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At least 685 records · Page 38

Deep optically thin cirrus clouds in the polar regions. I - Infrared extinction characteristics

The spectral data obtained by the infrared interferometer Spectrometer (IRIS) flown on Nimbus 4 satellite in 1970 indicated the existence of optically thin ice clouds in the upper troposphere that probably extended into lower stratosphere, in the polar regions, during winter and early spring. The spectral features of these clouds differ somewhat from that of the optically thin cirrus clouds in the tropics. From theoretical simulation of the infrared spectra in the 8-25 micron region, it is inferred that these polar clouds have a vertical stratification in particle size, with larger particles (about 12 microns) in the bottom of the cloud and smaller ones (less than 1 micron) aloft. Radiative transfer calculations also suggest that the equivalent ice-water content of these polar clouds is of the order of 1 mg/sq cm.

Prabhakara, C.↗

Digital Equivalent Data System for XRF Labeling of Objects

A digital equivalent data system (DEDS) is a system for identifying objects by means of the x-ray fluorescence (XRF) spectra of labeling elements that are encased in or deposited on the objects. As such, a DEDS is a revolutionary new major subsystem of an XRF system. A DEDS embodies the means for converting the spectral data output of an XRF scanner to an ASCII alphanumeric or barcode label that can be used to identify (or verify the assumed or apparent identity of) an XRF-scanned object. A typical XRF spectrum of interest contains peaks at photon energies associated with specific elements on the Periodic Table (see figure). The height of each spectral peak above the local background spectral intensity is proportional to the relative abundance of the corresponding element. Alphanumeric values are assigned to the relative abundances of the elements. Hence, if an object contained labeling elements in suitably chosen proportions, an alphanumeric representation of the object could be extracted from its XRF spectrum. The mixture of labeling elements and for reading the XRF spectrum would be compatible with one of the labeling conventions now used for bar codes and binary matrix patterns (essentially, two-dimensional bar codes that resemble checkerboards). A further benefit of such compatibility is that it would enable the conversion of the XRF spectral output to a bar or matrix-coded label, if needed. In short, a process previously used only for material composition analysis has been reapplied to the world of identification. This new level of verification is now being used for "authentication."

Schramm, Harry F.↗

Geologic mapping using LANDSAT data

The feasibility of automated classification for lithologic mapping with LANDSAT digital data was evaluated using three classification algorithms. The two supervised algorithms analyzed, a linear discriminant analysis algorithm and a hybrid algorithm which incorporated the Parallelepiped algorithm and the Bayesian maximum likelihood function, were comparable in terms of accuracy; however, classification was only 50 per cent accurate. The linear discriminant analysis algorithm was three times as efficient as the hybrid approach. The unsupervised classification technique, which incorporated the CLUS algorithm, delineated the major lithologic boundaries and, in general, correctly classified the most prominent geologic units. The unsupervised algorithm was not as efficient nor as accurate as the supervised algorithms. Analysis of spectral data for the lithologic units in the 0.4 to 2.5 microns region indicated that a greater separability of the spectral signatures could be obtained using wavelength bands outside the region sensed by LANDSAT.

Siegal, B. S.↗

Investigation of goodness of model data fit using PLSR and PCR regression models to determine informative wavelength band in NIR region for non-invasive blood glucose prediction

Diabetes mellitus is a metabolic disorder characterized by the deficiency in insulin secretion or insulin action on target tissues. Diabetes being diagnosed, requires frequent monitoring. Current measurement techniques are invasive in nature, which is painful. Non-invasive measurement methods for the prediction of blood glucose is a big challenge. Hence this paper focuses on a comparative study to analyze the performance of the two regression models: partial least square regression (PLSR) and principal component regression (PCR) models to arrive at the best regression model for the prediction of blood glucose non-invasively based on NIR diffuse reflectance spectroscopy. The regression model developed involves spectral data collected from 32 subjects from a diabetic center using diffuse reflectance spectrometer (DRS). The spectroscopic data were acquired from the subjects both invasively using clinical method and non-invasively using DRS setup in the NIR spectral range whose wavelength ranges from 750 to 1040 nm. Multivariate analysis using PLSR is found to be a better regression model in terms of the fitted response and estimated mean square prediction error. It is observed that the mean square error value is 0.04 mg/dl for the tenth component in the PLSR model. The developed regression model also proves to be a useful tool in identifying the informative wavelength bands for blood glucose measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Remote Sensing and Geologic Studies of the Schiller-Schickard Region of the Moon

Near-infrared reflectance spectra, multispectral images, and photogeologic data for the Schiller-Schickard (SS) region were obtained and analyzed in order to determine the composition and origin of a variety of geologic units. These include light plains deposits, Orientale-related deposits, mare units, and dark-haloed impact craters (DHCs). Spectral data indicate that the pre-Orientale highland surface was dominated by noritic anorthosite. Near-IR spectra show that DHCs in the region have excavated ancient (greater than 3.8 Ga) mare basalts from beneath highland-bearing material emplaced by the Orientale impact. Ancient mare basalts were widespread in the SS region prior to the Orientale event, and their distribution appears to have been controlled by the presence of several old impact basins, including the Schiller-Zucchius basin and a basin previously unrecognized. Both near-IR spectra and multispectral images indicate that light plains and other Orientale-related units in the SS region contain major amounts of local, pre-Orientale mare basalt. The amounts of local material in these deposits approach, but seldom exceed, the maximum values predicted by the local mixing hypothesis of Oberbeck and co-workers.

Blewett, David T.↗

Analysis of Nonequilibrium Molecular Nitrogen Ultraviolet Radiation in Pure N2 Shockwaves

This paper presents an analysis of data previously reported from a test series in the Electric Arc Shock Tube Facility for incident shocks composed of pure Nitrogen. The present work focuses on the lowest velocity measured in the test (approximately 7 km/s) where molecular radiation is significant. Analysis of the spectral data with the NEQAIR radiative transport code obtains post-shock trends in temperature and number densities of the states of N2. The results suggest that chemical, and possibly thermal, equilibrium has not been obtained within the distance/time measured (about 5 cm/120 s). In the nonequilibrium region of the shock, differences between rotational temperatures of different species are observed, as well as differences between rotational and vibrational temperatures. Population of rotational states above the dissociation limit is observed to occur over a distance of several cm. Finally, these data suggest that predissociation strongly affects the C^3 Π_u state of N2, leading to a lower measured radiation than predicted. An effective average pre-dissociation rate is shown to produce reasonable agreement under quasi-steady state approximation.

Augustin Tibere Inglesse↗

The Natural Products Magnetic Resonance Database (NP-MRD) for 2025

The Natural Products Magnetic Resonance Database or NP-MRD (https://np-mrd.org) is a comprehensive, freely accessible, web-based resource for the deposition, distribution, extraction and retrieval of nuclear magnetic resonance (NMR) data on natural products. The NP-MRD was initially established to support compound de-replication and data dissemination for the natural products community. However, that community has now grown to include many users from the metabolomics, microbiomics, foodomics and nutrition science fields. Indeed, since its launch in 2021, the NP-MRD has expanded enormously in size, scope and popularity. The current version of NP-MRD now contains nearly 7X more compounds (281,859 vs. 40,908) and 7X more NMR spectra (5.1 million vs. 817,000) than the first release. More specifically, an additional 4.6 million predicted spectra and another 11,000 spectra simulated from experimental chemical shifts were deposited into the database. Likewise, the number of NMR raw spectral data depositions has grown from a 165 spectra per year to more than 10,000 per year. As a result of this expansion, the number of monthly webpage views has grown from 55 to 20,000 and the number of monthly visitors has increased from 7 to 2500. To address this growth and to better support the expanding needs of its diverse community of users, many additional improvements to the NP-MRD have been made. These include significant enhancements to the data submission process, important improvements to the visualization and display of NMR spectra, notable updates to the database’s spectral search utilities and useful additions to support better NMR spectral analysis/prediction. Significant efforts have also been undertaken to remediate and update many of NP-MRD’s database entries. This manuscript describes these database improvements and expansion efforts, along with how they have been implemented and what future upgrades to the NP-MRD are planned.

Artifical Intelligence↗

Using neural networks to assist in OPAD data analysis

The space shuttle main engine (SSME) became the subject of plume emission spectroscopy in 1986 when researchers from NASA-Marshall Space Flight Center (MSFC), Arnold Engineering Development Center (AEDC), and Rocketdyne went to the SSME test stands at the NASA-Stennis Space Center and at Rocketdyne's Santa Susan Field Laboratory to optically observe the plume. Since then, plume spectral acquisitions have recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to promote the Optical Plume Anomaly Detection (OPAD) program with a goal of instrumenting all SSME test stands with customized spectrometer systems. A prototype OPAD system is now installed on the SSME Technology Test Bed (TTB) at MSFC. The OPAD system instrumentation consists of a broad-band, optical multiple-channel analyzer (OMA) and a narrow-band device called a polychrometer. The OMA is a high-resolution (1.5-2.0 Angstroms) 'super-spectrometer' covering the near-ultraviolet to near-infrared waveband (2800-7400 Angstroms), providing two scans per second. The polychrometer consists of sixteen narrow-band radiometers: fourteen monitoring discrete wavelengths of health and condition monitoring elements and two dedicated to monitoring background emissions. All sixteen channels are capable of providing 500 samples per second. To date, the prototype OPAD system has been used during 43 SSME firings on the TTB, collecting well over 250 megabytes of plume spectral data. One goal of OPAD data analysis is to determine interatively with the help of a computer code, SPECTRA4, developed at AEDC. Experience has shown that iteration with SPECTRA4 is an incredibly labor intensive task and not one to be performed by band. What is really needed is the 'inverse' of SPECTRA4 but the mathematical model for this inverse mapping is tenuous at best. However, the robustness of PSECTRA4 run in the 'forward' direction means that accurate input/output mappings can be obtained. If the mappings were inverted (i.e., input becomes output and output becomes input) then an 'inverse' of SPECTRA4 would be at hand but the 'model' would be specific to the data utilized and would in no way be general. Building a generalized model based upon known input/output mappings while ignoring the details of the governing physical model is possible through the use of a neural network. The research investigation described involves the development of a neural network to provide a generalized 'inverse' of SPECTRA4. The objectives of the research were to design an appropriate neural network architecture, train the network, and then evaluate its performance.

Whitaker, Kevin W.↗

Information content in Iris spectra

Spectra from the satellite instrument Iris (infrared interferometer spectrometer) were examined to find the number of independent variables needed to describe the broad-band high-resolution spectral data. The radiated power in the atmospheric window from 771 to 981 per cm was the first parameter chosen for fitting observed spectra. At succeeding levels of analysis, the residual variability (observed spectrum minus best-fit spectrum) in an ensemble of observations was partitioned into spectral eigenvectors. The eigenvector describing the largest fraction of this variability was examined for a strong spectral signature; the power in the corresponding spectral band was then used as the next fitting parameter. The measured power in nine spectral intervals, when it was inserted in the spectral-fitting functions, was adequate to describe most spectra to within the noise level of Iris. Considerations of relative signal strength and scales of atmospheric variability suggest a combination sounder (multichannel, broad field of view) scanner (window channel, small field of view) as an efficient observing instrument.

Price, J. C.↗

Spectral evidence for carbonates on Mars: Hydrous carbonates

Although many of the spectral features of the Martian samples studied are not unique mineralogical indicators, much of the current spectral data is consistent with (possibly abundant) hydrous carbonates on the surface of Mars. The absorption features in the measured samples were quite weak compared with those of anhydrous carbonates. The weak features imply that significantly more hydrous carbonates can be incorporated onto the surface before becoming spectrally evident; however, exact limits have yet to be determined. The stability of these materials in the Martian environment is not known, but their formation and occurrence in low temperature terrestrial environments makes them appealing candidates for weathering products on Mars.

Calvin, W. M.↗

Analysis of nonequilibrium molecular nitrogen ultraviolet radiation in pure N2 shockwaves

An analysis of data previously reported from a test series in the Electric Arc Shock Tube Facility for incident shocks composed of pure Nitrogen was performed. The present work focuses on the lowest velocity measured in the test (approximately 7 km/s) where molecular radiation is significant. Analysis of the spectral data with the NEQAIR radiative transport code obtains post-shock trends in temperature and number densities of the states of N2. The results suggest that chemical, and possibly thermal, equilibrium has not been obtained within the distance/time measured (about 5 cm/120 ms). In the nonequilibrium region of the shock, differences between rotational temperatures of different species are observed, as well as differences between rotational and vibrational temperatures. Population of rotational states above the dissociation limit is observed to occur over a distance of several cm. Finally, these data suggest that predissociation strongly affects the C^3 Π_u state of N2, leading to a lower measured radiation than predicted. An effective average pre-dissociation rate is shown to produce reasonable agreement under quasi-steady state approximation.

Augustin Tibere-Inglesse↗

A robust clustering algorithm for analysis of composition-dependent organic aerosol thermal desorption measurements

Abstract. One of the challenges of understanding atmospheric organic aerosol (OA) particles stems from its complex composition. Mass spectrometry is commonly used to characterize the compositional variability of OA. Clustering of a mass spectral dataset helps identify components that exhibit similar behavior or have similar properties, facilitating understanding of sources and processes that govern compositional variability. Here, we developed an algorithm for clustering mass spectra, the noise-sorted scanning clustering (NSSC), appropriate for application to thermal desorption measurements of collected OA particles from the Filter Inlet for Gases and AEROsols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). NSSC, which extends the common density-based special clustering of applications with noise (DBSCAN) algorithm, provides a robust, reproducible analysis of the FIGAERO temperature-dependent mass spectral data. The NSSC allows for the determination of thermal profiles for compositionally distinct clusters of mass spectra, increasing the accessibility and enhancing the interpretation of FIGAERO data. Applications of NSSC to several laboratory biogenic secondary organic aerosol (BSOA) systems demonstrate the ability of NSSC to distinguish different types of thermal behaviors for the components comprising the particles along with the relative mass contributions and chemical properties (e.g., average molecular formula) of each mass spectral cluster. For each of the systems examined, more than 80 % of the total mass is clustered into 9–13 mass spectral clusters. Comparison of the average thermograms of the mass spectral clusters between systems indicates some commonality in terms of the thermal properties of different BSOA, although with some system-specific behavior. Application of NSSC to sets of experiments in which one experimental parameter, such as the concentration of NO, is varied demonstrates the potential for mass spectral clustering to elucidate the chemical factors that drive changes in the thermal properties of OA particles. Further quantitative interpretation of the thermograms of the mass spectral clusters will allow for a more comprehensive understanding of the thermochemical properties of OA particles.

54 ENVIRONMENTAL SCIENCES↗

High resolution measurements of the low state of Cyg X-1

Cyg X-1 was observed on two occasions separated by a year by the same X-ray rocket payload. High resolution temporal and spectral data reveal that Cyg X-1 was essentially unchanged in these two observations a year apart, with bursts of millisecond duration observed in the earlier flight and also, observed in the second. Analysis of these bursts has failed to reveal any internal temporal structure, either luminous or spectral. The shot noise character of temporal fluctuations on timescales approximately 1 second can be explained by the presence of exponential pulses with a fraction of a second time constant and a rate near 8 sec/1. The possible connection of these pulses with the bursts is examined.

Rothschild, R. E.↗

An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation

Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

classification↗

Advanced Polymer Characterization: Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry encodes structural information across diverse homo- and copolymer ensembles, yet decrypting these spectra requires a systematic analytical approach. We introduce Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)─a general cipher algorithm that applies modular arithmetic to filter monomer-derived mass contributions and cluster MALDI peaks by nonconstitutional repeating units (non-CRUs). MOSAIC performs sequential modular operations using monomer mass differences as base units to compress complex spectral data, revealing end-group distributions and comonomer incorporation. As a demonstration, we applied MOSAIC to five copolymers formed by two different polymerization mechanisms. Furthermore, the resulting remainder–mass plots clearly resolve polymer homologs with distinct non-CRUs into visually apparent clusters, enabling intuitive assignment of mass spectral features.

Wang, Hanlin M. [University of Illinois at Urbana−↗

Submillisecond measurements of the low state of Cygnus X-1

Cygnus X-1 was observed on two occasions separated by a year by the same Goddard X-ray rocket payload. High-resolution temporal and spectral data reveal that Cyg X-1 was essentially unchanged in these two observations a year apart; the bursts of millisecond duration observed in the earlier flight were observed in the second as well. Analysis of these bursts has failed to reveal any internal temporal structure, either luminous or spectral. The shot-noise character of temporal fluctuations on time scales of at least 1 s can be explained by the presence of exponential pulses with a time constant of a fraction of a second and a rate near 8 per sec. The possible connection of these pulses with the bursts is examined.

Rothschild, R. E.↗

Determination of collisional linewidths and shifts by a convolution method

A technique is described for fitting collisional linewidths and shifts from experimental spectral data. The method involves convoluting a low-pressure reference spectrum with a Lorentz shape function and comparing the convoluted spectrum with higher pressure spectra. Several experimental examples are given. One advantage of the method is that no extra information is needed about the instrument response function or spectral modulation. In addition, the method is shown to be relatively insensitive to the presence of reflections in the sample cell.

Pickett, H. M.↗

The Burst and Transient Source Experiment(BATSE)Earth Occultation Catalog of Low-Energy Gamma-Ray Sources. Short title: BATSE Earth Occultation Catalog v2.0

The Burst and Transient Source Experiment (BATSE), aboard the Compton Gamma Ray Observatory (CGRO), provided a record of the low-energy gamma-ray sky (approx. 20-1000 keV) between 1991 April and 2000 May (9.1y). BATSE monitored the high energy sky using the Earth occultation technique (EOT) for point sources whose emission extended for times on the order of the CGRO orbital period (approx. 92m) or greater. Using the EOT to extract flux - 2 - information, a catalog of sources using data from the BATSE large area detectors has been prepared. The first part of the catalog consists of results from the all-sky monitoring of 58 sources, mostly Galactic, with intrinsic variability on timescales of hours to years. For these sources, we have included tables of flux and spectral data, and outburst times for transients. Light curves (or flux histories) covering the entire nine mission are being placed on the world wide web. We then performed a deep-sampling of these 58 objects, plus a selection of 121 more objects, combining data from the entire 9.ly BATSE dataset. Source types considered were primarily accreting binaries, but a small number of representative active galaxies, X-ray-emitting stars, and supernova remnants were also included. The sample represents a compilation of sources monitored and/or discovered with BATSE and other high energy instruments between 1991 and 2000, known sources taken from the HEAO 1 A-4 (Levine et al. 1984) and Macomb and Gehrels (1999) catalogs. The deep sample results include definite detections of 82 objects and possible detections of 36 additional objects. The definite detections spanned three classes of sources: accreting black hole and neutron star binaries, active galaxies and supernova remnants. The average fluxes measured for the fourth class, the X-ray emitting stars, were below the confidence limit for definite detection. Flux data for the deep sample are presented in four energy bands: 20-40, 40-70, 70-160, and 160-430 keV. The limiting average flux level (9.1 y) for the sample varies from 3.5 to 20 mCrab (5delta) between 20 and 430 keV, depending on systematic error, which in turn is primarily dependent on the sky location. To strengthen the credibility of detection of weaker sources (approx.5-25 mCrab), we generated Earth occultation images, searched for periodic behavior using FFT and epoch folding methods, and critically evaluated the energy-dependent emission in the four flux bands. The deep sample results are intended for guidance in performing future all-sky surveys or pointed observations in the hard X-ray and low-energy gamma-ray band, as well as more detailed studies with the BATSE EOT.

Harmon, B. A.↗