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Time dependent signatures: Moisture content interpretation in well logging applications with a D-T neutron generator
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Interpreting effective hydrologic depth estimates derived from soil moisture remote sensing: A Bayesian non-linear modeling approach
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Peakaboo: Advanced software for the interpretation of X-ray fluorescence spectra from synchrotrons and other intense X-ray sources
Abstract not provided
Clarifying the interpretation of carbon use efficiency in soil through methods comparison
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Opening the Black Box: Interpretable Machine Learning for Geneticists
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Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks
Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.
Theoretical Prediction and Interpretation of 237 Np Mössbauer Isomer Shifts
Different theoretical approaches for the calculation of 237 Np Mössbauer isomer shifts are investigated. The traditional contact density route is compared to a previously proposed alternative approach that uses energy derivatives with respect to the nuclear radius. Both approaches yield similar results as long as suitable basis sets augmented with large exponents and relativistic methods are used. Density functional theory (DFT) calculations do not show a strong dependency of the 237 Np isomer shift on the chosen functional. Wavefunction calculations show that dynamic electron correlation can be important when covalent bonding influences the isomer shift. Effects from spin–orbit coupling are small. The isomer shifts of ionic solids and Np(III) organometallic complexes are largely governed by the oxidation state of Np. Isomer shifts of organometallic Np(IV) complexes are strongly affected by donation bonding. Furthermore, detailed analysis of the wavefunction results with different active spaces demonstrates that correlation among the outer core Np and occupied ligand frontier orbitals contributes significantly to isomer shifts of Np(IV) compounds.
Extracting an Empirical Intermetallic Hydride Design Principle from Limited Data via Interpretable Machine Learning.
Abstract not provided.
Calculation and interpretation of classical turning surfaces in solids
Abstract Classical turning surfaces of Kohn–Sham potentials separate classically allowed regions (CARs) from classically forbidden regions (CFRs). They are useful for understanding many chemical properties of molecules but need not exist in solids, where the density never decays to zero. At equilibrium geometries, we find that CFRs are absent in perfect metals, rare in covalent semiconductors at equilibrium, but common in ionic and molecular crystals. In all materials, CFRs appear or grow as the internuclear distances are uniformly expanded. They can also appear at a monovacancy in a metal. Calculations with several approximate density functionals and codes confirm these behaviors. A classical picture of conduction suggests that CARs should be connected in metals, and disconnected in wide-gap insulators, and is confirmed in the limits of extreme compression and expansion. Surprisingly, many semiconductors have no CFR at equilibrium, a key finding for density functional construction. Nonetheless, a strong correlation with insulating behavior can still be inferred. Moreover, equilibrium bond lengths for all cases can be estimated from the bond type and the sum of the classical turning radii of the free atoms or ions.
Interpretation of proton radiography experiments of hohlraums with three-dimensional simulations [Interpretation of proton radiography experiments of hohlraums with 3D simulations]
Proton radiography experiments of laser-irradiated hohlraums performed at the OMEGA laser facility are analyzed using three-dimensional (3D) hydrodynamic simulations coupled to a proton trajectography package. Experiments with three different laser irradiation patterns were performed, and each produced a distinct proton image. By comparing these results with synthetic proton images obtained by sending protons through plasma profiles in the hohlraum obtained from 3D radiation hydrodynamic simulations, it is found that the simulated images agree favorably with the experimental images when electric fields, due to the electron pressure gradients that arise from 3D structures occurring during plasma expansion, are included. Furthermore, these comparisons provide quantitative estimates of the electric field present inside the hohlraums.
PRELIMINARY ANALYSIS OF FEASIBILITY OF MAPPING THE MOON BY MEANS OF PHOTOGRAMMETRY AND PHOTO INTERPRETATION PART II. PHOTOGRAPHIC INTERPRETATION
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On the interpretation of echos at a great dis- tance observed on certain ionograms of the satellite ''alouette'' <sur l'interpretation d'echos a grande distance observes sur certains ionogrammes du satellite 'alouette'<
Echos at great distance observed on ionograms of alouette satellite
Oceanographic Interpretation of Apollo Photographs. Coastal Oceanographic and Sedimentologic Interpretation of Apollo 9 Space Photographs; Carolina's Continental Shelf, USA
Apollo 9 photographs, color band separations, and oceanographic and meteorological data are used in the study of the origin, movement, and dissipation of masses of discolored water near the shores of North and South Carolina. A model has been developed incorporating jet theory, climatology, currents, surface temperatures, color separations, and other oceanographic data to explain the processes involved in the life cycle of the discolored water masses. Special treatment is afforded the Gulf Stream boundary definition and the Cape Hatteras oceanographic barrier.
Radar interpretation of lava fields as a function of incidence angle - Implications for interpretation of Magellan SAR data on Venus
The capability of a single frequency, single polarization radar to distinguish different lava flows solely on the basis of their relative radar backscatter as measured by scatterometer profiles is addressed. It is found that mantled and unmantled flow surfaces can be separated by their radar backscatter and become more distinct with increasing incidence angle. Pristine pahoehoe surfaces have backscatter coefficients distinctly different from older flows at small angles, whereas the most modified pahoehoe units are identifiable at larger incidence angles. At all latitudes on Venus, it should be possible to distinguish the style of volcanism responsible for volcanic plains emplacement.
Assimilation of Geosat Altimetric Data in a Nonlinear Shallow-Water Model of the Indian Ocean by Adjoint Approach. Part II: Some Validation and Interpretation of the Assimilated Results: Some Validation and Interpretation of the Assimilated Results - Part 2
This paper examines the results of assimilating Geosat sea level variations relative to the November 1986-November 1988 mean reference, in a nonlinear reduced-gravity model of the Indian Ocean, Data have been assimilated during one year starting in November 1986 with the objective of optimizing the initial conditions and the yearly averaged reference surface. The thermocline slope simulated by the model with or without assimilation is validated by comparison with the signal, which can be derived from expandable bathythermograph measurements performed in the Indian Ocean at that time. The topography simulated with assimilation on November 1986 is in very good agreement with the hydrographic data. The slopes corresponding to the South Equatorial Current and to the South Equatorial Countercurrent are better reproduced with assimilation than without during the first nine months. The whole circulation of the cyclonic gyre south of the equator is then strongly intensified by assimilation. Another assimilation experiment is run over the following year starting in November 1987. The difference between the two yearly mean surfaces simulated with assimilation is in excellent agreement with Geosat. In the southeastern Indian Ocean, the correction to the yearly mean dynamic topography due to assimilation over the second year is negatively correlated to the one the year before. This correction is also in agreement with hydrographic data. It is likely that the signal corrected by assimilation is not only due to wind error, because simulations driven by various wind forcings present the same features over the two years. Model simulations run with a prescribed throughflow transport anomaly indicate that assimilation is rather correcting in the interior of the model domain for inadequate boundary conditions with the Pacific.