Academic Articles

May 2012
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Vegetation cover analysis of hazardous waste sites in utah and arizona using hyperspectral remote sensing

This study investigated the usability of hyperspectral remote sensing for characterizing vegetation at hazardous waste sites. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. HyMap airborne data (126 bands at 2.3 × 2.3 m spatial resolution), collected over the U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona, were used. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. Regression trees resulted in the best calibration performance of LAI estimation (R² > 0.80. The use of REPs failed to accurately predict LAI (R² < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (<1 m) found on the sites. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: GROUND vegetation cover, HAZARDOUS waste sites -- Field screening, MACHINE learning, PHYTOREMEDIATION, REMOTE sensing, VEGETATION mapping
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Two linear unmixing algorithms to recognize targets using supervised classification and orthogonal rotation in airborne hyperspectral images

The goal of the paper is to detect pixels that contain targets of known spectra. The target can be present in a sub- or above pixel. Pixels without targets are classified as background pixels. Each pixel is treated via the content of its neighborhood. A pixel whose spectrum is different from its neighborhood is classified as a “suspicious point”. In each suspicious point there is a mix of target(s) and background. The main objective in a supervised detection (also called “target detection”) is to search for a specific given spectral material (target) in hyperspectral imaging (HSI) where the spectral signature of the target is known a priori from laboratory measurements. In addition, the fractional abundance of the target is computed. To achieve this we present two linear unmixing algorithms that recognize targets with known (given) spectral signatures. The CLUN is based on automatic feature extraction from the target’s spectrum. These features separate the target from the background. The ROTU algorithm is based on embedding the spectra space into a special space by random orthogonal transformation and on the statistical properties of the embedded result. Experimental results demonstrate that the targets’ locations were extracted correctly and these algorithms are robust and efficient. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: ALGORITHMS, IMAGE converters, ORTHOGONALIZATION methods, PARAMETER estimation, PIXELS, REMOTE sensing, SPECTROPHOTOMETRY
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Trpv1 antagonists and chronic pain: beyond thermal perception

In the last decade, considerable evidence as accumulated to support the development of Transient Receptor Potential Vanilloid 1 (TRPV1) antagonists for the treatment of various chronic pain conditions. Whereas there is a widely accepted rationale for the development of TRPV1 antagonists for the treatment of various inflammatory pain conditions, their development for indications of chronic pain, where conditions of tactical, mechanical and spontaneous pain predominate, is less clear. Preclinical localization and expression studies provide a firm foundation for the use of molecules targeting TRPV1 for conditions of bone pain, osteoarthritis and neuropathic pain. Selective TRPV1 antagonists weakly attenuate tactile and mechanical hypersensivity and are partially effective for behavioral and electrophysiological endpoints that incorporate aspects of spontaneous pain. While initial studies with TRPV1 antagonist in normal human subjects indicate a loss of warm thermal perception, clinical studies assessing allelic variants suggests that TRPV1 may mediate other sensory modalities under certain conditions. The focus of this review is to summarize the current perspectives of TRPV1 for the treatment of conditions beyond those with a primary thermal sensitivity. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: CHRONIC pain, NEURALGIA, OSTEOARTHRITIS, PUBLIC health, TRP channelsMECHANOTRANSDUCTION (Cytology)
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Tree species detection accuracies using discrete point lidar and airborne waveform lidar

Species information is a key component of any forest inventory. However, when performing forest inventory from aerial scanning Lidar data, species classification can be very difficult. We investigated changes in classification accuracy while identifying five individual tree species (Douglas-fir, western redcedar, bigleaf maple, red alder, and black cottonwood) in the Pacific Northwest United States using two data sets: discrete point Lidar data alone and discrete point data in combination with waveform Lidar data. Waveform information included variables which summarize the frequency domain representation of all waveforms crossing individual trees. Discrete point data alone provided 79.2 percent overall accuracy (kappa = 0.74) for all 5 species and up to 97.8 percent (kappa = 0.96) when comparing individual pairs of these 5 species. Incorporating waveform information improved the overall accuracy to 85.4 percent (kappa = 0.817) for five species, and in several two-species comparisons. Improvements were most notable in comparing the two conifer species and in comparing two of the three hardwood species. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: CATHODE ray oscillographs, FOREST mapping, FOURIER transform optics, MULTIPURPOSE trees, OPTICAL radar, SUPPORT vector machines
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Synthesis and properties of poly(isothianaphthene methine)s with chiral alkyl chain

We synthesized poly(isothianaphthene methine)s with chiral alkyl chains in the substituent. Resultant polymers are soluble in THF and CHCl3. Structure of the polymers was characterized with FT-IR, FT-Raman, and UV-Vis-NIR optical absorption spectroscopy. They showed low-bandgap both in solution and in a form of film. Optical activity of the polymers was confirmed with optical rotatory dispersion. Doping effects on the polymer were also examined with UV-Vis-NIR spectroscopy and ESR measurement. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: ALKYLATION, CARBON compounds -- Spectra, CARBYNES, CHEMICAL reactions, CHIRALITY, NEAR infrared spectroscopy
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Structure based antibody-like peptidomimetics

Biologics such as monoclonal antibodies (mAb) and soluble receptors represent new classes of therapeutic agents for treatment of several diseases. High affinity and high specificity biologics can be utilized for variety of clinical purposes. Monoclonal antibodies have been used as diagnostic agents when coupled with radionuclide, immune modulatory agents or in the treatment of cancers. Among other limitations of using large molecules for therapy the actual cost of biologics has become an issue. There is an effort among chemists and biologists to reduce the size of biologics which includes monoclonal antibodies and receptors without a reduction of biological efficacy. Single chain antibody, camel antibodies, Fv fragments are examples of this type of deconstructive process. Small high-affinity peptides have been identified using phage screening. Our laboratory used a structure-based approach to develop small-size peptidomimetics from the three-dimensional structure of proteins with immunoglobulin folds as exemplified by CD4 and antibodies. Peptides derived either from the receptor or their cognate ligand mimics the functions of the parental macromolecule. These constrained peptides not only provide a platform for developing small molecule drugs, but also provide insight into the atomic features of protein-protein interactions. A general overview of the reduction of monoclonal antibodies to small exocyclic peptide and its prospects as a useful diagnostic and as a drug in the treatment of cancer are discussed. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: BIOLOGICALS, CANCER -- Treatment, IMMUNE response -- Regulation, MONOCLONAL antibodies, PROTEIN-protein interactionsTHERAPEUTIC use, RADIOISOTOPES
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Stresses and displacements in functionally graded materials of semi-infinite extent induced by rectangular loadings

This paper presents the stress and displacement fields in a functionally graded material (FGM) caused by a load. The FGM is a graded material of Si3N4-based ceramics and is assumed to be of semi-infinite extent. The load is a distributed loading over a rectangular area that is parallel to the external surface of the FGM and either on its external surface or within its interior space. The point-load analytical solutions or so-called Yue’s solutions are used for the numerical integration over the distributed loaded area. The loaded area is discretized into 200 small equal-sized rectangular elements. The numerical integration is carried out with the regular Gaussian quadrature. Weak and strong singular integrations encountered when the field points are located on the loaded plane, are resolved with the classical methods in boundary element analysis. The numerical integration results have high accuracy. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: MATERIALS -- Dynamic testing, NUMERICAL analysis, NUMERICAL integration, STRAINS & stresses, STRENGTH of materials, STRUCTURAL analysis (Engineering)
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Sorbate transport in carbon molecular sieve membranes and fau/emt intergrowth by diffusion nmr

In this paper we present and discuss selected results of our recent studies of sorbate self-diffusion in microporous materials. The main focus is given to transport properties of carbon molecular sieve (CMS) membranes as well as of the intergrowth of FAU-type and EMT-type zeolites. CMS membranes show promise for applications in separations of mixtures of small gas molecules, while FAU/EMT intergrowth can be used as an active and selective cracking catalyst. For both types of applications diffusion of guest molecules in the micropore networks of these materials is expected to play an important role. Diffusion studies were performed by a pulsed field gradient (PFG) NMR technique that combines advantages of high field (17.6 T) NMR and high magnetic field gradients (up to 30 T/m). This technique has been recently introduced at the University of Florida in collaboration with the National Magnet Lab. In addition to a more conventional proton PFG NMR, also carbon-13 PFG NMR was used. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: CHEMICAL engineering, DIFFUSION, MOLECULAR dynamics, MOLECULAR rotation, MOLECULAR sieves, NUCLEAR magnetic resonance
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Satellite ndvi assisted monitoring of vegetable crop evapotranspiration in california’s san joaquin valley

Reflective bands of Landsat-5 Thematic Mapper satellite imagery were used to facilitate the estimation of basal crop evapotranspiration (ETcb), or potential crop water use, in San Joaquin Valley fields during 2008. A ground-based digital camera measured green fractional cover (Fc) of 49 commercial fields planted to 18 different crop types (row crops, grains, orchard, vineyard) of varying maturity over 11 Landsat overpass dates. Landsat L1T terrain-corrected images were transformed to surface reflectance and converted to normalized difference vegetation index (NDVI). A strong linear relationship between NDVI and Fc was observed (r² = 0.96, RMSE = 0.062). The resulting regression equation was used to estimate Fc for crop cycles of broccoli, bellpepper, head lettuce, and garlic on nominal 7-9 day intervals for several study fields. Prior relationships developed by weighing lysimeter were used to transform Fc to fraction of reference evapotranspiration, also known as basal crop coefficient (Kcb). Measurements of grass reference evapotranspiration from the California Irrigation Management Information System were then used to calculate ETcb for each overpass date. Temporal profiles of Fc, Kcb, and ETcb were thus developed for the study fields, along with estimates of seasonal water use. Daily ETcb retrieval uncertainty resulting from error in satellite-based Fc estimation was <0.5 mm/d, with seasonal uncertainty of 6-10%. Results were compared with FAO-56 irrigation guidelines and prior lysimeter observations for reference. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: BASAL area (Forestry), EVAPOTRANSPIRATION, REMOTE-sensing images, THEMATIC maps, VEGETABLES -- Drying
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Recovery of forest canopy parameters by inversion of multispectral lidar data

We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC) and reversible jump MCMC (RJMCMC) methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging) data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI), which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI) which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion. [ABSTRACT FROM AUTHOR]

June 1, 2012 Tags: BAYESIAN statistical decision theory, FOREST canopy ecology, MARKOV processes, MONTE Carlo method, OPTICAL radar, PARAMETER estimation
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