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We announce the release of visible and near-infrared reflectance spectroscopy measurements for nearly 2000 asteroids obtained by the MIT Small Main-Belt Asteroid Spectroscopic Survey (SMASS) program. Data are being released via http://smass.mit.edu. Additional information is contained in the original extended abstract.
Consideration is given to the effects of canopy closure, understory vegetation, and background reflectance on the relationship between Landsat TM data and the leaf area index (LAI) of temperate coniferous forests in the western U.S. A methodology for correcting TM data for atmospheric conditions and sun-surface-sensor geometry is discussed. Strong inverse curvilinear relationships were found between coniferous forest LAI and TM bands 3 and 5. It is suggested that these inverse relationships are due to increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI.
The laboratory established at NASA-Goddard to measure and model the light-scattering properties of soil samples and individual plant leaves employs two goniometers: one for the measurement of directional reflectance and transmittance from vertically-mounted leaf samples, and the other for measurement of directional reflectance from such horizontal, semiinfinite particulate surfaces as soil samples. Sample observations of various soil minerals and plant leaves are presented; these goniometric data are compared to the results of a reflectance model from particulate surfaces and those of a ray-tracing model of leaf reflectance and transmittance.
Research activities to date are discussed. Selected Mariner 9 UV spectra were obtained. Radiative transfer models were updated and then exercised to simulate spectra. Simulated and observed spectra compare favorably. It is noted that large amounts of ozone are currently not retrieved with reflectance spectroscopy, raising large doubts about earlier published ozone abundances. As these published abundances have been used as a benchmark for all theoretical photochemical models of Mars, this deserves further exploration. Three manuscripts were published, and one is in review. Papers were presented and published at three conferences, and are planned for five more conferences in the next six months. The research plan for the next reporting period is discussed and involves continuing studies of reflectance spectroscopy, further examination of Mariner 9 data, and climate change studies of ozone.
This paper reports measurements of the reflection spectra of sodium- and potassium-doped ammonia frosts as a function of alkali metal concentration for the wavelength range 0.35-2.5 microns. The purpose of the measurements was to determine whether or not the reflection spectra for such a solid was compatible with the spectra albedo of Io. The data show that, with a sufficiently large alkali metal concentration, the reflection spectra of the doped ammonia frosts do not display the characteristic ammonia features at 2.0 and 2.25 micron. The high reflectance of the more concentrated samples and the character of the observed reflection spectrum make it difficult to rule out sodium-doped ammonia frost as a surface constituent on Io on the basis of existing data.
Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.
The author has identified the following significant results. Preliminary results of a spectral ratioing technique are shown for a region at the southern end of the Wind River Range, Wyoming. Digital ratio graymaps and analog ratio images have been produced for the test site, but ground truth is not yet available for thorough interpretation of these products. ERTS-1 analog ratio images were found generally better than either ERTS-1 single channel images or high altitude aerial photos for the discrimination of vegetation from non-vegetation in the test site region. Some linear geological features smaller than the ERTS-1 spatial resolution are seen as well in ERTS-1 ratio and single channel images as in high altitude aerial photography. Geochemical information appears to be extractable from ERTS-1 data. Good preliminary quantitative agreement between ERTS-1 derived ratios and laboratory derived reflectance ratios of rocks and minerals encourage plans to use lab data as training sets for a simple ratio gating logic approach to automatic recognition maps. Empirical atmospheric corrections indicate that atmospheric corrections are needed to make the ratio method, and possibly other types of data processing, consistent over large geographical and temporal displacements.
An experimental method has been developed to determine the water droplet impingement characteristics on two- and three-dimensional aircraft surfaces. The experimental water droplet impingement data are used to validate particle trajectory analysis codes that are used in aircraft icing analyses and engine inlet particle separator analyses. The aircraft surface is covered with thin strips of blotter paper in areas of interest. The surface is then exposed to an airstream that contains a dyed-water spray cloud. The water droplet impingement data are extracted from the dyed blotter paper strips by measuring the optical reflectance of each strip with an automated reflectometer. Experimental impingement efficiency data represented for a NLF (1)-0414 airfoil, a swept MS (1)-0317 airfoil, a Boeing 737-300 engine inlet model, two simulated ice shapes and a swept NACA 0012 wingtip. Analytical impingement efficiency data are also presented for the NLF (1)-0414 airfoil and the Boeing 737-300 engine inlet model.
The amount of UV irradiance reaching the Earth's surface is estimated from the measured cloud reflectivity, ozone, aerosol amounts, and surface reflectivity time series from 1980 to 1992 and 1997 to 2000 to estimate changes that have occurred over a 21-year period. Recent analysis of the TOMS data shows that there has been an apparent increase in reflectivity (decrease in W) in the Southern Hemisphere that is related to a calibration error in EP-TOMS. Data from the well-calibrated SeaWiFS satellite instrument have been used to correct the EP-TOMS reflectivity and UV time series. After correction, some of the local trend features seen in the N7 time series (1980 to 1992) have been continued in the combined time series, but the overall zonal average and global trends have changed. In addition to correcting the EP-TOMS radiance calibration, the use of SeaWiFS cloud data permits estimation of UV irradiance at higher spatial resolution (1 to 4 km) than is available from TOMS (100 km) under the assumption that ozone is slowly varying over a scale of 100 km. The key results include a continuing decrease in cloud cover over Europe and North America with a corresponding increase in UV and a decrease in UV irradiance near Antarctica.
The Skylab EREP S192 multispectral scanner data have provided an opportunity to examine the reflectance characteristics of snow cover in several spectral bands extending from the visible into the near infrared spectral region to about 2 microns. The analysis of the S192 imagery and digital tape data from five EREP passes, two from the SL-2 mission and three from the SL-4 mission, indicates a sharp drop in reflectance of snow in the near infrared, with snow becoming essentially nonreflective in Bands 11 (1.55-1.75 microns) and 12 (2.10-2.35 microns). The results are in good agreement with the results of laboratory experiments. Two potential applications to snow mapping of measurements in the near infrared spectral region are possible: (1) the use of a near infrared band in conjunction with a visible band to distinguish automatically between snow and water droplet clouds, and (2) the use of one or more near infrared bands to detect areas of melting snow.
Although TiNb 2 O 7 is regarded as a fast-rechargeable lithium-ion battery (LIB) anode material, the intrinsic poor electrochemical kinetics of TiNb 2 O 7 still dramatically impedes its development. Herein, an ionothermal synthesis-assisted doping strategy is proposed for the preparation of a new W 6+ -doped TiNb 2 O 7 material (Ti 0.95 W 0.05 Nb 2 O 7 ) with nanoporous structure (denoted as NPTWNO). The improved Li + diffusion coefficient of NPTWNO suggests that the ionic-liquid-templated nanoporous architecture improves the Li+ diffusion kinetics. The density functional theory computational study reveals that the doped W 6+ successfully boosts the electronic conductivity due to the narrowed conduction-valance bandgap resulted from charge redistribution, which is reflected by the electrochemical impedance spectroscopy data. With the simultaneously enhanced Li+ diffusivity and electronic conductivity, NPTWNO achieves fast-rechargeability in LIBs. So this work indicates the potential of ionothermal synthesis-assisted doping strategy on energy storage materials and offers NPTWNO material with promising electrochemical performance.
In this erratum we report a correction to the previously published photofission cross-section ratio data. The actinide fission-chamber foils utilized in this work were extensively characterized during a new campaign using α- and γ-ray spectroscopy, and 2π alpha counting. These three techniques agreed, resulting in an improved accuracy of the fission-chamber foil masses used in the original experiment. The foil masses measured by α spectroscopy are detailed in Table I. All foils were counted on the same α spectrometer, using an identical geometry, which reduces the systematic uncertainty in the calculated mass ratios since the α spectrometer efficiency cancels out in the ratio. This results in a relative uncertainty on the mass ratio of 1.0% for 235 U/ 238 U, 0.62% for 239 Pu/ 235 U, and 1.1% for 239 Pu/ 238 U. The published cross-section ratio data are re-calculated to reflect the updated target masses and uncertainties. The new mass values cause a 2.40% decrease for the σ( 235 U(γ, f)/ 238 U(γ, f)) ratio, a 5.10% decrease for the σ( 235 U(γ, f)/ 239 Pu(γ, f)) ratio, and a 2.77% decrease for the σ( 238 U(γ, f)/ 239 Pu(γ, f)) ratio. The updated cross-section ratios are presented in Tables II, III, and IV, which are corrected versions of Tables III, IV, and V in Ref. [1]
Single crystals of the layered, van der Waals compound VBr 3 were synthesized by a vapor transport technique, and characterized by single-crystal x-ray diffraction, temperature- and field-dependent magnetization, and temperature-dependent specific-heat measurements. VBr 3 has a honeycomb-based BiI 3 -type structure with space group $R$-3 (no. 148) at 100 K, analogous to the structure of other honeycomb trihalides. Structural stacking faults were observed as evidenced by the streaking of reflections along $c*$ in the diffraction data. VBr 3 goes through a structural phase transition at 90.4 K and a subsequent antiferromagnetic phase transition at 26.5 K, below which the magnetic moments are primarily aligned along the $c$-axis.
Internet of Things (IoT) is becoming more pervasive in many installations, including homes, manufacturing plants, and industrial facilities of all kinds. The data that IoT produces is a reflection of usual behavior such as daily routines and scheduled tasks, but also from unexpected behavior due to unintentional or undesirable abnormalities. Here, we focus on achieving coordinated intelligence about normal and abnormal phenomena from multiple sensors that are geographically colocated in close proximity, monitoring and controlling a set of co-located devices. Given a set of co-located sensors, we seek an intelligent approach that would automatically determine the “normal” patterns of behaviors among the correlated sensors. After normal behavior is extracted, later monitoring should detect any deviant variations over time. An example application is an entry monitoring and alert system for facilities such as nuclear reactors, where badge readers, door locks, lights, weight trackers and other co-located sensors at the entry point are collectively tracked. To address this problem, we identify the possible solution approach that can be used to solve its different variants. The implemented model is developed as a combination of rules and Markov Chain methods.
Exciton-polaritons (EPs) are an emerging approach to achieve strong light-matter coupling and robust quantum phenomena, with application to areas such as photonic neuromorphic computing for instance reservoir computing. 2D transition metal dichalcogenides (TMDs) are promising candidates to host EPs due to their potential for strong coupling as evidenced by large Rabi splitting energies, which in the case of few-layer MoS2 has been demonstrated to reach 293 meV when coupled to the C exciton, placing it in the ultrastrong coupling regime, at room temperature. Here we examine how the Rabi splitting of CVD-grown monolayer MoS2 in a cavity can be optimized by tuning two variables: cavity geometry (thickness of silver and dielectric spacers) and the targeted exciton for coupling (A at about 1.9 eV, B at about 2.06 eV, or C at about 2.9 eV). With the cavity geometry, there is a tradeoff between optical field confinement and transmission. With the targeted exciton, there may be a tradeoff between Rabi splitting and lifetime. Transfer matrix simulations are used to inform how thick the cavity layers need to be, and at what angle measurements should be performed, to achieve Rabi splitting at a certain exciton energy. Experimentally, the Rabi splitting is measured by placing the cavity at a specified angle and measuring the optical reflectance and transmittance. By fitting the data, we find Rabi splittings of 124 meV, 194 meV, and 288 meV for the A, B, and C excitons, respectively, which places them in the strong, and on the edge of the ultrastrong, coupling regime.
Lead telluride films have been grown on Si (100) and BaF{sub 2} (100) substrates by a modified hot-wall method using a graphite reaction chamber. According to X-ray diffraction, X-ray microanalysis, and scanning electron microscopy characterization results, the average growth rate of PbTe films having compositions within the homogeneity range of lead telluride increases with increasing lead vapor partial pressure and decreases with increasing tellurium vapor partial pressure, independent of the nature of the substrate. The rate of PbTe film growth has been shown to be maximal in the initial stage of the process and decrease monotonically over time, independent of the nature of the substrate. Independent of the growth time, the average growth rate of the PbTe films on the Si (100) substrates is considerably higher than that on the BaF{sub 2} (100) substrates. Reflection high-energy electron diffraction data indicate that the texture of the PbTe films on Si (100) corresponds to the substrate orientation and that the misorientation angle of the mosaic blocks does not exceed 20°. On the BaF{sub 2} (100) substrates, we observe epitaxial PbTe film growth with the orientation relationship (100), [011] PbTe ║ (100), [011] BaF{sub 2}.
This brief is a compilation of data points and market insights that reflect the state of the project finance market for solar photovoltaic (PV) assets in the United States as of the third quarter of 2018. This information can generally be used as a simplified benchmark of the costs associated with securing financing for solar PV as well as the cost of the financing itself (i.e., the cost of capital). This work represents the third DOE sponsored effort to benchmark financing costs across the residential, commercial, and utility-scale PV markets, as part of its larger effort to benchmark the components of PV system costs. capital). This work represents the third DOE sponsored effort to benchmark financing costs across the residential, commercial, and utility-scale PV markets, as part of its larger effort to benchmark the components of PV system costs.
One challenge of using compartmental SEIR models for public health planning is the difficulty in manually tuning parameters to capture behavior reflected in the real-world data. This team conducted initial, exploratory analysis of a novel technique to use physics-informed machine learning tools to rapidly develop data-driven models for physical systems. This machine learning approach may be used to perform data assimilation of compartment models which account for unknown interactions between geospatial domains (i.e. diffusion processes coupling across neighborhoods/counties/states/etc.). Results presented here are early, proof-of-concept ideas that demonstrate initial success in using a physically informed neural network (PINN) model to assimilate data in a compartmental epidemiology model. The results demonstrate initial success and warrant further research and development.