Raman Spectroscopy Reveals Selective Interactions of Cytochrome c with Cardiolipin That Correlate with Membrane Permeability
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Search NASA
Results for “correlation selection”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Improvements to Ozone Analyses Using Hyperspectral Sounders in the 9.6 μm Band
Previously, hyperspectral sounder brightness temperatures assimilated in the Goddard Earth Observing System Atmospheric Data Assimilation System (GEOS-ADAS) were limited to assimilating temperature and moisture. The ozone sensitive 9.6 m region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 m region have been operational at ECMWF for several years (Dragani and McNally, 2013; Eresmaa et al., 2017). With this study, similar improvements using the GEOS-ADAS are presented. Channels were selected from available operational subsets evaluating information content and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered in developing the study. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes), and WOUDC (World Ozone and Ultraviolet Data Center). Inclusion of inter-channel correlation error to the selected ozone channels are expected to improve ozone analyses further along with improve analyses overall. It is anticipated that inclusion of these ozone sensitive channels will be used to improve NASA GMAO products in the near future.
GEOS-ADAS↗
Relative effect of anthropogenic warming and natural climate variability to changes in Compound drought and heatwaves
Compound drought and heatwave (CDHW) events can be influenced by large scale teleconnections and anthropogenic warming, leading to severe socio-economic impacts across various climate regions. Here, the relative influence of six different teleconnection patterns and anthropogenic global warming on the global CDHW occurrences is quantified systematically using the instrumental data period, 1982–2016. The results from the study suggest a substantial increase in the CDHW events (1–5 events per year) across various parts of the globe at the beginning of 21st century (2000–2016). A Bayesian approach is implemented to identify the most vulnerable climate regions based on the degree of susceptibility of heatwaves (DSHW) towards drought. As such, top ten most vulnerable regions are selected based on the DSHW magnitude, and a partial correlation analysis is performed to select the natural and anthropogenic drivers of CDHW in those regions, separately. A logistic regression model is then used to determine significant changes in the odds of CDHW due to changes in the selected drivers that suggest a significantly positive, and multiplicative effect of anthropogenic global warming in the top ten most vulnerable climate regions. Finally, the same logistic regression model, integrated with an analytical framework, is applied to determine the relative influence of anthropogenic global warming on the changes in odds of CDHW for the future, 1.5 °C and 2 °C warming limits. Finally, the results suggest that relative to the 2 °C global warming, constraining to the 1.5 °C global warming limit may conduce about 17-fold reduction in the odds of CDHW in the most vulnerable climate region, East Asia, 5–8-fold reduction in Western North America, Northern Australia, Central North America, Central Europe, South Asia, and the Mediterranean region, and 3–4-fold reduction in Northeastern Brazil, Eastern North America, and West Asia.
54 ENVIRONMENTAL SCIENCES↗
Intrinsic selectivity and structure sensitivity of Rhodium catalysts for C 2+ oxygenate production [On the intrinsic selectivity and structure sensitivity of Rhodium catalysts for C 2+ oxygenate production]
Synthesis gas (CO + H 2 ) conversion is a promising route to converting coal, natural gas, or biomass into synthetic liquid fuels. Rhodium has long been studied as it is the only elemental catalyst that has demonstrated selectivity to ethanol and other C 2+ oxygenates. However, the fundamentals of syngas conversion over rhodium are still debated. In this work a microkinetic model is developed for conversion of CO and H 2 into methane, ethanol, and acetaldehyde on the Rh (211) and (111) surfaces, chosen to describe steps and close-packed facets on catalyst particles. The model is based on DFT calculations using the BEEF-vdW functional. The mean-field kinetic model includes lateral adsorbate–adsorbate interactions, and the BEEF-vdW error estimation ensemble is used to propagate error from the DFT calculations to the predicted rates. The model shows the Rh(211) surface to be ~6 orders of magnitude more active than the Rh(111) surface, but highly selective toward methane, while the Rh(111) surface is intrinsically selective toward acetaldehyde. A variety of Rh/SiO 2 catalysts are synthesized, tested for catalytic oxygenate production, and characterized using TEM. The experimental results indicate that the Rh(111) surface is intrinsically selective toward acetaldehyde, and a strong inverse correlation between catalytic activity and oxygenate selectivity is observed. Furthermore, iron impurities are shown to play a key role in modulating the selectivity of Rh/SiO 2 catalysts toward ethanol. The experimental observations are consistent with the structure-sensitivity predicted from theory. As a result, this work provides an improved atomic-scale understanding and new insight into the mechanism, active site, and intrinsic selectivity of syngas conversion over rhodium catalysts and may also guide rational design of alloy catalysts made from more abundant elements.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optoelectronic associative memory
An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.
Chao, Tien-Hsin↗
Local Chain Dynamics in Sequence-Controlled Polymers as a Tunable Handle for Rare Earth Sequestration
Chain dynamics govern the intricate behaviors of proteins, underpinning functions such as catalysis, recognition, and stimulus response, and are an increasingly appreciated aspect of structure–function relationships. Analogously, manipulating chain dynamics and structure in abiotic polymers via sequence control is an exciting, yet underexplored, strategy for improving material functions. In this work, we report a systematic study relating the sequence of polymeric sequestrants to their structure and dynamics, as well as to their binding affinity and selectivity for model substrates, rare earth elements (REEs). A series of sequence-controlled polymers with metal chelating, solubilizing, and structure forming monomers was synthesized via multiblock polymerization, yielding compositionally identical polymers with spectroscopically resolved domains and distinct morphologies. Using a combination of small-angle X-ray scattering and 19 F NMR relaxometry measurements, we connected differences in polymer structure and dynamics to polymer sequence variables such as the patchiness (density) of the structure forming monomer and the location of the chelating monomer. Furthermore, we found that, relative to calcium, all polymers in the series collapse more and have slower dynamics when binding REEs (lanthanum and lutetium) , though the extent of these effects were sequence-dependent and localized to specific domains within the polymer. Notably, sequence-controlled polymers that exhibited the largest conformational and dynamic changes upon binding REEs also bound REEs with the greatest affinity and modest selectivity. Collectively, these results correlate monomer patterning with dynamics, morphology, and REE binding performance en route to the development of efficient and selective macromolecular chelators.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multiwavelength cluster mass estimates and machine learning
ABSTRACT One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is in contrast to finding mass estimates for each observable, normally by using a scaling relation, and then combining these scaling law based mass estimates using a likelihood. We also illustrate how the contributions of each observable to the accuracy of the resulting mass measurement can be compared via model-agnostic Importance Permutation values. Thirdly, as machine learning relies upon the accuracy of the training set in capturing observables, their correlations, and the observational selection function, and as the machine learning training set originates from simulations, two tests of whether a simulation’s correlations are consistent with observations are suggested and explored as well.
Cohn, J. D.↗
Learning Planar Ising Models Software
Learning Planar Ising Models is a software package written in Matlab for learning relationships among variable in a dataset using graphical models. The software package implements a generally-applicable algorithm for learning planar Ising models from any multivariate dataset. The code provides an algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. The software includes demonstrations of the algorithm in simulations and for applications on publicly available datasets. Details of the algorithm, demonstration simulations, and applications are given in Johnson, et al; 2016. Reference: Johnson, J. K., Oyen, D., Chertkov, M., and Netrapalli, P. (2016). Learning planar Ising models. Journal of Machine Learning Research.
Oyen, Diane↗
Quasi Stationary States in the Southern Hemisphere
Pattern correlations between daily anomalies (Horel 1984) were used to study the persistency of the Southern Hemisphere circulations. The data set consists of the daily Australian analyses of 500 mb heights and sea level pressure for the period from 1972 and 1983. Compared to the Northern Hemisphere, the pattern correlations are much smaller and more variable in the Southern Hemisphere. The mean one day lag is only 0.57, (0.82 for the NH). The correlations increase significantly for the filtered anomalies which consist of the long planetary waves from 0 to 4. Subjective criteria based on the pattern correlations are used to select the quasi stationary events. A series of 5 or more daily maps is quasi stationary if the pattern correlations between all consecutive pairs of maps in this time series are larger or equal to 0.5.
Mo, K. C.↗
Learning planar Ising models
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.
97 MATHEMATICS AND COMPUTING↗
Extraction of Furfural and Furfural/5-Hydroxymethylfurfural from Mixed Lignocellulosic Biomass-Derived Feedstocks
We present a combined in silico and experimental study on the extraction of furfural and 5-hydroxymethylfurfural (HMF) in aqueous–organic biphasic systems. We predict the liquid–liquid equilibria and furfural/HMF partition coefficients of over 2200 water-organic biphasic systems using the multiscale COSMO-RS model and measure experimentally single-component (furfural) and mixture (furfural and HMF) partition coefficients at room and dehydration reaction-relevant temperatures in 28 solvents. We find the experimental data to be within a factor of 2 from the COSMO-RS predictions. Even though furfural and HMF have chemical similarity, the slight differences in molecular structure render the separation of furfural easier by the supply of more solvents of higher partition coefficient for extraction. We leverage this molecular difference and experimentally demonstrate that with an additional extraction step, using dichloromethane or toluene, we can selectively extract furfural from furfural-HMF mixtures, which can coexist in lignocellulosic biomass dehydration products, despite their partition coefficients being generally correlated. We complement solvent selection criteria for biphasic lignocellulosic biomass processes with a simple mass balance extraction model for determining volume ratios in multistage extraction. Lastly, the molecular nature of the preferential furfural extraction is rationalized using COSMO-RS σ-profile analysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Quasi-stationary states in the Southern Hemisphere
Pattern correlations between daily anomalies have been used to study the persistence of the Southern Hemisphere circulations. The dataset consists of daily Australian analyses of 500 mb heights and sea level pressure for the period from 1972 to 1983. Compared to the Northern Hemisphere, the pattern correlations are much lower and more variable in the Southern Hemisphere. The mean one-day lag autocorrelation is only 0.57, compared to 0.81 in the Northern Hemisphere. The correlations increase significantly for the filtered anomalies, which consist of the planetary wavenumbers from 0 to 4. Subjective criteria based on the pattern correlations are used to select quasi-stationary events. A series of 5 or more daily maps is defined to be quasi-stationary if the pattern correlations between all pairs of five consecutive maps in this time series are larger than or equal to 0.5. In winter, quasi-stationary events can be classified in terms of wavenumbers. Waves 3 and 4 are by far the dominant waves. More than half of the events have large wave 3 amplitude with geographically fixed orientations.
Mo, K. C.↗
Supramolecular assemblies of polybenzimidazole and aromatic polycarboxylic acids with superior mechanical and H 2 /CO 2 separation properties
Aromatic polycarboxylic acids complex with imidazoles, forming supramolecular assemblies. Herein, we demonstrate that polybenzimidazole (PBI) can be augmented by aromatic polycarboxylic acids, including phthalic acid (PA), trimesic acid (TMA), and pyromellitic acid (PMA), and the resulting supramolecular assemblies exhibit attractive H 2 /CO 2 separation performance for precombustion carbon capture. The acid doping decreases the free volume and gas permeability but increases H 2 /CO 2 selectivity, which can be correlated with the molar ratio of the protons to PBI repeating units in the assemblies. Increasing the temperature decreases the H 2 /CO 2 selectivity because of weakened interactions. When challenged with model gas mixtures, a supramolecular assembly based on TMA shows H 2 /CO 2 separation properties superior to state-of-the-art materials and above Robeson's upper bound. Furthermore, this study elucidates the fruitful harnessing of dynamic non-covalent bonds to design robust and highly selective membranes for industrial gas separations.
36 MATERIALS SCIENCE↗
Assessing the Performance of Exchange‐Correlation Density Functionals in Describing the Iron‐Catalyzed Ammonia Synthesis System
Density functional theory (DFT) has been widely employed for elucidating mechanistic aspects of heterogeneous catalysis. However, the accuracy of DFT calculations relies heavily on selecting an exchange-correlation (XC) functional that correctly describes the electronic structure of materials involved in the reactions. This study assesses the accuracy of several XC density functionals for modeling the iron-catalyzed ammonia synthesis system. In the assessment of functional accuracy, experimental references are compared to DFT-calculated values for the formation energy of gas-phase ammonia and nitrogen, bulk Fe/Fe-nitride (γ′-Fe 4 N) lattice constants and cohesive/formation energies, and nitrogen and ammonia binding energies on Fe(100), Fe(111), Fe(110), and γ′-Fe 4 N(111). It is observed that the experimental value for each of these descriptors is accurately modeled by at least one functional. RPBE alone provides reliable estimates for both the lattice constant and cohesive energy of Fe and γ′-Fe 4 N. Temperature-programmed desorption experiments led to estimates for N and NH 3 adsorption across several Fe-based facets that are best captured by RPBE. These results highlight the importance of choosing an appropriate XC functional that accurately describes experimental systems and offer insights into effectively modeling the interactions between nitrogen and ammonia on Fe-based surfaces.
adsorption↗
The Radio luminosity Function of Radio-Loud Quasars from the 7C Redshift Survey
We present a complete sample of 24 radio-loud quasars (RLQs) from the new 7C Redshift Survey. Every quasar with a low-frequency (151 MHz) radio flux-density S(sub 151) > 0.5 Jy in two regions of the sky covering 0.013 sr is included; 23 of these have sufficient extended flux to meet the selection criteria, 18 of these have steep radio spectra (hereafter denoted as SSQs). The key advantage of this sample over most samples of RLQs is the lack of an optical magnitude limit. By combining the 7C and 3CRR samples, we have investigated the properties of RLQs as a function of redshift z and radio luminosity L(sub 151). We derive the radio luminosity function (RLF) of RLQs and find that the data are well fitted by a single power-law with slope alpha(sub 1) = 1.9 +/- 0.1 (for H(sub 0) = 50 km/s.Mpc, OMEGA(sub M) = 1, OMEGA(sub DELTA) = 0). We find that there must be a break in the RLQ RLF at log(sub 10)(L(sub 151)/W Hz.sr) approximately < or = 27, in order for the models to be consistent with the 7C and 6C source counts. The z-dependence of the RLF follows a one-tailed gaussian which peaks at z = 1.7 +/- 0.2. We find no evidence for a decline in the co-moving space density of RLQs at higher redshifts. A positive correlation between the radio and optical luminosities of SSQs is observed, confirming a result of Serjeant. We are able to rule out this correlation being due to selection effects or biases in our combined sample. The radio-optical correlation and best-fit model RLF enable us to estimate the distribution of optical magnitudes of quasars in samples selected at low radio frequencies, We con- clude that for samples with S(sub 151) approximately < or = 1 Jy one must use optical data significantly deeper than the POSS-I limit (R approximately equal 20), in order to avoid severe incompleteness.
Willott, Chris J.↗
A new generation of effective core potentials: Selected lanthanides and heavy elements
Here, we construct correlation-consistent effective core potentials (ccECPs) for a selected set of heavy atoms and ƒ-elements that are of significant current interest in materials and chemical applications, including Y, Zr, Nb, Rh, Ta, Re, Pt, Gd, and Tb. As is customary, ccECPs consist of spin orbit averaged relativistic effective potential (AREP) and effective spin-orbit (SO) terms. For the AREP part, our constructions are carried out within a relativistic coupled-cluster framework while also taking into account objective function one-particle characteristics for improved convergence in optimizations. The transferability is adjusted using binding curves of hydride and oxide molecules. We address the difficulties encountered with ƒ-elements, such as the presence of large cores and multiple near-degeneracies of excited levels. For these elements, we construct ccECPs with core valence partitioning that includes 4ƒ-subshell in the valence space. The developed ccECPs achieve an excellent balance between accuracy, size of the valence space, and transferability and are also suitable to be used in plane wave codes with reasonable energy cutoffs.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Correlated petrographic, electron microprobe, and ion microprobe studies of selected primitive and processed phase assemblages in meteorites
During the past three years we have received support to continue our research in elucidating the formation and alteration histories of selected meteoritic materials by a combination of petrographic, trace element, and isotopic analyses employing optical and scanning electron microscopes and electron and ion microprobes. The awarded research funds enabled the P.I. to attend the annual LPSC, the co-I to devote approximately 15 percent of his time to the research proposed in the grant, and partial support for a visiting summer post-doctoral fellow to conduct electron microprobe analyses of meteoritic samples in our laboratory. The research funds, along with support from the NASA Education Initiative awarded to P.I. G. Wasserburg, enabled the co-I to continue a mentoring program with inner-city minority youth. The support enabled us to achieve significant results in the five projects that we proposed (in addition to the Education Initiative), namely: studies of the accretional and post-accretional alteration and thermal histories in CV meteorites, characterization of periclase-bearing Fremdlinge in CV meteorites, characterization of Ni-Pt-Ge-Te-rich Fremdlinge in CV meteorites in an attempt to determine the constraints they place on the petrogenetic and thermal histories of their host CAI's, correlated electron and ion microprobe studies of silicate and phosphate inclusions in the Colomera meteorite in an attempt to determine the petrogenesis of the IE iron meteorites, and development of improved instrumental and correction procedures for improved accuracy of analysis of meteoritic materials with the electron microprobe. This grant supported, in part or whole, 18 publications so far by our research team, with at least three more papers anticipated. The list of these publications is included. The details of the research results are briefly summarized.
Albee, Arden L.↗
Surface roughness measuring system
Significant height information of ocean waves, or peaks of rough terrain is obtained by compressing the radar signal over different widths of the available chirp or Doppler bandwidths, and cross-correlating one of these images with each of the others. Upon plotting a fixed (e.g., zero) component of the cross-correlation values as the spacing is increased over some empirically determined range, the system is calibrated. To measure height with the system, a spacing value is selected and a cross-correlation value is determined between two intensity images at a selected frequency spacing. The measured height is the slope of the cross-correlation value used. Both electronic and optical radar signal data compressors and cross-correlations are disclosed for implementation of the system.
Jain, A.↗