab digester yielded 0.22 L CH4/g VS with 0.25 g VS/L-d and 30oC. The highest yield (0.30 L CH4/g VS) was achieved by the unmixed lab digesters operated at a constant 20oC. All digesters were operated with a 40-d hydraulic residence time. 6. In general, 50-75% of initial particulate N and P could be solubilized during anaerobic digestion and available for subsequent rounds of algae cultivation. 7. Bench-scale experiments showed the recovery from hydrothermal liquefaction (HTL) wastewater of carbon via anaerobic digestion and of nutrients to grow algae. To satisfy the nitrogen demand of algae cultivation, HTL wastewater would be diluted 400-fold, which was found to eliminate inhibition of algae growth by HTL wastewater. 8. Anaerobic digestion methane yield was lower for algal biomass containing coagulants such as would be used to aid harvesting or dewatering. Depending on doses, starch-based coagulant decreased yield by 10-14% and aluminum chlorohydrate decreased it by 14-26%. The lowest yield was 0.28 L CH 4/g volatile solids introduced to the digesters. 9. Algae harvested from raceways operated on recycled water had methane yields 13% higher than algae from raceways operated on both recycled water and nutrients provided by algae digestate. The slightly lower yield was expected due to the presence of previously digested biomass from the digestate fertilizer. 10. Defined media was replenished with nutrients and recycled repeatedly in sequential batch growth of Chlorella sorokiniana (DOE 1412). This laboratory study tested for inhibition and accumulation of inhibiting compounds (allelopathic or auto-inhibitory substances), information that would help estimate the blowdown ratio needed for an integrated system. In laboratory experiments in which water was recycled a total of five times, each successive round of reuse resulted in an average 4±3% reduction in log-phase specific growth rates. However, linear-phase growth inhibition was only observed in the final fifth round of reuse. 11. No decline in productivity was detected after 15 rounds of water recycling with nutrients provided by whole digestate in lab cultivation. Lab tests allowed for steady light and temperature, increasing the ability to detect inhibition. 12. In initial pilot inhibition studies, wastewater growth media was reused once while productivity was monitored. Media reuse was accomplished with triplicate sets of 33-m2 raceways operated in series. First-round gross productivity (based on effluent biomass flow) averaged 23 g/m 2-day annually while second-round gross productivity averaged 19 g/m 2-day annually. In terms of net productivity (based on raceway effluent biomass minus influent biomass), the first-round productivity averaged 15 g/m2-d and second round averaged 13 g/m 2-d during June-September operation. The higher productivity in the first-round ponds was likely due to heterotrophic/mixotrophic growth on the wastewater organic matter. 13. In a culminating pilot experiment, coagulant was used to decrease the carry-over of unsettled algae into subsequent rounds of growth. Over nearly 8 months, 93% of the media (the equivalent of 14 rounds of water reuse) was recycled without significant productivity loss compared to controls. Ponds receiving both recycled water and nutrients had net productivities of 14-24 g/m 2-d during fall and mid-summer, respectively. 14. Techno-economic analysis of the proposed facility found minimum fuel selling price to range from $7.01/gallon gasoline equivalent without revenue other than fuel to $3.85/GGE with revenue from wastewater treatment fees and LCFS and RIN (Low Carbon Fuel Standard and Renewable Identification Numbers) credits. 15. Life cycle assessment indicated GHG emissions of 40.7 g CO 2/MJ fuel and a net energy ratio (energy required/energy produced) of 0.37.« less

Determination of semi-arid landscape endmembers and seasonal trends using convex geometry spectral unmixing techniques

NASA Technical Reports Server (NTRS)

Yuhas, Roberta H.; Boardman, Joseph W.; Goetz, Alexander F. H.

1993-01-01

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired during three consecutive growing seasons (26 September 1989, 22 March 1990, and 7 August 1990) over an area of the High Plains east of Greeley, Colorado (40 deg 20 min N and 104 deg 16 min W). A repeat visit to assess vegetation at its peak growth was flown on 6 June 1993. This region contains extensive eolian deposits in the form of stabilized dune complexes (small scale parabolic dunes superimposed on large scale longitudinal and parabolic dunes). Due to the dunes' large scale (2-10 km) and low relief (1-5 m), the scaling and morphological relationships that contribute to the evolution of this landscape are nearly impossible to understand without the use of remote sensing. Additionally, this area and regions similarly situated could be the first to experience the effects caused by global climate change. During the past 10,000 years there were at least four periods of extensive sand activity due to climate change, followed by periods of landscape stability, as shown in the stratigraphic record of this area.

The globular cluster NGC 7492 and the Sagittarius tidal stream: together but unmixed

NASA Astrophysics Data System (ADS)

Carballo-Bello, J. A.; Corral-Santana, J. M.; Catelan, M.; Martínez-Delgado, D.; Muñoz, R. R.; Sollima, A.; Navarrete, C.; Duffau, S.; Côté, P.; Mora, M. D.

2018-03-01

We have derived from VIMOS spectroscopy the radial velocities for a sample of 71 stars selected from CFHT/Megacam photometry around the Galactic globular cluster NGC 7492. In the resulting velocity distribution, it is possible to distinguish two relevant non-Galactic kinematic components along the same line of sight: a group of stars at 〈vr〉 ˜ 125 km s-1 which is compatible with the velocity of the old leading arm of the Sagittarius tidal stream, and a larger number of objects at 〈vr〉 ˜ -110 km s-1 that might be identified as members of the trailing wrap of the same stream. The systemic velocity of NGC 7492 set at vr ˜ -177 km s-1 differs significantly from that of both components, thus our results confirm that this cluster is not one of the globular clusters deposited by the Sagittarius dwarf spheroidal in the Galactic halo, even if it is immersed in the stream. A group of stars with 〈vr〉 ˜ - 180 km s-1 might be comprised of cluster members along one of the tidal tails of NGC 7492.

Pristine Igneous Rocks and the Early Differentiation of Planetary Materials

NASA Technical Reports Server (NTRS)

Warren, Paul H.

2005-01-01

Our studies are highly interdisciplinary, but are focused on the processes and products of early planetary and asteroidal differentiation, especially the genesis of the ancient lunar crust. The compositional diversity that we explore is the residue of process diversity, which has strong relevance for comparative planetology. Most of the accessible lunar crust consists of materials hybridized by impact-mixing. Our lunar research concentrates on the rare pristine (unmixed) samples that reflect the original genetic diversity of the early crust. Among HED basalts (eucrites and clasts in howardites), we distinguish as pristine the small minority that escaped the pervasive thermal metamorphism of the parent asteroid's crust. We have found a correlation between metamorphically pristine HED basalts and the similarly small minority of compositionally evolved "Stannern trend" samples, which are enriched in incompatible elements and titanium compared to main group eucrites, and yet have relatively high mg ratios. Other topics under investigation included: lunar and SNC (martian?) meteorites; igneous meteorites in general; impact breccias, especially metal-rich Apollo samples and polymict eucrites; siderophile compositions of the lunar and martian mantles; and planetary bulk compositions and origins.

Changes in unique hues induced by chromatic surrounds.

PubMed

Klauke, Susanne; Wachtler, Thomas

2016-03-01

A chromatic surround can have a strong influence on the perceived hue of a stimulus. We investigated whether chromatic induction has similar effects on the perception of colors that appear pure and unmixed (unique red, green, blue, and yellow) as on other colors. Subjects performed unique hue settings of stimuli in isoluminant surrounds of different chromaticities. Compared with the settings in a neutral gray surround, unique hue settings altered systematically with chromatic surrounds. The amount of induced hue shift depended on the difference between stimulus and surround hues, and was similar for unique hue settings as for settings of nonunique hues. Intraindividual variability in unique hue settings was roughly twice as high as for settings obtained in asymmetric matching experiments, which may reflect the presence of a reference stimulus in the matching task. Variabilities were also larger with chromatic surrounds than with neutral gray surrounds, for both unique hue settings and matching of nonunique hues. The results suggest that the neural representations underlying unique hue percepts are influenced by the same neural processing mechanisms as the percepts of other colors.

Removal of BCG artifacts using a non-Kirchhoffian overcomplete representation.

PubMed

Dyrholm, Mads; Goldman, Robin; Sajda, Paul; Brown, Truman R

2009-02-01

We present a nonlinear unmixing approach for extracting the ballistocardiogram (BCG) from EEG recorded in an MR scanner during simultaneous acquisition of functional MRI (fMRI). First, an overcomplete basis is identified in the EEG based on a custom multipath EEG electrode cap. Next, the overcomplete basis is used to infer non-Kirchhoffian latent variables that are not consistent with a conservative electric field. Neural activity is strictly Kirchhoffian while the BCG artifact is not, and the representation can hence be used to remove the artifacts from the data in a way that does not attenuate the neural signals needed for optimal single-trial classification performance. We compare our method to more standard methods for BCG removal, namely independent component analysis and optimal basis sets, by looking at single-trial classification performance for an auditory oddball experiment. We show that our overcomplete representation method for removing BCG artifacts results in better single-trial classification performance compared to the conventional approaches, indicating that the derived neural activity in this representation retains the complex information in the trial-to-trial variability.

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.

Histochemical study of trans-polyisoprene accumulation by spectral confocal laser scanning microscopy and a specific dye showing fluorescence solvatochromism in the rubber-producing plant, Eucommia ulmoides Oliver.

PubMed

Nakazawa, Yoshihisa; Takeda, Tsuyoshi; Suzuki, Nobuaki; Hayashi, Tatsushi; Harada, Yoko; Bamba, Takeshi; Kobayashi, Akio

2013-09-01

A microscopic technique combining spectral confocal laser scanning microscopy with a lipophilic fluorescent dye, Nile red, which can emit trans-polyisoprene specific fluorescence, was developed, and unmixed images of synthesized trans-polyisoprene in situ in Eucommia ulmoides were successfully obtained. The images showed that trans-polyisoprene was initially synthesized as granules in non-articulated laticifers that changed shape to fibers during laticifer maturation. Non-articulated laticifers are developed from single laticiferous cells, which are differentiated from surrounding parenchyma cells in the cambium. Therefore, these observations suggested that trans-polyisoprene biosynthesis first started in laticifer cells as granules and then the granules accumulated and fused in the inner space of the laticifers over time. Finally, laticifers were filled with the synthesized trans-polyisoprene, which formed a fibrous structure fitting the laticifers shape. Both trans- and cis-polyisoprene are among the most important polymers naturally produced by plants, and this microscopic technique combined with histological study should provide useful information in the fields of plant histology, bioindustry and phytochemistry.

Desertification Assessment and Monitoring Based on Remote Sensing

NASA Astrophysics Data System (ADS)

Gao, Z.; del Barrio, G.; Li, X.

2016-08-01

The objective of Dragon 3 Project 10367 is the development of techniques research for desertification assessment and monitoring in China using remote sensing data in combination with climate and environmental-related data. The main achievements acquired during the last two years could be summarized as follows:(1) Photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) were estimated in Otindag sandy land by comparison of the pixel-invariant (Spectral Mixture Analysis, SMA) and pixel-variable (Multi-Endmember Spectral Mixture Analysis, MESMA, Automated Monte Carlo Unmixing Analysis, AutoMCU) methods, based on GF-1 data and field measured spectral library.(2) Based on GF-1 data, SMA was applied to solve vegetation cover and transitional sandy land detection in Zhenglan Banner, Inner Mongolia, China.(3) By defined a new indictor, Moisture-responded NPP(MNPP), a new method for identification of degraded lands was put forward, and the land degradation in Xinlin Gol league, Inner Mongolia Autonomous Region, China was assessed preliminarily. (4) The 2dRUE proved to be a good indicator for land degradation, based on which, land degradation status in the general potential extent of desertification in China (PEDC) was assessed.

Waste water biological purification plants of dairy products industry and energy management

NASA Astrophysics Data System (ADS)

Stepanov, Sergey; Solkina, Olga; Stepanov, Alexander; Zhukova, Maria

2017-10-01

The paper presents results of engineering and economical comparison of waste water biological purification plants of dairy products industry. Three methods of purification are compared: traditional biological purification with the use of secondary clarifiers and afterpurification through granular-bed filters, biomembrane technology and physical-and-chemical treatment together with biomembrane technology for new construction conditions. The improvement of the biological purification technology using nitro-denitrification and membrane un-mixing of sludge mixture is a promising trend in this area. In these calculations, an energy management which is widely applied abroad was used. The descriptions of the three methods are illustrated with structural schemes. Costs of equipment and production areas are taken from manufacturers’ data. The research is aimed at an engineering and economical comparison of new constructions of waste water purification of dairy products industry. The experiment demonstrates advantages of biomembrane technology in waste water purification. This technology offers prospects of 122 million rubles cost saving during 25 years of operation when compared with of the technology of preparatory reagent flotation and of 13.7 million rubles cost saving compared to the option of traditional biological purification.

A scaling theory for number-flux distributions generated during steady-state coagulation and settling and application to particles in Lake Zurich, Switzerland.

PubMed

Boehm, Alexandria B

2002-10-15

In this study, we extend the established scaling theory for cluster size distributions generated during unsteady coagulation to number-flux distributions that arise during steady-state coagulation and settling in an unmixed water mass. The scaling theory predicts self-similar number-flux distributions and power-law decay of total number flux with depth. The shape of the number-flux distributions and the power-law exponent describing the decay of the total number flux are shown to depend on the homogeneity and small i/j limit of the coagulation kernel and the exponent kappa, which describes the variation in settling velocity with cluster volume. Particle field measurements from Lake Zurich, collected by U. Weilenmann and co-workers (Limnol. Oceanogr.34, 1 (1989)), are used to illustrate how the scaling predictions can be applied to a natural system. This effort indicates that within the mid-depth region of Lake Zurich, clusters of the same size preferentially interact and large clusters react with one another more quickly than small ones, indicative of clusters coagulating in a reaction-limited regime.

Multispectral image restoration of historical documents based on LAAMs and mathematical morphology

NASA Astrophysics Data System (ADS)

Lechuga-S., Edwin; Valdiviezo-N., Juan C.; Urcid, Gonzalo

2014-09-01

This research introduces an automatic technique designed for the digital restoration of the damaged parts in historical documents. For this purpose an imaging spectrometer is used to acquire a set of images in the wavelength interval from 400 to 1000 nm. Assuming the presence of linearly mixed spectral pixels registered from the multispectral image, our technique uses two lattice autoassociative memories to extract the set of pure pigments conforming a given document. Through an spectral unmixing analysis, our method produces fractional abundance maps indicating the distributions of each pigment in the scene. These maps are then used to locate cracks and holes in the document under study. The restoration process is performed by the application of a region filling algorithm, based on morphological dilation, followed by a color interpolation to restore the original appearance of the filled areas. This procedure has been successfully applied to the analysis and restoration of three multispectral data sets: two corresponding to artificially superimposed scripts and a real data acquired from a Mexican pre-Hispanic codex, whose restoration results are presented.

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.

Significance of elevated K/Rb ratios in lower crustal rocks

NASA Technical Reports Server (NTRS)

Frost, B. Ronald; Frost, Carol D.

1988-01-01

The granulite uncertainty principle, which states that it is difficult or impossible to determine with certainty the maximum geopressure and geotemperature that a granulite has experienced, is addressed. Also, geochemical fingerprinting cannot always be used reliably in the nebulous region that is transitional between metamorphic and igneous environments. Ion exchange thermometers are typically useful to approximately 800 C in slowly cooled plutonic rocks unless one uses a reintegration technique on unmixed minerals, or unless a metastable mineral assemblage can be observed. It is argued that in most granulites, fossil temperatures are typically obliterated by reequilibration and/or deformation during slow cooling. Granulite metamorphism may be further complicated by the common association with igneous activity. The previously-used geochemical indicators such as high K/Rb ratios and LIL depletion may not be strictly the result of granulite facies metamorphic depletion, but also may result from igneous processes, which depend on bulk and mineral compositions and on the mineralogy of the protolith. Detailed geologic mapping will be the ultimate arbitrator of whether a given geochemical signature is the result of igneous or metamorphic processes.

A Protocol for Using Förster Resonance Energy Transfer (FRET)-force Biosensors to Measure Mechanical Forces across the Nuclear LINC Complex.

PubMed

Arsenovic, Paul T; Bathula, Kranthidhar; Conway, Daniel E

2017-04-11

The LINC complex has been hypothesized to be the critical structure that mediates the transfer of mechanical forces from the cytoskeleton to the nucleus. Nesprin-2G is a key component of the LINC complex that connects the actin cytoskeleton to membrane proteins (SUN domain proteins) in the perinuclear space. These membrane proteins connect to lamins inside the nucleus. Recently, a Förster Resonance Energy Transfer (FRET)-force probe was cloned into mini-Nesprin-2G (Nesprin-TS (tension sensor)) and used to measure tension across Nesprin-2G in live NIH3T3 fibroblasts. This paper describes the process of using Nesprin-TS to measure LINC complex forces in NIH3T3 fibroblasts. To extract FRET information from Nesprin-TS, an outline of how to spectrally unmix raw spectral images into acceptor and donor fluorescent channels is also presented. Using open-source software (ImageJ), images are pre-processed and transformed into ratiometric images. Finally, FRET data of Nesprin-TS is presented, along with strategies for how to compare data across different experimental groups.

Spectral mineral mapping for characterization of subtle geothermal prospects using ASTER data

NASA Astrophysics Data System (ADS)

Abubakar, A. J.; Hashim, M.; Pour, A. B.

2017-05-01

In this study, the performance of ASTER data is evaluated for mapping subtle geothermal prospects in an unexplored tropical region having a number of thermal springs. The study employed a simple Decorrelation stretch with specific absorptions to highlight possible alteration zones of interest related to Geothermal (GT) systems. Hydrothermal alteration minerals are subsequently mapped using Spectral Angle Mapper (SAM) and Linear Spectral Unmixing (LSU) algorithms to target representative minerals such as clays, carbonates and AL-OH minerals as indicators of GT activity. The results were validated through field GPS survey, rock sampling and laboratory analysis using latest smart lab X-Ray Diffractometer technology. The study indicates that ASTER broadband satellite data could be used to map subtle GT prospects with the aid of an in-situ verification. However, it also shows that ASTER could not discriminate within specie minerals especially for clays using SWIR bands. Subsequent studies are aimed at looking at both ASTER and Hyperion hyperspectral data in the same area as this could have significant implications for GT resource detection in unmapped aseismic and inaccessible tropical regions using available spaceborne data.

Development of a Front Tracking Method for Two-Phase Micromixing of Incompressible Viscous Fluids with Interfacial Tension in Solvent Extraction

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

Zhou, Yijie; Lim, Hyun-Kyung; de Almeida, Valmor F

2012-06-01

This progress report describes the development of a front tracking method for the solution of the governing equations of motion for two-phase micromixing of incompressible, viscous, liquid-liquid solvent extraction processes. The ability to compute the detailed local interfacial structure of the mixture allows characterization of the statistical properties of the two-phase mixture in terms of droplets, filaments, and other structures which emerge as a dispersed phase embedded into a continuous phase. Such a statistical picture provides the information needed for building a consistent coarsened model applicable to the entire mixing device. Coarsening is an undertaking for a future mathematical developmentmore » and is outside the scope of the present work. We present here a method for accurate simulation of the micromixing dynamics of an aqueous and an organic phase exposed to intense centrifugal force and shearing stress. The onset of mixing is the result of the combination of the classical Rayleigh- Taylor and Kelvin-Helmholtz instabilities. A mixing environment that emulates a sector of the annular mixing zone of a centrifugal contactor is used for the mathematical domain. The domain is small enough to allow for resolution of the individual interfacial structures and large enough to allow for an analysis of their statistical distribution of sizes and shapes. A set of accurate algorithms for this application requires an advanced front tracking approach constrained by the incompressibility condition. This research is aimed at designing and implementing these algorithms. We demonstrate verification and convergence results for one-phase and unmixed, two-phase flows. In addition we report on preliminary results for mixed, two-phase flow for realistic operating flow parameters.« less

Turbulent mixing& combustion in TNT explosions

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

Kuhl, A L; Ferguson, R E; Oppenheim, A K

2000-12-12

Effects of turbulent mixing induced by explosion of a 1-g spherical TNT charge in air are investigated. The detonation wave in the charge transforms the solid explosive (C{sub 7}H{sub 5}N{sub 3}O{sub 6}) to gaseous products, rich in C{sub (S)}, and CO. The detonation pressure ({approx}210 kb) causes the products to expand rapidly, driving a blast wave into the surrounding air (Brode, 1959). The interface between the products and air is unstable (Richtmyer, 1960; Meshkov, 1960; Anisimov & Zel'dovich, 1977). As shown in Collage Ia-c, this region rapidly transitions into a turbulent mixing layer (Kuhl, 1996). As the embedded shock, I,more » implodes, it draws the mixing structures (Taylor cavities) into the origin (Collage Id-e). In this way air becomes distributed throughout the hot detonation products gases. This process is enhanced by shock reflections from confining walls. In either case (confined or unconfined), rapid combustion takes place where the expanded detonation products play the role of fuel. This leads to a dramatic increase in chamber pressure (Fig. 1)-in contrast to a corresponding TNT explosion in nitrogen. The problem was modeled as turbulent combustion in an unmixed system at large Reynolds, Peclet and Damkohler numbers (Kuhl et al, 1997). The numerical solution was obtained by a high-order Godunov scheme (Colella & Glaz, 1985). Adaptive Mesh Refinement (Berger & Colella, 1989) was used to follow the turbulent mixing on the computational grid in as much detail as possible. The results reveal all the dynamic features (Fig. 2) of the exothermic process of combustion controlled by fluid-mechanic transport in a highly turbulent field (Kuhl & Oppenheim, 1997), in contrast to the conventional reaction-diffusion mechanism of Zel'dovich & Frank-Kamenetskii (1938).« less

Comparation of Organic and Elemental carbon concentrations in PM2.5 in five Mexican cities: Potencial Sources

NASA Astrophysics Data System (ADS)

Herrera Murillo, J.; Cardenas, B.; Campos-Ramos, A.; Blanco-Jimenez, S.; Angeles-Garcia, F.

2011-12-01

During 2006-2010 the National Center for Environmental Research and Training of the National Institute of Ecology of Mexico, carried out several short field studies in the cities of Salamanca, Gto, Tula, Hgo; Guadalajara, Jal; Toluca, Edo Mex; and Tijuana, BC to determine concentration and chemical compositions of PM2.5. These cities, although different in size population have all important industrial and area sources that contribute to high PM2.5 concentrations and therefore potential health impacts. Chemical analyses included organic and elemental carbon for which DRI Model 2001 Thermal/Optical Carbon Analyzer (Atmoslytic Inc, Calabasas, CA, USA) was used. Highest PM2.5 mass mean concentrations were obtained in Salamanca (46 μg/m3), followed by Toluca (43 μg/m3), Guadalajara (37 μg/m3), Tula (20 μg/m3) and Tijuana (18 μg/m3). For Salamanca and Tula, annual levels exceeded the Mexican PM2.5 annual standard of 15 μg/m3. Total carbonaceous aerosol accounted for 41.4%, 41.1%, 32.3%, 29.5% and 29.1% of PM2.5 mass in Tula, Toluca, Guadalajara, Salamanca and Tijuana, respectively. Higher OC2, OC3 and OC4 carbon fractions were observed in Guadalajara, Tijuana and Toluca, indicating an important contribution of gasoline and diesel vehicles emissions in these cities. As for Tula and Salamanca, cities in which refineries and power plants are present, OC3, OC4, EC1 and EC2 represent the higher fractions which could be attributed to stationary sources that use heavy fuels for their combustion process. UNMIX and PMF analyses were used in order to identify the most important sources that contributes to OC and EC concentrations.

Hyperspectral Image Classification using a Self-Organizing Map

NASA Technical Reports Server (NTRS)

Martinez, P.; Gualtieri, J. A.; Aguilar, P. L.; Perez, R. M.; Linaje, M.; Preciado, J. C.; Plaza, A.

2001-01-01

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Characterizing Drought Impacted Soils in the San Joaquin Valley of California Using Remote Sensing

NASA Astrophysics Data System (ADS)

Wahab, L. M.; Miller, D.; Roberts, D. A.

2017-12-01

California's San Joaquin Valley is an extremely agriculturally productive region of the country, and understanding the state of soils in this region is an important factor in maintaining this high productivity. In this study, we quantified changing soil cover during the drought and analyzed spatial changes in salinity, organic matter, and moisture using unique soil spectral characteristics. We used data from the Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) from Hyperspectral Infrared Imager (HyspIRI) campaign flights in 2013 and 2014 over the San Joaquin Valley. A mixture model was applied to both images that identified non- photosynthetic vegetation, green vegetation, and soil cover fractions through image endmembers of each of these three classes. We optimized the spectral library used to identify these classes with Iterative Endmember Selection (IES), and the images were unmixed using Multiple Endmember Spectral Mixture Analysis (MESMA). Maps of soil electrical conductivity, organic matter, soil saturated moisture, and field moisture were generated for the San Joaquin Valley based on indices developed by Ben-Dor et al. [2002]. Representative polygons were chosen to quantify changes between years. Maps of spectrally distinct soils were also generated for 2013 and 2014, in order to determine the spatial distribution of these soil types as well as their temporal dynamics between years. We estimated that soil cover increased by 16% from 2013-2014. Six spectrally distinct soil types were identified for the region, and it was determined that the distribution of these soil types was not constant for most areas between 2013 and 2014. Changes in soil pH, electrical conductivity, and soil moisture were strongly tied in the region between 2013 and 2014.

Interpreting spectral unmixing coefficients: From spectral weights to mass fractions

NASA Astrophysics Data System (ADS)

Grumpe, Arne; Mengewein, Natascha; Rommel, Daniela; Mall, Urs; Wöhler, Christian

2018-01-01

It is well known that many common planetary minerals exhibit prominent absorption features. Consequently, the analysis of spectral reflectance measurements has become a major tool of remote sensing. Quantifying the mineral abundances, however, is not a trivial task. The interaction between the incident light rays and particulate surfaces, e.g., the lunar regolith, leads to a non-linear relationship between the reflectance spectra of the pure minerals, the so-called ;endmembers;, and the surface's reflectance spectrum. It is, however, possible to transform the non-linear reflectance mixture into a linear mixture of single-scattering albedos of the Hapke model. The abundances obtained by inverting the linear single-scattering albedo mixture may be interpreted as volume fractions which are weighted by the endmember's extinction coefficient. Commonly, identical extinction coefficients are assumed throughout all endmembers and the obtained volume fractions are converted to mass fractions using either measured or assumed densities. In theory, the proposed method may cover different grain sizes if each grain size range of a mineral is treated as a distinct endmember. Here, we present a method to transform the mixing coefficients to mass fractions for arbitrary combinations of extinction coefficients and densities. The required parameters are computed from reflectance measurements of well defined endmember mixtures. Consequently, additional measurements, e.g., the endmember density, are no longer required. We evaluate the method based on laboratory measurements and various results presented in the literature, respectively. It is shown that the procedure transforms the mixing coefficients to mass fractions yielding an accuracy comparable to carefully calibrated laboratory measurements without additional knowledge. For our laboratory measurements, the square root of the mean squared error is less than 4.82 wt%. In addition, the method corrects for systematic effects originating from mixtures of endmembers showing a highly varying albedo, e.g., plagioclase and pyroxene.

ATMOSPHERIC AEROSOL SOURCE-RECEPTOR RELATIONSHIPS: THE ROLE OF COAL-FIRED POWER PLANTS

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

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2005-04-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of September 2004 through February 2005. Significant progress was made this project period on the analysis of ambient data, source apportionment, and deterministic modeling activities. The major experimental achievement this project period was the characterization of the mercury and fine particle emissions from two modern, large, commercial pulverized coal boilers. This testing completes the field work component of the Source Characterization Activity. This report highlights results from mercury emission measurements made using a dilution sampler. The measurements clearly indicate that mercury is beingmore » transformed from an oxidized to an elemental state within the dilution. However, wall effects are significant making it difficult to determine whether or not these changes occur in the gas phase or due to some interaction with the sampler walls. This report also presents results from an analysis that uses spherical aluminum silicate (SAS) particles as a marker for primary PM{sub 2.5} emitted from coal combustion. Primary emissions from coal combustion contribute only a small fraction of the PM{sub 2.5} mass (less than 1.5% in the summer and less than 3% in the winter) at the Pittsburgh site. Ambient SAS concentrations also appear to be reasonably spatially homogeneous. Finally, SAS emission factors measured at pilot-scale are consistent with measurements made at full-scale. This report also presents results from applying the Unmix and PMF models to estimate the contribution of different sources to the PM{sub 2.5} mass concentrations in Pittsburgh using aerosol composition information. Comparison of the two models shows similar source composition and contribution for five factors: crustal material, nitrate, an Fe, Mn, and Zn factor, specialty steel production, and a cadmium factor. PMF found several additional factors. Comparison between source contributions for the similar factors shows reasonable agreement between the two models. The sulfate factor shows the highest contribution to local PM{sub 2.5} with an annual average contribution of approximately 28% (from PMF). The nitrate, crustal material, and primary OC and EC factors also show significant contributions on the order of 10-14%. The sulfate factor is affected by photochemistry and therefore shows maximum values in summer.« less

Extraction and Analysis of Impervious Surfaces Based on a Spectral Un-Mixing Method Using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008

PubMed Central

Deng, Yingbin; Fan, Fenglei; Chen, Renrong

2012-01-01

Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd most important economic district of China, is chosen in this paper to extract the ISA information based on Landsat images of 1998, 2003 and 2008 by using a linear spectral un-mixing method and to monitor impervious surface change by analyzing the multi-temporal Landsat-derived fractional impervious surface. Results of this study were as follows: (1) the area of ISA in the PRD increased 79.09% from 1998 to 2003 and 26.88% from 2003 to 2008 separately; (2) the spatial distribution of ISA was described according to the 1998/2003 percentage respectively. Most of middle and high percentage ISA was located in northwestern and southeastern of the whole delta, and middle percentage ISA was mainly located in the city interior, high percentage ISA was mainly located in the suburban around the city accordingly; (3) the expanding direction and trend of high percentage ISA was discussed in order to understand the change of urban in this delta; High percentage ISA moved from inner city to edge of urban area during 1998–2003 and moved to the suburban area that far from the urban area mixed with jumpily and gradually during 2003–2008. According to the discussion of high percentage ISA spatial expanded direction, it could be found out that high percentage ISA moved outward from the centre line of Pearl River of the whole delta while a high ISA percentage in both shores of the Pearl River Estuary moved toward the Pearl River; (4) combining the change of ISA with social conditions, the driving relationship was analyzed in detail. It was evident that ISA percentage change had a deep relationship with the economic development of this region in the past ten years. Contemporaneous major sport events (16th Asia Games of Guangzhou, 26th Summer Universidad of Shenzhen) and the government policies also promoted the development of the ISA. Meanwhile, topographical features like the National Nature Reserve of China restricted and affected the expansion of the ISA. Above all, this paper attempted to extract ISA in a major region of the PRD; the temporal and spatial analyses to PRD ISA demonstrated the drastic changes in developed areas of China. These results were important and valuable for land use management, ecological protection and policy establishment. PMID:22438741

Extraction and analysis of impervious surfaces based on a spectral un-mixing method using Pearl River Delta of China Landsat TM/ETM+ imagery from 1998 to 2008.

PubMed

Deng, Yingbin; Fan, Fenglei; Chen, Renrong

2012-01-01

Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd most important economic district of China, is chosen in this paper to extract the ISA information based on Landsat images of 1998, 2003 and 2008 by using a linear spectral un-mixing method and to monitor impervious surface change by analyzing the multi-temporal Landsat-derived fractional impervious surface. Results of this study were as follows: (1) the area of ISA in the PRD increased 79.09% from 1998 to 2003 and 26.88% from 2003 to 2008 separately; (2) the spatial distribution of ISA was described according to the 1998/2003 percentage respectively. Most of middle and high percentage ISA was located in northwestern and southeastern of the whole delta, and middle percentage ISA was mainly located in the city interior, high percentage ISA was mainly located in the suburban around the city accordingly; (3) the expanding direction and trend of high percentage ISA was discussed in order to understand the change of urban in this delta; High percentage ISA moved from inner city to edge of urban area during 1998-2003 and moved to the suburban area that far from the urban area mixed with jumpily and gradually during 2003-2008. According to the discussion of high percentage ISA spatial expanded direction, it could be found out that high percentage ISA moved outward from the centre line of Pearl River of the whole delta while a high ISA percentage in both shores of the Pearl River Estuary moved toward the Pearl River; (4) combining the change of ISA with social conditions, the driving relationship was analyzed in detail. It was evident that ISA percentage change had a deep relationship with the economic development of this region in the past ten years. Contemporaneous major sport events (16th Asia Games of Guangzhou, 26th Summer Universidad of Shenzhen) and the government policies also promoted the development of the ISA. Meanwhile, topographical features like the National Nature Reserve of China restricted and affected the expansion of the ISA. Above all, this paper attempted to extract ISA in a major region of the PRD; the temporal and spatial analyses to PRD ISA demonstrated the drastic changes in developed areas of China. These results were important and valuable for land use management, ecological protection and policy establishment.

Multiband tissue classification for ultrasonic transmission tomography using spectral profile detection

NASA Astrophysics Data System (ADS)

Jeong, Jeong-Won; Kim, Tae-Seong; Shin, Dae-Chul; Do, Synho; Marmarelis, Vasilis Z.

2004-04-01

Recently it was shown that soft tissue can be differentiated with spectral unmixing and detection methods that utilize multi-band information obtained from a High-Resolution Ultrasonic Transmission Tomography (HUTT) system. In this study, we focus on tissue differentiation using the spectral target detection method based on Constrained Energy Minimization (CEM). We have developed a new tissue differentiation method called "CEM filter bank". Statistical inference on the output of each CEM filter of a filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We validate this method through 3-D inter/intra-phantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation in multiple tomographic slices. Also spectral coherence between target and object profiles of an identical tissue at different slices and phantoms is evaluated by conventional cross-correlation analysis. The performance of the proposed classifier is assessed using Receiver Operating Characteristic (ROC) analysis. Finally we apply our method to classify tiny structures inside a beef kidney such as Styrofoam balls (~1mm), chicken tissue (~5mm), and vessel-duct structures.

Optimizing homogenization by chaotic unmixing?

NASA Astrophysics Data System (ADS)

Weijs, Joost; Bartolo, Denis

2016-11-01

A number of industrial processes rely on the homogeneous dispersion of non-brownian particles in a viscous fluid. An ideal mixing would yield a so-called hyperuniform particle distribution. Such configurations are characterized by density fluctuations that grow slower than the standard √{ N}-fluctuations. Even though such distributions have been found in several natural structures, e.g. retina receptors in birds, they have remained out of experimental reach until very recently. Over the last 5 years independent experiments and numerical simulations have shown that periodically driven suspensions can self-assemble hyperuniformally. Simple as the recipe may be, it has one important disadvantage. The emergence of hyperuniform states co-occurs with a critical phase transition from reversible to non reversible particle dynamics. As a consequence the homogenization dynamics occurs over a time that diverges with the system size (critical slowing down). Here, we discuss how this process can be sped up by exploiting the stirring properties of chaotic advection. Among the questions that we answer are: What are the physical mechanisms in a chaotic flow that are relevant for hyperuniformity? How can we tune the flow parameters such to obtain optimal hyperuniformity in the fastest way? JW acknowledges funding by NWO (Netherlands Organisation for Scientific Research) through a Rubicon Grant.

Estimation of Biochemical Constituents From Fresh, Green Leaves By Spectrum Matching Techniques

NASA Technical Reports Server (NTRS)

Goetz, A. F. H.; Gao, B. C.; Wessman, C. A.; Bowman, W. D.

1990-01-01

Estimation of biochemical constituents in vegetation such as lignin, cellulose, starch, sugar and protein by remote sensing methods is an important goal in ecological research. The spectral reflectances of dried leaves exhibit diagnostic absorption features which can be used to estimate the abundance of important constituents. Lignin and nitrogen concentrations have been obtained from canopies by use of imaging spectrometry and multiple linear regression techniques. The difficulty in identifying individual spectra of leaf constituents in the region beyond 1 micrometer is that liquid water contained in the leaf dominates the spectral reflectance of leaves in this region. By use of spectrum matching techniques, originally used to quantify whole column water abundance in the atmosphere and equivalent liquid water thickness in leaves, we have been able to remove the liquid water contribution to the spectrum. The residual spectra resemble spectra for cellulose in the 1.1 micrometer region, lignin in the 1.7 micrometer region, and starch in the 2.0-2.3 micrometer region. In the entire 1.0-2.3 micrometer region each of the major constituents contributes to the spectrum. Quantitative estimates will require using unmixing techniques on the residual spectra.

Spec Tool; an online education and research resource

NASA Astrophysics Data System (ADS)

Maman, S.; Shenfeld, A.; Isaacson, S.; Blumberg, D. G.

2016-06-01

Education and public outreach (EPO) activities related to remote sensing, space, planetary and geo-physics sciences have been developed widely in the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev, Israel. These programs aim to motivate the learning of geo-scientific and technologic disciplines. For over the past decade, the facility hosts research and outreach activities for researchers, local community, school pupils, students and educators. As software and data are neither available nor affordable, the EPIF Spec tool was created as a web-based resource to assist in initial spectral analysis as a need for researchers and students. The tool is used both in the academic courses and in the outreach education programs and enables a better understanding of the theoretical data of spectroscopy and Imaging Spectroscopy in a 'hands-on' activity. This tool is available online and provides spectra visualization tools and basic analysis algorithms including Spectral plotting, Spectral angle mapping and Linear Unmixing. The tool enables to visualize spectral signatures from the USGS spectral library and additional spectra collected in the EPIF such as of dunes in southern Israel and from Turkmenistan. For researchers and educators, the tool allows loading collected samples locally for further analysis.

Phenological Unmixing of Sequential Wildfire and Windstorm Effects in the Southern Appalachians

NASA Astrophysics Data System (ADS)

Norman, S. P.; Hargrove, W. W.; Christie, W. M.

2017-12-01

High frequency observations of land surface phenology suggest that forest disturbances are remarkably common. Frequent high resolution imagery provides increasingly rich insights into local impacts. In this paper, we examine the impacts from two back-to-back disturbances in Great Smoky Mountains National Park located in the eastern deciduous hardwood forests of the Southeastern USA. In November 2016, the drought- and windstorm-associated Chimney Tops 2 fire creating large high severity patches on fire-adapted shrub and pine lands on wind-exposed slopes during the dormant season. Five months later, a high wind event from the same southern direction occurred on May 4th during mid-greenup and caused ephemeral leaf stripping and seasonally-persistent damage over this same area. High resolution Sentinel 2 satellite imagery captures change caused by both events, but effects must be interpreted in light of normal phenological transitions. In this paper, we map relative severity from both disturbances, then compare and contrast how these two disturbances were manifest topographically and vegetationally. This case study provides rare insight into the importance and characteristics of topographic exposure as it relates to different disturbance types, and how that may contribute to the resilience of ecological communities within this mountainous landscape.

Airborne multispectral detection of regrowth cotton fields

NASA Astrophysics Data System (ADS)

Westbrook, John K.; Suh, Charles P.-C.; Yang, Chenghai; Lan, Yubin; Eyster, Ritchie S.

2015-01-01

Effective methods are needed for timely areawide detection of regrowth cotton plants because boll weevils (a quarantine pest) can feed and reproduce on these plants beyond the cotton production season. Airborne multispectral images of regrowth cotton plots were acquired on several dates after three shredding (i.e., stalk destruction) dates. Linear spectral unmixing (LSU) classification was applied to high-resolution airborne multispectral images of regrowth cotton plots to estimate the minimum detectable size and subsequent growth of plants. We found that regrowth cotton fields can be identified when the mean plant width is ˜0.2 m for an image resolution of 0.1 m. LSU estimates of canopy cover of regrowth cotton plots correlated well (r2=0.81) with the ratio of mean plant width to row spacing, a surrogate measure of plant canopy cover. The height and width of regrowth plants were both well correlated (r2=0.94) with accumulated degree-days after shredding. The results will help boll weevil eradication program managers use airborne multispectral images to detect and monitor the regrowth of cotton plants after stalk destruction, and identify fields that may require further inspection and mitigation of boll weevil infestations.

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

PubMed

Peng, Tao; Bonamy, Ghislain M C; Glory-Afshar, Estelle; Rines, Daniel R; Chanda, Sumit K; Murphy, Robert F

2010-02-16

Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amount of fluorescence they contain. Unfortunately, this approach requires extensive hand-tuning of algorithms and is often cell type-dependent. Here we describe a machine-learning approach for estimating the amount of fluorescent signal in different subcellular compartments without hand tuning, requiring only the acquisition of separate training images of markers for each compartment. In testing on images of cells stained with mixtures of probes for different organelles, we achieved a 93% correlation between estimated and expected amounts of probes in each compartment. We also demonstrated that the method can be used to quantify drug-dependent protein translocations. The method enables automated and unbiased determination of the distributions of protein across cellular compartments, and will significantly improve imaging-based high-throughput assays and facilitate proteome-scale localization efforts.

Oil detection in the coastal marshes of Louisiana using MESMA applied to band subsets of AVIRIS data

USGS Publications Warehouse

Peterson, Seth H.; Roberts, Dar A.; Beland, Michael; Kokaly, Raymond F.; Ustin, Susan L.

2015-01-01

We mapped oil presence in the marshes of Barataria Bay, Louisiana following the Deepwater Horizon oil spill using Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) data. Oil and non-photosynthetic vegetation (NPV) have very similar spectra, differing only in two narrow hydrocarbon absorption regions around 1700 and 2300 nm. Confusion between NPV and oil is expressed as an increase in oil fraction error with increasing NPV, as shown by Multiple Endmember Spectral Mixture Analysis (MESMA) applied to synthetic spectra generated with known endmember fractions. Significantly, the magnitude of error varied depending upon the type of NPV in the mixture. To reduce error, we used stable zone unmixing to identify a nine band subset that emphasized the hydrocarbon absorption regions, allowing for more accurate detection of oil presence using MESMA. When this band subset was applied to post-spill AVIRIS data acquired over Barataria Bay on several dates following the 2010 oil spill, accuracies ranged from 87.5% to 93.3%. Oil presence extended 10.5 m into the marsh for oiled shorelines, showing a reduced oil fraction with increasing distance from the shoreline.

Mapping asphalt pavement aging and condition using multiple endmember spectral mixture analysis in Beijing, China

NASA Astrophysics Data System (ADS)

Pan, Yifan; Zhang, Xianfeng; Tian, Jie; Jin, Xu; Luo, Lun; Yang, Ke

2017-01-01

Asphalt road reflectance spectra change as pavement ages. This provides the possibility for remote sensing to be used to monitor a change in asphalt pavement conditions. However, the relatively narrow geometry of roads and the relatively coarse spatial resolution of remotely sensed imagery result in mixtures between pavement and adjacent landcovers (e.g., vegetation, buildings, and soil), increasing uncertainties in spectral analysis. To overcome this problem, multiple endmember spectral mixture analysis (MESMA) was used to map the asphalt pavement condition using Worldview-2 satellite imagery in this study. Based on extensive field investigation and in situ measurements, aged asphalt pavements were categorized into four stages-preliminarily aged, moderately aged, heavily aged, and distressed. The spectral characteristics in the first three stages were further analyzed, and a MESMA unmixing analysis was conducted to map these three kinds of pavement conditions from the Worldview-2 image. The results showed that the road pavement conditions could be detected well and mapped with an overall accuracy of 81.71% and Kappa coefficient of 0.77. Finally, a quantitative assessment of the pavement conditions for each road segment in this study area was conducted to inform road maintenance management.

Enhancing charge transfer kinetics by nanoscale catalytic cermet interlayer.

PubMed

An, Jihwan; Kim, Young-Beom; Gür, Turgut M; Prinz, Fritz B

2012-12-01

Enhancing the density of catalytic sites is crucial for improving the performance of energy conversion devices. This work demonstrates the kinetic role of 2 nm thin YSZ/Pt cermet layers on enhancing the oxygen reduction kinetics for low temperature solid oxide fuel cells. Cermet layers were deposited between the porous Pt cathode and the dense YSZ electrolyte wafer using atomic layer deposition (ALD). Not only the catalytic role of the cermet layer itself but the mixing effect in the cermet was explored. For cells with unmixed and fully mixed cermet interlayers, the maximum power density was enhanced by a factor of 1.5 and 1.8 at 400 °C, and by 2.3 and 2.7 at 450 °C, respectively, when compared to control cells with no cermet interlayer. The observed enhancement in cell performance is believed to be due to the increased triple phase boundary (TPB) density in the cermet interlayer. We also believe that the sustained kinetics for the fully mixed cermet layer sample stems from better thermal stability of Pt islands separated by the ALD YSZ matrix, which helped to maintain the high-density TPBs even at elevated temperature.

Neural basis of processing threatening voices in a crowded auditory world

PubMed Central

Mothes-Lasch, Martin; Becker, Michael P. I.; Miltner, Wolfgang H. R.

2016-01-01

In real world situations, we typically listen to voice prosody against a background crowded with auditory stimuli. Voices and background can both contain behaviorally relevant features and both can be selectively in the focus of attention. Adequate responses to threat-related voices under such conditions require that the brain unmixes reciprocally masked features depending on variable cognitive resources. It is unknown which brain systems instantiate the extraction of behaviorally relevant prosodic features under varying combinations of prosody valence, auditory background complexity and attentional focus. Here, we used event-related functional magnetic resonance imaging to investigate the effects of high background sound complexity and attentional focus on brain activation to angry and neutral prosody in humans. Results show that prosody effects in mid superior temporal cortex were gated by background complexity but not attention, while prosody effects in the amygdala and anterior superior temporal cortex were gated by attention but not background complexity, suggesting distinct emotional prosody processing limitations in different regions. Crucially, if attention was focused on the highly complex background, the differential processing of emotional prosody was prevented in all brain regions, suggesting that in a distracting, complex auditory world even threatening voices may go unnoticed. PMID:26884543

Raised incidence of ankylosing spondylitis among Inuit populations could be due to high HLA-B27 association and starch consumption.

PubMed

Rashid, Taha; Wilson, Clyde; Ebringer, Alan

2015-06-01

Ankylosing spondylitis (AS) is a chronic inflammatory arthritis mainly affecting the spinal joints. It would appear that the most likely causative agent in the development of AS is an environmental factor in the genetically susceptible, HLA-B27 positive, individuals. Extensive data from several countries support the notion that Klebsiella pneumonia bacteria are the most likely culprit in the causation of AS. These microbes possess antigens which resemble HLA-B27 and spinal collagens. Increased intake of high-starch diet is directly proportional to the gut-associated bacterial load, especially in the large intestine, and among these microbial agents, Klebsiella is considered as one of the main constituting components. Therefore, a low-starch diet intake alongside the currently used medical therapeutic modalities could be beneficial in the management of patients with early AS. It is suggested that a change in the dietary habits from high protein, low-starch marine components to the Westernized high-starch diet among the Inuit peoples of Alaska and Canada could be considered as one of the main contributing factors in the increased prevalence of AS during the last few decades within this genetically unmixed native population.

Hyperspectral cytometry.

PubMed

Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J

2014-01-01

Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.

The effect of mixing on fermentation of primary solids, glycerol, and biodiesel waste.

PubMed

Ghasemi, Marzieh; Randall, Andrew A

2018-03-01

In this study, the effect of mixing on volatile fatty acid (VFA) production and composition was investigated through running five identical bench-scale reactors that were filled with primary solid and dosed with either pure glycerol or biodiesel waste. Experimental results revealed that there was an inverse correlation between the mixing intensity and the VFA production. The total VFA production in the un-mixed reactor was 9,787 ± 3,601 mg COD/L, whereas in the reactor mixed at 100 rpm this dropped to 3,927 ± 1,175 mg COD/L, while both types of reactor were dosed with pure glycerol at the beginning of each cycle to reach the initial concentration of 1,000 mg/L (1,217 mg COD/L). Propionic acid was the dominant VFA in all the reactors except the reactor mixed at 30 rpm. It is hypothesized that low mixing facilitated hydrogen transfer between obligate hydrogen producing acetogens (OHPA) and hydrogen consuming acidogens in these non-methanogenic reactors. Also, in a narrower range of mixing (0 or 7 rpm), the total VFA production in biodiesel waste-fed reactors was considerably higher than that of pure glycerol-fed reactors.

Clean image synthesis and target numerical marching for optical imaging with backscattering light

PubMed Central

Pu, Yang; Wang, Wubao

2011-01-01

Scanning backscattering imaging and independent component analysis (ICA) are used to probe targets hidden in the subsurface of a turbid medium. A new correction procedure is proposed and used to synthesize a “clean” image of a homogeneous host medium numerically from a set of raster-scanned “dirty” backscattering images of the medium with embedded targets. The independent intensity distributions on the surface of the medium corresponding to individual targets are then unmixed using ICA of the difference between the set of dirty images and the clean image. The target positions are localized by a novel analytical method, which marches the target to the surface of the turbid medium until a match with the retrieved independent component is accomplished. The unknown surface property of the turbid medium is automatically accounted for by this method. Employing clean image synthesis and target numerical marching, three-dimensional (3D) localization of objects embedded inside a turbid medium using independent component analysis in a backscattering geometry is demonstrated for the first time, using as an example, imaging a small piece of cancerous prostate tissue embedded in a host consisting of normal prostate tissue. PMID:21483608

Microstructural characterization of dissimilar welds between Incoloy 800H and 321 Austenitic Stainless Steel

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

Sayiram, G., E-mail: sayiram.g@vit.ac.in; Arivazhagan, N.

2015-04-15

In this work, the microstructural character of dissimilar welds between Incoloy 800H and 321 Stainless Steel has been discussed. The microscopic examination of the base metals, fusion zones and interfaces was characterized using an optical microscope and scanning electron microscopy. The results revealed precipitates of Ti (C, N) in the austenitic matrix along the grain boundaries of the base metals. Migration of grain boundaries in the Inconel 82 weld metal was very extensive when compared to Inconel 617 weldment. Epitaxial growth was observed in the 617 weldment which increases the strength and ductility of the weld metal. Unmixed zone nearmore » the fusion line between 321 Stainless Steel and Inconel 82 weld metal was identified. From the results, it has been concluded that Inconel 617 filler metal is a preferable choice for the joint between Incoloy 800H and 321 Stainless Steel. - Highlights: • Failure mechanisms produced by dissimilar welding of Incoloy 800H to AISI 321SS • Influence of filler wire on microstructure properties • Contemplative comparisons of metallurgical aspects of these weldments • Microstructure and chemical studies including metallography, SEM–EDS • EDS-line scan study at interface.« less

Non-Intrusive Load Monitoring of HVAC Components using Signal Unmixing

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

Rahimpour, Alireza; Qi, Hairong; Fugate, David L

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving higher energy efficiency. In this paper, a novel non-intrusive load monitoring method based on group constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only measuring the whole building aggregated power signal. At the first level of this hierarchical approach, power consumptionmore » of the building is decomposed to energy consumption of the HVAC unit and all the other electrical devices operating in the building such as lighting and plug loads. Then, the estimated power signal of the HVAC is used for estimating the power consumption profile of the HVAC major electrical loads such as compressors, condenser fans and indoor blower. Experiments conducted on real data collected from a building testbed maintained at the Oak Ridge National Laboratory (ORNL) demonstrate high accuracy on the disaggregation task.« less

Enhancement of overwritten text in the Archimedes Palimpsest

NASA Astrophysics Data System (ADS)

Knox, Keith T.

2008-02-01

The Archimedes Palimpsest is a thousand-year old overwritten parchment manuscript, containing several treatises by Archimedes. Eight hundred years ago, it was erased, overwritten and bound into a prayer book. In the middle of the twentieth century, a few pages were painted over with forged Byzantine icons. Today, a team of imagers, scholars and conservators is recovering and interpreting the erased Archimedes writings. Two different methods have been used to reveal the erased undertext. Spectral information is obtained by illuminating the manuscript with narrow-band light from the ultraviolet, through the visible wavebands and into the near-infrared wavelengths. Characters are extracted by combining pairs of spectral bands or by spectral unmixing techniques adapted from remote sensing. Lastly, since all of the text was written with iron gall ink, X-Ray fluorescence has been used to expose the ink underneath the painted icons. This paper describes the use of color to enhance the erased text in the processed images and to make it visible to the scholars. Special pseudocolor techniques have been developed that significantly increase the contrast of the erased text and make it possible to be read by the scholars despite the presence of the obscuring, overlaid text.

Estimation of the number of fluorescent end-members for quantitative analysis of multispectral FLIM data.

PubMed

Gutierrez-Navarro, Omar; Campos-Delgado, Daniel U; Arce-Santana, Edgar R; Maitland, Kristen C; Cheng, Shuna; Jabbour, Joey; Malik, Bilal; Cuenca, Rodrigo; Jo, Javier A

2014-05-19

Multispectral fluorescence lifetime imaging (m-FLIM) can potentially allow identifying the endogenous fluorophores present in biological tissue. Quantitative description of such data requires estimating the number of components in the sample, their characteristic fluorescent decays, and their relative contributions or abundances. Unfortunately, this inverse problem usually requires prior knowledge about the data, which is seldom available in biomedical applications. This work presents a new methodology to estimate the number of potential endogenous fluorophores present in biological tissue samples from time-domain m-FLIM data. Furthermore, a completely blind linear unmixing algorithm is proposed. The method was validated using both synthetic and experimental m-FLIM data. The experimental m-FLIM data include in-vivo measurements from healthy and cancerous hamster cheek-pouch epithelial tissue, and ex-vivo measurements from human coronary atherosclerotic plaques. The analysis of m-FLIM data from in-vivo hamster oral mucosa identified healthy from precancerous lesions, based on the relative concentration of their characteristic fluorophores. The algorithm also provided a better description of atherosclerotic plaques in term of their endogenous fluorophores. These results demonstrate the potential of this methodology to provide quantitative description of tissue biochemical composition.

Ancient Genomics and the Peopling of the Southwest Pacific

PubMed Central

Skoglund, Pontus; Posth, Cosimo; Sirak, Kendra; Spriggs, Matthew; Valentin, Frederique; Bedford, Stuart; Clark, Geoffrey; Reepmeyer, Christian; Petchey, Fiona; Fernandes, Daniel; Fu, Qiaomei; Harney, Eadaoin; Lipson, Mark; Mallick, Swapan; Novak, Mario; Rohland, Nadin; Stewardson, Kristin; Abdullah, Syafiq; Cox, Murray P.; Friedlaender, Françoise R.; Friedlaender, Jonathan S.; Kivisild, Toomas; Koki, George; Kusuma, Pradiptajati; Merriwether, D. Andrew; Ricaut, Francois-X.; Wee, Joseph T. S.; Patterson, Nick; Krause, Johannes; Pinhasi, Ron; Reich, David

2017-01-01

The appearance of people associated with the Lapita culture in the South Pacific ~3,000 years ago1 marked the beginning of the last major human dispersal to unpopulated lands. However, the relationship of these pioneers to the long established Papuans of the New Guinea region is unclear. We report genome-wide ancient DNA data from four individuals from Vanuatu (~3100-2700 years before present) and Tonga (~2700-2300 years before present), and co-analyze them with 778 present-day East Asians and Oceanians. Today, indigenous peoples of the South Pacific harbor a mixture of ancestry from Papuans and a population of East Asian origin that does not exist in unmixed form today, but is a match to the ancient individuals. Most analyses have interpreted the minimum of twenty-five percent Papuan ancestry in the region today as evidence that the first humans to reach Remote Oceania, including Polynesia, were derived from population mixtures near New Guinea, prior to the further expansion into Remote Oceania2–5. However, our finding that the ancient individuals had little to no Papuan ancestry implies later human population movements that spread Papuan ancestry through the South Pacific after the islands’ first peopling. PMID:27698418

Level dependence of distortion product otoacoustic emission phase is attributed to component mixing

PubMed Central

Abdala, Carolina; Dhar, Sumitrajit; Kalluri, Radha

2011-01-01

Distortion product otoacoustic emissions (DPOAEs) measured in the ear canal represent the vector sum of components produced at two regions of the basilar membrane by distinct cochlear mechanisms. In this study, the effect of stimulus level on the 2f1 − f2 DPOAE phase was evaluated in 22 adult subjects across a three-octave range. Level effects were examined for the mixed DPOAE signal measured in the ear canal and after unmixing components to assess level effects individually on the distortion (generated at the f1, f2 overlap) and reflection (at fdp) sources. Results show that ear canal DPOAE phase slope becomes steeper with decreasing level; however, component analysis further explicates this result, indicating that interference between DPOAE components (rather than a shift in mechanics related to distortion generation) drives the level dependence of DPOAE phase measured in the ear canal. The relative contribution from the reflection source increased with decreasing level, producing more component interference and, at times, a reflection-dominated response at the lowest stimulus levels. These results have implications for the use of DPOAE phase to study cochlear mechanics and for the potential application of DPOAE phase for clinical purposes. PMID:21568415

Raman spectroscopic imaging as complementary tool for histopathologic assessment of brain tumors

NASA Astrophysics Data System (ADS)

Krafft, Christoph; Bergner, Norbert; Romeike, Bernd; Reichart, Rupert; Kalff, Rolf; Geiger, Kathrin; Kirsch, Matthias; Schackert, Gabriele; Popp, Jürgen

2012-02-01

Raman spectroscopy enables label-free assessment of brain tissues and tumors based on their biochemical composition. Combination of the Raman spectra with the lateral information allows grading of tumors, determining the primary tumor of brain metastases and delineating tumor margins - even during surgery after coupling with fiber optic probes. This contribution presents exemplary Raman spectra and images collected from low grade and high grade regions of astrocytic gliomas and brain metastases. A region of interest in dried tissue sections encompassed slightly increased cell density. Spectral unmixing by vertex component analysis (VCA) and N-FINDR resolved cell nuclei in score plots and revealed the spectral contributions of nucleic acids, cholesterol, cholesterol ester and proteins in endmember signatures. The results correlated with the histopathological analysis after staining the specimens by hematoxylin and eosin. For a region of interest in non-dried, buffer immersed tissue sections image processing was not affected by drying artifacts such as denaturation of biomolecules and crystallization of cholesterol. Consequently, the results correspond better to in vivo situations. Raman spectroscopic imaging of a brain metastases from renal cell carcinoma showed an endmember with spectral contributions of glycogen which can be considered as a marker for this primary tumor.

Comparison of the mineral composition of the sediment found in two Mars dunefields: Ogygis Undae and Gale crater - three distinct endmembers identified

NASA Astrophysics Data System (ADS)

Charles, Heather; Titus, Timothy; Hayward, Rosalyn; Edwards, Christopher; Ahrens, Caitlin

2017-01-01

The composition of two dune fields, Ogygis Undae and the NE-SW trending dune field in Gale crater (the "Bagnold Dune Field" and "Western Dune Field"), were analyzed using thermal emission spectra from the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) and the Mars Odyssey Thermal Emission Imaging System (THEMIS). The Gale crater dune field was used as a baseline as other orbital compositional analyses have been conducted, and in situ sampling results will soon be available. Results from unmixing thermal emission spectra showed a spatial variation between feldspar mineral abundances and pyroxene mineral abundances in Ogygis Undae. Other datasets, including nighttime thermal inertia values, also showed variation throughout the dune field. One explanation proposed for this variation is a bimodal distribution of two sand populations. This distribution is seen in some terrestrial dune fields. The two dune fields varied in both mineral types present and in uniformity of composition. These differences point to different source lithologies and different distances travelled from source material. Examining these differences further will allow for a greater understanding of aeolian processes on Mars.

AIRSAR Data for Geological and Geomorphological Mapping in the Great Sandy Desert and Pilbara Regions of Western Australia

NASA Technical Reports Server (NTRS)

Tapley, Ian J.

1996-01-01

Enhancements of AIRSAR data have demonstrated the benefits of synthetic aperture radar (SAR) for revealing an additional and mich higher level of information about the composition of the terrain than enhancements f either SPOT-PAN or Landsat TM data. With appropriate image processing techniques, surface and near surface geological structures, hydrological systems (both current and ancient) and landform features, have been evidenced in a diverse range of landscapes. In the Great Sandy Desert region where spectral variability is minimal, radar's sensitivity to the micromorphology of sparse exposures of subcrop and lag gravels has provided a new insight into the region's geological framework, its landforms, and their evolution. In the Pilbara region, advanced processing of AIRSAR data to unmix the backscatter between and within the three frequencies of data has highlighted subsurface extensions of greenstone lithologies below sand cover and morphological evidence of past flow conditions under former climate regimes. On the basis of these observations, it is recommend that radar remote sensing technology involving the use of high resolution, polarimetric data be seriously considered as a viable tool for exploration in erosional and depositional environments located within Australia's mineral and oil-prospective provinces.

Comparison of the mineral composition of the sediment found in two Mars dunefields: Ogygis Undae and Gale crater – three distinct endmembers identified

USGS Publications Warehouse

Charles, Heather; Titus, Timothy N.; Hayward, Rosalyn; Edwards, Christopher; Ahrens, Caitlin

2016-01-01

The composition of two dune fields, Ogygis Undae and the NE–SW trending dune field in Gale crater (the “Bagnold Dune Field” and “Western Dune Field”), were analyzed using thermal emission spectra from the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) and the Mars Odyssey Thermal Emission Imaging System (THEMIS). The Gale crater dune field was used as a baseline as other orbital compositional analyses have been conducted, and in situ sampling results will soon be available.Results from unmixing thermal emission spectra showed a spatial variation between feldspar mineral abundances and pyroxene mineral abundances in Ogygis Undae. Other datasets, including nighttime thermal inertia values, also showed variation throughout the dune field. One explanation proposed for this variation is a bimodal distribution of two sand populations. This distribution is seen in some terrestrial dune fields.The two dune fields varied in both mineral types present and in uniformity of composition. These differences point to different source lithologies and different distances travelled from source material. Examining these differences further will allow for a greater understanding of aeolian processes on Mars.

Laser microprobe analyses of noble gas isotopes and halogens in fluid inclusions: Analyses of microstandards and synthetic inclusions in quartz

USGS Publications Warehouse

Böhlke, J.K.; Irwin, J.J.

1992-01-01

Ar, Kr, Xe, Cl, Br, I, and K abundances and isotopic compositions have been measured in microscopic fluid inclusions in minerals by noble gas mass spectrometry following neutron irradiation and laser extraction. The laser microprobe noble gas mass spectrometric (LMNGMS) technique was quantified by use of microstandards, including air-filled capillary tubes, synthetic basalt glass grains, standard hornblende grains, and synthetic fluid inclusions in quartz. Common natural concentrations of halogens (Cl, Br, and I) and noble gases (Ar and Kr) in trapped groundwaters and hydrothermal fluids can be analyzed simultaneously by LMNGMS in as little as 10−11 L of inclusion fluid, with accuracy and precision to within 5–10% for element and isotope ratios. Multicomponent element and isotope correlations indicate contaminants or persistent reservoirs of excess Xe and/or unfractionated air in some synthetic and natural fluid inclusion samples. LMNGMS analyses of natural fluid inclusions using the methods and calibrations reported here may be used to obtain unique information on sources of fluids, sources of fluid salinity, mixing, boiling (or unmixing), and water-rock interactions in ancient fluid flow systems.

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.

Contribution of non-negative matrix factorization to the classification of remote sensing images

NASA Astrophysics Data System (ADS)

Karoui, M. S.; Deville, Y.; Hosseini, S.; Ouamri, A.; Ducrot, D.

2008-10-01

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. The classification process requires some pre-processing, especially for data size reduction. The most usual technique is Principal Component Analysis. Another approach consists in regarding each pixel of the multispectral image as a mixture of pure elements contained in the observed area. Using Blind Source Separation (BSS) methods, one can hope to unmix each pixel and to perform the recognition of the classes constituting the observed scene. Our contribution consists in using Non-negative Matrix Factorization (NMF) combined with sparse coding as a solution to BSS, in order to generate new images (which are at least partly separated images) using HRV SPOT images from Oran area, Algeria). These images are then used as inputs of a supervised classifier integrating textural information. The results of classifications of these "separated" images show a clear improvement (correct pixel classification rate improved by more than 20%) compared to classification of initial (i.e. non separated) images. These results show the contribution of NMF as an attractive pre-processing for classification of multispectral remote sensing imagery.

NIR & MIR spectroscopy as an effective tool for detecting urban influences on soils

NASA Astrophysics Data System (ADS)

Brook, Anna; Kopel, Daniella; Wittenberg, Lea

2016-04-01

Soil supports ecosystem functions and services, sustains ecosystems and biodiversity, yet in the urban spreading world of today, soil as a resource is in constant danger. Human society takes for granted the services provided by open green patches allocated within and nearby cities, with no consideration of ramifications of urban development on those areas. The urban ecology science recognizes the need to learn, identify and monitor the soils of cities - urban soils. The definitions of those soils are mainly descriptive, since urban soils do not submitted to the pedological process as natural soils. The main objective of this paper is to characterize urban soils in open green undisturbed patches by mineralogical composition. This goal was achieved using field and laboratory spectroscopy across visible near, short wave infrared regions and laboratory thermal mid infrared region. The majority of the studies on urban soils concentrate on identifying and mapping of pollution mostly heavy metals. In this study a top-down analysis (a simple and intuitive spectral feature for detecting the presence of minerals, organic matter and pollutants in mixed soil samples) is applied. This method uses spectral activity (SA) detection in a structured hierarchical approach to quickly and, more importantly, correctly identify dominant spectral features. The applied method is adopted by multiple in-production tools including continuum removal normalization, guided by polynomial generalization, and spectral-likelihood algorithms: orthogonal subspace projection (OSP) and iterative spectral mixture analysis (ISMA) were compared to feature likelihood methods. A total of 70 soil samples were collected at different locations: in remnant area within the city (edge and core), on the borders of the neighborhoods (edge) and in the fringe zone and in 2 locations in the protected park. The park samples were taken in locations found more than 100m from roads or direct anthropogenic disturbances. The samples were collected outside the setback of the residential areas (edge), and the fringe samples were taken away from the edge, where construction debris or waste was no longer visible - approximately 18 m-50 m down the slopes. The samples were taken from the upper layer of the soils, after the course organic or trash residues were removed. A soil sample drill, 5 cm in diameter and 10 cm deep, was used collecting up to 100 ml sample caps. The samples were air-dried, sifted through a 2 mm sieve to remove large particles and rock fragments and ground to <200 nm samples for spectral analysis across 400-2500 nm and laboratory mid-IR analysis. A ratio between the spectral features of soils' aliphatic and aromatic groups and calcite or hydroxyls to estimate the total organic matter via method proposed by Dlapa et al., 2014; base on the ratio indices between aliphatic hydrocarbons (3000-2800cm-1) to calcite mineral (peak area at 875cm-1, central wave length) and between carboxyl aromatic groups (1800-1200cm-1) to calcite mineral, were calculated for soil total carbon estimation. Results of the proposed top-down unmixing method suggest that the analysis is made very fast due to the simplified hierarchy which avoids the high-learning curve associated with unmixing algorithms showed that the most abundant components found in the all the samples taken within city boundaries were organic matter. In the "organic matter" category, we summarized all forms of vegetation endmembers including coarse vegetation and organic carbon. The second component was concrete followed by plastic and bricks. We found traces of concrete in all the urban study samples, even samples taken as far as 150 m from the edge of patches. In the park soils, we found a low diversity of materials and only two identifications of anthropogenic substances. The results of the soils pH, measured electrometrically and the particle size distribution, measured by Laser diffraction, indicate there is no difference between the samples particle size distribution and the pH values of the samples but they are not significantly different from the expected, except for the OM percentage. The suggested method was very effective for tracing the man-made substances, we could find concrete and asphalt, plastic and synthetic polymers after they were assimilated, broken down and decomposed into soil particles. By the top-down unmixing method we did not limit the substances we characterize and so we could detect unexpected materials and contaminants.

Pristine Igneous Rocks and the Early Differentiation of Planetary Materials

NASA Technical Reports Server (NTRS)

Warren, Paul H.

1998-01-01

Our studies are highly interdisciplinary, but are focused on the processes and products of early planetary and asteroidal differentiation, especially the genesis of the ancient lunar crust. Most of the accessible lunar crust consists of materials hybridized by impact-mixing. Rare pristine (unmixed) samples reflect the original genetic diversity of the early crust. We studied the relative importance of internally generated melt (including the putative magma ocean) versus large impact melts in early lunar magmatism, through both sample analysis and physical modeling. Other topics under investigation included: lunar and SNC (martian?) meteorites; igneous meteorites in general; impact breccias, especially metal-rich Apollo samples and polymict eucrites; effects of regolith/megaregolith insulation on thermal evolution and geochronology; and planetary bulk compositions and origins. We investigated the theoretical petrology of impact melts, especially those formed in large masses, such as the unejected parts of the melts of the largest lunar and terrestrial impact basins. We developed constraints on several key effects that variations in melting/displacement ratio (a strong function of both crater size and planetary g) have on impact melt petrology. Modeling results indicate that the impact melt-derived rock in the sampled, megaregolith part of the Moon is probably material that was ejected from deeper average levels than the non-impact-melted material (fragmental breccias and unbrecciated pristine rocks). In the largest lunar impacts, most of the impact melt is of mantle origin and avoids ejection from the crater, while most of the crust, and virtually all of the impact-melted crust, in the area of the crater is ejected. We investigated numerous extraordinary meteorites and Apollo rocks, emphasizing pristine rocks, siderophile and volatile trace elements, and the identification of primary partial melts, as opposed to partial cumulates. Apollo 15 sample 15434,28 is an extraodinarily large glass spherule, nearly if not entirely free of meteoritic contamination, and provides insight into the diversity of mare basalts in the Hadley-Apennine region. Apollo 14 sample 14434 is in many respects a new rock type, intermediate between nonmare gabbronorites and mare basalts. We helped to both plan and implement a consortium to study the Yamato-793605 SNC/martian meteorite.