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DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.

Source record↗

DOE OSTI2025

Fundamental microscopic properties as predictors of large-scale quantities of interest: Validation through grain boundary energy trends

Correlations between fundamental microscopic properties computable from first principles, which we term canonical properties, and complex large-scale quantities of interest (QoIs) provide an avenue to predictive materials discovery. Here, we propose that such correlations can be efficiently discovered through simulations utilizing approximate interatomic potentials (IPs), which serve as an ensemble of “synthetic materials”. As a proof of principle we build a regression model relating canonical properties to the symmetric tilt grain boundary (GB) energy curves in face-centered cubic crystals, characterized by the scaling factor in the universal lattice matching model of Runnels et al. (2016), which we take to be our QoI. Our analysis recovers known correlations of GB energy to other properties and discovers new ones. We also demonstrate, using available density functional theory (DFT) GB energy data, that the regression model constructed from IP data is consistent with DFT results, confirming the assumption that the IPs and DFT belong to same statistical pool and thereby validating the approach. Regression models constructed in this fashion can be used to predict large-scale QoIs based on first-principles data and provide a general method for training IPs for QoIs beyond the scope of first-principles calculations.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Accelerating rates of cognitive decline and imaging markers associated with β-amyloid pathology

Objective: Our objective is to estimate points along the spectrum of β-amyloid pathology at which rates of change of several measures of neuronal injury and cognitive decline begin to accelerate. Methods: In 460 patients with mild cognitive impairment (MCI), we estimated the points at which rates of florbetapir PET, fluorodeoxyglucose (FDG) PET, MRI, and cognitive and functional decline begin to accelerate with respect to baseline CSF Aβ 42 . Points of initial acceleration in rates of decline were estimated using mixed-effects regression. Results: Rates of neuronal injury and cognitive and even functional decline accelerate substantially before the conventional threshold for amyloid positivity, with rates of florbetapir PET and FDG PET accelerating early. Temporal lobe atrophy rates also accelerate prior to the threshold, but not before the acceleration of cognitive and functional decline. Conclusions: A considerable proportion of patients with MCI would not meet inclusion criteria for a trial using the current threshold for amyloid positivity, even though on average, they are experiencing cognitive/functional decline associated with prethreshold levels of CSF Aβ 42 . Lastly, future trials in early Alzheimer disease might consider revising the criteria regarding β-amyloid thresholds to include the range of amyloid associated with the first signs of accelerating rates of decline.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Three differential expression profiles of miRNAs as potential biomarkers for lung adenocarcinoma

Highlights: • To identify the differential miRNAs expression between lung cancer and normal tissues. • Data analysis was based on a computational approach to detect survival-associated signatures. • Three-miRNA signature could be used as a prognostic marker in LACA. Owing to the poor prognosis, novel biomarkers for lung adenocarcinoma (LACA) are needed nowadays. The aim of the study was to identify the differential miRNAs expression between lung cancer and normal tissues and evaluate the prognostic values of the miRNAs. Multidimensional data of 528 samples were retrieved from The Cancer Genome Atlas archive. Data analysis was based on a computational approach to detect survival-associated molecular signatures. A total of 191 differentially expressed miRNAs were identified between LACA tissues and normal tissues, including 88 up-regulated and 103 down-regulated miRNAs. The Kaplan-Meier survival method revealed the prognostic function of the three miRNAs (miR-1293, miR-873 and miR-1914). Cox regression analysis showed that the three-miRNA signature was an independent prognostic factor in LACA. The functional enrichment analysis suggested that the target genes of three miRNAs may be involved in various pathways related to the cancer. This study demonstrated that the three-miRNA signature (miR-1293, miR-873 and miR-1914) could be used as a prognostic marker in LACA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

An Integrated Study to Analyze Soil Microbial Community Structure and Metabolic Potential in Two Forest Types

Soil microbial metabolic potential and ecosystem function have received little attention owing to difficulties in methodology. In this study, we selected natural mature forest and natural secondary forest and analyzed the soil microbial community and metabolic potential combing the high-throughput sequencing and GeoChip technologies. Phylogenetic analysis based on 16S rRNA sequencing showed that one known archaeal phylum and 15 known bacterial phyla as well as unclassified phylotypes were presented in these forest soils, and Acidobacteria, Protecobacteria, and Actinobacteria were three of most abundant phyla. The detected microbial functional gene groups were related to different biogeochemical processes, including carbon degradation, carbon fixation, methane metabolism, nitrogen cycling, phosphorus utilization, sulfur cycling, etc. The Shannon index for detected functional gene probes was significantly higher (P<0.05) at natural secondary forest site. The regression analysis showed that a strong positive (P<0.05) correlation was existed between the soil microbial functional gene diversity and phylogenetic diversity. Mantel test showed that soil oxidizable organic carbon, soil total nitrogen and cellulose, glucanase, and amylase activities were significantly linked (P<0.05) to the relative abundance of corresponded functional gene groups. Variance partitioning analysis showed that a total of 81.58% of the variation in community structure was explained by soil chemical factors, soil temperature, and plant diversity. Therefore, the positive link of soil microbial structure and composition to functional activity related to ecosystem functioning was existed, and the natural secondary forest soil may occur the high microbial metabolic potential. Although the results can’t directly reflect the actual microbial populations and functional activities, this study provides insight into the potential activity of the microbial community and associated feedback responses of the terrestrial ecosystem to environmental changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Density functional modeling of the binding energies between aluminosilicate oligomers and different metal cations

Interactions between negatively charged aluminosilicate species and positively charged metal cations are critical to many important engineering processes and applications, including sustainable cements and aluminosilicate glasses. In an effort to probe these interactions, here we have calculated the pair-wise interaction energies (i.e., binding energies) between aluminosilicate dimer/trimer and 17 different metal cations M n+ (M n+ = Li + , Na + , K + , Cu + , Cu 2+ , Co 2+ , Zn 2+ , Ni 2+ , Mg 2+ , Ca 2+ , Ti 2+ , Fe 2+ , Fe 3+ , Co 3+ , Cr 3+ , Ti 4+ and Cr 6+ ) using a density functional theory (DFT) approach. Analysis of the DFT-optimized structural representations for the clusters (dimer/trimer + M n+ ) shows that their structural attributes (e.g., interatomic distances) are generally consistent with literature observations on aluminosilicate glasses. The DFT-derived binding energies are seen to vary considerably depending on the type of cations (i.e., charge and ionic radii) and aluminosilicate species (i.e., dimer or trimer). A survey of the literature reveals that the difference in the calculated binding energies between different M n+ can be used to explain many literature observations associated with the impact of metal cations on materials properties (e.g., glass corrosion, mineral dissolution, and ionic transport). Analysis of all the DFT-derived binding energies reveals that the correlation between these energy values and the ionic potential and field strength of the metal cations are well captured by 2nd order polynomial functions ( R 2 values of 0.99–1.00 are achieved for regressions). Given that the ionic potential and field strength of a given metal cation can be readily estimated using well-tabulated ionic radii available in the literature, these simple polynomial functions would enable rapid estimation of the binding energies of a much wider range of cations with the aluminosilicate dimer/trimer, providing guidance on the design and optimization of sustainable cements and aluminosilicate glasses and their associated applications. Finally, the limitations associated with using these simple model systems to model complex interactions are also discussed.

Gong, Kai↗

NASA NTRS1998

Predicting lettuce canopy photosynthesis with statistical and neural network models

An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).

Non-NASA Center↗

DOE OSTI2021

Calibration approach and range of observed sap flow influences transpiration estimates from thermal dissipation sensors

Calibrating thermal dissipation (TD) sap flow sensors has become increasingly important to accurately estimate whole-tree transpiration, but it is unclear how the calibration approach itself influences the resulting coefficients and estimates. Here, we compare the two most common calibration approaches, gravimetric and potometric, using TD sensors inserted into Eucalyptus benthamii tree stems. The gravimetric approach uses an excised stem segment devoid of branches and leaves and pushes water through the stem using gravity, a positive force. The potometric approach uses a severed stem containing an intact canopy placed upright in a reservoir where water is pulled through the stem via transpiration, a negative force. We hypothesized that the positive pressure associated with gravimetric calibration would overestimate conductive sapwood area relative to that estimated from potometric calibration and that coefficients from these different approaches would result in different estimates of transpiration when applied to intact trees. We also predicted that calibrations could improve transpiration estimates by targeting the range of observed sap flow rates (i.e., K values) in intact trees. Conductive sapwood area was higher under gravimetric calibrations and resulting estimates of transpiration were lower compared to potometric calibrations. Segmented calibration curves, which fit two separate curves for the relationship between sap flux density (Fd) and sap flux index (K) based on the range of sap flow rates observed in intact trees, increased transpiration estimates from both gravimetric and potometric coefficients and diminished the magnitude of difference in transpiration estimates between approaches. Researchers should be aware that calibration approach and range of observed sap flow profoundly influences transpiration estimates from TD sensors and this likely applies to calibrations of other heat-based sap flow sensors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Coiled-coil forming peptides for the induction of silver nanoparticles

Biopolymers with defined sequence patterns offer an attractive alternative for the formation of silver nanoparticle (AgNP). A set of coiled-coil dimer forming peptides was tested for their AgNP formation ability. Seventeen of those peptides mediated the formation of AgNPs in aqueous solution at neutral pH, while the formation of a coiled-coil dimer inhibited the nanoparticle generation. A QSAR regression model on the relationship between sequence and function suggests that in this peptide type the patterns KXQQ and KXEE are favorable, whereas Ala residues appear to have an inhibitory effect. UV–VIS spectra of the obtained nanoparticles gave a peak at around 420 nm, typical for AgNPs in the size range around 40 nm, which was confirmed by dynamic light scattering and transmission electron microscopy. Peptide-induced AgNPs exhibited good antibacterial activity, even after a 15 min contact time, while they had low toxicity to human cells at the same concentrations. These results show that our designed peptides generate AgNPs with antibacterial activity at mild conditions and might be used for antibacterial coatings. - Highlights: • 17 of the 30 tested coiled-coil forming peptides induce AgNP formation. • Coiled-coil dimer formation suppresses AgNP generation of individual peptides. • Size of the peptide-induced silver nanoparticles is around 40 nm. • QSAR analysis points to the importance of KXQQ and KXEE motifs for AgNP generation. • Peptide-induced silver nanoparticles exhibit antibacterial activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

Angular momentum↗

DOE OSTI2019

Unscented Kalman Filter-based Unbiased Minimum-Variance Estimation for Nonlinear Systems with Unknown Inputs

This paper proposes an unscented Kalman filter (UKF)-based unbiased minimum-variance estimation (UMV) method for the nonlinear system with unknown inputs. By utilizing the statistical linerization, the nonlinear system and measurement functions are transformed into a “linear-like” regression form. The latter preserves the nonlinearity of the system and the measurement models. To this end, the unknown inputs can be estimated by the weighted least-squares. This “linear-like” regression form also allows us to resort to the UMV state estimation framework for the development of new nonlinear filter to handle unknown inputs. Specifically, two approaches have been developed: 1) given the estimated inputs, we derive a filter by minimizing the trace of the state error covariance matrix; 2) without input estimation, we derive the filter by minimizing the trace of the state error covariance matrix subject to a constraint imposed on the gain matrix. We prove that these two approaches provide the same results. Numerical results validate the effectiveness of the proposed method.

Unscented Kalman filter, unbiased minimumvariance ↗

DOE OSTI2020

Psychological Distress and Alzheimer’s Disease Mortality in the United States: Results from the 1997–2014 National Health Interview Survey-National Death Index Record Linkage Study

Objective: This study examines the association between psychological distress and Alzheimer’s disease mortality among US adults aged ≥45. Methods: We analyzed the Kessler 6-item psychological distress scale as a risk factor for Alzheimer’s mortality using the pooled 1997–2014 National Health Interview Survey (NHIS)- National Death Index (NDI) database ( N = 265,089). Cox regression was used to model mortality as a function of psychological distress and sociodemographic and behavioral covariates. Results: The Alzheimer’s mortality risk was 97% higher (HR = 1.97; 95% confidence interval [CI] = 1.37, 2.84) in adults with serious psychological distress compared with those without psychological distress, controlling for sociodemographic covariates. The relative mortality risk remained statistically significant (HR = 1.49; 95% CI = 1.04, 2.13) after additional adjustment for smoking, alcohol consumption, health status, activity limitation, and body mass index. Discussion: US adults had significantly higher risks of Alzheimer’s disease mortality at higher psychological distress levels. These findings underscore the significance of addressing psychological well-being as a strategy for reducing Alzheimer’s disease mortality.

Singh, Gopal K.↗

DOE OSTI2014

Sensitivity of Beam Parameters to a Station C Solenoid Scan on Axis II

Magnet scans are a standard technique for determining beam parameters in accelerators. Beam parameters are inferred from spot size measurements using a model of the beam optics. The sensitivity of the measured beam spot size to the beam parameters is investigated for typical DARHT Axis II beam energies and currents. In a typical S4 solenoid scan, the downstream transport is tuned to achieve a round beam at Station C with an envelope radius of about 1.5 cm with a very small divergence with S4 off. The typical beam energy and current are 16.0 MeV and 1.625 kA. Figures 1-3 show the sensitivity of the bean size at Station C to the emittance, initial radius and initial angle respectively. To better understand the relative sensitivity of the beam size to the emittance, initial radius and initial angle, linear regressions were performed for each parameter as a function of the S4 setting. The results are shown in Figure 4. The measured slope was scaled to have a maximum value of 1 in order to present the relative sensitivities in a single plot. Figure 4 clearly shows the beam size at the minimum of the S4 scan is most sensitive to emittance and relatively insensitive to initial radius and angle as expected. The beam emittance is also very sensitive to the beam size of the converging beam and becomes insensitive to the beam size of the diverging beam. Measurements of the beam size of the diverging beam provide the greatest sensitivity to the initial beam radius and to a lesser extent the initial beam angle. The converging beam size is initially very sensitive to the emittance and initial angle at low S4 currents. As the S4 current is increased the sensitivity to the emittance remains strong while the sensitivity to the initial angle diminishes.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Updated Value of Service Reliability Estimates for Electric Utility Customers in the United States

This report updates the 2009 meta-analysis that provides estimates of the value of service reliability for electricity customers in the United States (U.S.). The meta-dataset now includes 34 different datasets from surveys fielded by 10 different utility companies between 1989 and 2012. Because these studies used nearly identical interruption cost estimation or willingness-to-pay/accept methods, it was possible to integrate their results into a single meta-dataset describing the value of electric service reliability observed in all of them. Once the datasets from the various studies were combined, a two-part regression model was used to estimate customer damage functions that can be generally applied to calculate customer interruption costs per event by season, time of day, day of week, and geographical regions within the U.S. for industrial, commercial, and residential customers. This report focuses on the backwards stepwise selection process that was used to develop the final revised model for all customer classes. Across customer classes, the revised customer interruption cost model has improved significantly because it incorporates more data and does not include the many extraneous variables that were in the original specification from the 2009 meta-analysis. The backwards stepwise selection process led to a more parsimonious model that only included key variables, while still achieving comparable out-of-sample predictive performance. In turn, users of interruption cost estimation tools such as the Interruption Cost Estimate (ICE) Calculator will have less customer characteristics information to provide and the associated inputs page will be far less cumbersome. The upcoming new version of the ICE Calculator is anticipated to be released in 2015.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1975

A digital algorithm for characteristic film curves

The task of establishing a film calibration scheme for magnitude studies of Skylab photographic images of Comet Kohoutek is examined. Since the data are recorded in terms of film density and have to be used in terms of exposure, the conversion from density to exposure is critical. In this film calibration scheme, the hardware deals with the data sources, recording medium, and data conversion to a computer compatible program, whereas the software deals with signal to noise enhancement, stepwedge calibration curve and leads to modeling of the film characteristic curves. A mathematical model of the characteristic curve is obtained using a modified version of Efroymson's (1960) stepwise multiple linear regression algorithm, which gives log exposure as a function of density. The difference in the calibration curves from pre- and postflight exposures is well accounted for in the model as a result of sensitive statistical tests. The characteristic curve modeling program requires about 4K of core and is executed in about 3 min.

Buckner, J.↗

NASA NTRS1980

Collisional redistribution of radiation. II - The effects of degeneracy on the equations of motion for the density matrix. III - The equation of motion for the correlation function and the scattered spectrum

The effect of correlations between an absorber atom and perturbers in the binary-collision approximation are applied to degenerate atomic systems. A generalized absorption profile which specifies the final state of the atom after an absorption event is related to the total intensities of Rayleigh scattering and fluorescence from the atom. It is suggested that additional dynamical information to that obtainable from ordinary absorption experiments is required in order to describe redistributed atomic radiation. The scattering of monochromatic radiation by a degenerate atom is computed in a binary-collision approximation; an equation of motion is derived for the correlation function which is valid outside the quantum-regression regime. Solutions are given for the weak-field conditions in terms of generalized absorption and emission profiles that depend on the indices of the atomic multipoles.

Burnett, K.↗

NASA NTRS1984

On long-term periodicities in the sunspot record

Sunspot records are systematically maintained, with the knowledge that an 11 year average period exists since about 1850. Thus, the sunspot record of highest quality and considered to be the most reliable is that of cycle eight through the present. On the basis of cycles 8 through 20, various combinations of sine curves were used to approximate the observed R sub MAX values (where R sub MAX is the smoothed sunspot number at cycle maximum). It is found that a three component sinusoidal function, having an 11 cycle and a 2 cycle variation on a 90 cycle periodicity, yields computed R sub MAX values which fit, reasonably well, observed R sub MAX values for the modern sunspot cycles. Extrapolation of the empirical functions forward in time allows for the projection of values of R sub MAX for cycles 21 and 22. For cycle 21, the function projects a value of 157.3, very close to the actually observed value of 164.5. For cycle 22, the function projects a value of about 107. Linear regressions applied to cycle 22 indicate a long-period cycle (cycle duration 132 months). An extensive bibliography on techniques used to estimate the time dependent behavior of sunspot cycles is provided.

Wilson, R. M.↗

NASA NTRS1990

Seasonal recession of Mars' south polar cap in 1986

Photographs of Mars obtained during the 1986 opposition of the planet have been used to derive the regression curve for the south polar cap between Ls = 190 deg and Ls = 255 deg. The 1986 regression appears to have been unexceptional until after Ls = 230 deg, when it becomes retarded relative to the normal established by the 1971 and 1977 regressions. A study of the data as a function of the filter used suggests that circumpolar clouds were present in early spring, unlike the case in the 1977 recession.

James, Philip B.↗